Search results for: facial expression production

Authors: Lanchi Xie, Zhihui Li, Zhigang Li, Guiqiang Wang, Lei Xu, Yuwen Yan

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Image-based facial features can be classified into category recognition features and individual recognition features. Current automated face recognition systems extract a specific feature vector of different dimensions from a facial image according to their pre-trained neural network. However, to improve the efficiency of parameter calculation, an algorithm generally reduces the image details by pooling. The operation will overlook the details concerned much by forensic experts. In our experiment, we adopted a variety of face recognition algorithms based on deep learning, compared a large number of naturally collected face images with the known data of the same person's frontal ID photos. Downscaling and manual handling were performed on the testing images. The results supported that the facial recognition algorithms based on deep learning detected structural and morphological information and rarely focused on specific markers such as stains and moles. Overall performance, distribution of genuine scores and impostor scores, and likelihood ratios were tested to evaluate the accuracy of biometric systems and forensic experts. Experiments showed that the biometric systems were skilled in distinguishing category features, and forensic experts were better at discovering the individual features of human faces. In the proposed approach, a fusion was performed at the score level. At the specified false accept rate, the framework achieved a lower false reject rate. This paper contributes to improving the interpretability of the objective method of facial comparison and provides a novel method for human-machine collaboration in this field.

Keywords: likelihood ratio, automated facial recognition, facial comparison, biometrics

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Authors: Zunjarrao Kadam, Vikas Minchekar

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The facial recognition is an important task in criminal investigation procedure. The security guards-constantly watching the persons-can help to identify the suspected accused. The forensic psychologists are tackled such cases in the criminal justice system. The security personnel may loss their ability to correctly identify the persons due to constant stress while performing the duty. The present study aimed at to identify the effect of experimentally induced stress on facial recognition ability of security personnel’s. For this study 50, security guards from Sangli, Miraj & Jaysingpur city of the Maharashtra States of India were recruited in the experimental study. The randomized two group design was employed to carry out the research. In the initial condition twenty identity card size photographs were shown to both groups. Afterward, artificial stress was induced in the experimental group through the difficultpuzzle-solvingtask in a limited period. In the second condition, both groups were presented earlier photographs with another additional thirty new photographs. The subjects were asked to recognize the photographs which are shown earliest. The analyzed data revealed that control group has ahighest mean score of facial recognition than experimental group. The results were discussed in the present research.

Keywords: experimentally induced stress, facial recognition, cognition, security personnel

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Authors: Peter. M. Kusen, Georg Wandrey, Christopher Probst, Dietrich Kohlheyer, Jochen Buchs, Jorg Pietruszkau

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Light as a stimulus provides the capability to develop regulation techniques for customizable gene expression. A great advantage is the extremely flexible and accurate dosing that can be performed in a non invasive and sterile manner even for high throughput technologies. Therefore, light regulation in a multiwell microbioreactor system was realized providing the opportunity to control gene expression with outstanding complexity. A light-regulated gene expression system in Saccharomyces cerevisiae was designed applying the strategy of caged compounds. These compounds are photo-labile protected and therefore biologically inactive regulator molecules which can be reactivated by irradiation with certain light conditions. The “caging” of a repressor molecule which is consumed after deprotection was essential to create a flexible expression system. Thereby, gene expression could be temporally repressed by irradiation and subsequent release of the active repressor molecule. Afterwards, the repressor molecule is consumed by the yeast cells leading to reactivation of gene expression. A yeast strain harboring a construct with the corresponding repressible promoter in combination with a fluorescent marker protein was applied in a Photo-BioLector platform which allows individual irradiation as well as online fluorescence and growth detection. This device was used to precisely control the repression duration by adjusting the amount of released repressor via different irradiation times. With the presented screening platform the regulation of complex expression procedures was achieved by combination of several repression/derepression intervals. In particular, a stepwise increase of temporally-constant expression levels was demonstrated which could be used to study concentration dependent effects on cell functions. Also linear expression rates with variable slopes could be shown representing a possible solution for challenging protein productions, whereby excessive production rates lead to misfolding or intoxication. Finally, the very flexible regulation enabled accurate control over the expression induction, although we used a repressible promoter. Summing up, the continuous online regulation of gene expression has the potential to synchronize gene expression levels to optimize metabolic flux, artificial enzyme cascades, growth rates for co cultivations and many other applications addicted to complex expression regulation. The developed light-regulated expression platform represents an innovative screening approach to find optimization potential for production processes.

Keywords: caged-compounds, gene expression regulation, optogenetics, photo-labile protecting group

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Authors: D. P. Gangwar

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Identification of human through facial images has got great importance in forensic science. The video recordings, CCTV footage, passports, driver licenses and other related documents are invariably sent to the laboratory for comparison of the questioned photographs as well as video recordings with suspected photographs/recordings to prove the identity of a person. More than 300 questioned and 300 control photographs received in actual crime cases, received from various investigation agencies, have been compared by me so far using various familiar analysis and comparison techniques such as Holistic comparison, Morphological analysis, Photo-anthropometry and superimposition. On the basis of findings obtained during the examination huge photo exhibits, a realistic and comprehensive technique has been proposed which could be very useful for forensic.

