Search results for: expression recognition

Authors: P. Shrivastava, A. Shukla, K. Verma, S. Rungta

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Parkinson's disease is a chronic neurological disorder that directly affects human gait. It leads to slowness of movement, causes muscle rigidity and tremors. Gait serve as a primary outcome measure for studies aiming at early recognition of disease. Using gait techniques, this paper implements efficient binary bat algorithm for an early detection of Parkinson's disease by selecting optimal features required for classification of affected patients from others. The data of 166 people, both fit and affected is collected and optimal feature selection is done using PSO and Bat algorithm. The reduced dataset is then classified using neural network. The experiments indicate that binary bat algorithm outperforms traditional PSO and genetic algorithm and gives a fairly good recognition rate even with the reduced dataset.

Keywords: parkinson, gait, feature selection, bat algorithm

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Authors: Hanan Mohamed Abd Elmoneim, Rawan Saleh AlJawi, Razan Saleh AlJawi, Aseel Abdullah AlMasoudi , Zyad Adnan Turkistani, Anas Abdulkarim Alkhoutani , Ohood Musaed AlJuhani , Hanan Attiyah AlZahrani

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Background Esophageal cancer is the eighth most common cancer worldwide. More than 90% of esophageal cancers are either squamous cell carcinoma or adenocarcinoma. Squamous dysplasia is a precancerous lesion for squamous cell carcinoma and Barrett's esophagus is the precancerous lesion for adenocarcinoma. Gastro-esophageal reflux disease (GERD) is the initiation factor for Barrett's esophagus. Cyclooxygenase-2 (COX-2) is a key enzyme in arachidonic metabolism. It appears to play an important role in gastrointestinal carcinogenesis. COX-2 activity may be a potential target for the prevention of cancer progression by selective COX-2 inhibitors, which decrease proliferation and increase apoptosis. Objectives To assess COX-2 expression in premalignant and malignant esophageal epitheliums changes and detect its roles in progression of these lesions. Materials and Methods We analyzed the expression of COX-2 immunohistochemically in 40 esophageal biopsies utilizing the streptavidin-biotin-peroxidase complex method on archival formalin fixed-paraffin embedded blocks. Histopathologically, 17 (42.5%) of cases were non-malignant cases which included GERD, Barrett's esophagus and squamous dysplasia. The malignant cases were 23 (57.5%) squamous cell carcinoma, adenocarcinoma and undifferentiated carcinoma. Results In non-malignant cases 7 (41.2%) out of 17 cases had high COX-2 expression. In squamous cell carcinoma 10 (83.3%) out of 12 cases had high COX-2 expression. The expression of COX-2 was high in all 9 (100%) cases of adenocarcinoma. COX-2 expression is significantly increased (P=0.005 and P=0.0001) in squamous cell carcinoma and adenocarcinoma respectively. There was a significant difference in COX-2 immunoreactivity between malignant and non-malignant lesions (P=0.0003). Conclusion COX-2 is responsible for the progression of esophageal diseases from benign to malignant. We recommend that COX-2 immunohistochemistry should be done routinely for premalignant and malignant esophageal lesions as selective COX-2 inhibitors will be helpful in the treatment. Further studies on molecular and genetic basis of COX-2 expression are needed to unmask its role and relation to progression of esophageal lesions.

Keywords: Cox-2, Esophageal adinocarcinoma, Esophageal squamous cell carcinoma, Immunohistochemistry.

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Authors: Rasoul Eslami, Reza Gharakhanlou

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NT-4/5 and TrkB have been proposed to be involved in the coordinated adaptations of the neuromuscular system to elevated level of activity. Despite the persistence of this neurotrophin and its receptor expression in adult skeletal muscle, little attention has been paid to the functional significance of this complex in the mature neuromuscular system. Therefore, the purpose of this research was to study the effect of one session of resistance exercise on mRNA expression of NT4/5 and TrkB proteins in slow and fast muscles of Wistar Rats. Male Wistar rats (10 mo of age, preparation of Pasteur Institute) were housed under similar living conditions in cages (in groups of four) at room temperature under a controlled light/dark (12-h) cycle with ad libitum access to food and water. A number of sixteen rats were randomly divided to two groups (resistance exercise (T) and control (C); n=8 for each group). The resistance training protocol consisted of climbing a 1-meter–long ladder, with a weight attached to a tail sleeve. Twenty-four hours following the main training session, rats of T and C groups were anaesthetized and the right soleus and flexor hallucis longus (FHL) muscles were removed under sterile conditions via an incision on the dorsolateral aspect of the hind limb. For NT-4/5 and TrkB expression, quantitative real time RT-PCR was used. SPSS software and independent-samples t-test were used for data analysis. The level of significance was set at P < 0.05. Data indicate that resistance training significantly (P<0.05) decreased mRNA expression of NT4/5 in soleus muscle. However, no significant alteration was detected in FHL muscle (P>0.05). Our results also indicate that no significant alterations were detected for TrkB mRNA expression in soleus and FHL muscles (P>0.05). Decrease in mRNA expression of NT4/5 in soleus muscle may be as result of post-translation regulation following resistance training. Also, non-alteration in TrkB mRNA expression was indicated in probable roll of P75 receptor.

