Search results for: pattern recognition receptor

Authors: Saad Mahmud Khan, Sarah El Hajj Chehadeh, Mehera Abdulrahman, Wael Osman, Habiba Al Safar

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Obesity is a non-communicable disease that is widely prevalent with approximately 600 million people classified as obese worldwide. Its etiology is multifactorial and involves a complex interplay between genes and the environment. Over the past few decades, obesity rates among the Emirati population have been increasing. The aim of this study was to investigate the association of candidate gene single nucleotide polymorphisms (SNPs), namely the fat mass and obesity associated (FTO) gene SNP rs9939609 and Vitamin D Receptor (VDR) gene SNP rs1544410, with obesity in the UAE population. Methods: This is a case-control study in which 414 individuals were enrolled during their routine visit to endocrinology clinics in Abu Dhabi, United Arab Emirates between the period of June 2012 and December 2013. Several biochemical tests and clinical assessments along with a lifestyle questionnaire for each participant were completed at the clinic. Genomic DNA was extracted from saliva samples of 201 obese, 114 overweight and 99 normal subjects. Genotyping for the variants was performed using TaqMan assay. Results: The mean Body Mass Index (BMI) ± SD for the obese, overweight, and normal subjects was 35.76 ± 4.54, 27.53 ± 1.45 and 22.69 ± 1.84 kg/m2, respectively. Increasing BMI values were associated with an increase in values for systolic blood pressure, diastolic blood pressure, HbA1c, and triglycerides. The SNP rs9939609 in the FTO gene was found to be significantly associated with the BMI (p=0.028), with the minor allele A having a clear additive effect on BMI values. No significant association was detected between BMI and rs1544410 of the VDR gene. Conclusions: Our study findings indicate that the minor allele A of the rs9939609 has a significant association with increasing BMI values. In addition, our findings support the fact that increasing BMI is associated with increasing risks of other comorbidities such as higher blood pressure, poorer glycemic control and higher triglycerides.

Keywords: body mass index, FTO gene, obesity, rs9939609, United Arab Emirates

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Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

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The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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Authors: Hong Im Shin

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Previous research demonstrated that self-objectification (women view themselves as objects for use) is related to system-justification. Three studies investigated whether cultural disposition as its system-justifying function could have an impact on self-objectification and dehumanization of sexualized women and men. Study 1 (N = 91) employed a survey methodology to examine the relationship between cultural disposition (collectivism vs. individualism), trait of system-justification, and self-objectification. The results showed that the higher tendency of collectivism was related to stronger system-justification and self-objectification. Study 2 (N = 60 females) introduced a single category implicit association task (SC-IAT) to assess the extent to which sexually objectified women were associated with uniquely human attributes (i.e., culture) compared to animal-related attributes (i.e., nature). According to results, female participants associated sexually objectified female targets less with human attributes compared to animal-related attributes. Study 3 (N = 46) investigated whether priming to individualism or collectivism was associated to system justification and sexual objectification of men and women with the use of a recognition task involving upright and inverted pictures of sexualized women and men. The results indicated that the female participants primed to individualism showed an inversion effect for sexualized women and men (person-like recognition), whereas there was no inversion effect for sexualized women in the priming condition of collectivism (object-like recognition). This implies that cultural disposition plays a mediating role for rationalizing the gender status, implicit dehumanization of sexualized females and self-objectification. Future research directions are discussed.

Keywords: cultural disposition, dehumanization, implicit test, self-objectification

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Authors: Ratna Sharma, Kaveri Dutta

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Assam (India), the gate way to the Northeast India is mainly known for its exquisite silks, the art and craft. The state has a rich collection of traditional jewellery which is unique and exclusive to the state. These jewelleries hold a special place in the heart of the Assamese women. Similarly handloom industry of Assam is basically silk oriented. Among the wild silk, Eri silk fabric has remained as “the poor man’s silk” but it is closely attached to the assamese society, dress for it's warm quality. In view of the changing market trends, fashion and consumer demands, Silk is emerging as a fashion fabric both in India and abroad. In case of Eri silk fabric it has limited use in clothing and accessories. Hence the restructured and redesigned traditional jewellery motifs of Assam (India) over Eri silk products will have greater potential in reviving the decline of art, generate revenue, self employment towards craftsmen and also recognition of the art. The information incorporated in the paper is primary and the data have been collected by purposive sampling method. This work of art was expressed on Eri silk fabric in the form of traditional hand embroidery as it is closely connected with the era of the individual in history of mankind and reflects the personal expression of an entity. For this study selected traditional motifs of Assamese ornaments was used. Some of the popular traditional Assamese jewellery include earrings with exquisite Lokaparo, Keru, Thuriya, Jangphai, etc. An array of necklaces including Golpata, Satsori, Jon biri, Bena, Gejera, Dhol biri, Doog doogi, Biri Moni, Mukuta Moni, Poalmoni, Silikha Moni and Magardana and diversified rings including Senpata, Horinsakua, Jethinejia, bakharpata and others. Selected two motifs each from necklace, earring and finger ring designs. Selected motifs were further developed into 3 categories- the border, the main motif and all over butta followed by placement of developed patterns on products. Products developed were stoles, scarf’s, purses, brooch pins, skirts for women and ties, handkerchief, jackets for men. The developed products were surveyed by selected respondents. From the present study it can be observed that the embellished traditional jewellery motifs resulted in fresh and colourful pattern on developed Eri silk products. Moreover the motifs which were gradually fading among the community itself showed a very good recognition towards art. The embroidered Eri silk fabric also created a huge change in a positive way among craftsman.

