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Over the last years, social robots have been conceived to be used in various domains and for different purposes. This paper presents a survey on different applications and aspects of social robots in education. Different contexts are seen, ranging from children education, until higher education. A variety of applications and studies are reported, in areas like as second language tutoring, teaching assistance, and storytelling. Robotic platforms used in these applications are observed, and means of evaluation of users perception of robots are presented.

Recurrence and metastasis are the major causes of mortality in head and neck squamous cell carcinoma (HNSCC). It is suggested that cancer stem cells (CSCs) play pivotal roles in recurrence and metastasis. Thus, a greater understanding of the mechanisms of CSC regulation may provide opportunities to develop novel therapies for improving survival by controlling recurrence or metastasis. Here, we report that overexpression of the gene encoding the catalytic subunit of PI3K (PIK3CA), the most frequently amplified oncogene in HNSCC, promotes epithelial‐to‐mesenchymal transition and enriches the CSC population. However, PIK3CA is not required to maintain these traits and inhibition of the phosphatidylinositol 3‐kinase (PI3K) signaling pathway paradoxically promotes CSC population. Molecular analysis revealed that overexpression of PIK3CA activates multiple receptor tyrosine kinases (RTKs), in which ephrin receptors (Ephs), tropomyosin receptor kinases (TRK) and mast/stem cell growth factor receptor (c‐Kit) contribute to maintain CSC population. Accordingly, simultaneous inhibition of these RTKs using a multi‐kinase inhibitor ponatinib has a superior effect at eliminating the CSC population and reduces metastasis of PIK3CA‐overexpressing HNSCC cells. Our result suggests that co‐targeting of Ephs, TRKs and the c‐Kit pathway may be effective at eliminating the PI3K‐independent CSC population, thereby providing potential targets for future development of a novel anti‐CSC therapeutic approach for HNSCC patients, particularly for patients with PIK3CA amplification., We report that overexpression of the gene encoding the catalytic subunit of PI3K (PIK3CA) promotes epithelial‐to‐mesenchymal transition and enriches the cancer stem cell (CSC) population. However, PIK3CA is not required to maintain these traits. Molecular analysis revealed that PIK3CA overexpression activates multiple receptor tyrosine kinases (RTK), in which tropomyosin receptor kinases, ephrin receptors, and mast/stem cell growth factor receptor (c‐Kit) contribute to maintain CSCs. Accordingly, co‐inhibition of these RTKs using a multi‐kinase inhibitor ponatinib eliminates CSCs and reduces metastasis of PIK3CA‐overexpressing head and neck squamous cell carcinoma cells.

Ayman Nasr Hashem,1 Sherif Said Tolees,2 Ahmed Samir3 1Eye City Hospital, Cairo, Egypt; 2Magrabi Eye and Ear Hospital, Jeddah, KSA; 3Faculty of Medicine, Zagazig University, Zagazig, Egypt Correspondence: Ayman Nasr HashemEye City Hospital, Fifth Settlement, Cairo, EgyptTel +2 01009769598Email aymannhashem@gmail.comPurpose: To describe the outcomes of a case series of patients who underwent a novel technique for managing macroperforation during deep anterior lamellar keratoplasty (DALK).Methods: Nine eyes of 9 patients with advanced keratoconus who underwent DALK comprised the case series. A macroperforation occurred in all eyes during DALK. The stromal patch suturing technique was used to manage all cases; a large piece of the previously excised stromal tissue was sutured to the edge of the trephine to seal the perforation. The technical aspects of the procedure are described and data are presented on the visual outcomes, endothelial microscopy, and postoperative complications at last postoperative visit (average 18 months; range, 7 to 23 months).Results: All 9 cases were managed successfully with the stromal patch suturing technique. Postoperatively, the graft was clear in all cases. At day 1, seven eyes had a Descemet’s membrane detachment, 3 of these eyes resolved spontaneously within 2 weeks and 4 required air bubble injection for successful reattachment. At last follow up seven eyes had a corrected distance visual acuity of 20/30 or better and 2 eyes had 20/40 vision. The average endothelial cell count was 2162 cell/mm2. There were no cases with excessive inflammation or vascularisation during the postoperative follow-up.Conclusion: The stromal patch suturing technique was successfully used to manage intraoperative macroperforation during DALK. This technique resulted in endothelial changes that were consistent with uncomplicated DALK and function visual acuity of 20/40 or better in all cases with no postoperative sequelae.Keywords: DALK, keratoplasty, corneal transplant, stromal patch suturing technique, macroperforation