Keywords: neurotrophin-4/5 (NT-4/5), TrkB receptor, resistance training, slow and fast muscles

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Authors: Rabab M. Ramadan, Elaraby A. Elgallad

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With extensive application, the performance of unimodal biometrics systems has to face a diversity of problems such as signal and background noise, distortion, and environment differences. Therefore, multimodal biometric systems are proposed to solve the above stated problems. This paper introduces a bimodal biometric recognition system based on the extracted features of the human palm print and iris. Palm print biometric is fairly a new evolving technology that is used to identify people by their palm features. The iris is a strong competitor together with face and fingerprints for presence in multimodal recognition systems. In this research, we introduced an algorithm to the combination of the palm and iris-extracted features using a texture-based descriptor, the Scale Invariant Feature Transform (SIFT). Since the feature sets are non-homogeneous as features of different biometric modalities are used, these features will be concatenated to form a single feature vector. Particle swarm optimization (PSO) is used as a feature selection technique to reduce the dimensionality of the feature. The proposed algorithm will be applied to the Institute of Technology of Delhi (IITD) database and its performance will be compared with various iris recognition algorithms found in the literature.

Keywords: iris recognition, particle swarm optimization, feature extraction, feature selection, palm print, the Scale Invariant Feature Transform (SIFT)

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Authors: Sayed Ali Garossi, Azar Heidarizadi, Shahla Mohammad Ganji

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Context: Colorectal cancer is the second type of cancer-related mortality globally. Expression of cas8 (caspase 8) is closely connected to growth and metastasis of colorectal cancer.Cas8/Rip1 plays a vital role in the apoptosis pathway and resistance to chemotherapy. The aim of the present study is to investigate the pattern of gene expression in colorectal cancer and compare the differences using Real-Time PCR to find a potential biomarker candidate for colorectal cancer. Methodology: This study conducted real-time PCR to evaluate gene expression of Cas8 in colorectal cancer patients. The gene-specific primer sequences exon–exon junction was designed by OLIGO7 software for the expression of the gene under investigation. Forty-six patient samples without any chemotherapy were selected, including tumoral tissue and adjacent normal tissue samples. The age of the patients was 50 and the size of the tumors was 5.5 cm. The categories were before and after age 50. Findings: Here, we found that Caspase 8 was overexpressed in CRC tissues compared to corresponding adjacent colon tissues (Cas8: 5.2 vs. 1 ratio); high expression of Cas8 was associated with poor overall survival and independent risk factors for the prognosis of CRC patients. Conclusion: In conclusion, our study pioneered the reporting of high Casp8 expression as a predictor of poor prognosis and chemical resistance in CRC patients.Cas8 overexpression suppressed Cas 8 / Rip1-dependent apoptosis and activated the proliferation of tumor cells by activating necroptosis. The necroptosis pathway has also emerged as a new approach to anti-tumor in cancer treatment.

Keywords: Cas8, necroptosis, apoptosis, Real-Time PCR

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: Abdullah A. AlShaher

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In this paper, we demonstrate how regression curves can be used to recognize 2D non-rigid handwritten shapes. Each shape is represented by a set of non-overlapping uniformly distributed landmarks. The underlying models utilize 2^nd order of polynomials to model shapes within a training set. To estimate the regression models, we need to extract the required coefficients which describe the variations for a set of shape class. Hence, a least square method is used to estimate such modes. We then proceed by training these coefficients using the apparatus Expectation Maximization algorithm. Recognition is carried out by finding the least error landmarks displacement with respect to the model curves. Handwritten isolated Arabic characters are used to evaluate our approach.

