Search results for: distance image

Authors: Akinsola Oluwatosin, Udofia Samuel, Odofin Mayowa

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The study is aimed at assessing the Geographic Information System (GIS)-based spatial analysis of Survival Pattern and Treatment Outcomes of Multi-Drug Resistant Tuberculosis (MDR-TB) cases for Lagos, Nigeria, with an objective to inform priority areas for public health planning and resource allocation. Multi-drug resistant tuberculosis (MDR-TB) develops due to problems such as irregular drug supply, poor drug quality, inappropriate prescription, and poor adherence to treatment. The shapefile(s) for this study were already georeferenced to Minna datum. The patient’s information was acquired on MS Excel and later converted to . CSV file for easy processing to ArcMap from various hospitals. To superimpose the patient’s information the spatial data, the addresses was geocoded to generate the longitude and latitude of the patients. The database was used for the SQL query to the various pattern of the treatment. To show the pattern of disease spread, spatial autocorrelation analysis was used. The result was displayed in a graphical format showing the areas of dispersing, random and clustered of patients in the study area. Hot and cold spot analysis was analyzed to show high-density areas. The distance between these patients and the closest health facility was examined using the buffer analysis. The result shows that 22% of the points were successfully matched, while 15% were tied. However, the result table shows that a greater percentage of it was unmatched; this is evident in the fact that most of the streets within the State are unnamed, and then again, most of the patients are likely to supply the wrong addresses. MDR-TB patients of all age groups are concentrated within Lagos-Mainland, Shomolu, Mushin, Surulere, Oshodi-Isolo, and Ifelodun LGAs. MDR-TB patients between the age group of 30-47 years had the highest number and were identified to be about 184 in number. The outcome of patients on ART treatment revealed that a high number of patients (300) were not ART treatment while a paltry 45 patients were on ART treatment. The result shows the Z-score of the distribution is greater than 1 (>2.58), which means that the distribution is highly clustered at a significance level of 0.01.

Keywords: tuberculosis, patients, treatment, GIS, MDR-TB

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Authors: Tanjil Sowgat, Shamim Kobir

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World is now experiencing the consequences of climate change such as increased heat stress due to high temperature rise. In the context of changing climate, this study intends to find out the planning interventions necessary to adapt to the current heat stress in the planned residential areas of Khulna city. To carry out the study Sonadanga residential area (phase I) of Khulna city has been taken as the study site. This residential neighbourhood covering an area of 30 acres has 206 residential plots. The study area comprises twelve access roads, one park, one playfield, one water body and two street furniture’s. This study conducts visual analysis covering green, open space, water body, footpath, drainage and street trees and furniture and questionnaire survey deals with socio-economic, housing tenancy, experience of heat stress and urban design interventions. It finds that the current state that accelerates the heat stress condition such as lack of street trees and inadequate shading, maximum uses are not within ten minutes walking distance, no footpath for the pedestrians and lack of well-maintained street furniture. It proposes that to adapt to the heat stress pedestrian facilities, buffer sidewalk with landscaping, street trees and open spaces, soft scape, natural and man-made water bodies, green roofing could be effective urban design interventions. There are evidences of limited number of heat stress adaptive planned residential area. Since current sub-division planning practice focuses on rigid land use allocation, it partly addresses the climatic concerns through creating open space and street trees. To better respond to adapt to the heat stress, urban design considerations in the context of sub-division practice would bring more benefits.

Keywords: climate change, urban design, adaptation, heat stress, water-logging

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Authors: Bo Wang

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The geometric processing of multi-source remote sensing data using control data of different scale and different accuracy is an important research direction of multi-platform system for earth observation. In the existing block bundle adjustment methods, as the controlling information in the adjustment system, the approach using single observation scale and precision is unable to screen out the control information and to give reasonable and effective corresponding weights, which reduces the convergence and adjustment reliability of the results. Referring to the relevant theory and technology of quotient space, in this project, several subjects are researched. Multi-layer quotient space of multi-geometric features is constructed to describe and filter control data. Normalized granularity merging mechanism of multi-layer control information is studied and based on the normalized scale factor, the strategy to optimize the weight selection of control data which is less relevant to the adjustment system can be realized. At the same time, geometric positioning experiment is conducted using multi-source remote sensing data, aerial images, and multiclass control data to verify the theoretical research results. This research is expected to break through the cliché of the single scale and single accuracy control data in the adjustment process and expand the theory and technology of photogrammetry. Thus the problem to process multi-source remote sensing data will be solved both theoretically and practically.

Keywords: multi-source image geometric process, high precision geometric positioning, quotient space of multi-geometric features, optimized weight selection

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Authors: Azin Shakibabarough, Mojtaba Valinejadshoubi, Ashutosh Bagchi

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Catastrophic bridge failure happens due to the lack of inspection, lack of design and extreme events like flooding, an earthquake. Bridge Management System (BMS) is utilized to diminish such an accident with proper design and frequent inspection. Visual inspection cannot detect any subsurface defects, so using Non-Destructive Evaluation (NDE) techniques remove these barriers as far as possible. Among all NDE techniques, Ground Penetrating Radar (GPR) has been proved as a highly effective device for detecting internal defects in a reinforced concrete bridge deck. GPR is used for detecting rebar location and rebar corrosion in the reinforced concrete deck. GPR profile is composed of hyperbola series in which sound hyperbola denotes sound rebar and blur hyperbola or signal attenuation shows corroded rebar. Interpretation of GPR images is implemented by numerical analysis or visualization. Researchers recently found that interpretation through visualization is more precise than interpretation through numerical analysis, but visualization is time-consuming and a highly subjective process. Automating the interpretation of GPR image through visualization can solve these problems. After interpretation of all scans of a bridge, condition assessment is conducted based on the generated corrosion map. However, this such a condition assessment is not objective and precise. Condition assessment based on structural integrity and strength parameters can make it more objective and precise. The main purpose of this study is to present an automated interpretation method of a reinforced concrete bridge deck through a visualization technique. In the end, the combined analysis of the structural condition in a bridge is implemented.

