Search results for: brain tumor classification

Authors: Navya Saira George, Patroba Achola Odera

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This study aims to determine spatio-temporal expansion of Kochi City, situated on the west coast of Kerala State in India. Remote sensing and GIS techniques have been used to determine land use/cover and urban expansion of the City. Classification of Landsat images of the years 1973, 1988, 2002 and 2018 have been used to reproduce a visual story of the growth of the City over a period of 45 years. Accuracy range of 0.79 ~ 0.86 is achieved with kappa coefficient range of 0.69 ~ 0.80. Results show that the areas covered by vegetation and water bodies decreased progressively from 53.0 ~ 30.1% and 34.1 ~ 26.2% respectively, while built-up areas increased steadily from 12.5 to 42.2% over the entire study period (1973 ~ 2018). The shift in land use from agriculture to non-agriculture may be attributed to the land reforms since 1980s.

Keywords: Geographical Information Systems, Kochi City, Land use/cover, Remote Sensing, Urban Sprawl

Procedia PDF Downloads 127

Authors: Ehsan Mehryaar, Seyed Armin Motahari Tabari

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Without a doubt, soil shear strength is the most important property of the soil. The majority of fatal and catastrophic geological accidents are related to shear strength failure of the soil. Therefore, its prediction is a matter of high importance. However, acquiring the shear strength is usually a cumbersome task that might need complicated laboratory testing. Therefore, prediction of it based on common and easy to get soil properties can simplify the projects substantially. In this paper, A hybrid model based on the classification and regression tree algorithm and logistic regression is proposed where each leaf of the tree is an independent regression model. A database of 189 points for clay soil, including Moisture content, liquid limit, plastic limit, clay content, and shear strength, is collected. The performance of the developed model compared to the existing models and equations using root mean squared error and coefficient of correlation.

Keywords: model tree, CART, logistic regression, soil shear strength

Procedia PDF Downloads 192

Authors: Vidhula Ahire, Amit Kumar, K. P. Mishra, Gauri Kulkarni

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Herbal polyphenols have gained significance because of their increasing promise in prevention and treatment of cancer. Therefore, development of a dietary compound as an effective radiosensitizer and a radioprotector is highly warranted for cervical cancer patients undergoing therapy. This study describes the cytotoxic effects of the flavonoid, ellagic acid (EA) when administered either alone or in combination with gamma radiation on cervical cancer HeLa cells in vitro. Apoptotic index and proliferation were measured by using trypan blue assay. Reproductive cell death was analyzed by clonogenic assay. Propidium iodide staining for flowcytometry was performed to analyze cell cycle modulation. Nuclear and mitochondrial changes were studied with specific dyes. DNA repair kinetics was analyzed by immunofluorescence assay. Evaluation and comparison of EA effects were performed with other clinically used breast cancer drugs. When tumor cells were exposed to 2 and 4 Gy of irradiation in presence of EA (10 μM), it yielded a synergistic cytotoxic effect on cervical cancer cells whereas in NIH3T3 cells it reversed the injury caused by irradiation and abetted in the regaining of normal healthy cells. At 24h ~25foci/cell was observed and 2.6 fold decrease in the mitochondrial membrane potential. Up to 40% cell were arrested in the G1 phase and 20-36% cells exhibited apoptosis. Our results demonstrate the role of increased apoptosis and cell cycle modulation in the mechanism of EA mediated radiosensitization of cervical cancer cells and thus advocating EA as an adjuvant for preclinical trials in cancer chemo- radiotherapy.

Keywords: cervical cancer, ellagic acid, sensitization, radiation therapy

Procedia PDF Downloads 318

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

Procedia PDF Downloads 67

Authors: Stefanie Rukavina, Sascha Gruss, Steffen Walter, Holger Hoffmann, Harald C. Traue

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OPEN-EmoRecII is an open multimodal corpus with experimentally induced emotions. In the first half of the experiment, emotions were induced with standardized picture material and in the second half during a human-computer interaction (HCI), realized with a wizard-of-oz design. The induced emotions are based on the dimensional theory of emotions (valence, arousal and dominance). These emotional sequences - recorded with multimodal data (mimic reactions, speech, audio and physiological reactions) during a naturalistic-like HCI-environment one can improve classification methods on a multimodal level. This database is the result of an HCI-experiment, for which 30 subjects in total agreed to a publication of their data including the video material for research purposes. The now available open corpus contains sensory signal of: video, audio, physiology (SCL, respiration, BVP, EMG Corrugator supercilii, EMG Zygomaticus Major) and mimic annotations.

