Search results for: KK remote station

Authors: Hyunsun Lee, Yi Zhu

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Wireless ad-hoc network is a decentralized type of temporary machine-to-machine connection that is spontaneous or impromptu so that it does not rely on any fixed infrastructure and centralized administration. As unmanned aerial vehicles (UAVs), also called drones, have recently become more accessible and widely utilized in military and civilian domains such as surveillance, search and detection missions, traffic monitoring, remote filming, product delivery, to name a few. The communication between these UAVs become possible and materialized through Flying Ad-hoc Networks (FANETs). However, due to the high mobility of UAVs that may cause different types of transmission interference, it is vital to design robust routing protocols for FANETs. In this talk, the multicast routing method based on a modified stochastic branching process is proposed. The stochastic branching process is often used to describe an early stage of an infectious disease outbreak, and the reproductive number in the process is used to classify the outbreak into a major or minor outbreak. The reproductive number to regulate the local transmission rate is adapted and modified for flying ad-hoc network communication. The performance of the proposed routing method is compared with other well-known methods such as flooding method and gossip method based on three measures; average reachability, average node usage and average branching factor. The proposed routing method achieves average reachability very closer to flooding method, average node usage closer to gossip method, and outstanding average branching factor among methods. It can be concluded that the proposed multicast routing scheme is more efficient than well-known routing schemes such as flooding and gossip while it maintains high performance.

Keywords: Flying Ad-hoc Networks, Multicast Routing, Stochastic Branching Process, Unmanned Aerial Vehicles

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Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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Authors: Ju-Hong Lee, Ching-Wei Liao

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Adaptive beamforming using antenna array of sensors is useful in the process of adaptively detecting and preserving the presence of the desired signal while suppressing the interference and the background noise. For conventional adaptive array beamforming, we require a prior information of either the impinging direction or the waveform of the desired signal to adapt the weights. The adaptive weights of an antenna array beamformer under a steered-beam constraint are calculated by minimizing the output power of the beamformer subject to the constraint that forces the beamformer to make a constant response in the steering direction. Hence, the performance of the beamformer is very sensitive to the accuracy of the steering operation. In the literature, it is well known that the performance of an adaptive beamformer will be deteriorated by any steering angle error encountered in many practical applications, e.g., the wireless communication systems with massive antennas deployed at the base station and user equipment. Hence, developing effective signal processing techniques to deal with the problem due to steering angle error for array beamforming systems has become an important research work. In this paper, we present an effective signal processing technique for constructing an adaptive beamformer against the steering angle error. The proposed array beamformer adaptively estimates the actual direction of the desired signal by using the presumed steering vector and the received array data snapshots. Based on the presumed steering vector and a preset angle range for steering mismatch tolerance, we first create a matrix related to the direction vector of signal sources. Two projection matrices are generated from the matrix. The projection matrix associated with the desired signal information and the received array data are utilized to iteratively estimate the actual direction vector of the desired signal. The estimated direction vector of the desired signal is then used for appropriately finding the quiescent weight vector. The other projection matrix is set to be the signal blocking matrix required for performing adaptive beamforming. Accordingly, the proposed beamformer consists of adaptive quiescent weights and partially adaptive weights. Several computer simulation examples are provided for evaluating and comparing the proposed technique with the existing robust techniques.

Keywords: adaptive beamforming, robustness, signal blocking, steering angle error

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Authors: Ismail Elkhrachy

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Determination of land use changing is an important component of regional planning for applications ranging from urban fringe change detection to monitoring change detection of land use. This data are very useful for natural resources management.On the other hand, the technologies and methods of change detection also have evolved dramatically during past 20 years. So it has been well recognized that the change detection had become the best methods for researching dynamic change of land use by multi-temporal remotely-sensed data. The objective of this paper is to assess, evaluate and monitor land use change surrounding the area of Najran city, Kingdom of Saudi Arabia (KSA) using Landsat images (June 23, 2009) and ETM+ image(June. 21, 2014). The post-classification change detection technique was applied. At last,two-time subset images of Najran city are compared on a pixel-by-pixel basis using the post-classification comparison method and the from-to change matrix is produced, the land use change information obtained.Three classes were obtained, urban, bare land and agricultural land from unsupervised classification method by using Erdas Imagine and ArcGIS software. Accuracy assessment of classification has been performed before calculating change detection for study area. The obtained accuracy is between 61% to 87% percent for all the classes. Change detection analysis shows that rapid growth in urban area has been increased by 73.2%, the agricultural area has been decreased by 10.5 % and barren area reduced by 7% between 2009 and 2014. The quantitative study indicated that the area of urban class has unchanged by 58.2 km〗^2, gained 70.3 〖km〗^2 and lost 16 〖km〗^2. For bare land class 586.4〖km〗^2 has unchanged, 53.2〖km〗^2 has gained and 101.5〖km〗^2 has lost. While agriculture area class, 20.2〖km〗^2 has unchanged, 31.2〖km〗^2 has gained and 37.2〖km〗^2 has lost.