Keywords: bridge condition assessment, ground penetrating radar, GPR, NDE techniques, visualization

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Authors: Pedro Barros, Ana Breda, Eugenio Rocha, M. Isabel Santos

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As visual and spatial awareness develops, children apprehension of the concept of direction, (relative) distance and (relative) location materializes. Here we present the educational inclusive digital game ORIESPA, under development by the Thematic Line Geometrix, for children aged between 6 and 10 years old, aiming the improvement of their visual and spatial awareness. Visual-spatial abilities are of crucial importance to succeed in many everyday life tasks. Unavoidable in the technological age we are living in, they are essential in many fields of study as, for instance, mathematics.The game, set on a 2D/3D environment, focusses in tasks/challenges on the following categories (1) static orientation of the subject and object, requiring an understanding of the notions of up–down, left–right, front–back, higher-lower or nearer-farther; (2) interpretation of perspectives of three-dimensional objects, requiring the understanding of 2D and 3D representations of three-dimensional objects; and (3) orientation of the subject in real space, requiring the reading and interpreting of itineraries. In ORIESPA, simpler tasks are based on a quadrangular grid, where the front-back and left-right directions and the rotations of 90º, 180º and 270º play the main requirements. The more complex ones are produced on a cubic grid adding the up and down movements. In the first levels, the game's mechanics regarding the reading and interpreting maps (from point A to point B) is based on map routes, following a given set of instructions. In higher levels, the player must produce a list of instructions taking the game character to the desired destination, avoiding obstacles. Being an inclusive game the user has the possibility to interact through the mouse (point and click with a single button), the keyboard (small set of well recognized keys) or a Kinect device (using simple gesture moves). The character control requires the action on buttons corresponding to movements in 2D and 3D environments. Buttons and instructions are also complemented with text, sound and sign language.

Keywords: digital game, inclusion, itinerary, spatial ability

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Authors: Dongqi Li, Yunjia Huang, Tomo Inoue, Kohei Inoue

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With urbanization, urban cultural heritage is facing the impact and destruction of modernization and urbanization. Many historical areas are losing their historical information and regional cultural characteristics, so it is necessary to carry out systematic color planning for historical areas in conservation. As an early focus on urban color planning, Japan has a systematic approach to urban color planning. Hence, this paper selects five merchant towns from the category of important traditional building preservation areas in Japan as the subject of this study to explore the color structure and emotion of this type of historic area. First, the image semantic segmentation method identifies the buildings, roads, and landscape environments. Their color data were extracted for color composition and emotion analysis to summarize their common features. Second, the obtained Internet evaluations were extracted by natural language processing for keyword extraction. The correlation analysis of the color structure and keywords provides a valuable reference for conservation decisions for this historic area in the town. This paper also combines the color structure and Internet evaluation results with generative adversarial networks to generate predicted images of color structure improvements and color improvement schemes. The methods and conclusions of this paper can provide new ideas for the digital management of environmental colors in historic districts and provide a valuable reference for the inheritance of local traditional culture.

Keywords: historic districts, color planning, semantic segmentation, natural language processing

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Authors: Tahir Ali Akbar, Hirra Jabbar

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Land cover change analysis plays a significant role in understanding the trends of urban sprawl and land use transformation due to anthropogenic activities. In this study, the spatio-temporal dynamics of major land covers were analyzed in the last twenty years (1988-2016) for District Lahore located in the Punjab Province of Pakistan. The Landsat satellite imageries were downloaded from USGS Global Visualization Viewer of Earth Resources Observation and Science Center located in Sioux Falls, South Dakota USA. The imageries included: (i) Landsat TM-5 for 1988 and 2001; and (ii) Landsat-8 OLI for 2016. The raw digital numbers of Landsat-5 images were converted into spectral radiance and then planetary reflectance. The digital numbers of Landsat-8 image were directly converted into planetary reflectance. The normalized difference vegetation index (NDVI) was used to classify the processed images into six major classes of water, buit-up, barren land, shrub and grassland, sparse vegetation and dense vegetation. The NDVI output results were improved by visual interpretation using high-resolution satellite imageries. The results indicated that the built-up areas were increased to 21% in 2016 from 10% in 1988. The decrease in % areas was found in case of water, barren land and shrub & grassland. There were improvements in percentage of areas for the vegetation. The increasing trend of urban sprawl for Lahore requires implementation of GIS based spatial planning, monitoring and management system for its sustainable development.

Keywords: land cover changes, NDVI, remote sensing, urban sprawl

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Authors: A.Boularouk, F. Chouikh, M. Lamri, H. Moualkia, Y. Bouznit

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The principal aim of this study is to considerably reduce the resistivity of the SnO2 thin layers. In this order, we have doped tin oxide with aluminum and antimony incorporation with different atomic percentages (0 and 4%). All the pure and doped SnO2 films were grown by simple, flexible and cost-effective Automatic Spray Pyrolysis Method (ASPM) on glass substrates at a temperature of 350 °C. The microstructural, optical, morphological and electrical properties of the films have been studied. The XRD results demonstrate that all films have polycrystalline nature with a tetragonal rutile structure and exhibit the (200) preferential orientation. It has been observed that all the dopants are soluble in the SnO2 matrix without forming secondary phases. However, dopant introduction does not modify the film growth orientation. The crystallite size of the pure SnO2 film is about 36 nm. The films are highly transparent in the visible region with an average transmittance reaching up to 80% and it slightly reduces with increasing doping concentration (Al and Sb). The optical band gap value was evaluated between 3.60 eV and 3.75 eV as a function of doping. The SEM image reveals that all films are nanostructured, densely continuous, with good adhesion to the substrate. We note again that the surface morphology change with the type and concentration dopant. The minimum resistivity is 0.689*10-4, which is observed for SnO2 film doped 4% Al. This film shows better properties and is considered the best among all films. Finally, we concluded that the physical properties of the pure and doped SnO2 films grown on a glass substrate by ASPM strongly depend on the type and concentration dopant (Al and Sb) and have highly desirable optical and electrical properties and are promising materials for several applications.