Keywords: character recognition, regression curves, handwritten Arabic letters, expectation maximization algorithm

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Authors: Thuy Bui Anh, Ngan Nguyen Thi Thanh

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Currently, social work in Vietnam is entering the first step in the development process to become a true profession with a strong position in society. However, Spirit of helping and sharing of social work has already existed in the daily life of Vietnamese people for a very long time, becoming a precious heritage passed down from ancestors to the next generations while expanding the territory, building and defending for the country. Following the stream of history, charity work in Vietnam has gradually transformed itself towards a more professional work, especially in the last 2 decades. Accordingly, more than 50 universities and educational institutions in Vietnam have been licensed to train social work, ensuring a stronger foundation on human resources working in this field. Despite the strong growth, social work profession, social work education and the recognition of the role of the social workers still need to be fueled to develop, responded to the increasing demand of Vietnam society.

Keywords: education, history, recognition, social work, Vietnam

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Authors: Sarocha Vivatvakin, Thanaporn Ratchataswan, Thiratest Leesutipornchai, Komkrit Ruangritchankul, Somboon Keelawat, Virachai Kerekhanjanarong, Patnarin Mahattanasakul, Saknan Bongsebandhu-Phubhakdi

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In this globalization era, much attention has been drawn to various molecular biomarkers, which may have the potential to predict the progression of cancer. Epidermal growth factor receptor (EGFR) is the classic member of the ErbB family of membrane-associated intrinsic tyrosine kinase receptors. EGFR expression was found in several organs throughout the body as its roles involve in the regulation of cell proliferation, survival, and differentiation in normal physiologic conditions. However, anomalous expression, whether over- or under-expression is believed to be the underlying mechanism of pathologic conditions, including carcinogenesis. Even though numerous discussions regarding the EGFR as a prognostic tool in head and neck cancer have been established, the consensus has not yet been met. The aims of the present study are to assess the correlation between the level of EGFR expression and demographic data as well as clinicopathological features and to evaluate the ability of EGFR as a reliable prognostic marker. Furthermore, another aim of this study is to investigate the probable pathophysiology that explains the finding results. This retrospective study included 30 squamous cell laryngeal carcinoma patients treated at King Chulalongkorn Memorial Hospital from January 1, 2000, to December 31, 2004. EGFR expression level was observed to be significantly downregulated with the progression of the laryngeal cancer stage. (one way ANOVA, p = 0.001) A statistically significant lower EGFR expression in the late stage of the disease compared to the early stage was recorded. (unpaired t-test, p = 0.041) EGFR overexpression also showed the tendency to increase recurrence of cancer (unpaired t-test, p = 0.128). A significant downregulation of EGFR expression was documented in advanced stage laryngeal cancer. The results indicated that EGFR level correlates to prognosis in term of stage progression. Thus, EGFR expression might be used as a prevailing biomarker for laryngeal squamous cell carcinoma prognostic prediction.

Keywords: downregulation, epidermal growth factor receptor, immunohistochemistry, laryngeal squamous cell carcinoma

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Authors: Muhammad Azam, Micheal Olaolu Arowolo, Fei He, Mihail Popescu, Dong Xu

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The number of biological papers is growing quickly, which means that the number of biological pathway figures in those papers is also increasing quickly. Each pathway figure shows extensive biological information, like the names of genes and how the genes are related. However, manually annotating pathway figures takes a lot of time and work. Even though using advanced image understanding models could speed up the process of curation, these models still need to be made more accurate. To improve gene name recognition from pathway figures, we applied a Siamese network to map image segments to a library of pictures containing known genes in a similar way to person recognition from photos in many photo applications. We used a triple loss function and a triplet spatial pyramid pooling network by combining the triplet convolution neural network and the spatial pyramid pooling (TSPP-Net). We compared VGG19 and VGG16 as the Siamese network model. VGG16 achieved better performance with an accuracy of 93%, which is much higher than OCR results.

Keywords: biological pathway, image understanding, gene name recognition, object detection, Siamese network, VGG

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Authors: Mohamed A. Dkhil, Denis Delic, Saleh Al-Quraishy

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Coccidiosis causes considerable economic loss in the poultry industry. The current study aimed to investigate the response of goblet cells as well as the induced tissue damage during Eimeria papilata infection. Mice were infected with sporulated E. papillata oocyts. On day 5 post-infection, the fecal output was determined. Also, the jejunum was prepared for the histological, histochemical and molecular studies. Our results revealed that the intestinal coccidian infection with E. papillata induced a marked goblet cell hypoplasia and depleted mucus secretion. Also, the infection was able to alter the jejuna architecture and increased the apoptotic cells inside the villi. In addition, the real time PCR results indicated that, the inflammatory cytokines TNF-α, iNOS, IFN-y and IL-1β were significantly up-regulated. In contrast, the mRNA expression patterns of IL-6 in response to E. papillata infection did not differ significantly between control and infected mice. Moreover, the mRNA expression of TLR4 was significantly up-regulated, whereas the expression of MUC2 is significantly down-regulated upon infection. Further studies are required to understand the regulatory mechanisms of goblet cells related genes.