With the development in the areas such as high performance graphic processing units (GPU), sensor technologies and artificial networks the goal of self-driving vehicles has never been closer. With the promise of massive decrease in the road accidents, self-driving cars have been the center of attention for the past few years. In this paper we discuss the major components of a self-driving vehicles along with the methodologies required to produce a self-driving vehicle. With the added advent of the 3D printed body our aim is to rapid prototype a 3D printed Electric Vehicle with the goal to test and improve the current self-driving algorithms. The chassis of the car, with an initial body design was simulated and tested along with some basic parameters such as vehicle speed acceleration and traction force. The paper also presents the simulated results of an end-to-end approach to steering vehicle using convolutional neural networks, that would later be the basis of the self-driving algorithm.

Electrical biosignals have the potential for use as biometric authenticators, owing to their ability to facilitate liveness detection and concealed nature. In this work, the viability of using surface electromyogram (sEMG) as a biometric modality for users verification is investigated. A database of multi-channel sEMG signals is created using a wearable armband from able-bodied users. Each user used his/her muscles to form a password that consists of a unique combination of specific hand gestures. A total of 18 features are extracted from the signals in order to distinguish between the users. Several features are extracted in the frequency domain after estimating the power spectral density while using the Welch&rsquo, s method. Specifically, average frequency, signal power, median frequency, Kurtosis, Deciles, coefficient of dissymmetry, and the peak frequency of the sEMG signal are considered. To further increase the accuracy of the classifier, time domain features are also extracted through segmentation of the signal into 10 segments, and then calculating both the root mean square and length of the signal. Several classifiers that are based on K-nearest Neighbors (KNN), Linear Discernment Analysis (LDA), and Ensemble of Classifiers are constructed, trained, and statistically compared, resulting in an average accuracy in 97.4%, 98.3%, and 98.5%, respectively. False acceptance rate (FAR) and False Rejection Rate (FRR) are estimated for each classifier in order to determine the effectiveness of the biometrics verification system. Although the ensemble classifier accuracy was found to be the highest, the results show that the KNN classifier exhibits a FAR of 0.2% and FRR of 2.9%. Thus, the KNN classifier was found to he the optimum classifier after the extraction of all 18 features. This work demonstrates the usefulness of sEMG as a biometric authenticator in user verification.

In this paper, a customizable wearable 3D-printed bionic arm is designed, fabricated, and optimized for a right arm amputee. An experimental test has been conducted for the user, where control of the artificial bionic hand is accomplished successfully using surface electromyography (sEMG) signals acquired by a multi-channel wearable armband. The 3D-printed bionic arm was designed for the low cost of 295 USD, and was lightweight at 428 g. To facilitate a generic control of the bionic arm, sEMG data were collected for a set of gestures (fist, spread fingers, wave-in, wave-out) from a wide range of participants. The collected data were processed and features related to the gestures were extracted for the purpose of training a classifier. In this study, several classifiers based on neural networks, support vector machine, and decision trees were constructed, trained, and statistically compared. The support vector machine classifier was found to exhibit an 89.93% success rate. Real-time testing of the bionic arm with the optimum classifier is demonstrated.

In this research human gait database is collected using different possible methods such as Wearable sensors, Smartphone and Cameras. For a gait recognition accelerometer data from wearable shimmer modules and smartphone are used. Data from different sensors location is compared to know which sensor location have better recognition rate. Different walking scenarios like slow, normal and fast walk were investigated. Wearable sensors and smartphone data are compared to know whether mobile phones can be used for gait recognition or not. Also effects of age, height, weight on gait recognition are also studied. The obtained results of gait biometric matrices like Genuine Recognition Rate (GRR), Total Recognition Rate (TRR) and Equal Error Rate (EER) showed better results. EER in different walking scenarios ranged from 0.17% to 2.27% for the five wearable sensors at different locations, whereas EER results of smartphone data ranged from 1.23% to 4.07%. For sensors located at leg, pocket and hand the average GRR value falls with increase in age group, while for sensors located at upper pocket and bag, the GRR value doesn’t follow any trend. Moreover GRR results on all sensors show no significance regarding height or weight variations.