Keywords: land use, remote sensing, change detection, satellite images, image classification

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Authors: Muhammad Nasar-u-Minallah, Dagmar Haase, Salman Qureshi

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Rapid urbanization significantly change land use, urban nature, land surface vegetation cover, and heat distribution, leading to the formation of urban heat island (UHI) effect and affecting the healthy growth of cities and the comfort of human living style. Past information and present changes in Land Surface Temperature (LST) and urban landscapes could be useful to geographers, environmentalists, and urban planners in an attempt to shape the urban development process and mitigate the effects of urban heat islands (UHI). This study aims at using Satellite Remote Sensing (SRS) and GIS techniques to develop an approach for assessing the urban nature and UHI effects in Lahore, Pakistan. The study employed the Radiative Transfer Method (RTM) in estimating LST to assess the SUHI effect during the interval of 20 years (2000-2020). The assessment was performed by the available Landsat 7/ETM+ and Landsat 8/OIL_TIRs data for the years 2000, 2010, and 2020 respectively. Pearson’s correlation and normalized mutual information were applied to investigate the relationship between green space characteristics and LST. The result of this work revealed that the influence of urban heat island is not always at the city centers but sometimes in the outskirt where a lot of development activities were going on towards the direction of expansion of Lahore, Pakistan. The present study explores the usage of image processing and spatial analysis in the drive towards achieving urban greening of Lahore and a sustainable urban environment in terms of urban planning, policy, and decision making and promoting the healthy and sustainable urban environment of the city.

Keywords: urban nature, urban heat islands, urban green space, land use, Lahore

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Authors: Eronini Iheanyi Umez-Eronini

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Most studies and existing implementations of compressed air energy storage (CAES) coupled with a wind farm to overcome intermittency and variability of wind power are based on bulk or centralized CAES plants. A dynamic model of a hybrid wind farm with wind turbines and distributed CAES, consisting of air storage tanks and compressor and expander trains at each wind turbine station, is developed and simulated in MATLAB. An ad hoc supervisory controller, in which the wind turbines are simply operated under classical power optimizing region control while scheduling power production by the expanders and air storage by the compressors, including modulation of the compressor power levels within a control range, is used to regulate overall farm power production to track minute-scale (3-minutes sampling period) TSO absolute power reference signal, over an eight-hour period. Simulation results for real wind data input with a simple wake field model applied to a hybrid plant composed of ten 5-MW wind turbines in a row and ten compatibly sized and configured Diabatic CAES stations show the plant controller is able to track the power demand signal within an error band size on the order of the electrical power rating of a single expander. This performance suggests that much improved results should be anticipated when the global D-CAES control is combined with power regulation for the individual wind turbines using available approaches for wind farm active power control. For standalone power plant fuel electrical efficiency estimate of up to 60%, the round trip electrical storage efficiency computed for the distributed CAES wherein heat generated by running compressors is utilized in the preheat stage of running high pressure expanders while fuel is introduced and combusted before the low pressure expanders, was comparable to reported round trip storage electrical efficiencies for bulk Adiabatic CAES.

Keywords: hybrid wind farm, distributed CAES, diabatic CAES, active power control, dynamic modeling and simulation

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Authors: Kyosuke Kamada, Christoph Kapeller, Michael Jordan, Mostafa Mohammadpour, Christy Li, Christoph Guger

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Cortico-cortical evoked potentials (CCEP) refer to responses generated by cortical electrical stimulation at distant brain sites. These responses provide insights into the functional networks associated with language or motor functions, and in the context of epilepsy, they can reveal pathological networks. Locating the origin and spread of seizures within the cortex is crucial for pre-surgical planning. This process can be enhanced by employing cortical stimulation at the seizure onset zone (SOZ), leading to the generation of CCEPs in remote brain regions that may be targeted for disconnection. In the case of a 24-year-old male patient suffering from intractable epilepsy, corpus callosotomy was performed as part of the treatment. DTI-MRI imaging, conducted using a 3T MRI scanner for fiber tracking, along with CCEP, is used as part of an assessment for surgical planning. Stimulation of the SOZ, with alternating monophasic pulses of 300µs duration and 15mA current intensity, resulted in CCEPs on the contralateral frontal cortex, reaching a peak amplitude of 206µV with a latency of 31ms, specifically in the left pars triangularis. The related fiber tracts were identified with a two-tensor unscented Kalman filter (UKF) technique, showing transversal fibers through the corpus callosum. The CCEPs were monitored through the progress of the surgery. Notably, the SOZ-associated CCEPs exhibited a reduction following the resection of the anterior portion of the corpus callosum, reaching the identified connecting fibers. This intervention demonstrated a potential strategy for mitigating the impact of intractable epilepsy through targeted disconnection of identified cortical regions.

Keywords: CCEP, SOZ, Corpus callosotomy, DTI

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Authors: Wegene Demeke

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Background: The demand for healthcare services is growing in developing and developed countries. Information and communication technology is used to facilitate healthcare services. In the case of developing countries, implementing telemedicine is aimed at providing healthcare for people living in remote areas where health service is not accessible. The implementations of telemedicine in developing countries are unsuccessful. For example, the recent study indicates that 90% of telemedicine projects are abandoned or failed in developing countries. Several researchers reported the technological challenges as the main factor for the non-adoption of telemedicine. However, this research reports the health professionals’ perspectives arising from technical, social and organizational factors that are considered as key elements for the setting and running of telemedicine in Ethiopia. The importance and significance of telemedicine for healthcare is growing. For example, the use of telemedicine in the current pandemic situation becomes an essential strategic element in providing healthcare services in developed countries. Method: Qualitative and quantitative exploratory research methods used to collect data to find factors affecting the adoption of Information and communication technologies for telemedicine use. The survey was distributed using emails and Google forms. The email addresses were collected from personal contact and publicly available websites in Ethiopia. The thematic analysis used to build the barriers and facilitators factors for establishing telemedicine services. A survey questionnaire with open-and-close questions was used to collect data from 175 health professionals. Outcome: The result of this research will contribute to building the key barriers and facilitators factors of telemedicine from the health professional perspectives in developing countries. The thematic analysis provides barriers and facilitators factors arising from technical, organizational, and social sources.