Keywords: goblet cells, Eimeria papillata, mice, jejunum

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Authors: Jae Young Song, In-Ohk Ouh, Seyeon Park, Byeong Sul Kang, Soo Dong Cho, In-Soo Cho

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Canine parvovirus (CPV) is a major pathogen of diarrhea disease in dogs. CPV type 2 has three of antigenic variants such as 2a, 2b, and 2c. CPV constructs a small non-enveloped, icosahedral capsid that contains single-stranded DNA. It has capsids that two largely overlapping virion proteins (VP), VP1 (82 kDa), and VP2 (65 kDa). Baculoviruses are insect pathogens that regulate insect populations in nature and are being successfully used to control insect pests. The proteins produced in the baculovirus-expression system are used for instance for functional studies, vaccine preparations, or diagnostics. The vaccines produced by baculovirus-expression system showed elicitation of antibodies. The recombinant baculovirus infected SF9 cells showed broken shape. The recombinant VP2 proteins from cell pellet or supernatant were confirmed by western blotting. The result showed that the recombinant VP2 protein bands were appeared at 65 kDa molecular weight in both cell pellet and supernatant of infected SF9 cell. These results indicated that the recombinant baculovirus infected SF9 cell express the recombinant VP2 protein successfully. In addition, the expressed recombinant VP2 protein is secreted from cell to supernatant. The baculovirus expression system can be used to produce the VP2 protein of CPV 2c. In addition, the secretion property of the expression of VP2 protein may decrease the cost of production, because it can be skipped the cell breaking step. The produced VP2 protein could be used for vaccine and the agent of diagnostic tests. This study provides the foundation of the production of CPV 2c vaccine and the diagnostic agent.

Keywords: baculovirus, canine parvovirus 2c, dog, Korea

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Authors: Henni Sid Ahmed, Belbachir Mohamed Faouzi, Jean Caelen

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Behavior recognition has been studied for realizing drivers assisting system and automated navigation and is an important studied field in the intelligent Building. In this paper, a recognition method of behavior recognition separated from a real image was studied. Images were divided into several categories according to the actual weather, distance and angle of view etc. SIFT was firstly used to detect key points and describe them because the SIFT (Scale Invariant Feature Transform) features were invariant to image scale and rotation and were robust to changes in the viewpoint and illumination. My goal is to develop a robust and reliable system which is composed of two fixed cameras in every room of intelligent building which are connected to a computer for acquisition of video sequences, with a program using these video sequences as inputs, we use SIFT represented different images of video sequences, and SVM (support vector machine) Lights as a programming tool for classification of images in order to classify people’s behaviors in the intelligent building in order to give maximum comfort with optimized energy consumption.

Keywords: video analysis, people behavior, intelligent building, classification

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Authors: Seok Woo Chang

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Aim: Capseal I and Capseal II are calcium silicate and calcium phosphate based experimental root canal sealer. The aim of this study was to evaluate the biocompatibility and mineralization potential of Capseal I and Capseal II. Materials and Methods: The biocompatibility and mineralization-related gene expression (alkaline phosphatase (ALP), bone sialoprotein (BSP), and osteocalcin (OCN)) of Capseal I and Capseal II were compared using methylthiazol tetrazolium assay and reverse transcription-polymerization chain reaction analysis, respectively. The results were analyzed by Kruskal-Wallis test. P-value of < 0.05 was considered significant. Result: Both Capseal I and Capseal II were favorable in biocompatibility and influenced the messenger RNA expression of ALP and BSP. Conclusion: Within the limitation of this study, Capseal is biocompatible and have mineralization promoting potential, and thus could be a promising root canal sealer.

Keywords: biocompatibility, mineralization-related gene expression, Capseal I, Capseal II

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Authors: F. Polito, M. Cucinotta, A. Conti, C. Lo Giudice, C. Tomasello, F. Angileri, D. La Torre, M. Aguennouz