Keywords: open multimodal emotion corpus, annotated labels, intelligent interaction

Procedia PDF Downloads 408

Authors: Matthieu-P. Schapranow

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Recruitment of participants for clinical trials requires the screening of a big number of potential candidates, i.e. the testing for trial-specific inclusion and exclusion criteria, which is a time-consuming and complex task. Today, a significant amount of time is spent on identification of adequate trial participants as their selection may affect the overall study results. We introduce a unique patient eligibility metric, which allows systematic ranking and classification of candidates based on trial-specific filter criteria. Our web application enables real-time analysis of patient data and assessment of candidates using freely definable inclusion and exclusion criteria. As a result, the overall time required for identifying eligible candidates is tremendously reduced whilst additional degrees of freedom for evaluating the relevance of individual candidates are introduced by our contribution.

Keywords: in-memory technology, clinical trials, screening, eligibility metric, data analysis, clustering

Procedia PDF Downloads 485

Authors: Birmohan Singh, V.K.Jain

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Computer aided diagnosis systems provide vital opinion to radiologists in the detection of early signs of breast cancer from mammogram images. Masses and microcalcifications, architectural distortions are the major abnormalities. In this paper, a computer aided diagnosis system has been proposed for distinguishing abnormal mammograms with architectural distortion from normal mammogram. Four types of texture features GLCM texture, GLRLM texture, fractal texture and spectral texture features for the regions of suspicion are extracted. Support Vector Machine has been used as classifier in this study. The proposed system yielded an overall sensitivity of 96.47% and accuracy of 96% for the detection of abnormalities with mammogram images collected from Digital Database for Screening Mammography (DDSM) database.

Keywords: architecture distortion, mammograms, GLCM texture features, GLRLM texture features, support vector machine classifier

Procedia PDF Downloads 484

Authors: S. Athiralakshmi, B.E. Bhojaraja, U. Pruthviraj

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In agriculture, remote sensing is applied for monitoring of plant development, evaluating of physiological processes and growth conditions. Especially valuable are the spatio-temporal aspects of the remotely sensed data in detecting crop state differences and stress situations. In this study, hyperion imagery is used for classifying arecanut crops based on their age so that these maps can be used in yield estimation of crops, irrigation purposes, applying fertilizers etc. Traditional hard classifiers assigns the mixed pixels to the dominant classes. The proposed method uses a sub pixel level classifier called linear spectral unmixing available in ENVI software. It provides the relative abundance of surface materials and the context within a pixel that may be a potential solution to effectively identifying the land-cover distribution. Validation is done referring to field spectra collected using spectroradiometer and the ground control points obtained from GPS.

Keywords: FLAASH, Hyperspectral remote sensing, Linear Spectral Unmixing, Spectral Angle Mapper Classifier.

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Authors: Antoine F. Dedewanou, Eric N. Ekpinda

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We investigate whether and how deposit insurance program affects savings decisions in the Economic Community of Central African States (ECCAS). Specifically, using the World Bank’s 2014 and 2011 Global Financial Inclusion (Global Findex) databases, we apply special regressor approach. We find that the deposit insurance program increases significantly, everything else equal, the probability that people save their money at a financial institution by 11 percentage points in Gabon, by 22.2 percentage points in DR Congo and by 15.1 percentage points in Chad. These effects are matched with positive effects of age and education level. But in Cameroon, the effect of deposit insurance is not significant. The policies aimed at fostering financial inclusion will be more effective if there is a deposit insurance scheme in place, along with awareness among young people, and education programs. JEL Classification: G21, O12, O16