Keywords: CCTV Images, facial features, photo-anthropometry, superimposition

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Authors: P. S. Jagadeesh Kumar, Yang Yung, Wenli Hu

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Speech emotion classification is a dominant research field in finding a sturdy and profligate classifier appropriate for different real-life applications. This effort accentuates on classifying different emotions from speech signal quarried from the features related to pitch, formants, energy contours, jitter, shimmer, spectral, perceptual and temporal features. Tensor deep stacking neural networks were supported to examine the factors that influence the classification success rate. Facial electromyography signals were composed of several forms of focuses in a controlled atmosphere by means of audio-visual stimuli. Proficient facial electromyography signals were pre-processed using moving average filter, and a set of arithmetical features were excavated. Extracted features were mapped into consistent emotions using bilinear mapping. With facial electromyography signals, a database comprising diverse emotions will be exposed with a suitable fine-tuning of features and training data. A success rate of 92% can be attained deprived of increasing the system connivance and the computation time for sorting diverse emotional states.

Keywords: speech emotion classification, tensor deep stacking neural networks, facial electromyography, bilinear mapping, audio-visual stimuli

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Authors: Islam Nowisser, Noha Farag, Mohamed El Azizi

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Helicobacter pylori is a highly important human pathogen which inhabits about 50% of the population worldwide. Infection with this bacteria is very hard to treat, with high probability of recurrence. H. pylori causes severe gastric diseases, including peptic ulcer, gastritis, and gastric cancer, which has been linked to chronic inflammation. The infection has been reported to be associated with high levels of pro-inflammatory cytokines, especially IL-1β and TNF-α. The aim of the current study is to investigate the molecular mechanisms by which H. pylori activates NLRP3 inflammasome and its contribution to Il-1 β production in an innate cellular model. H. pylori PMSS1 and G27 standard strains, as well as the PMSS1 isogenic mutant strain PMSS1ΔVacA and G27ΔVacA, G27ΔCagA in addition to clinical isolates obtained from biopsy samples from the antrum and corpus mucosa of chronic gastritis patients, were used to establish infection in RAW-264.7 macrophages. The production levels of TNF-α and IL-1β was assessed using ELISA. Since expression of these cytokines is often regulated by the transcription factor complex, nuclear factor-kB (NF-kB), the activation of NF-κB in H. pylori infected cells was also evaluated by luciferase assay. Genomic DNA was extracted from bacterial cultures of H. pylori clinical isolates as well as the standard strains and their corresponding mutants, where they were evaluated for the cagA pathogenicity island and vacA expression. The correlation between these findings and expression of the cagA Pathogenicity Island and vacA in the bacteria was also investigated. The results showed IL-1β, and TNF-α production significantly increased in raw macrophages following H. pylori infection. The cagA+ and vacA+ H. pylori strains induced significant production of IL-1β compared to cagA- and vacA- strains. The activation pattern of NF-κB was correlated in the isolates to their cagA and vacA expression profiles. A similar finding could not be confirmed for TNF-α production. Our study shows the ability of H. pylori to activate NF-kB and induce significant IL-1β production as a possible mechanism for the augmented inflammatory response seen in subjects infected with cagA+ and vacA+ H. pylori strains that would lead to the progression to more severe form of the disease.

Keywords: Helicobacter pylori, IL-1β, inflammatory cytokines, nuclear factor KB, TNF-α

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Authors: J. K. Adedeji, M. O. Oyekanmi

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This paper has critically examined the use of Machine Learning procedures in curbing unauthorized access into valuable areas of an organization. The use of passwords, pin codes, user’s identification in recent times has been partially successful in curbing crimes involving identities, hence the need for the design of a system which incorporates biometric characteristics such as DNA and pattern recognition of variations in facial expressions. The facial model used is the OpenCV library which is based on the use of certain physiological features, the Raspberry Pi 3 module is used to compile the OpenCV library, which extracts and stores the detected faces into the datasets directory through the use of camera. The model is trained with 50 epoch run in the database and recognized by the Local Binary Pattern Histogram (LBPH) recognizer contained in the OpenCV. The training algorithm used by the neural network is back propagation coded using python algorithmic language with 200 epoch runs to identify specific resemblance in the exclusive OR (XOR) output neurons. The research however confirmed that physiological parameters are better effective measures to curb crimes relating to identities.

