Search results for: healthy architecture

Authors: Yaser Kazemzadeh, Keyvan Molanoruzy, Mojtaba Izady

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The balance is the key component of motor skills to maintain postural control and the execution of complex skills. The present study was designed to evaluate the impact of soft knee pads on static and dynamic balance of male athletes. For this aim, thirty young athletes in different sport fields with 3 years professional sport training background and thirty healthy young men nonathletic (age: 24.5 ± 2.9, 24.3 ± 2.4, weight: 77.2 ± 4.3 and 80/9 ± 6/3 and height: 175 ± 2/84, 172 ± 5/44 respectively) as subjects selected. Then, subjects in two manner (without knee and with soft knee pads made of neoprene) execute standard error test (BESS) to assess static balance and star test to assess dynamic balance. For analyze of data, t-tests and one-way ANOVA were significant 05/0 ≥ α statistical analysis. The results showed that the use of soft knee significantly reduced error rate in static balance test (p ≥ 0/05). Also, use a soft knee pads decreased score of athlete group and increased score of nonathletic group in star test (p ≥ 0/05). These findings, indicates that use of knees affects static and dynamic balance in athletes and nonathletic in different manner and may increased athletic performance in sports that rely on static balance and decreased performance in sports that rely on dynamic balance.

Keywords: static balance, dynamic balance, soft knee, athletic men, non athletic men

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Authors: Johann Van Niekerk

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The disciplines of conducting (instrumental or choral) and of singing presume a willingness toward an open posture and, in many cases, demand it for effective communication and technique. Yet, this very openness, with the "spread-eagle" gesture as an extreme, is oftentimes counterintuitive for musicians and within the trajectory of human evolution. Conversely, it is in this very gesture of "taking up space" that confidence-gaining techniques such as the popular "power pose" are based. This paper consists primarily of a literature review, exploring the topics of physical openness and vulnerability, considering the semiotics of the "spread-eagle" and its accompanying letter X. A major finding of this research is the discrepancy between evolutionary instinct towards physical self-protection and “folding in” and the demands of the discipline of physical and gestural openness, expansiveness and vulnerability. A secondary finding is ways in which encouragement of confidence-gaining techniques may be more effective in obtaining the required results than insistence on vulnerability, which is influenced by various cultural contexts and socialization. Choral conductors and music educators are constantly seeking ways to promote engagement and healthy singing. Much of the information and direction toward this goal is gleaned by students from conducting gestures and other pedagogies employed in the rehearsal. The findings of this research provide yet another avenue toward reaching the goals required for sufficient and effective teaching and artistry on the part of instructors and students alike.

Keywords: conducting, gesture, music, pedagogy, posture, vulnerability

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Authors: Jamshid Hussain, Kuen Song Lin

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For prospective applications, chemists and materials scientists are particularly interested in creating 3D-micro/nanocomposite structures with shapes and unique characteristics. Ceria has recently been produced with a variety of morphologies, including one-dimensional structures (nanoparticles, nanorods, nanowires, and nanotubes). It is anticipated that this material can be used in different fields, such as catalysis, methanol decomposition, carbon monoxide oxidation, optical materials, and environmental protection. Distinct three-dimensional hydrated ceria-BTC (CeO₂-1,3,5-Benzenetricarboxylic-acid) microstructures were successfully synthesized via a hydrothermal route in an aqueous solution. FE-SEM and XRD patterns reveal that a ceria-BTC framework diameter and length are approximately 1.45–2.4 and 5.5–6.5 µm, respectively, at 130 oC and with pH 2 for 72 h. It was demonstrated that the reaction conditions affected the 3D ceria-BTC architecture. The hexagonal ceria-BTC microrod comprises organic linkers, which are transformed into hierarchical ceria microrod in the presences of air at 400 oC was confirmed by Fourier transform infrared spectroscopy. The Ce-O bonding of the hierarchical ceria microrod (HCMs) species has a bond distance and coordination number of 2.44 and 6.89, respectively, which attenuates the EXAFS spectra. Compared to the ceria powder, the HCMs produced more oxygen vacancies and Ce3+ as shown by the XPS and XANES/EXAFS analyses.