Keywords: deposit insurance, savings, special regressor, ECCAS countries

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Authors: Ognen Kostovski, Svetozar Antovic, Rubens Jovanovic, Irena Kostovska, Nikola Jankulovski

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Introduction:Colorectal carcinoma (CRC) is one of the most common malignancies in the world. The cancer stem cell (CSC) markers are associated with aggressive cancer types and poor prognosis. The aim of study was to determine whether the expression of colorectal cancer stem cell markers CD133 and CD44 could be significant in prediction of clinically aggressive form of CRC. Materials and methods: Our study included ninety patients (n=90) with CRC. Patients were divided into two subgroups: with metatstatic CRC and non-metastatic CRC. Tumor samples were analyzed with standard histopathological methods, than was performed immunohistochemical analysis with monoclonal antibodies against CD133 and CD44 stem cell markers. Results: High coexpression of CD133 and CD44 was observed in 71.4% of patients with metastatic disease, compared to 37.9% in patients without metastases. Discordant expression of both markers was found in 8% of the subgroup with metastatic CRC, and in 13.4% of the subgroup without metastatic CRC. Statistical analyses showed a significant association of increased expression of CD133 and CD44 with the disease stage, T - category and N - nodal status. With multiple regression analysis the stage of disease was designate as a factor with the greatest statistically significant influence on expression of CD133 (p <0.0001) and CD44 (p <0.0001). Conclusion: Our results suggest that the coexpression of CD133 and CD44 have an important role in prediction of clinically aggressive form of CRC. Both stem cell markers can be routinely implemented in standard pathohistological diagnostics and can be useful markers for pre-therapeutic oncology screening.

Keywords: colorectal carcinoma, stem cells, CD133+, CD44+

Procedia PDF Downloads 143

Authors: Raymond Feng, Shadi Ghiasi

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An electroencephalogram (EEG) is a non-invasive technique that records electrical activity in the brain using scalp electrodes. Researchers have studied the use of EEG to detect emotions and moods by collecting signals from participants and analyzing how those signals correlate with their activities. In this study, researchers investigated the relationship between EEG signals and music enjoyment. Participants listened to music while data was collected. During the signal-processing phase, power spectral densities (PSDs) were computed from the signals, and dominant brainwave frequencies were extracted from the PSDs to form a comprehensive feature matrix. A machine learning approach was then taken to find correlations between the processed data and the music enjoyment level indicated by the participants. To improve on previous research, multiple machine learning models were employed, including K-Nearest Neighbors Classifier, Support Vector Classifier, and Decision Tree Classifier. Hyperparameters were used to fine-tune each model to further increase its performance. The experiments showed that a strong correlation exists, with the Decision Tree Classifier with hyperparameters yielding 85% accuracy. This study proves that EEG is a reliable means to detect music enjoyment and has future applications, including personalized music recommendation, mood adjustment, and mental health therapy.

Keywords: EEG, electroencephalogram, machine learning, mood, music enjoyment, physiological signals

Procedia PDF Downloads 51

Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

Procedia PDF Downloads 405

Authors: Mewa Singh

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Nanomedicine, a fusion of nanotechnology and medicine, is an emerging technology ideally suited to the targeted therapies. Nanoparticles overcome the low selectivity of anti-cancer drugs toward the tumor as compared to normal tissue and hence result-in less severe side-effects. Our new technology, HYBRID-NANOENGINEERING™, uses a new molecule (MR007) in the creation of nanoparticles that not only helps in nanonizing the medicine but also provides synergy to the medicine. The simplified manufacturing process will result in reduced manufacturing costs. Treatment is made more convenient because hybrid nanomedicines can be produced in oral, injectable or transdermal formulations. The manufacturing process uses no protein, oil or detergents. The particle size is below 180 nm with a narrow distribution of size. Importantly, these properties confer great stability of the structure. The formulation does not aggregate in plasma and is stable over a wide range of pH. The final hybrid formulation is stable for at least 18 months as a powder. More than 97 drugs, including paclitaxel, docetaxel, tamoxifen, doxorubicinm prednisone, and artemisinin have been nanonized in water soluble formulations. Preclinical studies on cell cultures of tumors show promising results. Our HYBRID-NANOENGINEERING™ platform enables the design and development of hybrid nano-pharmaceuticals that combine efficacy with tolerability, giving patients hope for both extended overall survival and improved quality of life. This study would discuss or present this new discovery of HYBRID-NANOENGINEERING™ which targets drug delivery, synergistic, and potentiating effects, and barriers of drug delivery and advanced drug delivery systems.