Distraction, drowsiness, and fatigue are the main factors of car accidents recently. To solve such problems, an Eye-tracking system based on camera is proposed in this paper. The system detects the driver’s Distraction or sleepiness and gives an alert to the driver as an assistance system. The camera best position is chosen to be on the dashboard without distracting the driver. The system will detect the driver’s face and eyes by using Viola-Jones Algorithm that includes Haar Classifiers that showed significant advantages regarding processing time and correct detection algorithms. A prepared scenario is tested in a designed simulator that is used to simulate real driving conditions in an indoor environment. The system is added in real-vehicle and tested in an outdoor environment. Whenever the system detects the distraction or sleepiness of the driver, the driver will be alerted through a displayed message on a screen and an audible sound for more attention. The results show the accuracy of the system with a correct detection rate of 82% for indoor tests and 72.8 % for the outdoor environment.

Electrical bio-signals have the potential to be used in different applications due to their hidden nature and their ability to facilitate liveness detection. This paper investigates the feasibility of using the Convolutional Neural Network (CNN) to classify and analyze electroencephalogram (EEG) data with their time-frequency representations and class activation mapping (CAM) to detect epilepsy disease. Several types of pre-trained CNNs are employed for a multi-class classification task (AlexNet, GoogLeNet, ResNet-18, and ResNet-50) and their results are compared. Also, a novel convolutional neural network architecture comprised of two horizontally concatenated GoogLeNets is proposed with two inputs scalograms and spectrogram of the eplictic EEG signal. Four segment lengths (4097, 2048, 1024, and 512 sampling points) with three time-frequency representations (short-time Fourier, Wavelet, and Hilbert-Huang transform) are statistically evaluated. The dataset used in this research is collected at the University of Bonn. The dataset is reorganized as normal, interictal, and ictal. The maximum achieved accuracies for 4097, 2048, 1024, and 512 sampling points are 100 %, 100 %, 100 %, and 99.5 % respectively. The CAM method is used to analyze discriminative regions of time-frequency representations of EEG segments and networks' decisions. This method showed CNN models used different time and frequency regions of input images for each class with correct and incorrect predictions.

In this chapter, a case study using a specific wearable Multi-Channel EMG device will be considered. In particular, eight EMG channels will be used through Myo Armband system. The purpose is to deploy a verification biometric system using EMG signals corresponding to hand gestures. More specifically, the idea behind this concept is the capacity to generate a digital signature for each specific hand gesture.

In this research paper, customizable wearable robust 3D printed bionic arm been designed and implemented for a right arm. An experimental test has been conducted for a person who has been born without a right arm. A control of a 9 DOF hand is accomplished successfully using EMG signals acquired by MYO armband. Different gestures are recognized and mapped to control different movements of the hand. Basic daily activities have been accomplished after training of that person. The arm is a lightweight for daily use for long time. The cost of the arm is cheap compared to available solutions available on the market.

The rise in popularity of humanoid robots will eventually lead to including them in all of our daily lives. Since these robots are opted to have the ability to move, act, and communicate like humans, eventually they will be used to replace humans in certain minimalist tasks or hazardous situation. In this paper, we propose a review of recent project discussing utilization of humanoid robots as service robots. Moreover, a scenario framework will be proposed where a humanoid robot (Pepper) will be performing certain service tasks at AUM reception.

This paper proposed an initial engineering realization of an underwater remotely operated vehicle (ROV) with multisensory system for oil spills monitoring and detection in seawater. It covers hardware and software designs to tackle the purposes. Four environmental sensors, i.e. temperature, dissolved oxygen (DO), electrical conductivity (EC), and oxygen reduction potential (ORP), were attached on the ROV to monitor water quality parameters. Data from these sensors were transfered wirelessly to a ground segment to be analyzed. The ROV was also equipped with an HD camera for video imagery, an inertial measurement unit (IMU) sensor to monitor the ROV’s attitude, two LED flashlights to give extra lumens during underwater operation, and a customized 3D printed gripper. The ROV was actuated with three brushless DC motors with silicone-based coating. The software design was a binary difference image processing under MATLAB environment to identify oil spills based on video captures from the camera. Experiments for the water quality parameter monitoring and image processing have been carried out under seawater, oil contaminated seawater, and gaseous seawater samples, to show the performance of the designed hardware and software.