Keywords: biometric characters, facial recognition, neural network, OpenCV

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Authors: W. Linthicum-Blackhorse, P. Martens

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This present study seeks to discover attitudinal commonalities and differences within a musician population relative to the communication of emotion via music. We hypothesized that instrument type, as well as age and gender, would bear significantly on musicians’ opinions. A survey was administered to 178 participants; 152 were current music majors (mean age 20.3 years, 62 female) and 26 were adult participants in a community choir (mean age 54.0 years, 12 female). The adult participants were all vocalists, while student participants represented the full range of orchestral instruments. The students were grouped by degree program, (performance, music education, or other) and instrument type (voice, brass, woodwinds, strings, percussion). The survey asked 'How important are each of the following areas to you for portraying emotion in music?' Participants were asked to rate each of 15 items on a scale of 1 (not at all important) to 10 (very important). Participants were also instructed to leave blank any item that they did not understand. The 15 items were: dynamic contrast, overall volume, phrasing, facial expression, staging (placement), pitch accuracy, tempo changes, bodily movement, your mood, your attitude, vibrato, rubato, stage/room lighting, clothing type, and clothing color. Contrary to our hypothesis, there was no overall effect of gender or age, and neither did any single response item show a significant difference due to these subject parameters. Among the student participants, however, one-way ANOVA revealed a significant effect of degree program on the rated importance of four items: dynamic contrast, tempo changes, vibrato, and rubato. Significant effects of instrument type were found in the responses to eight items: facial expression, staging, body movement, vibrato, rubato, lighting, clothing type, and clothing color. Post hoc comparisons (Tukey) show that some variation follows from obvious differences between instrument types (e.g. string players are more concerned with vibrato than everyone but woodwind players; vocalists are significantly more concerned with facial expression than everyone but string players), but other differences could point to communal mindsets toward vicarious cues within instrument type. These mindsets could be global (e.g. brass players deeming body movement significantly less important than string players, being less often featured as soloists and appearing less often at the front of the stage) or local (e.g. string players being significantly more concerned than all other groups about both clothing color and type, perhaps due to the strongly-expressed opinions of specific teachers). Future work will attempt to identify the source of these self-appraisals, whether enculturated via explicit pedagogy, or whether absorbed from individuals' observations and performance experience.

Keywords: performance, vicarious cues, communication, emotion

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Tetyana Baydyk, Ernst Kussul, Sandra Bonilla Meza

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There are many articles that attempt to establish the role of different facial fragments in face recognition. Various approaches are used to estimate this role. Frequently, authors calculate the entropy corresponding to the fragment. This approach can only give approximate estimation. In this paper, we propose to use a more direct measure of the importance of different fragments for face recognition. We propose to select a recognition method and a face database and experimentally investigate the recognition rate using different fragments of faces. We present two such experiments in the paper. We selected the PCNC neural classifier as a method for face recognition and parts of the LFW (Labeled Faces in the Wild) face database as training and testing sets. The recognition rate of the best experiment is comparable with the recognition rate obtained using the whole face.

Keywords: face recognition, labeled faces in the wild (LFW) database, random local descriptor (RLD), random features

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Authors: Mukesh N. Kher, Anju P. Kunjadia, Dev S. Nauriyal, Chaitanya G. Joshi, Navin R. Sheth, Vaibhav D. Bhatt

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In-vivo immunotherapeutic potential on cytokines production and antibacterial activity of a topical herbal gel was evaluated in two breeds of cattle in bovine subclinical mastitis. The response to treatment was evaluated by enumerating somatic cell count (SCC), determining total bacterial count and studying the expression of different cytokines like (interleukin 6, 8, 12, GMCSF, interferon–γ and TNF‑α). The pre‑ and post‑treatment SCC in mastitic quarters did not differ statistically-significantly. However, total bacterial count declined significantly from day 0 onwards in both the breeds. Significant differences (P < 0.01) were observed in all types of cytokines production on day 0, 5, and 21 post last treatments in both the breeds. The comparison of cytokine expression profiles between crossbred and Gir cattle affirmed a significant difference in expression of IL-6 and TNF-α. The topical herbal gel showed immunomodulatory and antimicrobial activities in subclinical mastitis, and therefore the work supports its use as substitute herbal therapy against subclinical mastitis in bovines.

Keywords: antibacterial activity, immunomodulation, herbal gel, subclinical mastitis

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Authors: Brittany Richardson, Ying Wang

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For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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Authors: Sevil Yildiz

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Audio visual communication is a type of collective expression. Collective expression activity informs the masses, gives direction to opinions and establishes public opinion. Due to these characteristics, audio visual communication must be subjected to special restrictions. This has been stipulated in both the Constitution and the European Human Rights Agreement. This paper aims to review freedom of expression and its restriction in audio visual media. For this purpose, the authorisation of the Radio and Television Supreme Council to impose sanctions as an independent administrative authority empowered to regulate the field of audio visual communication has been reviewed with regard to freedom of expression and its limits.