Keywords: Art and craft of Assam, eri silk, hand embroidery, traditional Assamese jewellery motifs

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Authors: Bahaa Eltahawy, Mikko Ylihärsilä, Reino Virrankoski, Esko Petäjä

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Sheet metal processing is automated, but the step from product models to the production machine control still requires human intervention. This may cause time consuming bottlenecks in the production process and increase the risk of human errors. In this paper we present a system, which automatically recognizes features from the CAD-model of the sheet metal product. By using these features, the system produces a complete model of the particular sheet metal product. Then the model is used as an input for the sheet metal processing machine. Currently the system is implemented, capable to recognize more than 11 of the most common sheet metal structural features, and the procedure is fully automated. This provides remarkable savings in the production time, and protects against the human errors. This paper presents the developed system architecture, applied algorithms and system software implementation and testing.

Keywords: feature recognition, automation, sheet metal manufacturing, CAD, CAM

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Authors: Marjan Mahdavi-Roshan, Arsalan Salari, Mahboobeh Gholipour, Moona Naghshbandi

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Background and objectives: Before any nutritional intervention, it is necessary to have the prospect of eating habits of people with cardiovascular risk factors. In this study, we assessed the adherence of healthy diet based on Mediterranean dietary pattern and related factors in adults in the north of Iran. Methods: This study was conducted on 550 men and women with cardiovascular risk factors that referred to Heshmat hospital in Rasht, northern Iran. Information was collected by interview and reading medical history and measuring anthropometric indexes. The Mediterranean Diet Adherence Screener was used for assessing dietary adherence, this screener was modified according to religious beliefs and culture of Iran. Results: The mean age of participants was 58±0.38 years. The mean of body mass index was 27±0.01 kg/m², and the mean of waist circumference was 98±0.2 cm. The mean of dietary adherence was 5.76±0.07. 45% of participants had low adherence, and just 4% had suitable adherence. The mean of dietary adherence in men was significantly higher than women (p=0. 07). Participants in rural area and high educational participants insignificantly had an unsuitable dietary Adherence. There was no significant association between some cardiovascular disease risk factors and dietary adherence. Conclusion: Education to different group about dietary intake correction and using a Mediterranean dietary pattern that is similar to dietary intake in the north of Iran, for controlling cardiovascular disease is necessary.

Keywords: dietary adherence, Mediterranean dietary pattern, cardiovascular disease, north of Iran

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Authors: Hadri Hussain, M.Nasir Ibrahim, Chee-Ming Ting, Mariani Idroas, Fuad Numan, Alias Mohd Noor

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A biometric security system has become an important application in client identification and verification system. A conventional biometric system is normally based on unimodal biometric that depends on either behavioural or physiological information for authentication purposes. The behavioural biometric depends on human body biometric signal (such as speech) and biosignal biometric (such as electrocardiogram (ECG) and phonocardiogram or heart sound (HS)). The speech signal is commonly used in a recognition system in biometric, while the ECG and the HS have been used to identify a person’s diseases uniquely related to its cluster. However, the conventional biometric system is liable to spoof attack that will affect the performance of the system. Therefore, a multimodal biometric security system is developed, which is based on biometric signal of ECG, HS, and speech. The biosignal data involved in the biometric system is initially segmented, with each segment Mel Frequency Cepstral Coefficients (MFCC) method is exploited for extracting the feature. The Hidden Markov Model (HMM) is used to model the client and to classify the unknown input with respect to the modal. The recognition system involved training and testing session that is known as client identification (CID). In this project, twenty clients are tested with the developed system. The best overall performance at 44 kHz was 93.92% for ECG and the worst overall performance was ECG at 88.47%. The results were compared to the best overall performance at 44 kHz for (20clients) to increment of clients, which was 90.00% for HS and the worst overall performance falls at ECG at 79.91%. It can be concluded that the difference multimodal biometric has a substantial effect on performance of the biometric system and with the increment of data, even with higher frequency sampling, the performance still decreased slightly as predicted.

Keywords: electrocardiogram, phonocardiogram, hidden markov model, mel frequency cepstral coeffiecients, client identification

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Authors: Chien-Hung Chen, Yan-Chun Hsing, Yung-Chun Chang

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The Internet has grown into a powerful medium for information dispersion and social interaction that leads to a rapid growth of social media which allows users to easily post their emotions and perspectives regarding certain topics online. Our research aims at using natural language processing and text mining techniques to explore the public emotions expressed on Twitter by analyzing the sentiment behind tweets. In this paper, we propose a composite kernel method that integrates tree kernel with the linear kernel to simultaneously exploit both the tree representation and the distributed emotion keyword representation to analyze the syntactic and content information in tweets. The experiment results demonstrate that our method can effectively detect public emotion of tweets while outperforming the other compared methods.