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Glioblastoma multiforme (GBM) is the most aggressive form of brain tumors, with an extremely poor prognosis. Telomeres lenght is associated with tumor progression in several type of human cancers and telomere elongation is a common molecular feature of advanced malignancies. Among the telomeric shelterin proteins PTOP is required for telomeric protein complex assembly, telomerase recruitment and activity, and telomere length regulation through a PTOP-telomerase interaction. Previous studies suggest that PTOP upregulation is involved in radioresistance and telomere lengthening in colorectal cancer cells. Moreover, in human osteosarcoma cells PTOP deletion led to telomere shortening, increased apoptosis and radiation sensitivity enhancement. However, to date, little is known about the role of PTOP in progression of glioma cancers. In light of this background aim of the study is to investigate the expression of PTOP in different grades of human glioma and its correlation with the pathological grade of gliomas, grades of malignancy, proliferative activity and apoptosis. Fifteen Low Grade Astrocytomas (LGA), 18 Anaplastic Astrocytomas (AA) and 26 Glioblastoma Multiforme (GBM) samples were analyzed. Three samples of normal brain tissue (NBT) were used as controls. The expression levels of PTOP, h-TERT, BIRC1 and cyclin D1 were determined by real time PCR and/or western blot. Results obtained shows that PTOP expression in glioma tissues is tightly correlated with clinical grade ( p < 0.01 ). No correlation was found between PTOP expression and other clinicopathologic parameters. The expression of PTOP was positively correlated with the expression of hTERT and TERF1. Furthermore PTOP positively correlates with cyclin D1 and negatively correlates with the expression of BIRC1. Our findings indicate that PTOP might play key role in the progression of glioma regulating telomerase activity and likely through regulation of cell cycle and apoptosis. In conclusion results obtained prompted us to speculate that PTOP might represents a potential molecular bio marker and a therapeutic target for the treatment of glioblastoma tumors.

Keywords: glioblastoma, PTOP, telomere, brain tumors

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Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

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We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

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Authors: Hsiu-Tsu Cho

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Collective efficacy refers to a group’s sense of its capacity to complete a task successfully or to reach objectives. Little effort has been expended on investigating the relationship between the emotion expression of a leader and collective efficacy. In this study, we examined the impact of the different emotions and emotion expression of a group leader on collective efficacy and explored whether the emotion–expressive effects differed under conditions of negative and positive emotions. A total of 240 undergraduate and graduate students recruited using Facebook and posters at a university participated in this research. The participants were separated randomly into 80 groups of four persons consisting of three participants and a confederate. They were randomly assigned to one of five conditions in a 2 (pride vs. guilt) × 2 (emotion expression of group leader vs. no emotion expression of group leader) factorial design and a control condition. Each four-person group was instructed to get the reward in a group competition of solving the five-disk Tower of Hanoi puzzle and making decisions on an investment case. We surveyed the participants by employing the emotional measure revised from previous researchers and collective efficacy questionnaire on a 5-point scale. To induce an emotion of pride (or guilt), the experimenter announced whether the group performance was good enough to have a chance of getting the reward (ranking the top or bottom 20% among all groups) after group task. The leader (confederate) could either express or not express a feeling of pride (or guilt) following the instruction according to the assigned condition. To check manipulation of emotion, we added a control condition under which the experimenter revealed no results regarding group performance in maintaining a neutral emotion. One-way ANOVAs and post hoc pairwise comparisons among the three emotion conditions (pride, guilt, and control condition) involved assigning pride and guilt scores (pride: F(1,75) = 32.41, p < .001; guilt: F(1,75) = 6.75, p < .05). The results indicated that manipulations of emotion were successful. A two-way between-measures ANOVA was conducted to examine the predictions of the main effects of emotion types and emotion expression as well as the interaction effect of these two variables on collective efficacy. The experimental findings suggest that pride did not affect collective efficacy (F(1,60) = 1.90, ns.) more than guilt did and that the group leader did not motivate collective efficacy regardless of whether he or she expressed emotion (F(1,60) = .89, ns.). However, the interaction effect of emotion types and emotion expression was statistically significant (F(1,60) = 4.27, p < .05, ω2 = .066); the effects accounted for 6.6% of the variance. Additional results revealed that, under the pride condition, the leader enhanced group efficacy when expressing emotion, whereas, under the guilt condition, an expression of emotion could reduce collective efficacy. Overall, these findings challenge the assumption that the effect of expression emotion are the same on all emotions and suggest that a leader should be cautious when expressing negative emotions toward a group to avoid reducing group effectiveness.

Keywords: collective efficacy, group leader, emotion expression, pride, guilty

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Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

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Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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Authors: Aliya Ashraf, Mehreen Sirshar, Fatima Akhtar, Farwa Kazmi, Jawaria Wazir

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Vision, the basis for performing navigational tasks, is absent or greatly reduced in visually impaired people due to which they face many hurdles. For increasing the navigational capabilities of visually impaired people a desktop application ODAPTA is presented in this paper. The application uses camera to capture video from surroundings, apply various image processing algorithms to get information about path and obstacles, tracks them and delivers that information to user through voice commands. Experimental results show that the application works effectively for straight paths in daylight.