Keywords: audio visual media, freedom of expression, its limits, radio and television supreme council

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Authors: Priya Saha, Sourav Dey Roy Jr., Debotosh Bhattacharjee, Mita Nasipuri, Barin Kumar De, Mrinal Kanti Bhowmik

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Biometric face recognition technology (FRT) has gained a lot of attention due to its extensive variety of applications in both security and non-security perspectives. It has come into view to provide a secure solution in identification and verification of person identity. Although other biometric based methods like fingerprint scans, iris scans are available, FRT is verified as an efficient technology for its user-friendliness and contact freeness. Accurate facial feature localization plays an important role for many facial analysis applications including biometrics and emotion recognition. But, there are certain factors, which make facial feature localization a challenging task. On human face, expressions can be seen from the subtle movements of facial muscles and influenced by internal emotional states. These non-rigid facial movements cause noticeable alterations in locations of facial landmarks, their usual shapes, which sometimes create occlusions in facial feature areas making face recognition as a difficult problem. The paper proposes a new hybrid based technique for automatic landmark detection in both neutral and expressive frontal and near frontal face images. The method uses the concept of thresholding, sequential searching and other image processing techniques for locating the landmark points on the face. Also, a Graphical User Interface (GUI) based software is designed that could automatically detect 16 landmark points around eyes, nose and mouth that are mostly affected by the changes in facial muscles. The proposed system has been tested on widely used JAFFE and Cohn Kanade database. Also, the system is tested on DeitY-TU face database which is created in the Biometrics Laboratory of Tripura University under the research project funded by Department of Electronics & Information Technology, Govt. of India. The performance of the proposed method has been done in terms of error measure and accuracy. The method has detection rate of 98.82% on JAFFE database, 91.27% on Cohn Kanade database and 93.05% on DeitY-TU database. Also, we have done comparative study of our proposed method with other techniques developed by other researchers. This paper will put into focus emotion-oriented systems through AU detection in future based on the located features.

Keywords: biometrics, face recognition, facial landmarks, image processing

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Authors: Kanza Tahir, Mubassar Fida, Rashna Hoshang Sukhia

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Background/Objective: A contemporary concept states that dental midline deviation towards the direction of facial flow line (FFL) can mask the compromised smile esthetics. This study aimed to identify a range of midline deviations that can be perceived towards or away from the FFL influencing smile esthetics. Materials and methods: A cross-sectional study was conducted using a frontal smile photograph of an adult female. The photograph was altered on Adobe Photoshop software into six different photographs by deviating the dental midlines towards and away from the FFL. A constant deviation of the chin towards the left side was incorporated in all the photographs. Forty-three laypersons (LP)and dental professionals (DPs) evaluated those photographs onVisual Analog Scale (VAS). An Independent t-test was used to compare the perception of dental midline deviation between LP and DPs. Simple linear regression was run to identify the factors associated with the VAS scoring. Results: A statistically significant difference was observed for picture two with 4 mm towards FFL in the perception of midline deviation between LP and DPs. LP could not perceive the midline deviations up to 4 mm, while DPs were able to perceive deviations above 2 mm. Age was positively associated with the VAS score, while the female gender had a negative association. Limitations: Only one component of mini-esthetics was studied. This study did not include an ideal picture for comparison. Only one female subject was studied of normal facial type. Conclusions: 2-4 mm of midline deviation towards the facial flow line can be tolerated by laypersons and dental professionals.

Keywords: midline, facial flow line, smile esthetics, female

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Authors: Vandana Singh, Subash Singh

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Introduction: Oral squamous cell carcinoma is the most common malignant tumor of the oral cavity. Normally the death of cell and the growth are active processes and depend not only on external factors but also on the expression of genes like Bcl-2, which activate and inhibit apoptosis. The term Bcl-2 is an acronym for B-cell lymphoma/ leukemia -2 genes. Objectives: An attempt was made to evaluate Bcl-2 oncoprotein expression in patients with oral precancer and cancer and to assess possible correlation between Bcl-2 oncoprotein expression and clinicopathological features of oral precancer and cancer. Material and Methods: This is a selective prospective clinical and immunohistochemical study. Clinicopathological examination is correlated with immunohistochemical findings. The immunolocalization of Bcl-2 protein is performed using the labeled streptavidin biotin (LSAB) method. To visualize the reaction, 3, 3-diaminobenzidine (DAB) is used. Results: Bcl-2 expression was positive in 11 [36.66 %, low Bcl-2 expression 3 (10.00 %), moderate Bcl-2 expression 7 (23.33 %), and high Bcl-2 expression 1 (3.33 %)] oral cancer cases and in 14 [87.50 %, low expression 8 (50 %), moderate expression 6 (37.50 %)] precancer cases. Conclusion: On the basis of the results of our study we conclude that positive Bcl-2 expression may be an indicator of poor prognosis in oral cancer and precancer. Relevance: It has been reported that there is deregulation of Bcl-2 expression during progression from oral epithelial dysplasia to squamous cell carcinoma. It can be used for revealing progression of epithelial dysplasia to malignancy and as a prognostic marker in oral precancer and cancer.

Keywords: BcL-2, immunohistochemistry, oral cancer, oral precancer

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Authors: Akulov M. A., Orlova O. R., Zaharov V. O., Tomskij A. A.