Keywords: telemedicine, ICT, developing country, Ethiopia, health service

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Authors: ȘercăIanu Mihai, Aldea Mihaela, Iacoboaea Cristina, Luca Oana, Nenciu Ioana

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The emergence and neutralization of illegal waste dumps represent a global concern for waste management ecosystems with a particularly pronounced impact on disadvantaged communities. All over the world, and in this particular case in Romania, a relevant number of people resided in houses lacking any legal forms such as land ownership documents or building permits. These areas are referred to as “informal settlements”. An increasing number of regions and cities in Romania are struggling to manage their waste dumps, especially in the context of increasing poverty and lack of regulation related to informal settlements. An example of such informal settlement can be found at the terminus of Bistra Street in Câlnic, which falls under the jurisdiction of the Municipality of Reșița in Caras Severin County. The article presents a case study that focuses on employing remote sensing techniques and spatial data to monitor and map illegal waste practices, with subsequent integration into a geographic information system tailored for the Reșița community. In addition, the paper outlines the steps involved in devising strategies aimed at enhancing waste management practices in disadvantaged areas, aligning with the shift toward a circular economy. Results presented in the paper contain a spatial mapping and visualization methodology calibrated with in situ data collection applicable for identifying illegal landfills. The emergence and neutralization of illegal dumps pose a challenge in the field of waste management. These approaches, which prove effective where conventional solutions have failed, need to be replicated and adopted more wisely.

Keywords: waste dumps, waste management, monitoring, GIS, informal settlements

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Authors: Eloise Thomson

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The COVID-19 global pandemic challenged our normative conceptualization of teaching across all age levels, requiring the transition to remote instruction, in some instances, literally overnight. Included in the rapidly changing education environment was the delivery of early childhood education. In Victoria, Australia, the capital city, Melbourne, became known as the most locked down city in the world. This presentation examines the ways educators used social media to collaborate with families before the COVID-19 pandemic and during the lockdown phase through the use of a Third Space conceptual framework and case study methodology. As a first step, the paper examines how social media may offer new opportunities for collaborative practice between educators and families. Second, the data is outlined and discussed with respect to collaborative practice and quality. Finally, a postscript then allows for insight into how educators’ practice of using social media to collaborate with families has been impacted by the COVID-19 global pandemic. Finally, the implications of the ways in which educators are using social media to collaborate with families are discussed. The use of social media in early-childhood education has the potential to provide a valuable platform for educators to connect with families and students. However, the use of social media by educators uncovered a dialogue of ‘quality’ and appeared to be dominated by evidence around compliance and attaining quality in a very specific, and perhaps narrow, way. The findings suggest a culture of compliance that is dominated by outcomes, standards and assessments and that this has changed the dynamics by which educators engage with families. Furthermore, findings highlighted the disparity between educators' and families' understanding of the intent of the collaborations themselves. This research was significant as it exposed the ways in which educators are engaging with social media, resulting in a discussion on the intent of collaborations, the questioning of imposed quality, and the notion that quality is measurable and exists in only one form.

Keywords: collaboration, compliance, early childhood, third space, pedagogy of caring, social media

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Authors: Musse Mohamud Ahmed, Tina Linda Achilles, Mohammad Kamrul Hasan

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Deterioration of the mother nature is evident these day with clear danger of human catastrophe emanating from greenhouses (GHG) with increasing CO2 emissions to the environment. PV technology can help to reduce the dependency on fossil fuel, decreasing air pollution and slowing down the rate of global warming. The objective of this paper is to propose, develop and design the production of clean water supply to rural communities using an appropriate technology such as Internet of Things (IOT) that does not create any CO2 emissions. Additionally, maximization of solar energy power output and reciprocally minimizing the natural characteristics of solar sources intermittences during less presence of the sun itself is another goal to achieve in this work. The paper presents the development of critical automated control system for solar energy power output optimization using several new techniques. water pumping system is developed to supply clean water with the application of IOT-renewable energy. This system is effective to provide clean water supply to remote and off-grid areas using Photovoltaics (PV) technology that collects energy generated from the sunlight. The focus of this work is to design and develop a submersible solar water pumping system that applies an IOT implementation. Thus, this system has been executed and programmed using Arduino Software (IDE), proteus, Maltab and C++ programming language. The mechanism of this system is that it pumps water from water reservoir that is powered up by solar energy and clean water production was also incorporated using filtration system through the submersible solar water pumping system. The filtering system is an additional application platform which is intended to provide a clean water supply to any households in Sarawak State, Malaysia.

Keywords: IOT, automated production and control system, water filtration, automated submersible water pump, solar energy

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Authors: Kateryna Zharan, Jan C. Bongaerts

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In recent years, economic attractiveness of renewable energy (RE) for the mining industry, especially for off-grid mines, and a negative environmental impact of fossil energy are stimulating to use RE for mining needs. Being that remote area mines have higher energy expenses than mines connected to a grid, integration of RE may give a mine economic benefits. Regarding the literature review, there is a lack of business models for adopting of RE at mine. The main aim of this paper is to develop an optimized model of RE integration into the German mining industry (GMI). Hereby, the GMI with amount of around 800 mill. t. annually extracted resources is included in the list of the 15 major mining country in the world. Accordingly, the mining potential of Germany is evaluated in this paper as a perspective market for RE implementation. The GMI has been classified in order to find out the location of resources, quantity and types of the mines, amount of extracted resources, and access of the mines to the energy resources. Additionally, weather conditions have been analyzed in order to figure out where wind and solar generation technologies can be integrated into a mine with the highest efficiency. Despite the fact that the electricity demand of the GMI is almost completely covered by a grid connection, the hybrid energy system (HES) based on a mix of RE and fossil energy is developed due to show environmental and economic benefits. The HES for the GMI consolidates a combination of wind turbine, solar PV, battery and diesel generation. The model has been calculated using the HOMER software. Furthermore, the demonstrated HES contains a forecasting model that predicts solar and wind generation in advance. The main result from the HES such as CO2 emission reduction is estimated in order to make the mining processing more environmental friendly.