Keywords: hierarchical ceria microrod, three-dimensional ceria, methanol decomposition, reaction mechanism, XANES/EXAFS

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Authors: Burak Köken, Hatice D. Arslan, Bilgehan Y. Çakmak

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Analyzing the relation networks between the hospital buildings which have complex structure and distinctive spatial relationships is quite difficult. The hospital buildings which require specialty in spatial relationship solutions during design and self-innovation through the developing technology should survive and keep giving service even after the disasters such as earthquakes. In this study, a hospital building where the load-bearing system was strengthened because of the insufficient earthquake performance and the construction of an additional building was required to meet the increasing need for space was discussed and a comparative spatial evaluation of the hospital building was made with regard to its status before the change and after the change. For this reason, spatial organizations of the building before change and after the change were analyzed by means of Space Syntax method and the effects of the change on space organization parameters were searched by applying an analytical procedure. Using Depthmap UCL software, connectivity, visual mean depth, beta and visual integration analyses were conducted. Based on the data obtained after the analyses, it was seen that the relationships between spaces of the building increased after the change and the building has become more explicit and understandable for the occupants. Furthermore, it was determined according to findings of the analysis that the increase in depth causes difficulty in perceiving the spaces and the changes considering this problem generally ease spatial use.

Keywords: architecture, hospital building, space syntax, strengthening

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Authors: Mohammad Rusdi Mohd Nasir, Ismail Hafiz Salleh

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Kota Bharu, as an Islamic City, represents a symbolic icon in the urban development of the Islamic state of Kelantan, Malaysia. This research seeks to provide a basis for new approaches to landscape planning that shows greater respect for the traditional vernacular landscape. In addition, this research also intends to distinguish the prospects for the future Kelantan Malay cultural landscape, building upon the multiple historical influences in the evolution of the cultural landscape using multiple methods including literature review, observation, document analysis and content analysis. The study of the Kelantan Malay cultural landscape is particularly important in view of its distinctive contribution to Malay heritage by identifying the elements, characteristics, history and their influences. As a result, this research recognizes the importance of incorporating the existing heritage alongside contemporary design as well as further research on the Kelantan Malay cultural landscape. Optimistically, there will be better landscape practices in the future to understand the past, the present and the future prospects of the vernacular tradition, in order to ensure that our architecture, landscape and urbanism practices express its values.

Keywords: Malay culture, Malay heritage, cultural landscape, Islamic concept

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Authors: Hanan Azzam1, Nashwa Abousamra1, Amany Mansour1, Yaser Abd El-dayem2, , Solafa Elsharawy1

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Background: Inherited thrombophilias are a heterogenous group of conditions which have been implicated in a variety of pregnancy complications. More recently, deficiency of protein Z (PZ) has been liked to pregnancy complications, including preterm delivery. Aim: We designed this study to evaluate the association of inherited thrombophilias including [Protein C (PC), Protein S (PS), Anti thrombin III (ATIII) deficiency and activated protein C (APC) resistance] and protein Z deficiency with a variety of pregnancy complications. Patients and Methods: 60 women with different pregnancy complications, including 20 patients with preeclampsia, 20 patients with intrauterine growth resistance (IUGR), and 20 patients with intrauterine fetal death (IUFD), in addition to 30 healthy pregnant women were recruited for the present study. PC and free PS antigen, ATIII activity, modified functional APC-resistance, and PZ levels were determined. Results: There was no significant association between inherited thrombophilias and complicated pregnancies as regards PC deficiency (p=1.0), AT III and PS deficiency (p=0.312), and APC-resistance (P=0.083). PZ was significantly associated with complicated pregnancies (p=0.012). Patients with protein Z levels below 1.5 µg/ml were considered deficient. Accordingly, we demonstrated protein Z deficiency in 30% of complicated pregnancies (RR 6.0, 95% CI 1.29-27.90;p=0.022), 20% of preeclampsia (RR 3.5, 95% CI 0.57 – 21.28; P = 0.174), 40% of IUGR (RR 9.3 95% CI 1.72-50.61; P = 0.010) and 30% of IUFD (RR 6, 95% CI 1.07 – 33.64; P = 0.042). Conclusions: These findings indicate the absence of association of inherited thrombophilias, including PC, PS, AT III deficiency, and APC resistance with pregnancy complications. However, PZ deficiency is associated with increased risk of pregnancy complications, especially intrauterine growth restriction and intrauterine fetal death.

Keywords: protein C, protein S, thrombophelia, pregnancy, protein Z

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Authors: Nishank Raisinghani

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Efficiently predicting drug response remains a challenge in the realm of drug discovery. To address this issue, we propose four model architectures that combine graphical representation with varying positions of multiheaded self-attention mechanisms. By leveraging two types of multi-omics data, transcriptomics and genomics, we create a comprehensive representation of target cells and enable drug response prediction in precision medicine. A majority of our architectures utilize multiple transformer models, one with a graph attention mechanism and the other with a multiheaded self-attention mechanism, to generate latent representations of both drug and omics data, respectively. Our model architectures apply an attention mechanism to both drug and multiomics data, with the goal of procuring more comprehensive latent representations. The latent representations are then concatenated and input into a fully connected network to predict the IC-50 score, a measure of cell drug response. We experiment with all four of these architectures and extract results from all of them. Our study greatly contributes to the future of drug discovery and precision medicine by looking to optimize the time and accuracy of drug response prediction.