Keywords: visually impaired, ODAPTA, Region of Interest (ROI), driver fatigue, face detection, expression recognition, CCD camera, artificial intelligence

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Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau

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Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that aims to prove that all conditions involved in a Boolean expression can influence the result of that expression. In the context of automotive, MC/DC is highly recommended and even required for most security and safety applications testing. However, due to complex Boolean expressions that often embedded in those applications, generating a set of MC/DC compliant test cases for any of these expressions is a nontrivial task and can be time consuming for testers. In this paper we present an approach to automatically generate MC/DC test cases for any Boolean expression. We introduce novel techniques, essentially based on binary trees to quickly and optimally generate MC/DC test cases for the expressions. Thus, the approach can be used to reduce the manual testing effort of testers.

Keywords: binary trees, MC/DC, test case generation, nontrivial task

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Authors: Laura Kahn, Paul Rodrigues, Onur Savas, Shannon Hahn

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An empirical understanding of an individual's personality expression can have a profound impact on organizations seeking to strengthen team performance and improve employee retention. A team's personality composition can impact overall performance. Creating a tiered information framework that leverages proxies for a user's social context and lexical and linguistic content provides insight into location-specific personality expression. We leverage the layered framework to examine domain-specific, psychological, and lexical cues within social media posts. We apply DistilBERT natural language transfer learning models with real world data to examine the relationship between Big Five personality expressions of people in Science, Technology, Engineering and Math (STEM) fields.

Keywords: big five, personality expression, social media analysis, workforce development

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Authors: Jin Hwan Cheong, Mina Hwang, Myung Hoon Han, Je Il Ryu, Young ha Oh, Seong Ho Koh, Wu Duck Won, Byung Jin Ha

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Leucine-rich repeat-containing G-protein coupled receptor 5 (LGR5) has been reported to play critical roles in the proliferation of various cancer cells. However, the roles of LGR5 in brain tumors and the specific intracellular signaling proteins directly associated with it remain unknown. Expression of LGR5 was first measured in normal brain tissue, meningioma, and pituitary adenoma of humans. To identify the downstream signaling pathways of LGR5, siRNA-mediated knockdown of LGR5 was performed in SH-SY5Y neuroblastoma cells followed by proteomics analysis with 2-dimensional polyacrylamide gel electrophoresis (2D-PAGE). In addition, the expression of LGR5-associated proteins was evaluated in LGR5-inꠓhibited neuroblastoma cells and in human normal brain, meningioma, and pituitary adenoma tissue. Proteomics analysis showed 12 protein spots were significantly different in expression level (more than two-fold change) and subsequently identified by peptide mass fingerprinting. A protein association network was constructed from the 12 identified proteins altered by LGR5 knockdown. Direct and indirect interactions were identified among the 12 proteins. HSP 90-beta was one of the proteins whose expression was altered by LGR5 knockdown. Likewise, we observed decreased expression of proteins in the hnRNP subfamily following LGR5 knockdown. In addition, we have for the first time identified significantly higher hnRNP family expression in meningioma and pituitary adenoma compared to normal brain tissue. Taken together, LGR5 and its downstream sigꠓnaling play critical roles in neuroblastoma and brain tumors such as meningioma and pituitary adenoma.

Keywords: LGR5, neuroblastoma, meningioma, pituitary adenoma, hnRNP

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Authors: Merry Meryam Martgrita, Marselina Irasonia Tan

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One of several aggresive cancer is cancer that overexpress c-erbB2 receptor along with the expression of estrogen receptor. Components of extracellular matrix play an important role to increase cancer cells proliferation, migration and invasion. Both components can affect cancer development by regulating the signal transduction pathways in cancer cells. In recent research, SKOV-3 ovarian cancer cell line, that overexpress c-erbB2 receptor was cultured on type IV collagen and treated with estradiol-17β, to reveal the role of both components on RNA and protein level of c-erbB2 receptor. In this research we found a modulation phenomena of increasing and decreasing of c-erbB2 RNA level and a stabilisation phenomena of c-erbB2 protein expression due to estradiol-17β and type IV collagen. It seemed that estradiol-17β has an important role to increase c-erbB2 transcription and the stability of c-erbB2 protein expression. Type IV collagen has an opposite role. It blocked c-erbB2 transcription when it bound to integrin receptor in SKOV-3 cells.