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Introduction: One of the common postoperative complications of posterior cranial fossa (PCF) and cerebello-pontine angle tumor treatment is a facial nerve palsy, which leads to multiple and resistant to treatment impairments of mimic muscles structure and functions. After 4-6 months after facial nerve palsy with insufficient therapeutic intervention patients develop a postparalythic syndrome, which includes such symptoms as mimic muscle insufficiency, mimic muscle contractures, synkinesis and spontaneous muscular twitching. A novel method of treatment is the use of a recent local neuromuscular blocking agent– botulinum toxin A (BTA). Experience of BTA treatment enables an assumption that it can be successfully used in late facial nerve palsy complications to significantly increase quality of life of patients. Study aim. To evaluate the efficacy of botulinum toxin A (BTA) (Xeomin) treatment in patients with late facial nerve palsy complications. Patients and Methods: 31 patients aged 27-59 years 6 months after facial nerve palsy development were evaluated. All patients received conventional treatment, including massage, movement therapy etc. Facial nerve palsy developed after acoustic nerve tumor resection in 23 (74,2%) patients, petroclival meningioma resection – in 8 (25,8%) patients. The first group included 17 (54,8%) patients, receiving BT-therapy; the second group – 14 (45,2%) patients continuing conventional treatment. BT-injections were performed in synkinesis or contracture points 1-2 U on injured site and 2-4 U on healthy side (for symmetry). Facial nerve function was evaluated on 2 and 4 months of therapy according to House-Brackman scale. Pain syndrome alleviation was assessed on VAS. Results: At baseline all patients in the first and second groups demonstrated аpostparalytic syndrome. We observed a significant improvement in patients receiving BTA after only one month of treatment. Mean VAS score at baseline was 80,4±18,7 and 77,9±18,2 in the first and second group, respectively. In the first group after one month of treatment we observed a significant decrease of pain syndrome – mean VAS score was 44,7±10,2 (р<0,01), whereas in the second group VAS score was as high as 61,8±9,4 points (p>0,05). By the 3d month of treatment pain syndrome intensity continued to decrease in both groups, but, the first group demonstrated significantly better results; mean score was 8,2±3,1 and 31,8±4,6 in the first and second group, respectively (р<0,01). Total House-Brackman score at baseline was 3,67±0,16 in the first group and 3,74±0,19 in the second group. Treatment resulted in a significant symptom improvement in the first group, with no improvement in the second group. After 4 months of treatment House-Brockman score in the first group was 3,1-fold lower, than in the second group (р<0,05). Conclusion: Botulinum toxin injections decrease postparalytic syndrome symptoms in patients with facial nerve palsy.

Keywords: botulinum toxin, facial nerve palsy, postparalytic syndrome, synkinesis

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Authors: Katerina H. Takova, Ivan N. Minkov, Gergana G. Zahmanova

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Molecular farming is the production of recombinant proteins in plants with the aim to use the protein as a purified product, crude extract or directly in the planta. Plants gain more attention as expression systems compared to other ones due to the cost effective production of pharmaceutically important proteins, appropriate post-translational modifications, assembly of complex proteins, absence of human pathogens to name a few. In addition, transient expression in plant leaves enables production of recombinant proteins within few weeks. Hepatitis E virus (HEV) is a causative agent of acute hepatitis. HEV causes epidemics in developing countries and is primarily transmitted through the fecal-oral route. Presently, all efforts for development of Hepatitis E vaccine are focused on the Open Read Frame 2 (ORF2) capsid protein as it contains epitopes that can induce neutralizing antibodies. For our purpose, we used the CMPV-based vector-pEAQ-HT for transient expression of HEV ORF2 in Nicotiana benthamina. Different molecular analysis (Western blot and ELISA) showed that HEV ORF2 capsid protein was expressed in plant tissue in high-yield up to 1g/kg of fresh leaf tissue. Electron microscopy showed that the capsid protein spontaneously assembled in low abundance virus-like particles (VLPs), which are highly immunogenic structures and suitable for vaccine development. The expressed protein was recognized by both human and swine HEV positive sera and can be used as a diagnostic reagent for the detection of HEV infection. Production of HEV capsid protein in plants is a promising technology for further HEV vaccine investigations. Here, we reported for a rapid high-yield transient expression of a recombinant protein in plants suitable for vaccine production as well as a diagnostic reagent. Acknowledgments -The authors’ research on HEV is supported with grants from the Project PlantaSYST under the Widening Program, H2020 as well as under the UK Biotechnological and Biological Sciences Research Council (BBSRC) Institute Strategic Programme Grant ‘Understanding and Exploiting Plant and Microbial Secondary Metabolism’ (BB/J004596/1). The authors want to thank Prof. George Lomonossoff (JIC, Norwich, UK) for his contribution.