Keywords: nano-medicine, nano-particles, drug delivery system, pharmaceuticals

Procedia PDF Downloads 480

Authors: Eugene Stepanov, Arcady Ponosov

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To model gene regulatory networks one uses ordinary differential equations with switching nonlinearities, where the initial value problem is known to be well-posed if the trajectories cross the discontinuities transversally. Otherwise, the initial value problem is usually ill-posed, which lead to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid dynamical systems, rather than switched ones, to regularize the problem. 'Hybridization' of the switched system means that one attaches a dynamic discrete component ('automaton'), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness of the initial value problem making it well-posed. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. Several examples are provided in the presentation, which support the suggested analysis. The method can also be of interest in other applied fields, where differential equations contain switchings, e.g. in neural field models.

Keywords: hybrid dynamical systems, ill-posed problems, singular perturbation analysis, switching nonlinearities

Procedia PDF Downloads 176

Authors: Sujan Mahamud

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Purpose: A major challenge in radiotherapy treatment is to deliver precise dose of radiation to the tumor with minimum dose to the healthy normal tissues. Recently, gel dosimetry has emerged as a powerful tool to measure three-dimensional (3D) dose distribution for complex delivery verification and quality assurance. These dosimeters act both as a phantom and detector, thus confirming the versatility of dosimetry technique. The aim of the study is to know the application of Gel Dosimeters in Radiotherapy and find out the comparison with 1D and 2D dimensional dosimeters. Methods and Materials: The study is carried out from Gel Dosimeter literatures. Secondary data and images have been collected from different sources such as different guidelines, books, and internet, etc. Result: Analyzing, verifying, and comparing data from treatment planning system (TPS) is determined that gel dosimeter is a very excellent powerful tool to measure three-dimensional (3D) dose distribution. The TPS calculated data were in very good agreement with the dose distribution measured by the ferrous gel. The overall uncertainty in the ferrous-gel dose determination was considerably reduced using an optimized MRI acquisition protocol and a new MRI scanner. The method developed for comparing measuring gel data with calculated treatment plans, the gel dosimetry method, was proven to be a useful for radiation treatment planning verification. In 1D and 2D Film, the depth dose and lateral for RMSD are 1.8% and 2%, and max (Di-Dj) are 2.5% and 8%. Other side 2D+ ( 3D) Film Gel and Plan Gel for RMSDstruct and RMSDstoch are 2.3% & 3.6% and 1% & 1% and system deviation are -0.6% and 2.5%. The study is investigated that the result fined 2D+ (3D) Film Dosimeter is better than the 1D and 2D Dosimeter. Discussion: Gel Dosimeters is quality control and quality assurance tool which will used the future clinical application.

Keywords: gel dosimeters, phantom, rmsd, QC, detector

Procedia PDF Downloads 149

Authors: Samaneh Nadali, Masrah Azrifah Azmi Murad

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As a result of the growth of the web, people are able to express their views and opinions. They can now post reviews of products at merchant sites and express their views on almost anything in internet forums, discussion groups, and blogs. Therefore, the number of product reviews has grown rapidly. The large numbers of reviews make it difficult for manufacturers or businesses to automatically classify them into different semantic orientations (positive, negative, and neutral). For sentiment classification, most existing methods utilize a list of opinion words whereas this paper proposes a fuzzy approach for evaluating sentiments expressed in customer product reviews, to predict the strength levels (e.g. very weak, weak, moderate, strong and very strong) of customer product reviews by combinations of adjective, adverb and verb. The proposed fuzzy approach has been tested on eight benchmark datasets and obtained 74% accuracy, which leads to help the organization with a more clear understanding of customer's behavior in support of business planning process.