Keywords: emotion recognition, natural language processing, composite kernel, sentiment analysis, text mining

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Mohammad Saifuddin, Shahjada Selim

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Patients with diabetes mellitus (DM) are prone to develop infection, especially urinary tract infection (UTI) in comparison with non-diabetics. Due to the emergence of multidrug resistant (MDR) uropathogenic strains, the choice of antimicrobial agent is sometimes difficult. This study is designed to reveal the distribution of uropathogens in Diabetic patients and corresponding sensitivity patterns and to correlate the microbiological results with various clinical parameters. A nine-month retrospective review of 100 urine culture reports of Diabetic patients from January 2015 to September 2015 from semiurbanmultispeciality hospital of Feni, Bangladesh were analyzed. Only Diabetic patients were included in this study who were clinically diagnosed as UTI patients with a corresponding urine culture showing a bacterial count of ˃105cfu/ml.Out of 100 patients with UTI, 39 (39%) were male, and 61 (61%) were female. Organisms grown in urine culture were Escherichia coli (64) followed by Klebsiella (11), Proteus (7), Staph Aureus (4), Pseudomonas (4), Acinetobacter (3), Sreptococcus(3), Enterococcus (2 ) and one each of Enterobacter and Fungi. Overall sensitivity pattern in decreasing order of various commonly used antibiotics was Meropenem (89%), Nitrofurantoin (86%), Amikacin (81%), Ceftriaxone (68%), Cefuroxime (61%), Cefixime (39%), Quinolones (28%), Amoxicillin (16%). The significance of the study lies in the determination of common pathogens in diabetic patients with UTI and the resistance pattern of antibiotics so that physicians and pharmacists get the proper information rationalizing the rational use of antibiotics.

Keywords: Bangladesh, Diabetes Mellitus, E. coli, urinary tract infection

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Authors: W. J. Zhang, Y. Q. Du, M. L. Wang

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Noninvasive diagnostics of diseases via breath analysis has attracted considerable scientific and clinical interest for many years and become more and more promising with the rapid advancement in nanotechnology and biotechnology. The volatile organic compounds (VOCs) in exhaled breath, which are mainly blood borne, particularly provide highly valuable information about individuals’ physiological and pathophysiological conditions. Additionally, breath analysis is noninvasive, real-time, painless and agreeable to patients. We have developed a wireless sensor array based on single-stranded DNA (ssDNA)-decorated single-walled carbon nanotubes (SWNT) for the detection of a number of physiological indicators in breath. Eight DNA sequences were used to functionalize SWNT sensors to detect trace amount of methanol, benzene, dimethyl sulfide, hydrogen sulfide, acetone and ethanol, which are indicators of heavy smoking, excessive drinking, and diseases such as lung cancer, breast cancer, cirrhosis and diabetes. Our tests indicated that DNA functionalized SWNT sensors exhibit great selectivity, sensitivity, reproducibility, and repeatability. Furthermore, different molecules can be distinguished through pattern recognition enabled by this sensor array. Thus, the DNA-SWNT sensor array has great potential to be applied in chemical or bimolecular detection for the noninvasive diagnostics of diseases and health monitoring.

Keywords: breath analysis, diagnosis, DNA-SWNT sensor array, noninvasive

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Authors: LuoJiaoyang, Yu Hongyang

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In this paper, we experimented with a new approach to multimodal identification using RGB, RGB-D and voice data. The multimodal combination of RGB and voice data has been applied in tasks such as emotion recognition and has shown good results and stability, and it is also the same in identity recognition tasks. We believe that the data of different modalities can enhance the effect of the model through mutual reinforcement. We try to increase the three modalities on the basis of the dual modalities and try to improve the effectiveness of the network by increasing the number of modalities. We also implemented the single-modal identification system separately, tested the data of these different modalities under clean and noisy conditions, and compared the performance with the multimodal model. In the process of designing the multimodal model, we tried a variety of different fusion strategies and finally chose the fusion method with the best performance. The experimental results show that the performance of the multimodal system is better than that of the single modality, especially in dealing with noise, and the multimodal system can achieve an average improvement of 5%.

Keywords: multimodal, three modalities, RGB-D, identity verification

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Authors: Agoston Restas

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Introduction: In case of managing disasters decision makers can face many times such a special situation where any pre-sign of the drastically change is missing therefore the improvised decision making can be required. The complexity, ambiguity, uncertainty or the volatility of the situation can require many times the improvisation as decision making. It can be taken at any level of the management (strategic, operational and tactical) but at tactical level the main reason of the improvisation is surely time pressure. It is certainly the biggest problem during the management. Methods: The author used different tools and methods to achieve his goals; one of them was the study of the relevant literature, the other one was his own experience as a firefighting manager. Other results come from two surveys that are referred to; one of them was an essay analysis, the second one was a word association test, specially created for the research. Results and discussion: This article proves that, in certain situations, the multi-criteria, evaluating decision-making processes simply cannot be used or only in a limited manner. However, it can be seen that managers, directors or commanders are many times in situations that simply cannot be ignored when making decisions which should be made in a short time. The functional background of decisions made in a short time, their mechanism, which is different from the conventional, was studied lately and this special decision procedure was given the name recognition-primed decision. In the article, author illustrates the limits of the possibilities of analytical decision-making, presents the general operating mechanism of recognition-primed decision-making, elaborates on its special model relevant to managers at tactical level, as well as explore and systemize the factors that facilitate (catalyze) the processes with an example with fire managers.