Keywords: drug discovery, transformers, graph neural networks, multiomics

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Authors: Bimal Raj Regmi, Cassandra Star

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Climate change adaptation is now the priority of many Least Developed Countries (LDCs). The country governments in LDCs are designing institutional and financing architecture to implement adaptation programmes. Nepal has introduced the concept of Local Adaptation Plan of Action (LAPA) to facilitate adaptation at the local level. However, there is lack of clarity and ambiguity on whether or not LAPA can be effective means to reach to the most vulnerable. This research paper aims to generate evidences to assess the applicability and significance of LAPA. The study used a case study approach and relied on data gathered from field studies carried out in Pyuthan and Nawalparasi district of Nepal. The findings show that LAPA has potentials to link the community based adaptation with national adaptation initiatives and thus act as middle range approach to adaptation planning. However, the current scale of LAPA and its approaches to planning and delivery are constraints by socio-economic and governance barriers. This research paper argue that the in order to address the constraints a more flexible and co-management approach to LAPA is needed.

Keywords: community based adaptation, local adaptation, co-management, climate change

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Authors: Anton Hristozov, Eric Matson, Eric Dietz, Marcus Rogers

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Components are heavily used in many software systems, including robotics systems. The growth of sophistication and diversity of new capabilities for robotic systems presents new challenges to their architectures. Their complexity is growing exponentially with the advent of AI, smart sensors, and the complex tasks they have to accomplish. Such complexity requires a more rigorous approach to the creation, use, and interoperability of software components. The issue is exacerbated because robotic systems are becoming more and more reliant on third-party components for certain functions. In order to achieve this kind of interoperability, including dynamic component replacement, we need a way to standardize their interfaces. A formal approach is desperately needed to specify what an interface of a robotic software component should contain. This study performs an analysis of the issue and presents a universal and generic approach to standardizing component interfaces for robotic systems. Our approach is inspired by well-established robotic architectures such as ROS, PX4, and Ardupilot. The study is also applicable to other software systems that share similar characteristics with robotic systems. We consider the use of JSON or Domain Specific Languages (DSL) development with tools such as Antlr and automatic code and configuration file generation for frameworks such as ROS and PX4. A case study with ROS2 is presented as a proof of concept for the proposed methodology.

Keywords: CPS, robots, software architecture, interface, ROS, autopilot

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Authors: Ling Qi, Matloob Khushi, Josiah Poon

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This paper introduces a pre-trained Masked Candlestick Model (MCM) for trading time-series data. The pre-trained model is based on three core designs. First, we convert trading price data at each data point as a set of normalized elements and produce embeddings of each element. Second, we generate a masked sequence of such embedded elements as inputs for self-supervised learning. Third, we use the encoder mechanism from the transformer to train the inputs. The masked model learns the contextual relations among the sequence of embedded elements, which can aid downstream classification tasks. To evaluate the performance of the pre-trained model, we fine-tune MCM for three different downstream classification tasks to predict future price trends. The fine-tuned models achieved better accuracy rates for all three tasks than the baseline models. To better analyze the effectiveness of MCM, we test the same architecture for three currency pairs, namely EUR/GBP, AUD/USD, and EUR/JPY. The experimentation results demonstrate MCM’s effectiveness on all three currency pairs and indicate the MCM’s capability for signal extraction from trading data.

Keywords: masked language model, transformer, time series prediction, trading prediction, embedding, transfer learning, self-supervised learning

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Fidel Lòpez Saca, Carlos Avilés-Cruz, Miguel Magos-Rivera, José Antonio Lara-Chávez

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Automated object recognition and identification systems are widely used throughout the world, particularly in assembly lines, where they perform quality control and automatic part selection tasks. This article presents the design and implementation of an object recognition system in an assembly line. The proposed shapes-color recognition system is based on deep learning theory in a specially designed convolutional network architecture. The used methodology involve stages such as: image capturing, color filtering, location of object mass centers, horizontal and vertical object boundaries, and object clipping. Once the objects are cut out, they are sent to a convolutional neural network, which automatically identifies the type of figure. The identification system works in real-time. The implementation was done on a Raspberry Pi 3 system and on a Jetson-Nano device. The proposal is used in an assembly course of bachelor’s degree in industrial engineering. The results presented include studying the efficiency of the recognition and processing time.