Keywords: c-erbB2, estradiol-17β, SKOV-3, type IV collagen

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Authors: Endrick Barnacin, Jean-Luc Henry, Jack Molinié, Jimmy Nagau, Hélène Delatte, Gérard Lebreton

Abstract:

Palynology is a field of interest for many disciplines. It has multiple applications such as chronological dating, climatology, allergy treatment, and even honey characterization. Unfortunately, the analysis of a pollen slide is a complicated and time-consuming task that requires the intervention of experts in the field, which is becoming increasingly rare due to economic and social conditions. So, the automation of this task is a necessity. Pollen slides analysis is mainly a visual process as it is carried out with the naked eye. That is the reason why a primary method to automate palynology is the use of digital image processing. This method presents the lowest cost and has relatively good accuracy in pollen retrieval. In this work, we propose a system combining recognition and grouping of pollen. It consists of using a Logistic Model Tree to classify pollen already known by the proposed system while detecting any unknown species. Then, the unknown pollen species are divided using a cluster-based approach. Success rates for the recognition of known species have been achieved, and automated clustering seems to be a promising approach.

Keywords: pollen recognition, logistic model tree, expectation-maximization, local binary pattern

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Authors: Xuan Li, Xiaobing Cui, Nan Meng, Shuangshuang Guo, Lingling Wang

Abstract:

Objective: To investigate the influence of Paeonol on diabetic nephropathy progression in streptozocin (STZ) -induced diabetic rats. Method Male Wistar rats were injected STZ 30mg.kg-1 combined with Freund's complete adjuvant (CFA) 0.1mL/rat once a week for three weeks. The diabetic rats were treated with Paenol for 13 weeks. At the end of the experiments, the rats were anesthetized. Serum and the kidney were collected. Serum superoxide dismutase (SOD) activity, malondialdehyde (MDA), blood urea nitrogen (BUN), creatinine (Cr) and total cholesterol (Chol) level were detected; kidney paraffin sections were prepared and HE and PAS staining sections were used to evaluate the pathology changes of the kidney. Immunohistochemical analysis was used to observe the expression of VEGF and fibernectin expression in the kidney. Result The blood glucose level remained over 16mmol. L-1 for 13 weeks and the ECM accumulated in the diabetic kidney apparently. Paeonol treatment increased serum SOD activity, however, MDA, BUN, Cr, and Chol level was decreased by paeonol treatment. VEGF and fibernectin expression were increased significantly in the DN rats and paeonol treatment ameliorated the overexpression. Conclusion: paeonol prevented the progression of DN.

Keywords: paeonol, STZ, diabetic nephropathy, fibernectin expression, kidney paraffin sections

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Authors: Lola T. Alimkhodjaeva, Lola T. Zakirova, Soniya S. Ziyavidenova

Abstract:

Background: Breast cancer occupies the first place among the cancer in women in the world. It is urgent today to study the role of molecular markers which are capable of predicting the dynamics and outcome of the disease. The aim of this study is to define the prognostic value of the content of estrogen receptor (ER), progesterone receptor (PgR), and amplification of HER-2 / neu oncoprotein by studying 3 and 5-year overall and relapse-free survival in 470 patients with primary operable and 280 patients with locally–advanced breast cancer. Materials and methods: Study results of 3 and 5-year overall and relapse-free survival, depending on the content of RE, PgR in primary operable patients showed that ER positive (+) and PgR (+) survival was 100 (96.2%) and 97.3 (94.6%), for ER negative (-) and PgR (-) - 69.2 (60.3%) and 65.4 (57.7%), for ER positive (+) and negative PgR (-) 87.4 (80.1%) and 81.5 (79.3%), for ER negative (-) and positive PgR (+) - 97.4 (93.4%) and 90.4 (88.5%), respectively. Survival results depended also on the level of HER-2 / neu expression. In patients with HER-2 / neu negative the survival rates were as follows: 98.6 (94.7%) and 96.2 (92.3%). In group of patients with the level of HER-2 / neu (2+) expression these figures were: 45.3 (44.3%) and 45.1 (40.2%), and in group of patients with the level of HER-2 / neu (3+) expression - 41.2 (33.1%) and 34.3 (29.4%). The combination of ER negative (-), PgR (-), HER-2 / neu (-) they were 27.2 (25.4%) and 19.5 (15.3%), respectively. In patients with locally-advanced breast cancer the results of 3 and 5-year OS and RFS for ER (+) and PgR (+) were 76.3 (69.3%) and 62.2 (61.4%), for ER (-) and RP (-) 29.1 (23.7%) and 18.3 (12.6%), for ER (+) and PgR (-) 61.2 (47.2%) and 39.4 (25.6%), for ER (-) and PgR (+) 54.3 (43.1%) and 41.3 (18.3%), respectively. The level of HER-2 / neu expression also affected the survival results. Therefore, in HER-2/ neu negative patients the survival rate was 74.1 (67.6%) and 65.1 (57.3%), with the level of expression (2+) 20.4 (14.2%) and 8.6 (6.4%), with the level of expression (3+) 6.2 (3.1%) and 1.2 (1.5%), respectively. The combination for ER, PgR, HER-2 / neu negative was 22.1 (14.3%) and 8.4 (1.2%). Conclusion: Thus, the presence of steroid hormone receptors in breast tumor tissues at primary operable and locally- advanced process as the lack of HER-2/neu oncoprotein correlates with the highest rates of 3- and 5-year overall and relapse-free survival. The absence of steroid hormone receptors as well as of HER-2/neu overexpression in malignant breast tissues significantly degrades the 3- and 5-year overall and relapse-free survival. Tumors with ER, PgR and HER-2/neu negative have the most unfavorable prognostics.