Objectives: To describe a case of bilateral ear canal cholesteatomas in the setting of underlying first branchial cleft cyst anomalies and to review the pathophysiology underlying the development of external auditory canal cholesteatomas from branchial cleft cyst abnormalities. Methods and Results: We present a case study of a 61-year-old man who presented with chronic right-sided hearing loss and left-sided postauricular drainage. Clinical evaluation, radiographic work-up, and pathologic analysis confirmed a diagnosis of bilateral ear canal cholesteatoma in the setting of underlying first branchial cleft cyst anomalies. The patient’s clinical course, surgical treatment, and management considerations are discussed here. Conclusion: Ear canal cholesteatoma represents a rare clinical disease entity deserving a thorough initial assessment. Careful consideration of underlying diseases that result in chronic inflammation, such as branchial cleft lesions, should be included in the differential diagnosis of idiopathic canal cholesteatoma in the absence of prior otologic surgery or trauma.

The purpose of this chapter is to discuss the challenging and emerging technology namely “Wearable technology”. Based on bio-signal acquisition numerous applications in biomedical and biometrics are discussed. After highlighting some available systems in the market, the chapter focuses on a particular technology using an arm band. Biometrics is then considered from different points of view.

Designing a safe load-carrying component for mechanical structures requires sufficient information related to the distribution of loads, which is applied to the structure. One of the main design criteria is the level of stress. In some test cases, measuring the stress directly becomes very difficult due to a complex geometry for instance. In this case, the measurement of the physical displacement of the structure, which is known as strain (e) facilitates this procedure. The accurate strain gauges are mostly sensible and several factors can affect the measurement performance. It is obvious that the resistance tolerances and strain that induced during the application of the gauge, generate some initial offset voltage without the presence of forces. In addition, long lead wires can add resistance to the arm of the circuit bridge, which adds an offset error and desensitizes the output of the bridge. Hence, understanding the effects of significant parameters for analyzing the data is considered valuable. In this paper, the influence of the temperature, the length of wires and the set point of forces on the strain measurement are experimentally investigated at three levels. Furthermore, the design of experiment and related tools such as Taguchi and signal to noise ratio are employed to reduce the errors and uncertainty through the measurement process. Noise can be related to controllable factors or uncontrollable factors, which are extraneous factors. Using the Taguchi method assists to provide a better control over the right set of controllable factors only, to determine the significant factors with their optimal levels. The results indicate that the temperature has a maximum contribution to the measurement of the strain with 76.35%, which is followed by the effects of length of wires and the point of application with 7.66% and 6.77%, respectively.

Salivary gland tumor (SGT) is a rare tumor type, which exhibits broad-spectrum phenotypic, biological, and clinical heterogeneity. Currently, the molecular mechanisms that cause SGT pathogenesis remain poorly understood. A lack of animal models that faithfully recapitulate the naturally occurring process of human SGTs has hampered research progress on this field. In this report, we developed an inducible keratin 5-driven conditional knockout mouse model to delete gene(s) of interest in murine salivary gland upon local RU486 delivery. We have deleted two major tumor suppressors, Pten, a negative regulator of the PI3K pathway, and Smad4, the central signaling mediator of TGFβ pathway, in the murine salivary gland. Our results have shown that deletion of either Pten or Smad4 in murine salivary gland resulted in pleomorphic adenomas, the most common tumor in human SGT patients. Deletion of both Pten and Smad4 in murine salivary gland developed several malignancies, with salivary adenoid cystic carcinoma (SACC) being the most frequently seen. Molecular characterization showed that SACC exhibited mTOR activation and TGFβ1 overexpression. Examination of human SGT clinical samples revealed that loss of Pten and Smad4 is common in human SACC samples, particularly in the most aggressive solid form, and is correlated with survival of SACC patients, highlighting the human relevance of the murine models. In summary, our results offer significant insight into synergistic role of Pten and Smad4 in SGT, providing a rationale for targeting mTOR and/or TGFβ signaling to control SGT formation and progression.

Abnormality of the driver's Bio-physiological parameters has great impact on the driver's capability, and the ability to control a vehicle; which may cause severe car accidents. In this paper, a novel system was developed to monitor the driver's health status through a Wearable Bio-Sensors Bracelet that detects heath emergency threatening situations. The system collects live bio-signals data through a Wearable Bio-Sensors Bracelet that is embedded with multiple Bio-sensors such as Electromyography (EMG), Electrocardiography (ECG), Electrodermal Activity (EDA), Accelerometer (ACC) and Temperature. A robotics rover car model has been used as a testing vehicle scenario. The developed system detects an emergency and takes control over the rover maneuver when the driver lost his capacity, and automatically avoids any obstacle by sensing the surrounding area. The system has been demonstrated in a prepared emergency scenario and verified the potential. This paper describes the design concept, system configuration, and the future prospect of the study.