Keywords: decision making, disaster managers, recognition primed decision, model for making decisions in emergencies

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Authors: Anna Romanova, Morteza A. Alani

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Corrosion of concrete sewer pipes induced by sulfuric acid is an acknowledged problem and a ticking time-bomb to sewer operators. Whilst the chemical reaction of the corrosion process is well-understood, the indirect roles of other parameters in the corrosion process which are found in sewer environment are not highly reflected on. This paper reports on a field studies undertaken in Austria and United Kingdom, where the parameters of temperature, pH, H2S and CO2 were monitored over a period of time. The study establishes that (i) effluent temperature and pH have similar daily pattern and peak times, When examined in minutes scale, (ii) H2S and CO2 have an identical hourly pattern, (iii) H2S instant or shifted relation to effluent temperature is governed by the root mean square value of CO2.

Keywords: concrete corrosion, carbon dioxide, hydrogen sulphide, sewer pipe, sulfuric acid

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Authors: Marek Kuźniewski, Magdalena B. Kaziuk , Danuta Fedak, Paulina Dumnicka, Ewa Stępień, Beata Kuśnierz-Cabala, Władysław Sułowicz

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Background: The high prevalence of cardiovascular morbidity and mortality among patients with chronic kidney disease (CKD) is observed especially in those undergoing dialysis. Osteoprotegerin (OPG) and its ligands, receptor activator of nuclear factor kappa-B ligand (RANKL) and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) have been associated with cardiovascular complications. Our aim was to study their role as cardiovascular risk factors in stage 5 CKD patients. Methods: OPG, RANKL and TRAIL concentrations were measured in 69 hemodialyzed CKD patients and 35 healthy volunteers. In CKD patients, cardiovascular dysfunction was assessed with aortic pulse wave velocity (AoPWV), carotid artery intima-media thickness (CCA-IMT), coronary artery calcium score (CaSc) and N-terminal pro-B-type natriuretic peptide (NT-proBNP) serum concentration. Cardiovascular and overall mortality data were collected during a 7-years follow-up. Results: OPG plasma concentrations were higher in CKD patients comparing to controls. Total soluble RANKL was lower and OPG/RANKL ratio higher in patients. Soluble TRAIL concentrations did not differ between the groups and OPG/TRAIL ratio was higher in CKD patients. OPG and OPG/TRAIL positively predicted long-term mortality (all-cause and cardiovascular) in CKD patients. OPG positively correlated with AoPWV, CCA-IMT and NT-proBNP whereas OPG/TRAIL with AoPWV and NT-proBNP. Described relationships were independent of classical and non-classical cardiovascular risk factors, with exception of age. Conclusions: Our study confirmed the role of OPG as a biomarker of cardiovascular dysfunction and a predictor of mortality in stage 5 CKD. OPG/TRAIL ratio can be proposed as a predictor of cardiovascular dysfunction and mortality.

Keywords: osteoprotegerin, tumor necrosis factor-related apoptosis-inducing ligand, receptor activator of nuclear factor kappa-B ligand, hemodialysis, chronic kidney disease, cardiovascular disease

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Authors: Axel Mancebo, Ana M. Bada, Angel Casacó, Bárbara González, Avelina León, María E. Arteaga, Consuelo González, Belinda Sánchez, Adriana Carr, Nuris Ledón, Arianna Iglesias

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Despite the many preventive and therapeutic modalities aimed at curing cancer, it remains as a serious world health problem. Promising recent developments suggest that cancer immunotherapy may be the next great hope for cancer treatment. EGFRs are receptor tyrosine kinases and it is considered an important therapeutic target related with tumor progression, and several types of molecular therapies, including monoclonal antibodies, small molecules, and vaccines, have been developed to target the HER family of receptors. On the other hand, gangliosides are membrane glycosphingolipids that contain two variants of sialic acid, the N-acetylated (NeuAc) and the N-glycolylated (NeuGc) variant. The high expression of this antigen-specific molecule has been associated with malignant tumor progression and immunosuppressive mechanisms, so ganglioside could be considered as the target for cancer immunotherapy. We have been working for several years in the safety evaluation of cancer vaccines targeting these two systems, the EGF receptor and ganglioside. We presented in this work results of repeated dose toxicity studies performed in Sprague Dawley rats and Cynomolgus monkeys, including clinical observations, body weight and rectal temperature measuring, clinical pathology analysis, gross necropsy and histological examination in rodent studies, and immunological evaluation. Immunizations were capable of inducing mainly inflammatory effects at the injection site, with findings largely attributable to the adjuvants used and probably enhanced by the immunological properties of the antigens. In general, these vaccines were shown to be well tolerated, and these studies in relevant species allow treating cancer patients with tumors during long periods with relative weight safety margin.