Keywords: breast cancer, estrogen receptor, oncoprotein, progesterone receptor

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Authors: Rutusha Bhutada, Gaurav Chavan, Sarvesh Kasat, Varsha Mujumdar

Abstract:

This software system will be an Augmented Reality application designed to maximize the doctor’s productivity by providing tools to assist in automating the patient recognition and updating patient’s records using face and voice recognition features, which would otherwise have to be performed manually. By maximizing the doctor’s work efficiency and production, the application will meet the doctor’s needs while remaining easy to understand and use. More specifically, this application is designed to allow a doctor to manage his productive time in handling the patient without losing eye-contact with him and communicate with a group of other doctors for consultation, for in-place treatments through video streaming, as a video study. The system also contains a relational database containing a list of doctor, patient and display techniques.

Keywords: augmented reality, hand-held devices, head-mounted devices, marker based systems, speech recognition, face detection

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Authors: Jesus Alfredo Ortega Granados, Pandiyan Thangarasu

Abstract:

Antibiotic tetracycline presents as a micro-contaminant in fresh water, wastewater and soils, causing environmental and health problems. In this work, tetracycline (TC) has been employed as chemo-sensor for the recognition of Al³⁺ without interring other ions, and the results show that it enhances the fluorescence intensity for Al³⁺ and there is no interference from other coexisting cation ions (Cd²⁺, Ni²⁺, Co²⁺, Sr²⁺, Mg²⁺, Fe³⁺, K⁺, Sm³⁺, Ag⁺, Na⁺, Ba²⁺, Zn²⁺, and Mn²⁺). For the addition of Cu²⁺ to [TET-Al³⁺], it appears that the intensity of fluorescence has been quenched. Other combinations of metal ions in addition to TC do not change the fluorescence behavior. The stoichiometry determined by Job´s plot for the interaction of TC with Al³⁺ was found to be 1:1. Importantly, the detection of Al³⁺⁺ successfully employed in the real samples like living cells, and it was found that TC efficiently performs as a fluorescent probe for Al³⁺ ion in living systems, especially in Saccharomyces cerevisiae; this is confirmed by confocal laser scanning microscopy.

Keywords: chemo-sensor, recognition of Al³⁺ ion, Saccharomyces cerevisiae, tetracycline,

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Authors: R. R. Hordijk, O. J. G. Somsen

Abstract:

Traditionally, radar systems are the eyes and ears of a ship. However, these systems have their drawbacks and nowadays they are extended with systems that work with video and photos. Processing of data from these videos and photos is however very labour-intensive and efforts are being made to automate this process. A major problem when trying to recognize objects in water is that the 'background' is not homogeneous so that traditional image recognition technics do not work well. Main question is, can a method be developed which automate this recognition process. There are a large number of parameters involved to facilitate the identification of objects on such images. One is varying the resolution. In this research, the resolution of some images has been reduced to the extreme value of 1% of the original to reduce clutter before the polynomial fit (pre-processing). It turned out that the searched object was clearly recognizable as its grey value was well above the average. Another approach is to take two images of the same scene shortly after each other and compare the result. Because the water (waves) fluctuates much faster than an object floating in the water one can expect that the object is the only stable item in the two images. Both these methods (pre-processing and comparing two images of the same scene) delivered useful results. Though it is too early to conclude that with these methods all image problems can be solved they are certainly worthwhile for further research.

Keywords: image processing, image recognition, polynomial fit, water

Procedia PDF Downloads 506