Keywords: tin oxide, automatic spray, Al and Sb doped, transmittance, MEB, XRD and UV-VIS

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Authors: Alexander A. Karabutov, Natalia B. Podymova, Elena B. Cherepetskaya

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The theoretical analysis is carried out to get the relation between the ultrasonic wave velocity and the value of residual stresses. The laser-ultrasonic method is developed to evaluate the residual stresses and subsurface defects in metals. The method is based on the laser thermooptical excitation of longitudinal ultrasonic wave sand their detection by a broadband piezoelectric detector. A laser pulse with the time duration of 8 ns of the full width at half of maximum and with the energy of 300 µJ is absorbed in a thin layer of the special generator that is inclined relative to the object under study. The non-uniform heating of the generator causes the formation of a broadband powerful pulse of longitudinal ultrasonic waves. It is shown that the temporal profile of this pulse is the convolution of the temporal envelope of the laser pulse and the profile of the in-depth distribution of the heat sources. The ultrasonic waves reach the surface of the object through the prism that serves as an acoustic duct. At the interface ‚laser-ultrasonic transducer-object‘ the conversion of the most part of the longitudinal wave energy takes place into the shear, subsurface longitudinal and Rayleigh waves. They spread within the subsurface layer of the studied object and are detected by the piezoelectric detector. The electrical signal that corresponds to the detected acoustic signal is acquired by an analog-to-digital converter and when is mathematically processed and visualized with a personal computer. The distance between the generator and the piezodetector as well as the spread times of acoustic waves in the acoustic ducts are the characteristic parameters of the laser-ultrasonic transducer and are determined using the calibration samples. There lative precision of the measurement of the velocity of longitudinal ultrasonic waves is 0.05% that corresponds to approximately ±3 m/s for the steels of conventional quality. This precision allows one to determine the mechanical stress in the steel samples with the minimal detection threshold of approximately 22.7 MPa. The results are presented for the measured dependencies of the velocity of longitudinal ultrasonic waves in the samples on the values of the applied compression stress in the range of 20-100 MPa.

Keywords: laser-ultrasonic method, longitudinal ultrasonic waves, metals, residual stresses

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Authors: Almutazballlah Qablan, Jihan M. Muhaidat, Bana Abu Rajab

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Background: Acne vulgaris is the most common skin condition that general practitioners and dermatologists encounter. It represents a chronic inflammatory disease affecting the pilosebaceous unit. Although acne vulgaris is not a life-threatening condition, it has a considerable psychological impact on the affected person. Acne patients have poor body image, low self-esteem, social isolation, and restricted activities. As part of the emotional impact, increased levels of anxiety, anger, depression, and frustration have also been observed in acne patients. (1) In this study, we want to assess the association between two modifiable risk factors; BMI and smoking, regarding acne vulgaris. Methods: A case-control study was conducted at King Abdullah University Hospital in Irbid, north Jordan in 2019/2020. A total number of 163 Acne cases were collected and interviewed by the author; on the other hand, there were 162 control cases. Anthropometric measures for Acne patients and control individuals were taken, and BMI was calculated. Both groups were asked about smoking habits. Data on subjects between 14 and 33 years of age were extracted. The characteristics of people who reported acne were compared with those with no acne using univariate and multivariate analysis. The Statistical Package for Social Sciences (SPSS) was relied on to analyze the collected data. The crosstabs methods (chi-square) and odd ratios were relied on to test the study hypothesis. Results: Cigarette smoking was highly associated with no-acne, with an odds ratio of 0.4 (95% CI: 0.2–0.9), P-value = 0.018. BMI and waterpipe smoking were not significantly associated with acne in the multivariate analysis. Conclusion: Cigarette smoking was found to be protective from Acne. No significant relation between BMI nor waterpipe smoking and the development of Acne Vulgaris.

Keywords: acne, BMI, smoking, case-control

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Authors: Firouz Amani, Adalat Hoseinian, Sajjad Hakimian

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Background: The mortality due to Myocardial Infarction (MI) is often occur during the first hours after onset of symptom. So, for taking the necessary treatment and decreasing the mortality rate, timely visited of the hospital could be effective in this regard. The aim of this study was to investigate the impact of effective factors in mortality of MI patients by using Linear Logistic Regression. Materials and Methods: In this case-control study, all patients with Acute MI who referred to the Ardabil city hospital were studied. All of died patients were considered as the case group (n=27) and we select 27 matched patients without Acute MI as a control group. Data collected for all patients in two groups by a same checklist and then analyzed by SPSS version 24 software using statistical methods. We used the linear logistic regression model to determine the effective factors on mortality of MI patients. Results: The mean age of patients in case group was significantly higher than control group (75.1±11.7 vs. 63.1±11.6, p=0.001).The history of non-cardinal diseases in case group with 44.4% significantly higher than control group with 7.4% (p=0.002).The number of performed PCIs in case group with 40.7% significantly lower than control group with 74.1% (P=0.013). The time distance between hospital admission and performed PCI in case group with 110.9 min was significantly upper than control group with 56 min (P=0.001). The mean of delay time from Onset of symptom to hospital admission (patient delay) and the mean of delay time from hospital admissions to receive treatment (system delay) was similar between two groups. By using logistic regression model we revealed that history of non-cardinal diseases (OR=283) and the number of performed PCIs (OR=24.5) had significant impact on mortality of MI patients in compare to other factors. Conclusion: Results of this study showed that of all studied factors, the number of performed PCIs, history of non-cardinal illness and the interval between onset of symptoms and performed PCI have significant relation with morality of MI patients and other factors were not meaningful. So, doing more studies with a large sample and investigated other involved factors such as smoking, weather and etc. is recommended in future.