Keywords: diesel generation, German mining industry, hybrid energy system, hybrid optimization model for electric renewables, optimized model, renewable energy

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Authors: Mohanad Al-Behadili, Xiang Song, Djamila Ouelhadj, Alex Fraess-Ehrfeld

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In off-shore wind farms, turbine blade inspection accessibility under various sea states is very challenging and greatly affects the downtime of wind turbines. Maintenance of any offshore system is not an easy task due to the restricted logistics and accessibility. The multirotor unmanned helicopter is of increasing interest in inspection applications due to its manoeuvrability and payload capacity. These advantages increase when many of them are deployed simultaneously in a swarm. Hence this paper proposes a drone swarm framework for inspecting offshore wind turbine blades and nacelles so as to reduce downtime. One of the big challenges of this task is that when operating a drone swarm, an individual drone may not have enough power to fly and communicate during missions and it has no capability of refueling due to its small size. Once the drone power is drained, there are no signals transmitted and the links become intermittent. Vessels equipped with 5G masts and small power units are utilised as platforms for drones to recharge/swap batteries. The research work aims at designing a smart energy management system, which provides automated vessel and drone routing and recharging plans. To achieve this goal, a novel mathematical optimisation model is developed with the main objective of minimising the number of drones and vessels, which carry the charging stations, and the downtime of the wind turbines. There are a number of constraints to be considered, such as each wind turbine must be inspected once and only once by one drone; each drone can inspect at most one wind turbine after recharging, then fly back to the charging station; collision should be avoided during the drone flying; all wind turbines in the wind farm should be inspected within the given time window. We have developed a real-time Ant Colony Optimisation (ACO) algorithm to generate real-time and near-optimal solutions to the drone swarm routing problem. The schedule will generate efficient and real-time solutions to indicate the inspection tasks, time windows, and the optimal routes of the drones to access the turbines. Experiments are conducted to evaluate the quality of the solutions generated by ACO.

Keywords: drone swarm, routing, scheduling, optimisation model, ant colony optimisation

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Authors: Vibeke Sorensen, Nagaraju Thummanapalli, J. Stephen Lansing

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Inspired by the indigenous people of Borneo, Indonesia and their traditional bark cloth, artist and professor Vibeke Sorensen executed a “digital unwrapping” of several trees in Southeast Asia using a digital panorama camera and digitally “stitched” them together for printing onto sustainable silk and fashioning into the “Tree Dress”. This dress is a symbolic “un-wrapping” and “re-wrapping” of the tree’s bark onto a person as a second skin. The “digital bark” is directly responsive to the real tree through embedded and networked electronics that connect in real-time to sensors at the physical site of the living tree. LEDs and circuits inserted into the dress display the continuous measurement of the O2 / CO2, temperature, humidity, and light conditions at the tree. It is an “Internet of Living Things” (IOLT) textile that can be worn to track and interact with it. The computer system connecting the dress and the tree converts the gas emission data at the site of the real tree into sound and music as sonification. This communicates not only the scientific data but also translates it into a poetic representation. The wearer of the garment can symbolically identify with the tree, or “become one” with it by adorning its “skin.” In this way, the wearer also becomes a human agent for the tree, bringing its actual condition to direct perception of the wearer and others who may engage it. This project is an attempt to bring greater awareness to issues of deforestation by providing a direct access to living things separated by physical distance, and hopefully, to increase empathy for them by providing a way to sense individual trees and their daily existential condition through remote monitoring of data. Further extensions to this project and related issues of sustainability include the use of recycled and alternative plant materials such as bamboo and air plants, among others.

Keywords: IOLT, sonification, sustainability, tree, wearable technology

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Authors: Rachel Byrne

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Background: Due to patient and student safety concerns, combined with clinical teachers being redeployed to clinical practice, COVID-19 has resulted in a reduction in face-to-face teaching sessions for medical students. Traditionally such sessions are particularly important for final year medical students, especially in preparing for their final practical exams. A reduced student presence on the wards has also resulted in fewer opportunities for junior doctors to provide teaching sessions. This has implications for junior doctors achieving their own curriculum outcomes for teaching, as well as potentially hindering the development of a future interest in medical education. Aims: The aims of the study are 1) To create a safe face-to-face teaching environment during COVID-19 which focussed on exam preparation for final year medical students, 2) To provide a platform for doctors to gain teaching experience, 3 ) to enable doctors to gain feedback or assessments on their teaching, 4) To create beginners guide to designing a new teaching program for future junior doctors. Methods: We created a program of timed clinical stations consisting of four sessions every five weeks during the student’s medicine attachment. Each session could be attended by 6 students and consisted of 6 stations ran by junior doctors, with each station following social distancing and personal protective equipment requirements. Junior doctors were asked to design their own stations. The sessions ran out-of-hours on weekday evenings and were optional for the students. Results: 95/95 students and 20/40 doctors involved in the programme completed feedback. 100% (n=95) of students strongly agreed/agreed that sessions were aimed at an appropriate level and provided constructive feedback. 100% (n=95) of students stated they felt more confident in their abilities and would recommend the session to peers. 90% (n=18) of the teachers strongly agreed/agreed that they felt more confident in their teaching abilities and that the sessions had improved their own medical knowledge. 85% (n=17) of doctors had a teaching assessment completed, and 83% (n=16) said the program had made them consider a career in medical education. The difficulties of creating such a program were highlighted throughout, and a beginner’s guide was created with the hopes of helping future doctors who are interested in teaching address the common obstacles.