Keywords: hepatitis E virus, plant molecular farming, transient expression, vaccines

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Authors: Alexander A. Tokmakov

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Cell-free protein synthesis is widely used to synthesize recombinant proteins. It allows genome-scale expression of various polypeptides under strictly controlled uniform conditions. However, only a minor fraction of all proteins can be successfully expressed in the systems of protein synthesis that are currently used. The factors determining expression success are poorly understood. At present, the vast volume of data is accumulated in cell-free expression databases. It makes possible comprehensive bioinformatics analysis and identification of multiple features associated with successful cell-free expression. Here, we describe an approach aimed at identification of multiple physicochemical and structural properties of amino acid sequences associated with protein solubility and aggregation and highlight major correlations obtained using this approach. The developed method includes: categorical assessment of the protein expression data, calculation and prediction of multiple properties of expressed amino acid sequences, correlation of the individual properties with the expression scores, and evaluation of statistical significance of the observed correlations. Using this approach, we revealed a number of statistically significant correlations between calculated and predicted features of protein sequences and their amenability to cell-free expression. It was found that some of the features, such as protein pI, hydrophobicity, presence of signal sequences, etc., are mostly related to protein solubility, whereas the others, such as protein length, number of disulfide bonds, content of secondary structure, etc., affect mainly the expression propensity. We also demonstrated that amenability of polypeptide sequences to cell-free expression correlates with the presence of multiple sites of post-translational modifications. The correlations revealed in this study provide a plethora of important insights into protein folding and rationalization of protein production. The developed bioinformatics approach can be of practical use for predicting expression success and optimizing cell-free protein synthesis.

Keywords: bioinformatics analysis, cell-free protein synthesis, expression success, optimization, recombinant proteins

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Authors: Hashaam Akhtar

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IFNλR1 and IL10R2 collectively construct a heterodimer, which is an acknowledged functional receptor for all type III interferons (IFNs). Expression of IFNλR1 is highly tissue specific, which can help in making type III IFNs a drug of choice as comparable to its analogue, type I IFNs, for treating hepatitis C in the near future. Although, expression of IFNλR1 also varies with the concentration of type I IFNs, but in this study it was shown that the expression of IFNλR1 varies with the protein titers of IFN-α, IFN-λ3 and the newly discovered IFN-λ4. High dosage of IFN-α reduces the expression of IFNλR1 in HepG2 cells, which can affect the antiviral activity of type III IFNs in vivo. We premeditated an experimental strategy to differentiate monocytes into dendritic cells (DCs), type I and type II macrophages in vitro and quantified the expression of the IFNλR1 by qPCR. The exposure of newly discovered IFN-λ4 to macrophages and DCs also raised the expression of its own receptor, which shows that expression of IFN-λ4 protein in hepatitis C patient may augment type I treatment and help ease off viral titers. The results of this study may contribute in some understanding towards the mechanisms involved in the selective expression of IFNLR1 and exceptionalities associated with the receptor.

Keywords: IFNLR1, Interferon Lambda 4 (IFN-λ4), Mononuclear Phagocyte Cells (MPCs), expression

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Authors: K. Mardaleishvili, G. Loladze, G. Shatirishivili, D. Chakhunashvili, A. Vishnevskaya, Z. Kakabadze

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Benign osteoblastoma is a benign tumor of the bone, usually affecting the vertebrae and long tubular bones. It is a rarely seen tumor of the facial bones. The authors present a case of a 28-year-old male patient with a tumor in mandibular body. The lesion was radically resected and histological analysis of the specimen demonstrated features typical of a benign osteoblastoma. The defect of the jaw was reconstructed with titanium implants and decellularized and lyophilized cattle bone matrix with mesenchymal bone marrow stem cells transplantation. This presentation describes the procedures for rehabilitating a patient with decellularized bone scaffold in the region of the face, recovering the facial contours and esthetics of the patient.

Keywords: facial bones, osteoblastoma, stem cells, transplantation

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Authors: Yazun Jarrar

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Smoking has effect on platelet aggregation and the activity of anti-platelet drugs. The chemical 20-hydroxyeicosatetraenoic acid (20-HETE) is a cardiotoxic arachidonic acid metabolite which increases platelet aggregation. In this study, we investigated the influence of cigarette smoking on 20-HETE levels and protein expression of 20-HETE producing enzyme CYP4A11 in isolated platelets from smoker and non-smoker volunteers. The protein expression and 20-HETE levels were analyzed using immunoblot and High-Performance Liquid Chromatography with Mass Spectrometry (HPL-MS) assays. The results showed that 20-HETE level was higher significantly among smokers than non-smokers (t-test, p-value<0.05). The protein expression of CYP4A11 was significantly higher (t-test, p-value<0.05) among the platelets of smokers. We concluded that cigarette smoking increased the level of platelet activator 20-HETE through increasing the protein expression of CYP4A11. These findings may increase the understanding of smoking-drug interaction during antiplatelets therapy.

Keywords: smoking, 20-HETE, CYP4A11, platelet

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Authors: Eun Jung Sohn, Hwan Tae Park

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Autophagy is a cellular response to stress or environment on cell survival. Here, we investigated the role of ectopic expression of miR 200c-3p in autophagy. Ectopic expression of miR 200c-3p increased the expression of IRE1alpha, ATF6 and CHOP by western blot and RT-qPCR. Furthermore, the level of microRNA 200c-3p was enhanced by treatment of TG or overexpression of GRP 78. Also, ectopic expression of miR200c-3p increased the LC3 II expression by western blot and RT-qPCR. Also, we found that western blot assay showed that miR200c-3p inhibitor was blocked the starvation–induced LC3II levels. Furthermore, starvation stress increased the level of miR200c-3p in different kinetics. Ectopic expression of miR200c-3p attenuated LC3II expression in IRE1 siRNA transfected PC3 cells. Here, we first demonstrate that miR200c-3p regulates autophagy via ER stress pathway.