Keywords: acute MI, mortality, heart failure, arrhythmia

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Authors: Sijing Xiong, Ran Su, Lit-Hsin Loo, Daniele Zink

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The kidney is a major target for toxic effects of drugs, industrial and environmental chemicals and other compounds. Typically, nephrotoxicity is detected late during drug development, and regulatory animal models could not solve this problem. Validated or accepted in silico or in vitro methods for the prediction of nephrotoxicity are not available. We have established the first and currently only pre-validated in vitro models for the accurate prediction of nephrotoxicity in humans and the first predictive platforms based on renal cells derived from human pluripotent stem cells. In order to further improve the efficiency of our predictive models, we recently developed a high content screening (HCS) platform. This platform employed automated imaging in combination with automated quantitative phenotypic profiling and machine learning methods. 129 image-based phenotypic features were analyzed with respect to their predictive performance in combination with 44 compounds with different chemical structures that included drugs, environmental and industrial chemicals and herbal and fungal compounds. The nephrotoxicity of these compounds in humans is well characterized. A combination of chromatin and cytoskeletal features resulted in high predictivity with respect to nephrotoxicity in humans. Test balanced accuracies of 82% or 89% were obtained with human primary or immortalized renal proximal tubular cells, respectively. Furthermore, our results revealed that a DNA damage response is commonly induced by different PTC-toxicants with diverse chemical structures and injury mechanisms. Together, the results show that the automated HCS platform allows efficient and accurate nephrotoxicity prediction for compounds with diverse chemical structures.

Keywords: high content screening, in vitro models, nephrotoxicity, toxicity prediction

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Authors: Josephine K. Mule, Levi Obonyo

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Technology has changed human life over time. The COVID-19 pandemic has altered the work set-up, the school system, the shopping experience, church attendance, and even the way athletes train in Kenya. Although the use of technology to communicate and maintain interactions has been on the rise in the last 30 years, the uptake during the COVID-19 pandemic has been unprecedented. Traditionally, ‘paid’ work has been considered to take place outside the “home house” but COVID-19 has resulted in what is now being referred to as “the world’s largest work-from-home experiment” with up to 43 percent of employees working at least some of the time remotely. This study was conducted on 90 respondents from across remote work set-ups, school systems, merchants and customers of online shopping, church leaders and congregants and athletes, and their coaches. Data were collected by questionnaires and interviews that were conducted online. The data is based on the first three months since the first case of coronavirus was reported in Kenya. This study found that the use of technology is in the center of working remotely with work interactions being propelled on various online platforms including, Zoom, Microsoft Teams, and Google Meet, among others. The school system has also integrated the use of technology, including students defending their thesis/dissertations online and university graduations being conducted virtually. Kenya is known for its long-distance runners, due to the directives to reduce interactions; coaches have taken to providing their athletes with guidance on training on social media using applications such as WhatsApp. More local stores are now offering the shopping online option to their customers. Churches have also felt the brunt of the situation, especially because of the restrictions on crowds resulting in online services becoming more popular in 2020 than ever before. Artists, innovatively have started online musical concerts. The findings indicate that one of the outcomes in the Kenyan society that is evident as a result of the COVID-19 period is a population that is using technology more to communicate and get work done. Vices that have thrived in this season where the use of technology has increased, include the spreading of rumors on social media and cyberbullying. The place of technology seems to have been cemented by demand during this period.

Keywords: communication, coronavirus, COVID-19, Kenya, technology

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Authors: Robert Cazar, Nathaly Maza

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Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

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Authors: Sana Hamdi, Emna Bouazizi, Sami Faiz

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In recent years, real-time spatial applications, like location-aware services and traffic monitoring, have become more and more important. Such applications result dynamic environments where data as well as queries are continuously moving. As a result, there is a tremendous amount of real-time spatial data generated every day. The growth of the data volume seems to outspeed the advance of our computing infrastructure. For instance, in real-time spatial Big Data, users expect to receive the results of each query within a short time period without holding in account the load of the system. But with a huge amount of real-time spatial data generated, the system performance degrades rapidly especially in overload situations. To solve this problem, we propose the use of data partitioning as an optimization technique. Traditional horizontal and vertical partitioning can increase the performance of the system and simplify data management. But they remain insufficient for real-time spatial Big data; they can’t deal with real-time and stream queries efficiently. Thus, in this paper, we propose a novel data partitioning approach for real-time spatial Big data named VPA-RTSBD (Vertical Partitioning Approach for Real-Time Spatial Big data). This contribution is an implementation of the Matching algorithm for traditional vertical partitioning. We find, firstly, the optimal attribute sequence by the use of Matching algorithm. Then, we propose a new cost model used for database partitioning, for keeping the data amount of each partition more balanced limit and for providing a parallel execution guarantees for the most frequent queries. VPA-RTSBD aims to obtain a real-time partitioning scheme and deals with stream data. It improves the performance of query execution by maximizing the degree of parallel execution. This affects QoS (Quality Of Service) improvement in real-time spatial Big Data especially with a huge volume of stream data. The performance of our contribution is evaluated via simulation experiments. The results show that the proposed algorithm is both efficient and scalable, and that it outperforms comparable algorithms.

Keywords: real-time spatial big data, quality of service, vertical partitioning, horizontal partitioning, matching algorithm, hamming distance, stream query

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Authors: Taiwo Hassanat Bawa-Muhammad, Opeoluwa Hope Adegoke