Keywords: deep-learning, image classification, image identification, industrial engineering.

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Authors: Mei-Yi Wu, Shang-Ming Huang

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The online shoppers nowadays often search the product information on the Internet using some keywords of products. To use this kind of information searching model, shoppers should have a preliminary understanding about their interesting products and choose the correct keywords. However, if the products are first contact (for example, the worn clothes or backpack of passengers which you do not have any idea about the brands), these products cannot be retrieved due to insufficient information. In this paper, we discuss and study the applications in E-commerce using image retrieval and text mining techniques. We design a reasonable E-commerce application system containing three layers in the architecture to provide users product information. The system can automatically search and retrieval similar images and corresponding web pages on Internet according to the target pictures which taken by users. Then text mining techniques are applied to extract important keywords from these retrieval web pages and search the prices on different online shopping stores with these keywords using a web crawler. Finally, the users can obtain the product information including photos and prices of their favorite products. The experiments shows the efficiency of proposed system.

Keywords: mobile image retrieval, text mining, product information service system, online marketing

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Authors: Willie Eselebor

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Environmental governance is not new, but may consist of a series of actions taken to establish sanity and ensure sustainable environment. While there is a growing accord linking disaster risk reduction with the management of environment and natural resources, little is known about failure to act which constitute vulnerability and how improved governance reduces risk globally. The paper reviews emerging trends in the field of application of governance tools and approaches for reducing disaster risk. The Hyogo Framework for Action (HFA) enjoin all stakeholders to stimulate the sustainable use and management of ecosystems, which promote the implementation of integrated environmental and natural resource planning that incorporate disaster risk reduction, including structural and non-structural measures, such as integrated management of fragile ecosystems. The methodology adopted is a case study of disaster-prone sites, prompting guided analysis on which hazards are traceable to environmental degradation, why a degraded environment reduces community resilience; how healthy ecosystems provide natural defense, and which opportunities exist to address gaps in reduction of disasters in Nigeria. The paper further analyses the interaction between disaster risk and environmental change. It is established that environmental governance remains a challenge; which implies that there is the need for a shift in traditional approaches to disaster risk management; exploring new initiatives and allowing environmental managers to be docketed as disaster risk managers in context, potentially opening up a window of dialogue on disaster risk management.

Keywords: disaster, ecosystem, environment, risk

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Authors: N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Rita Magdalena, R. D. Atmaja, Sofia Saidah, Ocky Tiaramukti

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Colon cancer or colorectal cancer is a type of cancer that attacks the last part of the human digestive system. Lymphoma and carcinoma are types of cancer that attack human’s colon. Colon cancer causes deaths about half a million people every year. In Indonesia, colon cancer is the third largest cancer case for women and second in men. Unhealthy lifestyles such as minimum consumption of fiber, rarely exercising and lack of awareness for early detection are factors that cause high cases of colon cancer. The aim of this project is to produce a system that can detect and classify images into type of colon cancer lymphoma, carcinoma, or normal. The designed system used 198 data colon cancer tissue pathology, consist of 66 images for Lymphoma cancer, 66 images for carcinoma cancer and 66 for normal / healthy colon condition. This system will classify colon cancer starting from image preprocessing, feature extraction using Principal Component Analysis (PCA) and classification using K-Nearest Neighbor (K-NN) method. Several stages in preprocessing are resize, convert RGB image to grayscale, edge detection and last, histogram equalization. Tests will be done by trying some K-NN input parameter setting. The result of this project is an image processing system that can detect and classify the type of colon cancer with high accuracy and low computation time.

Keywords: carcinoma, colorectal cancer, k-nearest neighbor, lymphoma, principle component analysis

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Authors: Manuela Nayantara Jeyaraj

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PostgreSQL is an Object-Relational Database Management System (ORDBMS) with an architecture that ensures optimal quality data management. But due to the shading growth of similar ORDBMS, PostgreSQL has not been renowned among the database user community. Despite having its features and in-built functionalities shadowed, PostgreSQL renders a vast range of utilities for data manipulation and hence calling for it to be upheld more among users. But introducing PostgreSQL in order to stimulate its advantageous features among users, mandates endorsing learn-ability as an add-on as the target groups considered consist of both amateur as well as professional PostgreSQL users. The scope of this paper deliberates providing easy contemplation of query formulations and flows through a visual editor designed according to user interface principles that standby to support every aspect of making PostgreSQL learn-able by self-operation and creation of queries within the visual editor. This paper tends to scrutinize the importance of choosing PostgreSQL as the working database environment, the visual perspectives that influence human behaviour and ultimately learning, the modes in which learn-ability can be provided via visualization and the advantages reaped by the implementation of the proposed system features.