Keywords: Autophagy, ER stress, LC3II, miR200c-3p

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Authors: Dake Xiong, Ben Hankamer, Ian Ross

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The most urgent challenge of our time is to replace the depleting resources of fossil fuels by sustainable environmentally friendly alternatives. Hydrogen is a promising CO2-neutral fuel for a more sustainable future especially when produced photo-biologically. Hydrogen can be photosynthetically produced in unicellular green alga like Chlamydomonas reinhardtii, catalysed by the inducible highly active and bidirectional [FeFe]-hydrogenase enzymes (HydA). However, evolutionary and physiological constraints severely restrict the hydrogen yield of algae for industrial scale-up, mainly due to its competition among other metabolic pathways on photosynthetic electrons. Among them, a major challenge to be resolved is the inferior competitiveness of hydrogen production (catalysed by HydA) with NADPH production (catalysed by ferredoxin-NADP+-reductase (FNR)), which is essential for cell growth and takes up ~95% of photosynthetic electrons. In this work, the in vivo hydrogen production efficiency of mutants with ferredoxin-hydrogenase (Fd*-HydA1*) fusion protein construct, where the electron donor ferredoxin (Fd*) is fused to HydA1* and expressed in the model organism C. reinhardtii was investigated. Once Fd*-HydA1* fusion gene is expressed in algal cells, the fusion enzyme is able to draw the redistributed photosynthetic electrons and use them for efficient hydrogen production. From preliminary data, mutants with Fd*-HydA1* transgene showed a ~2-fold increase in the photosynthetic hydrogen production rate compared with its parental strain, which only possesses the native HydA in vivo. Therefore, a solid method of having more efficient hydrogen production in microalgae can be achieved through the expression of the synthetic enzymes.

Keywords: Chlamydomonas reinhardtii, ferredoxin, fusion protein, hydrogen production, hydrogenase

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Authors: Choki, Supatchai Boonpratham, Suwannee Luppanapornlarp

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The objective of this study was to find a correlation between cephalometric measurements and visual perception of facial profile in skeletal type II patients. In this study, 250 lateral cephalograms of female patients from age, 20 to 22 years were analyzed. The profile outlines of all the samples were hand traced and transformed into silhouettes by the principal investigator. Profile ratings were done by 9 orthodontists on Visual Analogue Scale from score one to ten (increasing level of convexity). 37 hard issue and soft tissue cephalometric measurements were analyzed by the principal investigator. All the measurements were repeated after 2 weeks interval for error assessment. At last, the rankings of visual perceptions were correlated with cephalometric measurements using Spearman correlation coefficient (P < 0.05). The results show that the increase in facial convexity was correlated with higher values of ANB (A point, nasion and B point), AF-BF (distance from A point to B point in mm), L1-NB (distance from lower incisor to NB line in mm), anterior maxillary alveolar height, posterior maxillary alveolar height, overjet, H angle hard tissue, H angle soft tissue and lower lip to E plane (absolute correlation values from 0.277 to 0.711). In contrast, the increase in facial convexity was correlated with lower values of Pg. to N perpendicular and Pg. to NB (mm) (absolute correlation value -0.302 and -0.294 respectively). From the soft tissue measurements, H angles had a higher correlation with visual perception than facial contour angle, nasolabial angle, and lower lip to E plane. In conclusion, the findings of this study indicated that the correlation of cephalometric measurements with visual perception was less than expected. Only 29% of cephalometric measurements had a significant correlation with visual perception. Therefore, diagnosis based solely on cephalometric analysis can result in failure to meet the patient’s esthetic expectation.

Keywords: cephalometric measurements, facial profile, skeletal type II, visual perception

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Authors: Koray U. Erbas

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Neural networks are appealing for many applications since they are able to learn complex non-linear relationships between input and output data. As the number of neurons and layers in a neural network increase, it is possible to represent more complex relationships with automatically extracted features. Nowadays Deep Neural Networks (DNNs) are widely used in Computer Vision problems such as; classification, object detection, segmentation image editing etc. In this work, Facial Emotion Recognition task is performed by proposed Convolutional Neural Network (CNN)-based DNN architecture using FER2013 Dataset. Moreover, the effects of different hyperparameters (activation function, kernel size, initializer, batch size and network size) are investigated and ablation study results for Pooling Layer, Dropout and Batch Normalization are presented.