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Introduction: This study aims to examine the knowledge and perceptions of preconception care among healthcare workers in Nigeria, recognizing its crucial role in ensuring safe pregnancies. Despite its significance, awareness of preconception care remains low in the country. The study seeks to assess the understanding of preconception services and identify the barriers that hinder their efficacy. Methods: Through semi-structured interviews, 129 healthcare workers across six states in Nigeria were interviewed between January and March 2023. The interviews explored the healthcare workers' knowledge of preconception care practices, the socio-cultural influences shaping decision-making, and the challenges that limit accessibility and utilization of preconception care services. Results: The findings reveal a limited knowledge of preconception care among healthcare workers, primarily due to inadequate information dissemination within the healthcare system. Additionally, cultural beliefs significantly influence perceptions surrounding preconception care. Furthermore, financial constraints, distance to healthcare facilities, and poor health infrastructure disproportionately restrict access to preconception services, particularly for vulnerable populations. The study also highlights insufficient skills and outdated training among healthcare workers regarding preconception guidance, primarily attributed to limited opportunities for professional development. Discussion: To improve preconception care in Nigeria, comprehensive education programs must be implemented, taking into account the societal influences that shape perceptions and behaviors. These programs should aim to dispel myths and promote evidence-based practices. Additionally, training healthcare workers and integrating preconception care services into primary care settings, with support from religious and community leaders, can help overcome barriers to access. Strategies should prioritize affordability while emphasizing the broader benefits of preconception care beyond fertility concerns alone. Lastly, widespread literacy campaigns utilizing trusted channels are crucial for effectively disseminating information and promoting the adoption of preconception practices in Nigeria.

Keywords: preconception care, knowledge, healthcare workers, Nigeria, barriers, education, training

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Authors: Ravneet Kaur, Joydeep Acharya, Sudhanshu Gaur

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Artificial Intelligence (AI) has the potential to transform manufacturing by improving shop floor processes such as production, maintenance and quality. However, industrial datasets are notoriously difficult to extract in a real-time, streaming fashion thus, negating potential AI benefits. The main example is some specialized industrial controllers that are operated by custom software which complicates the process of connecting them to an Information Technology (IT) based data acquisition network. Security concerns may also limit direct physical access to these controllers for data acquisition. To connect the Operational Technology (OT) data stored in these controllers to an AI application in a secure, reliable and available way, we propose a novel Industrial IoT (IIoT) solution in this paper. In this solution, we demonstrate how video cameras can be installed in a factory shop floor to continuously obtain images of the controller HMIs. We propose image pre-processing to segment the HMI into regions of streaming data and regions of fixed meta-data. We then evaluate the performance of multiple Optical Character Recognition (OCR) technologies such as Tesseract and Google vision to recognize the streaming data and test it for typical factory HMIs and realistic lighting conditions. Finally, we use the meta-data to match the OCR output with the temporal, domain-dependent context of the data to improve the accuracy of the output. Our IIoT solution enables reliable and efficient data extraction which will improve the performance of subsequent AI applications.

Keywords: human machine interface, industrial internet of things, internet of things, optical character recognition, video analytics

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Authors: Ludovic Fabre, Paola Melani, Patrick Lemaire

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The goal of this study was to test whether and how emotions influence drone operators in estimation skills. The empirical study was run in the context of numerical estimation. Participants saw a two-digit number together with a collection of cars. They had to indicate whether the stimuli collection was larger or smaller than the number. The two-digit numbers ranged from 12 to 27, and collections included 3-36 cars. The presentation of the collections was dynamic (each car moved 30 deg. per second on the right). Half the collections were smaller collections (including fewer than 20 cars), and the other collections were larger collections (i.e., more than 20 cars). Splits between the number of cars in a collection and the two-digit number were either small (± 1 or 2 units; e.g., the collection included 17 cars and the two-digit number was 19) or larger (± 8 or 9 units; e.g., 17 cars and '9'). Half the collections included more items (and half fewer items) than the number indicated by the two-digit number. Before and after each trial, participants saw an image inducing negative emotions (e.g., mutilations) or neutral emotions (e.g., candle) selected from International Affective Picture System (IAPS). At the end of each trial, participants had to say if the second picture was the same as or different from the first. Results showed different effects of emotions on RTs and percent errors. Participants’ performance was modulated by emotions. They were slower on negative trials compared to the neutral trials, especially on the most difficult items. They errored more on small-split than on large-split problems. Moreover, participants highly overestimated the number of cars when in a negative emotional state. These findings suggest that emotions influence numerical estimation, that effects of emotion in estimation interact with stimuli characteristics. They have important implications for understanding the role of emotions on estimation skills, and more generally, on how emotions influence cognition.

Keywords: drone operators, emotion, numerical estimation, arithmetic

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Authors: Xi Wang, Yoshio Bando

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Lithium-ion batteries (LIBs) can deliver high levels of energy storage density and offer long operating lifetimes, but their power density is too low for many important applications. Therefore, we developed some new strategies and fabricated novel electrodes for fast Li transport and its facile synthesis including N-doped graphene-SnO2 sandwich papers, bicontinuous nanoporous Cu/Li4Ti5O12 electrode, and binder-free N-doped graphene papers. In addition, by using advanced in-TEM, STEM techniques and the theoretical simulations, we systematically studied and understood their storage mechanisms at the atomic scale, which shed a new light on the reasons of the ultrafast lithium storage property and high capacity for these advanced anodes. For example, by using advanced in-situ TEM, we directly investigated these processes using an individual CuO nanowire anode and constructed a LIB prototype within a TEM. Being promising candidates for anodes in lithium-ion batteries (LIBs), transition metal oxide anodes utilizing the so-called conversion mechanism principle typically suffer from the severe capacity fading during the 1st cycle of lithiation–delithiation. Also we report on the atomistic insights of the GN energy storage as revealed by in situ TEM. The lithiation process on edges and basal planes is directly visualized, the pyrrolic N "hole" defect and the perturbed solid-electrolyte-interface (SEI) configurations are observed, and charge transfer states for three N-existing forms are also investigated. In situ HRTEM experiments together with theoretical calculations provide a solid evidence that enlarged edge {0001} spacings and surface "hole" defects result in improved surface capacitive effects and thus high rate capability and the high capacity is owing to short-distance orderings at the edges during discharging and numerous surface defects; the phenomena cannot be understood previously by standard electron or X-ray diffraction analyses.