Keywords: COVID-19, education, safety, medical

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Authors: Debra L. Stanley, Gabriela Wasileski

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Offenders face many challenges as they transition from being incarcerated to the community, ranging from housing and employment needs to long standing problems with addictions and mental health issues. A lack of appropriate behavioral health services in the more remote parts of the United States has led to a significant illegal substance abuse problem, housing instability, and unaddressed mental health and trauma issues. High rates of poverty and unemployment exacerbate the growing behavioral health issues, drug overdoses, co-occurring disorders, and crime that are so prevalent across rural communities. This study examines the challenges of rural jail reentry faced by offenders in a treatment capacity. The client-centered evidence-based program is uniquely designed to provide continuity of care that focuses on issues which affect rural communities. Prior to release from jail, individuals go through comprehensive assessment screenings to measure mental health and substance use disorder as well as trauma and prior crime victimization histories; the assessments help to target client-specific services. The quasi-experimental research design tracks clients throughout their recovery and reintegration into the community. Individuals in a rural program often do not have the benefit of easy access or peer mentoring that is so often found in urban recovery programs. Therefore, much of the support is provided through telehealth and e-services. The goal of this study is to explore the nature of rural reentry programs and measures of recidivism, drug overdoses, and other behavioral health needs and successful reentry to include stable housing and employment.

Keywords: jail reentry, rehabilitation, behavioral health, drug abuse, recidivism

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Authors: Eliza. E. Camaso, Guiller. B. Damian, Miguelito. F. Isip, Ronaldo T. Alberto

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Land-cover maps were important for many scientific, ecological and land management purposes and during the last decades, rapid decrease of soil fertility was observed to be due to land use practices such as rice cultivation. High-precision land-cover maps are not yet available in the area which is important in an economy management. To assure   accurate mapping of land cover to provide information, remote sensing is a very suitable tool to carry out this task and automatic land use and cover detection. The study did not only provide high precision land cover maps but it also provides estimates of rice production area that had undergone chemical degradation due to fertility decline. Land-cover were delineated and classified into pre-defined classes to achieve proper detection features. After generation of Land-cover map, of high intensity of rice cultivation, soil fertility degradation assessment in rice production area due to fertility decline was created to assess the impact of soils used in agricultural production. Using Simple spatial analysis functions and ArcGIS, the Land-cover map of Municipality of Quezon in Nueva Ecija, Philippines was overlaid to the fertility decline maps from Land Degradation Assessment Philippines- Bureau of Soils and Water Management (LADA-Philippines-BSWM) to determine the area of rice crops that were most likely where nitrogen, phosphorus, zinc and sulfur deficiencies were induced by high dosage of urea and imbalance N:P fertilization. The result found out that 80.00 % of fallow and 99.81% of rice production area has high soil fertility decline.

Keywords: aerial image, landcover, LiDAR, soil fertility degradation

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Authors: M. A. Hernández-Ceballos, M. Marín-Ferrer, G. Cinelli, L. De Felice, T. Tollefsen, E. Nweke, P. V. Tognoli, S. Vanzo, M. De Cort

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This study analyses the latitudinal impact of the spatial and temporal distribution on the cosmogenic isotope 7Be in surface air along Europe. The long-term database of the 6 sampling sites (Ivalo, Helsinki, Berlin, Freiburg, Sevilla and La Laguna), that regularly provide data to the Radioactivity Environmental Monitoring (REM) network managed by the Joint Research Centre (JRC) in Ispra, were used. The selection of the stations was performed attending to different factors, such as 1) heterogeneity in terms of latitude and altitude, and 2) long database coverage. The combination of these two parameters ensures a high degree of representativeness of the results. In the later, the temporal coverage varies between stations, being used in the present study sampling stations with a database more or less continuously from 1984 to 2011. The mean values of 7Be activity concentration presented a spatial distribution value ranging from 2.0 ± 0.9 mBq/m3 (Ivalo, north) to 4.8 ± 1.5 mBq/m3 (La Laguna, south). An increasing gradient with latitude was observed from the north to the south, 0.06 mBq/m3. However, there was no correlation with altitude, since all stations are sited within the atmospheric boundary layer. The analyses of the data indicated a dynamic range of 7Be activity for solar cycle and phase (maximum or minimum), having been observed different impact on stations according to their location. The results indicated a significant seasonal behavior, with the maximum concentrations occurring in the summer and minimum in the winter, although with differences in the values reached and in the month registered. Due to the large heterogeneity in the temporal pattern with which the individual radionuclide analyses were performed in each station, the 7Be monthly index was calculated to normalize the measurements and perform the direct comparison of monthly evolution among stations. Different intensity and evolution of the mean monthly index were observed. The knowledge of the spatial and temporal distribution of this natural radionuclide in the atmosphere is a key parameter for modeling studies of atmospheric processes, which are important phenomena to be taken into account in the case of a nuclear accident.

Keywords: Berilium-7, latitudinal impact in Europe, seasonal and monthly variability, solar cycle

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Authors: Racha El Kadiri, Mohamed Sultan, Henrique Momm, Zachary Blair, Rachel Schultz, Tamer Al-Bayoumi

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The Mediterranean Basin is a very diverse region of nationalities and climate zones, with a strong dependence on agricultural activities. Predicting long term (with a lead of 1 to 12 months) rainfall, and future droughts could contribute in a sustainable management of water resources and economical activities. In this study, an integrated approach was adopted to construct predictive tools with lead times of 0 to 12 months to forecast rainfall amounts over nine subzones of the Mediterranean Basin region. The following steps were conducted: (1) acquire, assess and intercorrelate temporal remote sensing-based rainfall products (e.g. The CPC Merged Analysis of Precipitation [CMAP]) throughout the investigation period (1979 to 2016), (2) acquire and assess monthly values for all of the climatic indices influencing the regional and global climatic patterns (e.g., Northern Atlantic Oscillation [NOI], Southern Oscillation Index [SOI], and Tropical North Atlantic Index [TNA]); (3) delineate homogenous climatic regions and select nine pilot study zones, (4) apply data mining methods (e.g. neural networks, principal component analyses) to extract relationships between the observed rainfall and the controlling factors (i.e. climatic indices with multiple lead-time periods) and (5) use the constructed predictive tools to forecast monthly rainfall and dry and wet periods. Preliminary results indicate that rainfall and dry/wet periods were successfully predicted with lead zones of 0 to 12 months using the adopted methodology, and that the approach is more accurately applicable in the southern Mediterranean region.