Keywords: database, learn-ability, PostgreSQL, query, visual-editor

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Authors: Patsorn Worawattananutai, Srisopa Ruangnoo, Arunporn Itharat

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Hibiscus sabdariffa (HS) leaves are vegetables which are extensively used as blood tonic and laxatives in Thai traditional medicine. They are popularly used as healthy sour soup for prevention of chronic diseases such as cancer. Therefore, the cytotoxic activity of different extracts of fresh and dried Hibiscus sabdariffa leaves were investigated via the sulforhodamine B (SRB) assay against three types of women’s cancer cell lines, namely the human cervical adenocarcinoma cell line (HeLa), the human ovarian adenocarcinoma cell line (SKOV-3), and the human breast adenocarcinoma cell line (MCF-7). Extraction methods were squeezing, boiling with water and maceration with 95% or 50% ethanol. The 95% ethanolic extracts of Hibiscus sabdariffa dry leaves (HSDE95) showed the highest cytotoxicity against all types of women’s cancer cell lines with the IC50 values in range 7.51±0.33 to 12.13±1.85 µg/ml. Its IC50 values against SKOV-3, HeLa and MCF-7 were 7.51±0.33, 9.44±1.41 and 12.13±1.85 µg/ml, respectively. In these results, this extract can be classified as “active” according to the NCI guideline which indicated that IC50 values of the active cytotoxic plant extracts have to be beneath 20 µg/ml. Thus, HSDE95 was concluded to be a potent cytotoxic drug for all women’s cancer cells. This extract should be further investigated to isolate active compounds against women’s cancer cells.

Keywords: breast adenocarcinoma, cervical adenocarcinoma, cytotoxic activity, Hibiscus sabdariffa, ovarian adenocarcinoma

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Authors: Vivek Kumar

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The effects of physical activity on the human body have been well understood. It just not only keeps us healthy and away from many diseases but also helpful in delay ageing. Those who exercise every day are physically as well as mentally strong. As the age advance, we often see that there is a loss of memory in the elderly people and their retention power weaken with time. The association between physical health and mental health of elderly people nowadays is an important topic of research. Many people at their old age who all were suffering from Alzheimer or Parkinson disease or were at the stage of dementia have been benefited significantly on exercise at daily basis. We would conduct a randomized control trial, where we will select a number of old age people (65 years old or above). These selected old age people will have some sorts of mental illness and currently receiving treatment for the same. We will divide them into 3 groups. The first group of people will receive their normal treatment i.e. taking medicines. The second group of people will receive medicine as well as will do exercise for 45 minutes every day in the early morning, the 3rd group of people will do exercise everyday for 45 minutes but will be given placebo instead of medicine. All the member of these groups will be monitored carefully for 6 months of time and making this sure that all the members of the group are taking medicines or doing exercise according to the group they belong to. The mental status of all the participants will be measured; the data will be analyzed accordingly. Expected results- This research will be helpful in establishing the effect of exercise on the mental health of the old age people. Also, it will be examined that whether the medicines along with regular exercise for can months can cure the mental illness significantly.

Keywords: mental health, elderly people, physical activity, randomized control trial

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Authors: Aftab Ahmed, Farhan Saeed, Muhammad Afzaal, Shinawar Waseem Ali, Ali Imran, Sadaf Munir

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Malnutrition is a globally increasing public health concern among children; it affects number of school children influencing their growth, development and academic performance. The tenet of the current cross sectional study was to assess the nutritional biomarkers of school going children of age 12-15 years resulting in stunting, underweight, overweight, bone deformities and other health disparities in nutritionally deprived urban and rural populations of Pakistan. A sample size comprising of 180 school going children was stipulated from the targeted urban and rural populations. The fallouts of investigation unveiled that both rural and urban populations were experiencing nutritional challenges however; on account of awareness paucity the rustic population was nutritionally more compromised. Hematological tests elucidated 16.7% and 7.8% cases for high glucose level, 35.6% and 27.8% cases for low hemoglobin levels, 14.4% and 15.6% cases for low calcium indices, 12.2% and 4.4% high white blood cell count (WBC), 20% and 14.4% low red blood cell count, 76.7% and 74.4% low hematocrit (HCT) values, among the rural and urban populations respectively. The above mentioned outcomes can serve as a way forward for policy and law maker institutions to curb the possible barricades in the way of healthy nutritional status in these areas