Keywords: fuzzy logic, customer product review, sentiment analysis

Procedia PDF Downloads 361

Authors: Elena Puica

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This paper aims to investigate the impact of Supply Chain Management (SCM) on the environment by applying a Machine Learning model while pointing out the efficiency of the technology used. The Machine Learning model was used to derive the efficiency and optimization of technology used in SCM and the environmental impact of SCM processes. The model applied is a predictive classification model and was trained firstly to determine which stage of the SCM has more outputs and secondly to demonstrate the efficiency of using advanced technology in SCM instead of recuring to traditional SCM. The outputs are the emissions generated in the environment, the consumption from different steps in the life cycle, the resulting pollutants/wastes emitted, and all the releases to air, land, and water. This manuscript presents an innovative approach to applying advanced technology in SCM and simultaneously studies the efficiency of technology and the SCM's impact on the environment. Identifying the conceptual relationships between SCM practices and their impact on the environment is a new contribution to the research. The authors can take a forward step in developing recent studies in SCM and its effects on the environment by applying technology.

Keywords: machine-learning model in SCM, SCM processes, SCM and the environmental impact, technology in SCM

Procedia PDF Downloads 112

Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

Procedia PDF Downloads 287

Authors: Ahmad Shah Farhat

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Background: Prenatal asphyxia or birth asphyxia is the medical situation resulting from a newborn infant that lasts long enough during the birth process to cause physical harm, usually to the brain. Human umbilical cord blood (UCB) is a well-established source of hematopoietic stem/progenitor cells (HSPCs) for allogeneic stem cell transplantation. These can be used clinically to care for children with malignant diseases. Low O2 can cause in proliferation and differentiation of stem cells. Method: the cord blood of 11 infants with 3-5 Apgar scores or need to cardiac pulmonary Resuscitation as an asphyxia group and ten normal infants with more than 8 Apgar scores as the normal group was collected, and after isolating hematopoietic stem cells, the cells were cultured in enriched media for 14 days to compare the numbers of colonies by microscope. Results: There was a significant difference in the number of RBC precursor colonies (red colonies) in cultured media with 107 cord blood hematopoietic stem cells of infants who were exposed to hypoxemia in two wells of palate. There was not a significant difference in the number of white cell colonies in the two groups in the two wells of the plate. Conclusion: Hypoxia in the perinatal period can cause the increase of hematopoietic stem cells of cord blood, special red precursor stem cells in vitro, like an increase of red blood cells in the body when exposed to low oxygen conditions. Thus, it will be usable.

Keywords: asphyxia, neonre, stem cell, red cell

Procedia PDF Downloads 65

Authors: Asimina Paparrigopoulou, John Pavlopoulos, Maria Konstantinidou

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Dating papyri accurately is crucial not only to editing their texts but also for our understanding of palaeography and the history of writing, ancient scholarship, material culture, networks in antiquity, etc. Most ancient manuscripts offer little evidence regarding the time of their production, forcing papyrologists to date them on palaeographical grounds, a method often criticized for its subjectivity. By experimenting with data obtained from the Collaborative Database of Dateable Greek Bookhands and the PapPal online collections of objectively dated Greek papyri, this study shows that deep learning dating models, pre-trained on generic images, can achieve accurate chronological estimates for a test subset (67,97% accuracy for book hands and 55,25% for documents). To compare the estimates of these models with those of humans, experts were asked to complete a questionnaire with samples of literary and documentary hands that had to be sorted chronologically by century. The same samples were dated by the models in question. The results are presented and analysed.

Keywords: image classification, papyri images, dating

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Authors: Ramon Hernán, Maria Teresa Corzo

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This study examines the impact and contribution of the main journals in the discipline of behavioral finance to determine the state of the art of the discipline and the growth lines and concepts studied to date. This is a unique and novel study given that a review of the discipline has not been carried out through the keywords of the articles that allows visualizing through this component of the research, which are the main topics of discussion and the relationships that arise between the concepts discussed. To carry out this study, 3,876 articles have been taken as a reference, which includes 15,859 keywords from the main journals responsible for the growth of the discipline.; Journal of Behavioral Finance, Review of Behavioral Finance, Journal of Behavioral and Experimental Economics, Journal of Behavioral and Experimental Economics and Review of Behavioral Finance. The results indicate which are the topics most covered in the discipline throughout the period from 2000 to 2020, how these concepts have been dealt with on a recurring basis along with others throughout the aforementioned period and how the different concepts have been grouped based on the keywords established by the authors for the classification of their articles with a network diagram to complete the analysis.