Keywords: cancer vaccines, safety, toxicology, rats, non human primates

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Authors: Xiaoping Zhang, Fengying Yan

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The implementation of the 'Urban Design Management Measures' requires that the master urban design should aim at creating a livable urban space. However, to our best knowledge, the existing researches and practices of master urban design not only focus less on the livable space but also face a number of problems such as paying more attention to the image of the city, ignoring the people-oriented and lacking dynamic continuity. In order to make the master urban design can better guide the construction of city. Firstly, the paper proposes the livable city hierarchy system to meet the needs of different groups of people and then constructs the framework of livable goal-oriented master urban design based on the theory of livable content and the ideological origin of people-oriented. Secondly, the paper takes the master urban design practice of Zibo as a sample and puts forward the design strategy of strengthening the pattern, improve the quality of space, shape the feature, and establish a series of action plans based on the strategy of urban space development. Finally, the paper explores the method system of livable goal-oriented master urban design from the aspects of safety pattern, morphology pattern, neighborhood scale, open space, street space, public interface, style feature, public participation and action plans.

Keywords: livable, master urban design, public participation, zibo city

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Authors: Afsaneh Mohammadnejad, Marianne Nygaard, Jan Baumbach, Shuxia Li, Weilong Li, Jesper Lund, Jacob v. B. Hjelmborg, Lene Christensen, Qihua Tan

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Cognitive impairment in the elderly is a key issue affecting the quality of life. Despite a strong genetic background in cognition, only a limited number of single nucleotide polymorphisms (SNPs) have been found. These explain a small proportion of the genetic component of cognitive function, thus leaving a large proportion unaccounted for. We hypothesize that one reason for this missing heritability is the misspecified modeling in data analysis concerning phenotype distribution as well as the relationship between SNP dosage and the phenotype of interest. In an attempt to overcome these issues, we introduced a model-free method based on the generalized correlation coefficient (GCC) in a genome-wide association study (GWAS) of cognitive function in twin samples and compared its performance with two popular linear regression models. The GCC-based GWAS identified two genome-wide significant (P-value < 5e-8) SNPs; rs2904650 near ZDHHC2 on chromosome 8 and rs111256489 near CD6 on chromosome 11. The kinship model also detected two genome-wide significant SNPs, rs112169253 on chromosome 4 and rs17417920 on chromosome 7, whereas no genome-wide significant SNPs were found by the linear mixed model (LME). Compared to the linear models, more meaningful biological pathways like GABA receptor activation, ion channel transport, neuroactive ligand-receptor interaction, and the renin-angiotensin system were found to be enriched by SNPs from GCC. The GCC model outperformed the linear regression models by identifying more genome-wide significant genetic variants and more meaningful biological pathways related to cognitive function. Moreover, GCC-based GWAS was robust in handling genetically related twin samples, which is an important feature in handling genetic confounding in association studies.

Keywords: cognition, generalized correlation coefficient, GWAS, twins

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Authors: Wenyang Wan

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The study of urban land use and landscape pattern is the current hotspot in the fields of planning and design, ecology, etc., which is of great significance for the construction of the overall humanistic ecosystem of the city and optimization of the urban spatial structure. Banan District, as the main part of the eastern eco-city planning of Chongqing Municipality, is a high ground for highlighting the ecological characteristics of Chongqing, realizing effective transformation of ecological value, and promoting the integrated development of urban and rural areas. The analytical methods of land use transfer matrix (GIS) and landscape pattern index (Fragstats) were used to study the characteristics and laws of the evolution of land use landscape pattern in Banan District from 2000 to 2020, which provide some reference value for Banan District to alleviate the ecological contradiction of landscape. The results of the study show that ① Banan District is rich in land use types, of which the area of cultivated land will still account for 57.15% of the total area of the landscape until 2020, accounting for an absolute advantage in land use structure of Banan District; ② From 2000 to 2020, land use conversion in Banan District is characterized as Cropland > woodland > grassland > shrubland > built-up land > water bodies > wetlands, with cropland converted to built-up land being the largest; ③ From 2000 to 2020, the landscape elements of Banan District were distributed in a balanced way, and the landscape types were rich and diversified, but due to the influence of human interference, it also presented the characteristics that the shape of the landscape elements tended to be irregular, and the dominant patches were distributed in a scattered manner, and the patches had poor connectivity. It is recommended that in future regional ecological construction, the layout should be rationally optimized, the relationship between landscape components should be coordinated, the connectivity between landscape patches should be strengthened, and the degree of landscape fragmentation should be reduced.

Keywords: land use transfer, landscape pattern evolution, GIS and Fragstats, Banan district

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Authors: Manutchanok Jongprasithporn, Rawiphorn Srivilai, Paweena Pongsopha

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Fall is the most serious accident leading to increased unintentional injuries and mortality. Falls are not only the cause of suffering and functional impairments to the individuals, but also the cause of increasing medical cost and days away from work. The early detection of falls could be an advantage to reduce fall-related injuries and consequences of falls. Smartphones, embedded accelerometer, have become a common device in everyday life due to decreasing technology cost. This paper explores a physical activity monitoring and fall detection application in smartphones which is a non-invasive biomedical device to determine physical activities and fall event. The combination of application and sensors could perform as a biomedical sensor to monitor physical activities and recognize a fall. We have chosen Android-based smartphone in this study since android operating system is an open-source and no cost. Moreover, android phone users become a majority of Thai’s smartphone users. We developed Thai 3 Axis (TH3AX) as a physical activities and fall detection application which included command, manual, results in Thai language. The smartphone was attached to right hip of 10 young, healthy adult subjects (5 males, 5 females; aged< 35y) to collect accelerometer and gyroscope data during performing physical activities (e.g., walking, running, sitting, and lying down) and falling to determine threshold for each activity. Dependent variables are including accelerometer data (acceleration, peak acceleration, average resultant acceleration, and time between peak acceleration). A repeated measures ANOVA was performed to test whether there are any differences between DVs’ means. Statistical analyses were considered significant at p<0.05. After finding threshold, the results were used as training data for a predictive model of activity recognition. In the future, accuracies of activity recognition will be performed to assess the overall performance of the classifier. Moreover, to help improve the quality of life, our system will be implemented with patients and elderly people who need intensive care in hospitals and nursing homes in Thailand.