Keywords: malnutrition, hematological study, child nutrition, bone mineral density, calcium, RBC

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Authors: Eri Sulyanti, Trimurti Habazar, Eti Farda Husen, Abdi Dharma, Nasril Nasir

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In this study, combination of some biocontrol agents with different mechanisms was an alternative to improve the effectiveness of the biological control agents. Single and combined applications of indigenous Pseudomonas fluorescens and Arbuscular Mychorrhizae Fungi (AM Fungi) isolates were tested to induce the resistance on susceptible Cavendish banana against F.oxysporum f. sp. cubense race 4 under greenhouse conditions. These isolates originally isolated from healthy banana rhizosphere at endemic Fusarium wilt areas in the centre of production banana in West Sumatra. These researches were conducted with Randomized Block Design with 16 treatments and 10 replications. The treatments were three indigenous isolates of Pseudomonas fluorescens (Par1-Cv, Par4-Rj1, Par2-Jt1) and 3 isolates of AM Fungi (Gl1BuA4, Gl2BuA6, and Gl1KeP3. The biocontrol agents were applied as single agents and combination two of them. This study demonstrated that the application of combination biocontrol organisms Pseudomonas fluorescens and AM Fungi provided were more effective than single application. The combination of Par1-Cv and Gl1BuA4 isolates was the most effective to control Fusarium wilt and followed by the combination of Par1-Cv and Gl2BuA6 and Par2-Jt1 and Gl1P3.

Keywords: pseudomonad fluorescens (Pf), arbuscular mychorrhizae fungi (AM Fungi) indigenous isolates, fusarium oxysporum f. sp. cubense, soil rhizosphere

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Authors: Jean-Francois Feller

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The analysis of the volatolome emitted by the human body with a sensor array (e-nose) is a method for clinical applications full of promises to make an olfactive fingerprint characteristic of people's health state. But the amount of volatile organic compounds (VOC) to detect, being in the range of parts per billion (ppb), and their diversity (several hundred) justifies developing ever more sensitive and selective vapor sensors to improve the discrimination ability of the e-nose, is still of interest. Quantum resistive vapour sensors (vQRS) made with nanostructured conductive polymer nanocomposite transducers have shown a great versatility in both their fabrication and operation to detect volatiles of interest such as cancer biomarkers. However, it has been shown that their chemo-resistive response was highly dependent on the quality of the inter-particular junctions in the percolated architecture. The present work investigates the effectiveness of poly(hedral oligomeric silsesquioxane) acting as a nanospacer to amplify the disconnectability of the conducting network and thus maximize the vQRS's sensitivity to VOC.

Keywords: volatolome, quantum resistive vapour sensor, nanostructured conductive polymer nanocomposites, olfactive diagnosis

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Authors: Afolabi Joseph Fasoranti

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Tuberculosis (TB) is an infectious disease caused by mycobacterium tuberculosis. Tuberculosis is a major public health problem in Nigeria, being one of the ten leading causes of hospital admissions and a leading cause of death in adults, especially among the economically productive age group. This paper critically examined the importance of health education towards the eradication and prevention of tuberculosis in Nigeria. It was reviewed and discussed under the following subheadings; Global burden of tuberculosis in Nigeria, concept, definition and etiology of tuberculosis, Signs and symptoms of tuberculosis, diagnosis of tuberculosis, causative agent, modes of infection and incubation period, risk factors of pulmonary tuberculosis Dots and stop TB programmes in Nigeria Treatment and prevention of tuberculosis TB treatment strategies, Dealing with treatment problems in Nigeria Stigmatization against Tuberculosis Patients Health education as a tool for achieving free tuberculosis country. Emphasis for Tb control has been placed on the development of improved vaccines, diagnostic and treatment courses but less on health education and awareness. Although the need for these tools is indisputable, the obstacle facing the spread of TB go beyond technological. The findings of this study may stimulate health system policy makers, Government and non- governmental organizations, donor agencies and other stakeholders in planning and designing health education intervention programs on the control and eradication of tuberculosis. It therefore recommended that Government should implement health education as part of the DOTs, this will thus empower the tuberculosis patients on ways to live healthy, lifestyle, in doing this, they will recover fast and prevent them from spreading the disease.