Keywords: behavioral finance, keywords, co-words, top journals, data visualization

Procedia PDF Downloads 186

Authors: Haslinda Nahazanan, Afshin Asadi, Zainuddin Md. Yusoff, Nik Nor Syahariati Nik Daud

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Mudrocks is considered as a problematic material due to their unexpected behaviour specifically when they are contacting with water or being exposed to the atmosphere. Many instability problems of cutting slopes were found lying on high slaking mudrocks. It has become one of the major concerns to geotechnical engineer as mudrocks cover up to 50% of sedimentary rocks in the geologic records. Mudrocks display properties between soils and rocks which can be very hard to understand. Therefore, this paper aims to review the definition, mineralogy, geo-chemistry, classification and engineering properties of mudrocks. As water has become one of the major factors that will rapidly change the behaviour of mudrocks, a review on the shear strength of mudrocks in Derbyshire has been made using a fully automated hydraulic stress path testing system under three states: dry, short-term inundated and long-term inundated. It can be seen that the strength of mudrocks has deteriorated as it condition changed from dry to short-term inundated and finally to long-term inundated.

Keywords: mudrocks, sedimentary rocks, inundation, shear strength

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Authors: Divya Pande

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The dynamics of culture expresses itself in language. Even after India got independence in 1947 English subtly crept in the language of the masses with a silent and powerful flow towards the vernacular. The culture contact resulted in learning and emergence of a new language across the Hindi speaking belt of Northern and Central India. The hybrid words thus formed displaced the original word and got contextualized and absorbed in the language of the common masses. The research paper explores the interesting new vocabulary used extensively in the urban and rural districts of the state of Uttar- Pradesh which is the most populous state of India. The paper adopts a two way classification- formal and contextual for the analysis of the hybrid vocabulary of the linguistic items where one element is necessarily from the English language and the other from the Hindi. The new vocabulary represents languages of the wider world cutting across the geographical and the cultural barriers. The paper also broadly points out to the Hinglish commonly used in the state.

Keywords: assimilation, culture contact, Hinglish, hybrid words

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Authors: Melliti Rihab, Zaeid Sonia, Khechine Wiem, Daldoul Amira

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Introduction: Lung cancer is the leading cause of cancer death. Its incidence is increasing, and its prognosis remains pejorative. We present the clinical, pathological, and therapeutic characteristics of bronchopulmonary cancer (BPC) in Tunisia. Methods: Retrospective study including patients followed in the oncology department of the University Hospital of Monastir between April 2014 and December 2021 suffering from lung cancer. Results: These are 117 patients, including 86.3% men and 13.7% women (sex ratio 6.3). The average age was 64 years ± 9 (37-83), with 95.7% being over 50 years old. Patients were smokers in 82% of cases. The clinical signs were dominated by chest pain (27.5%) and dyspnea in 21.1% of cases. In 6 patients, an episode of COVID-19 infection revealed the diagnosis. Half of the patients had a PS between 0 and 1. Small cell lung cancer was present in 18 patients (15.4%). The majority of non small cell lung cancer was of the adenocarcinoma type (68.7%). The diagnosis was late (stage IV) in 62.4% of cases. BPC was metastatic to bone (52%), contralateral lung (25.9%), and brain (27.3%). Patients were oligometastatic in 26% of cases. Surgery and radiotherapy were performed respectively in 14.5% and 23.1% of cases. Three-quarters of the patients had had nutrition (75.2%). The ROS1 mutation was present in 1 patient. PDL-1 expression was >40% in 2 patients. Survival was mean eight months ± 7.4. Conclusion: Lung cancer is diagnosed at a late stage in Tunisia. The lack of molecular study for non-small cell PBC and the lack of marketing authorization for tyrosine kinase inhibitors in Tunisia make the management incomplete.