Keywords: activity recognition, accelerometer, fall, gyroscope, smartphone

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Authors: Jia-Hong Lee, Mei-Yi Wu, Hsien-Tsung Kuo

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Texture is an important characteristic in real and synthetic scenes. Texture analysis plays a critical role in inspecting surfaces and provides important techniques in a variety of applications. Although several descriptors have been presented to extract texture features, the development of object recognition is still a difficult task due to the complex aspects of texture. Recently, many robust and scaling-invariant image features such as SIFT, SURF and ORB have been successfully used in image retrieval and object recognition. In this paper, we have tried to compare the performance for texture classification using these feature descriptors with k-means clustering. Different classifiers including K-NN, Naive Bayes, Back Propagation Neural Network , Decision Tree and Kstar were applied in three texture image sets － UIUCTex, KTH-TIPS and Brodatz, respectively. Experimental results reveal SIFTS as the best average accuracy rate holder in UIUCTex, KTH-TIPS and SURF is advantaged in Brodatz texture set. BP neuro network works best in the test set classification among all used classifiers.

Keywords: texture classification, texture descriptor, SIFT, SURF, ORB

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Authors: Zamri Abu Bakar Zamri, Normaly Kamal Ismail Normaly, Mohd Izani Mohamed Rawi Izani

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Malay noun compound are phrases that consist of two or more nouns. The key characteristic behind noun compounds lies on its frequent occurrences within the text. Therefore, extracting these noun compounds is essential for several domains of research such as Information Retrieval, Sentiment Analysis and Question Answering. Many research efforts have been proposed in terms of extracting Malay noun compounds using linguistic and statistical approaches. Most of the existing methods have concentrated on the extraction of bi-gram noun+noun compound. However, extracting noun+verb, noun+adjective and noun+prepositional is challenging due to the difficulty of selecting an appropriate method with effective results. Thus, there is still room for improvement in terms of enhancing the effectiveness of compound word extraction. Therefore, this study proposed a combination of linguistic approach and statistical measures in order to enhance the extraction of compound words. Several preprocessing steps are involved including normalization, tokenization, and stemming. The linguistic approach that has been used in this study is Part-of-Speech (POS) tagging. In addition, a new linguistic pattern for named entities has been utilized using a list of Malays named entities in order to enhance the linguistic approach in terms of noun compound recognition. The proposed statistical measures consists of NC-value, NTC-value and NLC value.

Keywords: Compound Word, Noun Compound, Linguistic Approach, Statistical Approach

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Authors: Fernando C. Labouriau, Ricardo M. Naveiro

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This paper presents a model for mapping the evolutive pattern of products in order to generate new ideas, to perceive emerging technologies and to manage product’s portfolios in new product development (NPD). According to the proposed model, the information extracted from the patent system is filtered and analyzed with TRIZ tools to produce the input information to the NPD process. The authors acknowledge that the NPD process is well integrated within the enterprises business strategic planning and that new products are vital in the competitive market nowadays. In the other hand, it has been observed the proactive use of patent information in some methodologies for selecting projects, mapping technological change and generating product concepts. And one of these methodologies is TRIZ, a theory created to favor innovation and to improve product design that provided the analytical framework for the model. Initially, it is presented an introduction to TRIZ mainly focused on the patterns of evolution of technical systems and its strategic uses, a brief and absolutely non-comprehensive description as the theory has several others tools being widely employed in technical and business applications. Then, it is introduced the model for mapping the products evolutive pattern with its three basic pillars, namely patent information, TRIZ and NPD, and the methodology for implementation. Following, a case study of a Brazilian bike manufacturing is presented to proceed the mapping of a product evolutive pattern by decomposing and analyzing one of its assemblies along ten evolution lines in order to envision opportunities for further product development. Some of these lines are illustrated in more details to evaluate the features of the product in relation to the TRIZ concepts using a comparison perspective with patents in the state of the art to validate the product’s evolutionary potential. As a result, the case study provided several opportunities for a product improvement development program in different project categories, identifying technical and business impacts as well as indicating the lines of evolution that can mostly benefit from each opportunity.