Keywords: tuberculosis, health education, panacea, Nigeria, prevention

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Authors: Sara Jelodarian

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Organic agriculture is a kind of living and dynamic agriculture that was introduced in the early 20^th century. The fundamental basis for organic agriculture is in harmony with nature. This version of farming emphasizes removing growth hormones, chemical fertilizers, toxins, radiation, genetic manipulation and instead, integration of modern scientific techniques (such as biologic and microbial control) that leads to the production of healthy food and the preservation of the environment and use of agricultural products such as forage and manure. Supports from governments for the markets producing organic products and taking advantage of the experiences from other successful societies in this field can help progress the positive and effective aspects of this technology, especially in developing countries. This research proves that till 2030, 25% of the global agricultural lands would be covered by organic farming. Consequently Iran, due to its rich genetic resources and various climates, can be a pioneer in promoting organic products. In addition, for sustainable farming, blend of organic and other innovative systems is needed. Important limitations exist to accept these systems, also a diversity of policy instruments will be required to comfort their development and implementation. The paper was conducted to results of compilation of reports, issues, books, articles related to the subject with library studies and research. Likewise we combined experimental and survey to get data.

Keywords: develop, production markets, progress, strategic role, technology

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Authors: M. Ahmadi, M. Kafil, H. Ebrahimi

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Nowadays, induction motors have a significant role in industries. Condition monitoring (CM) of this equipment has gained a remarkable importance during recent years due to huge production losses, substantial imposed costs and increases in vulnerability, risk, and uncertainty levels. Motor current signature analysis (MCSA) is one of the most important techniques in CM. This method can be used for rotor broken bars detection. Signal processing methods such as Fast Fourier transformation (FFT), Wavelet transformation and Empirical Mode Decomposition (EMD) are used for analyzing MCSA output data. In this study, these signal processing methods are used for broken bar problem detection of Mobarakeh steel company induction motors. Based on wavelet transformation method, an index for fault detection, CF, is introduced which is the variation of maximum to the mean of wavelet transformation coefficients. We find that, in the broken bar condition, the amount of CF factor is greater than the healthy condition. Based on EMD method, the energy of intrinsic mode functions (IMF) is calculated and finds that when motor bars become broken the energy of IMFs increases.

Keywords: broken bar, condition monitoring, diagnostics, empirical mode decomposition, fourier transform, wavelet transform

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Authors: Brahmi Brahim, Mohammad Habibur Rahman, Maarouf Saad, Cristóbal Ochoa Luna

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A repetitive training movement is an efficient method to improve the ability and movement performance of stroke survivors and help them to recover their lost motor function and acquire new skills. The ETS-MARSE is seven degrees of freedom (DOF) exoskeleton robot developed to be worn on the lateral side of the right upper-extremity to assist and rehabilitate the patients with upper-extremity dysfunction resulting from stroke. Practically, rehabilitation activities are repetitive tasks, which make the assistive/robotic systems to suffer from repetitive/periodic uncertainties and external perturbations induced by the high-order dynamic model (seven DOF) and interaction with human muscle which impact on the tracking performance and even on the stability of the exoskeleton. To ensure the robustness and the stability of the robot, a new nonlinear backstepping control was implemented with designed tests performed by healthy subjects. In order to limit and to reject the periodic/repetitive disturbances, an iterative estimator was integrated into the control of the system. The estimator does not need the precise dynamic model of the exoskeleton. Experimental results confirm the robustness and accuracy of the controller performance to deal with the external perturbation, and the effectiveness of the iterative estimator to reject the repetitive/periodic disturbances.

Keywords: backstepping control, iterative control, Rehabilitation, ETS-MARSE

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Authors: Amarjyoti Das Mahapatra, Umesh Kumar, Bhaskar Datta

Abstract:

A pseudo peptide can mimic the biological or structural properties of natural peptides. They have become an increasing attention in medicinal chemistry because of their interesting advantages like more bioavailability and less biodegradation than compare to the physiologically active native peptides which increase their therapeutic applications. Many biologically active compounds contain urea as functional groups, and they have improved pharmacokinetic properties because of their bioavailability and metabolic stability. Recently we have reported a single-step synthesis of sulfonyl urea and sulfonyltriuret from sulfonyl chloride and sodium cyanate. But the yield of sulfonyltriuret was less around 40-60% because of the formation of other products like sulfonamide and sulfonylureas. In the present work, we mainly focused on the selective synthesis of sulfonyltriuret using tetrabutylammonium cyanate and sulfonyl chloride. More precisely, we are interested in the controlled synthesis of oligomeric urea mainly sulfonyltriuret as a new class of pseudo peptide and their application as protease modulators. The distinctive architecture of these molecules in the form of their pseudo-peptide backbone offers promise as a potential pharmacophore. The synthesized molecules have been screened on trypsin enzyme, and we observed that these molecules are the efficient modulator of trypsin enzyme.