Keywords: rainfall, neural networks, climatic indices, Mediterranean

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Authors: Layan Moussa, Darine Salam, Samir Mustapha

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Heavy metal contamination in agricultural soils in Lebanon poses serious environmental and health problems. Intensive efforts are employed to improve existing quantification methods of heavy metals in contaminated environments since conventional detection techniques have shown to be time-consuming, tedious, and costly. The implication of hyperspectral remote sensing in this field is possible and promising. However, factors impacting the efficiency of hyperspectral imaging in detecting and quantifying heavy metals in agricultural soils were not thoroughly studied. This study proposes to assess the use of hyperspectral imaging for the detection of Ni in agricultural clay soil collected from the Bekaa Valley, a major agricultural area in Lebanon, under different contamination levels and soil moisture content. Soil samples were contaminated with Ni, with concentrations ranging from 150 mg/kg to 4000 mg/kg. On the other hand, soil with background contamination was subjected to increased moisture levels varying from 5 to 75%. Hyperspectral imaging was used to detect and quantify Ni contamination in the soil at different contamination levels and moisture content. IBM SPSS statistical software was used to develop models that predict the concentration of Ni and moisture content in agricultural soil. The models were constructed using linear regression algorithms. The spectral curves obtained reflected an inverse correlation between both Ni concentration and moisture content with respect to reflectance. On the other hand, the models developed resulted in high values of predicted R2 of 0.763 for Ni concentration and 0.854 for moisture content. Those predictions stated that Ni presence was well expressed near 2200 nm and that of moisture was at 1900 nm. The results from this study would allow us to define the potential of using the hyperspectral imaging (HSI) technique as a reliable and cost-effective alternative for heavy metal pollution detection in contaminated soils and soil moisture prediction.

Keywords: heavy metals, hyperspectral imaging, moisture content, soil contamination

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Authors: Sameer A. Pathan, Biswadev Mitra, Salman Mirza, Umais Momin, Zahoor Ahmed, Lubna G. Andraous, Dharmesh Shukla, Mohammed Y. Shariff, Magid M. Makki, Tinsy T. George, Saad S. Khan, Stephen H. Thomas, Peter A. Cameron

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Study objective: Emergency physician’s (EP) ability to identify hydronephrosis on point-of-care ultrasound (POCUS) has been assessed in the past using CT scan as the reference standard. We aimed to assess EP interpretation of POCUS to identify and grade the hydronephrosis in a direct comparison with the consensus-interpretation of POCUS by radiologists, and also to compare the EP and radiologist performance using CT scan as the criterion standard. Methods: Using data from a POCUS databank, a prospective interpretation study was conducted at an urban academic emergency department. All POCUS exams were performed on patients presenting with renal colic to the ED. Institutional approval was obtained for conducting this study. All the analyses were performed using Stata MP 14.0 (Stata Corp, College Station, Texas). Results: A total of 651 patients were included, with paired sets of renal POCUS video clips and the CT scan performed at the same ED visit. Hydronephrosis was reported in 69.6% of POCUS exams by radiologists and 72.7% of CT scans (p=0.22). The κ for consensus interpretation of POCUS between the radiologists to detect hydronephrosis was 0.77 (0.72 to 0.82) and weighted κ for grading the hydronephrosis was 0.82 (0.72 to 0.90), interpreted as good to very good. Using CT scan findings as the criterion standard, Eps had an overall sensitivity of 81.1% (95% CI: 79.6% to 82.5%), specificity of 59.4% (95% CI: 56.4% to 62.5%), PPV of 84.3% (95% CI: 82.9% to 85.7%), and NPV of 53.8% (95% CI: 50.8% to 56.7%); compared to radiologist sensitivity of 85.0% (95% CI: 82.5% to 87.2%), specificity of 79.7% (95% CI: 75.1% to 83.7%), PPV of 91.8% (95% CI: 89.8% to 93.5%), and NPV of 66.5% (95% CI: 61.8% to 71.0%). Testing for a report of moderate or high degree of hydronephrosis, specificity of EP was 94.6% (95% CI: 93.7% to 95.4%) and to 99.2% (95% CI: 98.9% to 99.5%) for identifying severe hydronephrosis alone. Conclusion: EP POCUS interpretations were comparable to the radiologists for identifying moderate to severe hydronephrosis using CT scan results as the criterion standard. Among patients with moderate or high pre-test probability of ureteric calculi, as calculated by the STONE-score, the presence of moderate to severe (+LR 6.3 and –LR 0.69) or severe hydronephrosis (+LR 54.4 and –LR 0.57) was highly diagnostic of the stone disease. Low dose CT is indicated in such patients for evaluation of stone size and location.