Keywords: product development, patents, product strategy, systems evolution

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Authors: Insiya Bhalloo

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It is quite common in the Muslim faith for non-Arabic speakers to be able to convert written Arabic, especially Quranic Arabic, into a phonological code without significant semantic or syntactic knowledge. This is due to prior experience learning to read the Quran (a religious text written in Classical Arabic), from a very young age such as via enrolment in Quranic Arabic classes. As compared to native speakers of Arabic, these Arabic readers do not have a comprehensive morpho-syntactic knowledge of the Arabic language, nor can understand, or engage in Arabic conversation. The study seeks to investigate whether mere phonological experience (as indicated by the Arabic readers’ experience with Arabic phonology and the sound-system) is sufficient to cause phonological-interference during word recognition of previously-heard words, despite the participants’ non-native status. Both native speakers of Arabic and non-native speakers of Arabic, i.e., those individuals that learned to read the Quran from a young age, will be recruited. Each experimental session will include two phases: An exposure phase and a test phase. During the exposure phase, participants will be presented with Arabic words (n=40) on a computer screen. Half of these words will be common words found in the Quran while the other half will be words commonly found in Modern Standard Arabic (MSA) but either non-existent or prevalent at a significantly lower frequency within the Quran. During the test phase, participants will then be presented with both familiar (n = 20; i.e., those words presented during the exposure phase) and novel Arabic words (n = 20; i.e., words not presented during the exposure phase. ½ of these presented words will be common Quranic Arabic words and the other ½ will be common MSA words but not Quranic words. Moreover, ½ the Quranic Arabic and MSA words presented will be comprised of nouns, while ½ the Quranic Arabic and MSA will be comprised of verbs, thereby eliminating word-processing issues affected by lexical category. Participants will then determine if they had seen that word during the exposure phase. This study seeks to investigate whether long-term phonological memory, such as via childhood exposure to Quranic Arabic orthography, has a differential effect on the word-recognition capacities of native Arabic speakers and Arabic readers; we seek to compare the effects of long-term phonological memory in comparison to short-term phonological exposure (as indicated by the presentation of familiar words from the exposure phase). The researcher’s hypothesis is that, despite the lack of lexical knowledge, early experience with converting written Quranic Arabic text into a phonological code will help participants recall the familiar Quranic words that appeared during the exposure phase more accurately than those that were not presented during the exposure phase. Moreover, it is anticipated that the non-native Arabic readers will also report more false alarms to the unfamiliar Quranic words, due to early childhood phonological exposure to Quranic Arabic script - thereby causing false phonological facilitatory effects.

Keywords: modern standard arabic, phonological facilitation, phonological memory, Quranic arabic, word recognition

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Authors: Vaishnavi Shivde, Shrishti Sinha, Trapti Mishra

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Traffic light detection from a moving vehicle is an important technology both for driver safety assistance functions as well as for autonomous driving in the city. This paper proposed a deep-learning-based traffic light recognition method that consists of a pixel-wise image segmentation technique and a fully convolutional network i.e., UNET architecture. This paper has used a method for detecting the position and recognizing the state of the traffic lights in video sequences is presented and evaluated using Traffic Light Dataset which contains masked traffic light image data. The first stage is the detection, which is accomplished through image processing (image segmentation) techniques such as image cropping, color transformation, segmentation of possible traffic lights. The second stage is the recognition, which means identifying the color of the traffic light or knowing the state of traffic light which is achieved by using a Convolutional Neural Network (UNET architecture).

Keywords: traffic light detection, image segmentation, machine learning, classification, convolutional neural networks

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Authors: Rima Hleiss, Elie Bitar, Mahmoud Hassan, Mohamad Khalil

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A comprehensive study of object recognition in the human brain requires combining both spatial and temporal analysis of brain activity. Here, we are mainly interested in three issues: the time perception of visual objects, the ability of discrimination between two particular categories (objects vs. animals), and the possibility to identify a particular spatial representation of visual objects. Our experiment consisted of acquiring dense electroencephalographic (EEG) signals during a picture-naming task comprising a set of objects and animals’ images. These EEG responses were recorded from nine participants. In order to determine the time perception of the presented visual stimulus, we analyzed the Event Related Potentials (ERPs) derived from the recorded EEG signals. The analysis of these signals showed that the brain perceives animals and objects with different time instants. Concerning the discrimination of the two categories, the support vector machine (SVM) was applied on the instantaneous EEG (excellent temporal resolution: on the order of millisecond) to categorize the visual stimuli into two different classes. The spatial differences between the evoked responses of the two categories were also investigated. The results showed a variation of the neural activity with the properties of the visual input. Results showed also the existence of a spatial pattern of electrodes over particular regions of the scalp in correspondence to their responses to the visual inputs.

Keywords: brain activity, categorization, dense EEG, evoked responses, spatio-temporal analysis, SVM, time perception

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Authors: Siddharth Soni, Gourav Kumar Pandey, Sneha Kumari, Dev Mani Pandey, Koel Mukherjee

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The silkworm Bombyx mori is a commercially important insect, but a major roadblock in silk production are silkworm diseases. Flacherie is one of the diseases of the silkworm, that affects the midgut of the 4th and 5th instar larvae and eventually makes them lethargic, stop feeding and finally result in their death. The concerned disease is a result of bacterial and viral infection and in some instances a combination of both. The present study aims to identify and study the expression level of genes in the flacherie condition. For the said work, total RNA was isolated from the infected larvae at their most probable infectious instar and cDNA was synthesized using Reverse Transcriptase PCR (RT-PCR). This cDNA was then used to amplify disease relalted genes whose expression levels were checked using quantitaive PCR (qPCR) using the double delta Ct method. Cry toxin receptors like APN and BtR-175, ROS mediator Dual Oxidase are few proteins whose genes were overexpressed. Interestingly, pattern recognition receptors (PRRs) C-type lectins' genes were found to be downregulated. The results explain about the strong expression of genes that can distinguish the concerned protein in the midgut of diseased silkworm and thereby aiding knowledge in the field of inhibitor designing research.