Purpose To report 2 interventional cases of dedifferentiated chondrosarcoma with orbital involvement after radiotherapy performed in childhood and to review the literature on chondrosarcoma in the orbit following radiation treatment. Methods Retrospective analysis of medical records of 2 patients with chondrosarcoma of the orbits with review of the literature. Results The first patient developed chondrosarcoma of the orbital and maxillary sinus 36 years after external beam radiation therapy to the OS to treat retinoblastoma. The second patient developed a large orbital chondrosarcoma 35 years after external beam radiation therapy in the treatment of craniofacial fibrous dysplasia. Conclusions These cases highlight the risk of secondary chondrosarcoma in patients following radiotherapy and the importance of lifetime monitoring.

Targeted therapy development in head and neck squamous cell carcinoma (HNSCC) is challenging given the rarity of activating mutations. Additionally, HNSCC incidence is increasing related to human papillomavirus (HPV). We sought to develop an in vivo model derived from patients reflecting the evolving HNSCC epidemiologic landscape, and use it to identify new therapies. Primary and relapsed tumors from HNSCC patients, both HPV+ and HPV-, were implanted on mice, giving rise to 25 strains. Resulting xenografts were characterized by detecting key mutations, measuring protein expression by IHC and gene expression/pathway analysis by mRNA-sequencing. Drug efficacy studies were run with representative xenografts using the approved drug cetuximab as well as the new PI3K inhibitor PX-866. Tumors maintained their original morphology, genetic profiles and drug susceptibilities through serial passaging. The genetic makeup of these tumors was consistent with known frequencies of TP53, PI3KCA, NOTCH1 and NOTCH2 mutations. Because the EGFR inhibitor cetuximab is a standard HNSCC therapy, we tested its efficacy and observed a wide spectrum of efficacy. Cetuximab-resistant strains had higher PI3K/Akt pathway gene expression and protein activation than cetuximab-sensitive strains. The PI3K inhibitor PX-866 had anti-tumor efficacy in HNSCC models with PIK3CA alterations. Finally, PI3K inhibition was effective in two cases with NOTCH1 inactivating mutations. In summary, we have developed an HNSCC model covering its clinical spectrum whose major genetic alterations and susceptibility to anticancer agents represent contemporary HNSCC. This model enables to prospectively test therapeutic-oriented hypotheses leading to personalized medicine.

Sinonasal malignant neoplasms comprise only 3% of all head and neck malignancies. Synchronous and metachronous tumors of the head and neck have been described, but rarely have there been reports of a single tumor with two distinct histologies. Here, we describe a case of a sinonasal malignant neoplasm with two distinct histologies. A case report and literature review was performed. We present a case of paranasal sinus neoplasm involving two malignant cell types. An 83-year-old woman presented with a 2-year history of symptoms suggestive of chronic sinusitis, which included nasal congestion and intermittent midface pressure. More recently, her symptoms progressed with the development of left-side epistaxis and she was found to have a mass in the left maxillary and ethmoid regions. A biopsy of the maxillary sinus mass revealed a moderately differentiated squamous cell carcinoma (SCC). She underwent complete resection of the lesion through an extended endoscopic approach. Final pathological analysis showed a malignant neoplasm with two distinct malignant morphologies; a moderately differentiated SCC and small cell neuroendocrine carcinoma. Appropriate diagnosis and treatment of head and neck malignancy depends on accurate tumor classification and staging. We present a case of a sinonasal tumor with two distinct malignant entities and review the available literature on the subject. Additionally, we discuss the etiologic theories and challenges in planning the optimal approach to management in this scenario.

This unique reference provides a comprehensive guide to pediatric head and neck pathology in patients up to the age of 21. Chapters take a clinicopathologic approach, offering insight into the pathobiology, diagnosis and treatment of both common and rare disorders. Imaging studies and immunohistochemical techniques are discussed alongside accepted and emerging molecular tools. The authors' holistic approach ensures coverage of the surgical management principles that pathologists must understand, particularly when called upon to diagnose odontogenic tumors and cysts, as well as benign and malignant salivary gland neoplasms. The book is richly illustrated in color throughout. Each copy of the printed book is packaged with a password, providing online access to the book's text and image library. Written by leaders in head and neck pathology and surgery, this is an essential guide to solving the diagnostic dilemmas that pathologists and clinicians encounter in the assessment of pediatric head and neck disease.