Keywords: renal colic, point-of-care, ultrasound, bedside, emergency physician

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Authors: Namugenyi Ephrance Eunice, Julianne Sansa Otim, Marco Zennaro, Stephen D. Wolthusen

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The Internet of Things (IoT) is a network of connected data processing devices, mechanical and digital machinery, items, animals, or people that may send data across a network without requiring human-to-human or human-to-computer interaction. Each component has sensors that can pick up on specific phenomena, as well as processing software and other technologies that can link to and communicate with other systems and/or devices over the Internet or other communication networks and exchange data with them. IoT is increasingly being used in fields other than consumer electronics, such as public safety, emergency response, industrial automation, autonomous vehicles, the Internet of Medical Things (IoMT), and general environmental monitoring. Consumer-based IoT applications, like smart home gadgets and wearables, are also becoming more prevalent. This paper presents the main IoT deployment areas for environmental monitoring in developing regions and the backhaul options suitable for them. A detailed review of each of the list of papers selected for the study is included in section III of this document. The study includes an overview of existing IoT deployments, the underlying communication architectures, protocols, and technologies that support them. This overview shows that Low Power Wireless Area Networks (LPWANs), as summarized in Table 1, are very well suited for monitoring environment architectures designed for remote locations. LoRa technology, particularly the LoRaWAN protocol, has an advantage over other technologies due to its low power consumption, adaptability, and suitable communication range. The prevailing challenges of the different architectures are discussed and summarized in Table 3 of the IV section, where the main problem is the obstruction of communication paths by buildings, trees, hills, etc.

Keywords: communication technologies, environmental monitoring, Internet of Things, IoT deployment challenges

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Authors: Danutė Jablonskytė-Raščė, Vidas Damanauskas

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The wheat (Triticum) genus is divided into many species, of which only two are widely distributed in the world - common wheat (Triticum aestivum L.) and durum wheat (Triticum durum Desf.). Common (soft) wheat is the most common type of wheat in the world and the most suitable for the harsh climate of Lithuania, but the grains have lower protein content and poorer nutritional properties. Durum wheat is characterized by a high protein content of the grain, but it is a crop of warmer climates grown in southern countries, Italy, Spain, the United States, Egypt, etc. Today's important issue is food, its resources and quality. The research focuses on healthier food grown in our conditions, the quality of which recently depends a lot not only on the cultivation technology but also on the warming climate conditions. Climatic conditions change the distribution of fungi and their hosts. Plants that have grown in our climate for many years have adapted to the use of fungicides, so the aim is to study cereal varieties grown in warmer climates and compare them with our country's varieties, studying their nutritional value and the spread of fungal diseases. The field experiments of different varieties of wheat were conducted at Joniškėlis Experimental Station of the Lithuanian Research Centre for Agriculture and Forestry in 2023. The soil of the experimental site was Endocalcari-Endohypogleyic Cambisol (CMg-n-w-can). The research was designed to identify the resistance to leaf diseases and the nutritional value of various wheat varieties. This research aims to focus on healthier food grown in our conditions, the quality of which recently depends a lot not only on the cultivation technology but also on the conditions of the warming climate. The study found that hot and humid summer weather led to the spread of foliar diseases in wheat. Tan spot (Pyrenophora tritici-repentis) is mostly spread in wheat crops. This disease had an average prevalence of 86.90%. The wheat crop was sparse, so this year was unfavorable for the spread of powdery mildew (Blumeria graminis). Dry weather prevailed during the period of flowering of cereals, which prevented the spread of ear diseases. Examining the qualitative indicators of grain, it was found that durum wheat had the best parameters.

Keywords: varieties, wheat, leaf disease, grain quality

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Authors: Jawaher A. Alsultan, Allen Feldman

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With the rapid switch to remote learning due to the COVID-19 pandemic, science teachers were suddenly required to teach their classes online. This breakneck shift to eLearning raised the question of how teacher educators could support science teachers who wanted to use reform-based methods of instruction while using virtual technologies. In this retrospective self-study, we, two science teacher educators, examined our practice as we worked with science teachers to implement inquiry, discussion, and argumentation [IDA] through eLearning. Ten high school science teachers from a large school district in the southeastern US participated virtually in the COVID-19 Community of Practice [COVID-19 CoP]. The CoP met six times from the end of April through May 2020 via Zoom. Its structure was based on a model of action research called enhanced normal practice [ENP], which includes exchanging stories, trying out ideas, and systematic inquiry. Data sources included teacher educators' meeting notes and reflective conversations, audio recordings of the CoP meetings, teachers' products, and post-interviews of the teachers. Findings included a new understanding of the role of existing relationships, shared goals, and similarities in the participants' situations, which helped build trust in the CoP, and the effects of our paying attention to the science teachers’ needs led to a well-functioning CoP. In addition, we became aware of the gaps in our knowledge of how the teachers already used apps in their practice, which they then shared with all of us about how they could be used for online teaching using IDA. We also identified the need to pay attention to feelings about tensions between the teachers and us around the expectations for final products and the project's primary goals. We found that if we are to establish relationships between us as facilitators and teachers that are honest, fair, and kind, we must express those feelings within the collective, dialogical processes that can lead to learning by all members of the CoP, whether virtual or face-to-face.

Keywords: community of practice, facilitators, self-study, action research

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Authors: Andrew Kanzunguze, Lusayo Mwabumba, Jason K. Gilbertson, Dominic B. Gondwe, George Z. Nxumayo

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Knowledge about the spatio-temporal distribution of invasive plants in protected areas provides a base from which hypotheses explaining proliferation of plant invasions can be made alongside development of relevant invasive plant monitoring programs. The aim of this study was to investigate the spatio-temporal distribution of bracken fern on the grassland plateau of Nyika National Park over the past 30 years (1986-2016) as well as to determine the current extent of the invasion. Remote sensing, machine learning, and statistical modelling techniques (object-based image analysis, image classification and linear regression analysis) in geographical information systems were used to determine both the spatial and temporal distribution of bracken fern in the study area. Results have revealed that bracken fern has been increasing coverage on the Nyika plateau at an estimated annual rate of 87.3 hectares since 1986. This translates to an estimated net increase of 2,573.1 hectares, which was recorded from 1,788.1 hectares (1986) to 4,361.9 hectares (2016). As of 2017 bracken fern covered 20,940.7 hectares, approximately 14.3% of the entire grassland plateau. Additionally, it was observed that the fern was distributed most densely around Chelinda camp (on the central plateau) as well as in forest verges and roadsides across the plateau. Based on these results it is recommended that Ecological Niche Modelling approaches be employed to (i) isolate the most important factors influencing bracken fern proliferation as well as (ii) identify and prioritize areas requiring immediate control interventions so as to minimize bracken fern proliferation in Nyika National Park.