Keywords: SCLC, NCSLC, ROS1, PDL1

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Authors: Juliza Hidayati, Sawarni Hasibuan

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PT. XYZ is a manufacturing company that produces Crude Palm Oil (CPO). The fierce competition in the global markets not only between companies but also a competition between supply chains. This research aims to analyze the supply chain and value chain of Crude Palm Oil (CPO) in the company. Data analysis method used is qualitative analysis and quantitative analysis. The qualitative analysis describes supply chain and value chain, while the quantitative analysis is used to find out value added and the establishment of the value chain. Based on the analysis, the value chain of crude palm oil (CPO) in the company consists of four main actors that are suppliers of raw materials, processing, distributor, and customer. The value chain analysis consists of two actors; those are palm oil plantation and palm oil processing plant. The palm oil plantation activities include nurseries, planting, plant maintenance, harvesting, and shipping. The palm oil processing plant activities include reception, sterilizing, thressing, pressing, and oil classification. The value added of palm oil plantations was 72.42% and the palm oil processing plant was 10.13%.

Keywords: palm oil, value chain, value added, supply chain

Procedia PDF Downloads 364

Authors: Liang Zhou, Xiaojing Zhu, Yin Lu

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Danshen can induce the angiogenesis in advanced ischemic heart disease while inhibiting the angiogenesis in cancer. Additionally, Danshen mainly contains two groups of ingredients: the hydrophilic phenolic acids (danshensu, caffeic acid and salvianolic acid B), and the lipophilic tanshinones (dihydrotanshinone I, tanshinone II A, and cryptotanshinone). The lipophilic tanshinones reduced the VEGF- and bFGF-induced proliferation of HUVECs in dose-dependent manner, but cannot perform in others. Conversely, caffeic acid and salvianolic acid B had the opposite effect. Danshensu inhibited the VEGF- and bFGF-induced migration of HUVECs, and others were not. Most of them interrupted the forming capillary-like structures of HUVECs, except the danshensu and caffeic acid. Oppositely, caffeic acid enhanced the ability of forming capillary-like structures of HUVECs. Ultimately, the lipophilic tanshinones, danshensu and salvianolic acid B inhibited the angiogenesis, whereas the caffeic acid induced the angiogenesis. These data provide useful information for the classification of ingredients of Danshen for angiogenesis.

Keywords: angiogenesis, Danshen, HUVECs, ingredients

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Authors: Nishtha Madaan, Prateek Chaudhury, Nishant Kumar, Srikanta Bedathur

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In modern NLP applications, word embeddings are a crucial backbone that can be readily shared across a number of tasks. However, as the text distributions change and word semantics evolve over time, the downstream applications using the embeddings can suffer if the word representations do not conform to the data drift. Thus, maintaining word embeddings to be consistent with the underlying data distribution is a key problem. In this work, we tackle this problem and propose TransDrift, a transformer-based prediction model for word embeddings. Leveraging the flexibility of the transformer, our model accurately learns the dynamics of the embedding drift and predicts future embedding. In experiments, we compare with existing methods and show that our model makes significantly more accurate predictions of the word embedding than the baselines. Crucially, by applying the predicted embeddings as a backbone for downstream classification tasks, we show that our embeddings lead to superior performance compared to the previous methods.

Keywords: NLP applications, transformers, Word2vec, drift, word embeddings

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Authors: Barari Alireza, Seyed Hossein Alavi, Ghasemi Mohamad

Abstract:

Objectives: VEGF and PDGF play central role in the processes of angiogenesis and vascular changes in most body tissues. The aim of the present study to determine effect of endurance training with ginseng on VEGF and PDGF levels is untrained female. Methods: Statistic society of this study was untraining male students of Azad University of Sari Branch in year of 2012-2013. Forty young untrained female (age 21.3 ± 0.90 year, height162.08±8.07cm , body weight 65.45± 7.6 kg and body mass index [BMI] 23.23 ± 2.64 kg/m2) were randomly divided into four groups: control(C), endurance(E), ginseng (G), endurance and ginseng (EG). Participants in training groups performed endurance training for 6 weeks and three sessions per week with 60-80% HRmax. Subjects perform endurance training and consumed ginseng for six weeks. Blood samples from the subjects before and after the test was performed. One wey ANOVA were used to test for differences between group and pair T-test were used for differences within groups. In all cases, P<0.05 was considered to be statistically significant. Results: A higher and significant Vo2 max was found in E and EG groups, while no change in other groups. BMI and Fat% were significantly decreased in EG group. No significant difference was found between and within groups in VEGF level. A higher and significant PDGF was only in endurance group, while there was significant reduction observed in G and EG groups. One-way ANOVA for PDGF showed significant difference between groups. Conclusion: The finding of the current study indicated that ginseng likely could through reducing of angiogenesis factors Such as VEGF and PDGF and reduced activity of tumor necrosis factor and inhibited inflammatory process.

Keywords: endurance, ginseng, VEGF, PDGF, untrained female

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Authors: Francesco Angelucci, Katerina Veverova, Alžbeta Katonová, Lydia Piendel, Martin Vyhnalek, Jakub Hort

Abstract:

Alzheimer's disease (AD) is a central nervous system (CNS) disease characterized by loss of memory, cognitive functions and neurodegeneration. Plasmin is an enzyme degrading many plasma proteins. In the CNS, plasmin may reduce the accumulation of A, and have other actions relevant to AD pathophysiology. Brain plasmin synthesis is regulated by two enzymes: one activating, the tissue plasminogen activator (tPA), and the other inhibiting, the plasminogen activator inhibitor-1 (PAI-1). We investigated whether tPA and PAI-1 serum levels in AD and amnestic mild cognitive impairment (aMCI) patients are altered compared to cognitively healthy controls. Moreover, we examined the PAI-1/tPA ratio in these patient groups. 40 AD, 40 aMCI and 10 healthy controls were recruited. Venous blood was collected and PAI-1 and tPA serum concentrations were quantified by sandwich ELISAs. The results showed that PAI-1 levels increased in AD and aMCI patients. This increase negatively correlated with cognitive deficit measured by MMSE. Similarly, the ratio between tPA and PAI-1 gradually increases in aMCI and AD patients. This study demonstrates that AD and aMCI patients have altered PAI-1 serum levels and PAI-1/tPA ratio. Since these enzymes are CNS regulators of plasmin, PAI-1 serum levels could be a marker reflecting a cognitive decline in AD.

Keywords: Alzheimer disease, amnestic mild cognitive impairment, plasmin, tissue-type plasminogen activator

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Authors: Anusha Bhardwaj, Shekhar Shinde

Abstract:

Nitric oxide (NO•) has been documented in research papers as one of the most versatile player in the therapeutics. It is identified as a biological multifunctional messenger molecule which is synthesized by the action of nitric oxide synthase (NOS) enzyme from L-arginine. The protective and the toxic effect in conjunction form the complete picture of the biological function of nitric oxide in humans. The dual nature is because of various factors such as concentration of NO, the isoform of NOS involved, type of cells in which it is synthesized, reaction partners like proteins, reactive oxygen intermediates, prosthetic groups, thiols etc., availability of the substrate L-arginine, intracellular environment in which NO is produced and generation of guanosine 3, 5’- cyclic monophosphate (cGMP). Activation of NOS through infection or trauma leads to one or more systemic effects including enhanced immune activity against invading pathogens, vaso/bronchodilatation in the cardiovascular and respiratory systems and altered neurotransmission which can be protective or toxic. Hence, NO affects the balance between healthy signaling and neurodegeneration in the brain. In lungs, it has beneficial effects on the function of airways as a bronchodilator and acts as the neurotransmitter of bronchodilator nerves. Whereas, on the other hand, NO may have deleterious effects by amplifying the asthmatic inflammatory response and also act as a vasodilator in the airways by increasing plasma exudation. But NOS Inhibitors and NO donors hamper the signalling pathway and hence a therapeutic application of NO is compromised.

Keywords: nitric oxide, multifunctional, dual nature, therapeutic applications

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