Keywords: Bombyx mori, flacherie disease, inhibitor designing, up and down regulation

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Authors: Yudia Mailani Putri, Martalena Purba, B. J. Istiti Kandarina

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Background: Obesity has been recognized as a global health problem. Individuals classified as overweight and obese are increasing at an alarming rate. This condition is associated with psychological and physiological problems. as a person reaches adulthood, somatic growth ceases. At this stage, the human body has developed fully, to a stable state. As the capital of Riau Province in Indonesia, Pekanbaru is dominated by Malay ethnic population habitually consuming cholesterol-rich fatty foods as a daily menu, a trigger to the onset of obesity resulting in high prevalence of degenerative diseases. Research objectives: The aim of this study is elaborating the relationship between high-fat consumption pattern, stress level, physical activity and the incidence of obesity in adult women in Pekanbaru city. Research Methods: Among the combined research methods applied in this study, the first stage is quantitative observational, analytical cross-sectional research design with adult women aged 20-40 living in Pekanbaru city. The sample consists of 200 women with BMI≥25. Sample data is processed with univariate, bivariate (correlation and simple linear regression) and multivariate (multiple linear regression) analysis. The second phase is qualitative descriptive study purposive sampling by in-depth interviews. six participants withdrew from the study. Results: According to the results of the bivariate analysis, there are relationships between the incidence of obesity and the pattern of high fat foods consumption (energy intake (p≤0.000; r = 0.536), protein intake (p≤0.000; r=0.307), fat intake (p≤0.000; r=0.416), carbohydrate intake (p≤0.000; r=0.430), frequency of fatty food consumption (p≤0.000; r=0.506) and frequency of viscera foods consumption (p≤0.000; r=0.535). There is a relationship between physical activity and incidence of obesity (p≤0.000; r=-0.631). However, there is no relationship between the level of stress (p=0.741; r=0.019-) and the incidence of obesity. Physical activity is a predominant factor in the incidence of obesity in adult women in Pekanbaru city. Conclusion: There are relationships between high-fat food consumption pattern, physical activity and the incidence of obesity in Pekanbaru city whereas physical activity is a predominant factor in the occurrence of obesity, supported by the unchangeable pattern of high-fat foods consumption.

Keywords: obesity, adult, high in fat, stress, physical activity, consumption pattern

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Authors: Zafar Iqbal Bhatti

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The present research aims to examine and evaluate the frequencies and practices of verb complementation patterns in English newspaper social columns published in Pakistan and Britain. The research will demonstrate that Pakistani English is a non-native variety of English having its own unique usual and logical characteristics, affected by way of the native languages and the culture, upon syntactic levels, making the variety users aware that any differences from British or American English that are systematic and regular, or another English language, are not even if they are unique, erroneous forms and typical characteristics of several kinds. The objectives are to examine the verb complementation patterns that British and Pakistani social columnists use in relation to their syntactic categories. Secondly, to compare the verb complementation patterns used in Pakistani and British English newspapers social columns. This study will figure out various verb complementation patterns in Pakistani and British English newspaper social columns and their occurrence and distribution. The word classes express different functions of words, such as action, event, or state of being. This research aims to evaluate whether there are any appreciable differences in the verb complementation patterns used in Pakistani and British English newspaper social columns. The results will show the number of varieties of verb complementation patterns in selected English newspapers social columns. This study will fill the gap of previous studies conducted in this field as they only explore a little about the differences between Pakistani and British English newspapers. It will also figure out a variety of languages used in Pakistani and British English journals, as well as regional and cultural values and variations. The researcher will use AntConc software in this study to extract the data for analysis. The researcher will use a concordance tool to identify verb complementation patterns in selected data. Then the researcher will manually categorize them because the same type of adverb can sometimes be used for various purposes. From 1st June 2022 to 30th Sep. 2022, a four-month written corpus of the social columns of PE and BE newspapers will be collected and analyzed. For the analysis of the research questions, 50 social columns will be selected from Pakistani newspapers and 50 from British newspapers. The researcher will collect a representative sample of data from Pakistani and British English newspaper social columns. The researcher will manually analyze the complementation patterns of each verb in each sentence, and then the researcher will determine how frequently each pattern occurs. The researcher will use syntactic characteristics of the verb complementation elements according to the description by Downing and Locke (2006). The researcher will examine all of the verb complementation patterns in the data, and the frequency and distribution of each verb complementation pattern will be evaluated using the software. The researcher will explore every possible verb complementation pattern in Pakistani and British English before calculating the occurrence and abundance of each verb pattern. The researcher will explore every possible verb complementation pattern in Pakistani English before calculating the frequency and distribution of each pattern.

Keywords: verb complementation, syntactic categories, newspaper social columns, corpus

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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