Keywords: pseudo peptide, pharmacophore, sulfonyltriuret, trypsin

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Authors: Pratap Sriram Sundar, Chandan Chowdhury, Sagar Kamarthi

Abstract:

Nature has perfected her designs over 3.5 billion years of evolution. Research fields such as biomimicry, biomimetics, bionics, bio-inspired computing, and nature-inspired designs have explored nature-made artifacts and systems to understand nature’s mechanisms and intelligence. Learning from nature, the researchers have generated sustainable designs and innovation in a variety of fields such as energy, architecture, agriculture, transportation, communication, and medicine. Axiomatic design offers a method to judge if a design is good. This paper analyzes design aspects of one of the nature’s amazing object: chicken egg. The functional requirements (FRs) of components of the object are tabulated and mapped on to nature-chosen design parameters (DPs). The ‘independence axiom’ of the axiomatic design methodology is applied to analyze couplings and to evaluate if eggs’ design is good (i.e., uncoupled design) or bad (i.e., coupled design). The analysis revealed that eggs design is a good design, i.e., uncoupled design. This approach can be applied to any nature’s artifacts to judge whether their design is a good or a bad. This methodology is valuable for biomimicry studies. This approach can also be a very useful teaching design consideration of biology and bio-inspired innovation.

Keywords: uncoupled design, axiomatic design, nature design, design evaluation

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Authors: Anupuma Raina, Ajay Parkash

Abstract:

In forensic investigation, DNA analysis helps in the identification of a particular individual under investigation. A set of Short Tandem Repeats loci are widely used for individualization at a molecular level in forensic testing. STRs with tetrameric repeats of DNA are highly polymorphic and widely used for forensic DNA analysis. Identification of an individual became challenging for forensic examiners after Hematopoietic Stem Cell Transplantation. HSCT is a well-accepted and life-saving treatment to treat malignant and nonmalignant diseases. It involves the administration of healthy donor stem cells to replace the patient’s own unhealthy stem cells. A successful HSCT results in complete donor-derived cells in a patient’s hematopoiesis and hence have the capability to change the genetic makeup of the patient. Although an individual who has undergone HSCT and then committed a crime is a very rare situation, but not impossible. Keeping such a situation in mind, various biological samples like blood, buccal swab, and hair follicle were collected and studied after a certain interval of time after HSCT. Blood was collected from both the patient and the donor before the transplant. The DNA profile of both was analyzed using a short tandem repeat kit for autosomal chromosomes. Among all exhibits studied, only hair follicles were found to be the most suitable biological exhibit, as no donor DNA profile was observed for up to 90 days of study.

Keywords: chimerism, HSCT, STRs analysis, forensic identification

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Authors: Duy M. P. Vo, Cornelia Sennewald, Gerald Hoffmann, Chokri Cherif

Abstract:

The development of solutions to improve the resistance of buildings to short-term dynamic loads, particularly impact load, is driven by the urgent demand worldwide on securing human life and critical infrastructures. The research training group GRK 2250/1 aims to develop mineral-bonded composites that allow the fabrication of thin-layered strengthening layers providing available concrete members with enhanced impact resistance. This paper presents the development of 3D woven wire cellular structures that can be used as innovative reinforcement for targeted composites. 3D woven wire cellular structures are truss-like architectures that can be fabricated in an automatized process with a great customization possibility. The specific architecture allows this kind of structures to have good load bearing capability and forming behavior, which is of great potential to give strength against impact loading. An appropriate combination of topology and material enables an optimal use of thin-layered reinforcement in concrete constructions.

Keywords: 3D woven cellular structures, ductile behavior, energy absorption, fiber-based reinforced concrete, impact resistant

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Authors: Felipe A. Guth, Shane Ward, Kevin McDonnell

Abstract:

In the precision agriculture area, one of the main tasks is the automated detection of diseases in crops. Machine Learning algorithms have been studied in recent decades for such tasks in view of their potential for improving economic outcomes that automated disease detection may attain over crop fields. The latest generation of deep learning convolution neural networks has presented significant results in the area of image classification. In this way, this work has tested the implementation of an architecture of deep learning convolution neural network for the detection of diseases in different types of crops. A data augmentation strategy was used to meet the requirements of the algorithm implemented with a deep learning framework. Two test scenarios were deployed. The first scenario implemented a neural network under images extracted from a controlled environment while the second one took images both from the field and the controlled environment. The results evaluated the generalisation capacity of the neural networks in relation to the two types of images presented. Results yielded a general classification accuracy of 59% in scenario 1 and 96% in scenario 2.

Keywords: convolutional neural networks, deep learning, disease detection, precision agriculture

Procedia PDF Downloads 259