Keywords: in-situ TEM, STEM, advanced anode, lithium-ion batteries, storage mechanism

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Authors: Safa Abdussalam

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Adolescence is a period of storm and stress. It is a transitional period. Adolescents undergo a lot of changes physically, emotionally and mentally during adolescence. Physical changes include puberty, sexual maturation, changes in height, weight, hormonal changes, changes in body image, changes in brain and in sexuality. Changes also occur in their cognition. According to Piaget’s theory, adolescent enter formal operational stage and engage in hypothetical-deductive reasoning. Main characteristic of adolescent cognition is adolescent egocentrism: imaginary audience and personal fable. One of the most common struggle majority of adolescents face is the conflict between parent and adolescent. They often complain that parents do not understand them/their situation. Common topics of conflict include identity crisis, issues with personal freedom and issues over personal preferences. Conflict resolution refers to solving conflicts in a healthy way. There is a lack of resources in dealing with such conflicts creatively. To deal with parent-adolescent conflict, a conflict resolution board game is designed. The board game consists of tokens, dice, 10 conflict situation cards and two conflict resolution sheets. Purpose of using a board game is to help adolescents understand the conflict situations and resolutions in a fun, creative and interactive way. It can be used for self-help or even therapists can use it in their clinical practice. The study aims to assess the effectiveness of the board game in dealing with the conflict. Experimental design will be used. Samples include 15 adolescents belonging to age group 10-19. Samples will be divided into two groups: Experimental group and control group. A pre-test and post-test will be conducted. The board game will be demonstrated to the experimental group. Results will be obtained after statistical analysis. Board games are a great way to be used with children and adolescents.

Keywords: adolescent, adolescence, parent-child conflict, conflict resolution

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Authors: Ling Xu, Giuseppe Loprencipe, Antonio D'Andrea

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Asphalt pavement with recycled and sustainable materials has become the most commonly adopted strategy for road construction, including reclaimed asphalt pavement (RAP) and crumb rubber (CR) from waste tires. However, the adhesion and cohesion characteristics of rubberized reclaimed asphalt pavement were still ambiguous, resulting in deteriorated adhesion behavior and life performance. This research investigated the effect of bonding characteristics on rutting resistance and moisture susceptibility of rubberized reclaimed asphalt pavement in terms of two RAP sources with different oxidation levels and two tire rubber with different particle sizes. Firstly, the binder bond strength (BBS) test and bonding failure distinguishment were conducted to analyze the surface behaviors of binder-aggregate interaction. Then, the compatibility and penetration grade of rubberized RAP binder were evaluated by rotational viscosity test and penetration test, respectively. Hamburg wheel track (HWT) test with high-temperature viscoelastic deformation analysis was adopted, which illustrated the rutting resistance. Additionally, a water boiling test was employed to evaluate the moisture susceptibility of the mixture and the texture features were characterized with the statistical parameters of image colors. Finally, the colloid structure model of rubberized RAP binder with surface interaction was proposed, and statistical analysis was established to release the correlation among various indexes. This study concluded that the gel-phase colloid structure and molecular diffusion of the free light fraction would affect the surface interpretation with aggregate, determining the bonding characteristic of rubberized RAP asphalt.

Keywords: bonding characteristics, reclaimed asphalt pavement, rubberized asphalt, sustainable material

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Authors: Lamees Nasser, Yago Diez, Robert Martí, Joan Martí, Ibrahim Sadek

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Automated 3D breast ultrasound (ABUS) screening is a novel modality in medical imaging because of its common characteristics shared with other ultrasound modalities in addition to the three orthogonal planes (i.e., axial, sagittal, and coronal) that are useful in analysis of tumors. In the literature, few automatic approaches exist for typical tasks such as segmentation or registration. In this work, we deal with two problems concerning ABUS images: nipple and rib detection. Nipple and ribs are the most visible and salient features in ABUS images. Determining the nipple position plays a key role in some applications for example evaluation of registration results or lesion follow-up. We present a nipple detection algorithm based on color and shape of the nipple, besides an automatic approach to detect the ribs. In point of fact, rib detection is considered as one of the main stages in chest wall segmentation. This approach consists of four steps. First, images are normalized in order to minimize the intensity variability for a given set of regions within the same image or a set of images. Second, the normalized images are smoothed by using anisotropic diffusion filter. Next, the ribs are detected in each slice by analyzing the eigenvalues of the 3D Hessian matrix. Finally, a breast mask and a probability map of regions detected as ribs are used to remove false positives (FP). Qualitative and quantitative evaluation obtained from a total of 22 cases is performed. For all cases, the average and standard deviation of the root mean square error (RMSE) between manually annotated points placed on the rib surface and detected points on rib borders are 15.1188 mm and 14.7184 mm respectively.

Keywords: Automated 3D Breast Ultrasound, Eigenvalues of Hessian matrix, Nipple detection, Rib detection

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Authors: Saman Keshavarzi

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The process of planning, designing and building neighborhoods is a complex and multidimensional part of urban planning. Understanding the elements that give a neighborhood a sense of identity can lead to successful city planning and result in a cohesive and functional community where people feel a sense of belonging. These factors are important in ensuring that the needs of the urban population are met to live in a safe, pleasant and healthy society. This research paper aims to identify the elements of the identity of traditional neighborhoods in Isfahan and analyzes ways of using these elements in the design of modern neighborhoods to increase social interaction between communities and cultural reunification of people. The neighborhood of Jolfa in Isfahan has a unique socio-cultural identity as it dates back to the Safavid Dynasty of the 16^th century, and most of its inhabitants are Christian Armenians of a religious minority. The elements of the identity of Jolfa were analyzed through the following research methods: field observations, distribution of questionnaires and qualitative analysis. The basic methodology that was used to further understand the Jolfa neighborhood and deconstruct the identity image that residents associate with their respective neighborhoods was a qualitative research method. This was done through utilizing questionnaires that respondents had to fill out in response to a series of research questions. From collecting these qualitative data, the major finding was that traditional neighborhoods that have elements of identity embedded in them are seen to have closer-knit communities whose residents have strong societal ties. This area of study in urban planning is vital to ensuring that new neighborhoods are built with concepts of social cohesion, community and inclusion in mind as they are what lead to strong, connected, and prosperous societies.