Keywords: convolutional neural network, deep learning, deep learning based FER, facial emotion recognition

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Authors: Alhadi Bustaman, Soeganda Formalidin, Titin Siswantining

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DNA microarray technology is used to analyze thousand gene expression data simultaneously and a very important task for drug development and test, function annotation, and cancer diagnosis. Various clustering methods have been used for analyzing gene expression data. However, when analyzing very large and heterogeneous collections of gene expression data, conventional clustering methods often cannot produce a satisfactory solution. Biclustering algorithm has been used as an alternative approach to identifying structures from gene expression data. In this paper, we introduce a transform technique based on singular value decomposition to identify normalized matrix of gene expression data followed by Mixed-Clustering algorithm and the Lift algorithm, inspired in the node-deletion and node-addition phases proposed by Cheng and Church based on Agglomerative Hierarchical Clustering (AHC). Experimental study on standard datasets demonstrated the effectiveness of the algorithm in gene expression data.

Keywords: agglomerative hierarchical clustering (AHC), biclustering, gene expression data, lymphoma, singular value decomposition (SVD)

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Authors: Idan Chiyanzu, Maruping Mangena

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Crude glycerol, a major by-product from the transesterification of triacylglycerides with alcohol to biodiesel, is known to have a broad range of applications. For example, its bioconversion can afford a wide range of chemicals including alcohols, organic acids, hydrogen, solvents and intermediate compounds. In bacteria, the 2-oxoglutarate dioxygenase (2-OGD) enzymes are widely found among the Pseudomonas syringae species and have been recognized with an emerging importance in ethylene formation. However, the use of optimized enzyme function in recombinant systems for crude glycerol conversion to ethylene is still not been reported. The present study investigated the production of ethylene from crude glycerol using engineered E. coli MG1655 and JM109 strains. Ethylene production with an optimized expression system for 2-OGD in E. coli using a codon optimized construct of the ethylene-forming gene was studied. The codon-optimization resulted in a 20-fold increase of protein production and thus an enhanced production of the ethylene gas. For a reliable bioreactor performance, the effect of temperature, fermentation time, pH, substrate concentration, the concentration of methanol, concentration of potassium hydroxide and media supplements on ethylene yield was investigated. The results demonstrate that the recombinant enzyme can be used for future studies to exploit the conversion of low-priced crude glycerol into advanced value products like light olefins, and tools including recombineering techniques for DNA, molecular biology, and bioengineering can be used to allowing unlimited the production of ethylene directly from the fermentation of crude glycerol. It can be concluded that recombinant E.coli production systems represent significantly secure, renewable and environmentally safe alternative to thermochemical approach to ethylene production.

Keywords: crude glycerol, bioethylene, recombinant E. coli, optimization

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Authors: Laszlo Vari

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In the digital age, the spread of the mobile world and the nature of the cyberspace, offers many new opportunities for the prevalence of the fundamental right to free expression, and therefore, for free speech and freedom of the press; however, these new information communication technologies carry many new challenges. Defamation, censorship, fake news, misleading information, hate speech, breach of copyright etc., are only some of the violations, all of which can be derived from the harmful exercise of freedom of expression, all which become more salient in the internet. Here raises the question: how can we eliminate these problems, and practice our fundamental freedom rightfully? To answer this question, we should understand the elements and the characteristic of the nature of freedom of expression, and the role of the actors whose duties and responsibilities are crucial in the prevalence of this fundamental freedom. To achieve this goal, this paper will explore the European practice to understand instructions found in the case-law of the European Court of Human rights for the rightful exercise of freedom of expression.

Keywords: collision of rights, European case-law, freedom opinion and expression, media law, freedom of information, online expression

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Authors: Rasha Ali Dheyab

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In today's increasingly interconnected and technologically-driven world, communication has evolved beyond traditional verbal exchanges. This paper delves into the fascinating realm of multimodal communication, a dynamic field at the intersection of linguistics, gesture studies, and technology. The study of how humans convey meaning through a combination of spoken language, gestures, facial expressions, and digital platforms has gained prominence as our modes of interaction continue to diversify. This exploration begins by examining the foundational theories in linguistics and gesture studies, tracing their historical development and mutual influences. It further investigates the role of nonverbal cues, such as gestures and facial expressions, in augmenting and sometimes even altering the meanings conveyed by spoken language. Additionally, the paper delves into the modern technological landscape, where emojis, GIFs, and other digital symbols have emerged as new linguistic tools, reshaping the ways in which we communicate and express emotions. The interaction between traditional and digital modes of communication is a central focus of this study. The paper investigates how technology has not only introduced new modes of expression but has also influenced the adaptation of existing linguistic and gestural patterns in online discourse. The emergence of virtual reality and augmented reality environments introduces yet another layer of complexity to multimodal communication, offering new avenues for studying how humans navigate and negotiate meaning in immersive digital spaces. Through a combination of literature review, case studies, and theoretical analysis, this paper seeks to shed light on the intricate interplay between language, gesture, and technology in the realm of multimodal communication. By understanding how these diverse modes of expression intersect and interact, we gain valuable insights into the ever-evolving nature of human communication and its implications for fields ranging from linguistics and psychology to human-computer interaction and digital anthropology.

Keywords: multimodal communication, linguistics ., gesture studies., emojis., verbal communication., digital

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