Keywords: development, housing, identity, neighborhood, policy, urbanization

Procedia PDF Downloads 171

Authors: H. Aljabiry, L. Bailey, S. Young

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Qatar is a desert with an average temperature 37⁰C, reaching over 40⁰C during summer. Precipitation is uncommon and mostly in winter. Qatar depends on desalination for drinking water and on groundwater and recycled water for irrigation. Water consumption and network leakage per capita in Qatar are amongst the highest in the world; re-use of treated wastewater is extremely limited with only 14% of treated wastewater being used for irrigation. This has led to the country disposing of unwanted water from various sources in lagoons situated around the country, causing concern over the possibility of environmental pollution. Accordingly, our hypothesis underpinning this research is that the quality and quantity of water in lagoons is having an impact on the groundwater reservoirs in Qatar. Lagoons (n = 14) and wells (n = 55) were sampled for both summer and winter in 2018 (summer and winter). Water, adjoining soil and plant samples were analysed for multiple elements by Inductively Coupled Plasma Mass Spectrometry. Organic and inorganic carbon were measured (CN analyser) and the major anions were determined by ion chromatography. Salinization in both the lagoon and the wells was seen with good correlations between Cl⁻, Na⁺, Li, SO₄, S, Sr, Ca, Ti (p-value < 0.05). Association of heavy metals was observed of Ni, Cu, Ag, and V, Cr, Mo, Cd which is due to contamination from anthropological activities such as wastewater disposal or spread of contaminated dust. However, looking at each elements none of them exceeds the Qatari regulation. Moreover, gypsum saturation in the system was observed in both the lagoon and wells water samples. Lagoons and the water of the well are found to be of a saline type as well as Ca²⁺, Cl⁻, SO₄²⁻ type evidencing both gypsum dissolution and salinization in the system. Moreover, Maps produced by Inverse distance weighting showed an increasing level of Nitrate in the groundwater in winter, and decrease chloride and sulphate level, indicating recharge effect after winter rain events. While E. coli and faecal bacteria were found in most of the lagoons, biological analysis for wells needs to be conducted to understand the biological contamination from lagoon water infiltration. As a conclusion, while both the lagoon and the well showed the same results, more sampling is needed to understand the impact of the lagoons on the groundwater.

Keywords: groundwater quality, lagoon, treated wastewater, water management, wastewater treatment, wetlands

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Authors: Dhanuja S. Patil, Sanjay B. Waykar

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Event detection is a standout amongst the most key parts for distinctive sorts of area applications of video data framework. Recently, it has picked up an extensive interest of experts and in scholastics from different zones. While detecting video event has been the subject of broad study efforts recently, impressively less existing methodology has considered multi-model data and issues related efficiency. Start of soccer matches different doubtful circumstances rise that can't be effectively judged by the referee committee. A framework that checks objectively image arrangements would prevent not right interpretations because of some errors, or high velocity of the events. Bayesian networks give a structure for dealing with this vulnerability using an essential graphical structure likewise the probability analytics. We propose an efficient structure for analysing and summarization of soccer videos utilizing object-based features. The proposed work utilizes the t-cherry junction tree, an exceptionally recent advancement in probabilistic graphical models, to create a compact representation and great approximation intractable model for client’s relationships in an interpersonal organization. There are various advantages in this approach firstly; the t-cherry gives best approximation by means of junction trees class. Secondly, to construct a t-cherry junction tree can be to a great extent parallelized; and at last inference can be performed utilizing distributed computation. Examination results demonstrates the effectiveness, adequacy, and the strength of the proposed work which is shown over a far reaching information set, comprising more soccer feature, caught at better places.

Keywords: summarization, detection, Bayesian network, t-cherry tree

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Authors: Wondmnew Derebe Yohannis

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Farming irrigation plays a crucial role in rural development strategies, impacting both annual household income and livelihood. This research aims to evaluate the factors influencing irrigation participation and assess the impact of small-scale irrigation on rural households' annual income. The study collected data from 287 farmers in the Dahana district of northern Ethiopia. The research investigates the driving forces behind farmers' decisions to adopt small-scale irrigation and its effect on annual income gain. The findings reveal that several factors positively influence the probability of adoption, including access to credit, cultivated land size, livestock holding, extension contact, and the education level of the household head. Conversely, the distance to local markets and water schemes negatively affects the likelihood of adoption. To understand the differences in annual income between farm households that adopted irrigation and those that did not, a simultaneous equations model with endogenous switching regression is estimated. This accounts for the heterogeneity in the adoption decision and unobservable characteristics of farmers and their farms. The analysis compares the expected income gain under actual and counterfactual scenarios, considering whether the farm household adopted irrigation or not. The study reveals that the group of farm households that adopted irrigation has distinct characteristics compared to those that did not adopt it. Furthermore, the research demonstrates that the adoption of irrigation practices leads to an increase in annual income. Interestingly, the impact of small-scale irrigation on annual income is greater for the farm households that actually adopted irrigation compared to those in the counterfactual scenario where they did not adopt. Based on the findings, the researcher concludes that small-scale irrigation is a practical solution for meeting household financial needs in the study area. It is recommended that investments in small-scale irrigation continue to further improve the livelihoods of rural farming communities by enhancing annual income gains.

Keywords: small-scale irrigation, income, rural farm households, endogenous switching regression, user, non-user

Procedia PDF Downloads 55

Authors: Arlene Caney, Linda Fellag

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To counter the adverse effect of Covid-19 on college student success, two faculty members at a US community college have used web-based assessment data to improve curricula and, thus, student outcomes. This case study exemplifies how “closing the loop” by analyzing outcome assessments in real time can improve student learning for academically underprepared students struggling during the pandemic. The purpose of the study was to develop ways to mitigate the negative impact of Covid-19 on student success of underprepared college students. Using the Assessment, Evaluation, Feedback and Intervention System (AEFIS) and other assessment tools provided by the college’s Office of Institutional Research, an English professor and a Music professor collected data in skill areas related to their curricula over four semesters, gaining insight into specific course sections and learners’ performance across different Covid-driven course formats—face-to-face, hybrid, synchronous, and asynchronous. Real-time data collection allowed faculty to shorten and close the assessment loop, and prompted faculty to enhance their curricula with engaging material, student-centered activities, and a variety of tech tools. Frequent communication, individualized study, constructive criticism, and encouragement were among other measures taken to enhance teaching and learning. As a result, even while student success rates were declining college-wide, student outcomes in these faculty members’ asynchronous and synchronous online classes improved or remained comparable to student outcomes in hybrid and face-to-face sections. These practices have demonstrated that even high-risk students who enter college with remedial level language and mathematics skills, interrupted education, work and family responsibilities, and language and cultural diversity can maintain positive outcomes in college across semesters, even during the pandemic.

Keywords: AEFIS, assessment, distance education, institutional research center

Procedia PDF Downloads 85

Authors: Zhongmin Wang, Wudong Fan, Hengshan Zhang, Yimin Zhou

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In data-driven prognostic methods, the prediction accuracy of the estimation for remaining useful life of bearings mainly depends on the performance of health indicators, which are usually fused some statistical features extracted from vibrating signals. However, the existing health indicators have the following two drawbacks: (1) The differnet ranges of the statistical features have the different contributions to construct the health indicators, the expert knowledge is required to extract the features. (2) When convolutional neural networks are utilized to tackle time-frequency features of signals, the time-series of signals are not considered. To overcome these drawbacks, in this study, the method combining convolutional neural network with gated recurrent unit is proposed to extract the time-frequency image features. The extracted features are utilized to construct health indicator and predict remaining useful life of bearings. First, original signals are converted into time-frequency images by using continuous wavelet transform so as to form the original feature sets. Second, with convolutional and pooling layers of convolutional neural networks, the most sensitive features of time-frequency images are selected from the original feature sets. Finally, these selected features are fed into the gated recurrent unit to construct the health indicator. The results state that the proposed method shows the enhance performance than the related studies which have used the same bearing dataset provided by PRONOSTIA.

Keywords: continuous wavelet transform, convolution neural net-work, gated recurrent unit, health indicators, remaining useful life

Procedia PDF Downloads 131

Authors: Erika Csanyi, Gyula Sandor

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In the course of the examination, we sought to answer the question of how and to what extent the home range and daily activity of a deer stag relocated from its habitual surroundings changes. We conducted the examination in two hunting areas in Hungary, about 50 km from one another. The control area was in the north of Somogy County, while the sample area was an area of similar features in terms of forest cover, tree stock, agricultural structure, altitude above sea level, climate, etc. in the south of Somogy County. Three middle-aged red deer stags were captured with rocket nets, immobilized and marked with GPS-Plus Collars manufactured by Vectronic Aerospace Gesellschaft mit beschränkter Haftung. One captured species was relocated. We monitored deer movements over 24-hour periods at 3 months. In the course of the examination, we analysed the behaviour of the relocated species and those that remained in their original habitat, as well as the temporal evolution of their behaviour. We examined the characteristics of the marked species’ daily activities and the hourly distance they covered. We intended to find out the difference between the behaviour of the species remaining in their original habitat and of those relocated to a more distant, but similar habitat. In summary, based on our findings, it can be established that such enforced relocations to a different habitat (e.g., game relocation) significantly increases the home range of the species in the months following relocation. Home ranges were calculated using the full data set and the minimum convex polygon (MCP) method. Relocation did not increase the nocturnal and diurnal movement activity of the animal in question. Our research found that the home range of the relocated species proved to be significantly higher than that of those species that were not relocated. The results have been presented in tabular form and have also been displayed on a map. Based on the results, it can be established that relocation inherently includes the risk of falling victim to poaching, vehicle collision. It was only in the third month following relocation that the home range of the relocated species subsided to the level of those species that were not relocated. It is advisable to take these observations into consideration in relocating red deer for nature conservation or game management purposes.

Keywords: Cervus elaphus, home range, relocation, red deer stag

Procedia PDF Downloads 132

Authors: Mosaab A. Omara, Layla O. Elmajdoubb, Mohammad Saleh Al-Aboodyc, Ahmed ElSifyd, Ahmed O. Elkhtamd

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The aim of this study is to present the molecular characterization of cysticercus tenuicolis of Taenia hydatigena from livestock isolates in Egypt, using the amplification of sequencing of the mt-CO1 gene. We introduce a detailed image of the Cysticercus tenuicolis infection in ruminant animals in Upper Egypt. Cysticercus tenuicolis inhabits such organs in ruminants as the omentum, viscera, and liver. In the present study, the infection rate of Cysticercus tenuicolis was found to be 16% and 19% in sheep and goat sample respectively. Firstly we report one larval stage of Taenia hydatigena detected in the camel liver in Egypt. Cysticercus tenuicolis infection manifested a higher prevalence in females than in males. Those above 2 years of age manifested a higher infection rate than younger animals. The preferred site for the infection was the omentum: a 70% preference in sheep and a 68% preference in goat samples. The molecular characterization using the mitochondrial cytochrome c oxidase subunit 1 (CO1) gene of isolates from sheep, goats and camels corresponded to T. hydatigena. For this study, molecular characterizations of T. hydatigena were done for the first time in Egypt. Molecular tools are of great assistance in characterizing the Cysticercus tenuicolis parasite especially when the morphological character cannot be detected because the metacestodes are frequently confused with infection by the Hydatid cyst, especially when these occur in the visceral organs. In the present study, Cysticercus tenuicolis manifested high identity in the goat and sheep samples, while differences were found more frequently in the camel samples (10 pairbase). Clearly molecular diagnosis for Cysticercus tenuicolis infection significantly helps to differentiate it from such other metacestodes.

Keywords: cysticercus tenuicolis, its2, genetic, qena, molecular and taenia hydatigena

Procedia PDF Downloads 521