Keywords: bracken fern, image classification, Landsat-8, Nyika National Park, spatio-temporal distribution

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Authors: Chukwukelue Uzodinma Umenyilorah

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The history of the crises in Niger-Delta is readily traceable to the post-colonial oil boom of the early 70s. Prior to this time, it was widely believed that the people of Niger-Delta; especially those in the present day Rivers, Delta and Bayelsa States enjoyed a peaceful coexistence pretty much as the rest of Nigerians. In the early 70s however, crude oil was discovered in commercial quantities in these areas and tranquility has become a far cry over the years ever since then. First, a number of multi-national oil explorers moved into the Niger-Delta for business, and then certain conditions resulted in sundry instances of oil spillage, which caused a lot of environmental damage, destroying nearly all of the people’s sources of livelihood. The result was a multiple chain reaction ranging from incessant agitations from the natives to institutionalized dialogue between the oil business owners, the natives and the government, and then to a proposition of compensation packages for the affected communities. The said compensation, which was meant to bring peace seem to have brought even more crises instead. Corruption and greed crept in, money changed hands, suffering increased and so was the agitation from the people. The whole turn of events gradually snowballed into the formation of various militant groups who are now fingered as responsible for the sundry cases of violence in the Niger-Delta. The oil boom can, therefore, be said to be the immediate cause of the Niger-Delta crises, but there are other remote causes as well; including poverty, neglect and illiteracy to mention but a few. This study is therefore aimed at examining the various reasons behind the seemingly unending crises in the Niger-Delta. It will also take a critical look at the roles played by the various parties in the Niger-Delta crises from the 70s to date; as well as the various human and environmental devastations done in the area with a view to making informed suggestions on how to stop further damage and start fixing that, which is already done. Esiaba Irobi’s Cemetery Road and Hangmen Also Die seem to vividly capture the realities of the Niger-Delta situation, and shall, therefore, be reviewed in this study.

Keywords: corruption, Niger-delta, oil boom, post-colonial

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Authors: H. A. Algahtani, A. S. Khan, O. Alzahrani, N. Hussein, M. A. Khan, Loudhi Y. I. Soliman

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Objective: To report on the Saudi experience (developing country) of neurological complications from bariatric surgery. The literature on the subject is reviewed. Method: This is a cross sectional study done in King Abdul Aziz Medical City Jeddah, WR, where we reviewed all charts of the patients who underwent bariatric surgery between January 1st, 2009 to December 31st , 2014. Personal and clinical data including age, sex, BMI, comorbidities, type of procedure, duration of stay in hospital, complications and postoperative follow up were collected. In addition follow up visit and remote complication if present were collected. All patients with neurological complications were reviewed in details including their clinical examination, laboratory and imaging results, treatment and prognosis. This report is essentially descriptive with no statistical analysis performed. Results: Fifteen cases were collected in this study (3%). Axonal polyneuropathy was the most frequent neurological complica¬tion, but cases of Wernicke syndrome, vitamin B12 deficiency, Guillain-Barre syndrome and cupper deficiency were also identified. Fourteen patients (93.3%) had full recovery from the neurological signs and symptoms but unfortunately one patient died. Conclusion: Bariatric surgery, a procedure that is continuously increasing in popularity, is not free of potential neurological complications. A clear education, guidelines and follow-up program should be planned and practiced. Facts should be clearly presented to the individual undergoing this type of surgery. Although a clear cause-effect relation cannot be established for the present cases, the cumulative literature on the subject makes it important to warn the patient of the potential risks of this procedure.

Keywords: bariatric surgery, neurological complications, neuropathy, Wenicke syndrome

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Authors: P. M. Kundu, L. R. Singo, J. O. Odiyo

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Luvuvhu River catchment in South Africa experiences floods resulting from heavy rainfall of intensities exceeding 15 mm per hour associated with the Inter-tropical Convergence Zone (ITCZ). The generation of runoff is triggered by the rainfall intensity and soil moisture status. In this study, remote sensing and GIS techniques were used to analyze the hydrologic response to land cover changes. Runoff was calculated as a product of the net precipitation and a curve number coefficient. It was then routed using the Muskingum-Cunge method using a diffusive wave transfer model that enabled the calculation of response functions between start and end point. Flood frequency analysis was determined using theoretical probability distributions. Spatial data on land cover was obtained from multi-temporal Landsat images while data on rainfall, soil type, runoff and stream discharges was obtained by direct measurements in the field and from the Department of Water. A digital elevation model was generated from contour maps available at http://www.ngi.gov.za. The results showed that land cover changes had impacted negatively to the hydrology of the catchment. Peak discharges in the whole catchment were noted to have increased by at least 17% over the period while flood volumes were noted to have increased by at least 11% over the same period. The flood time to peak indicated a decreasing trend, in the range of 0.5 to 1 hour within the years. The synergism between remotely sensed digital data and GIS for land surface analysis and modeling was realized, and it was therefore concluded that hydrologic modeling has potential for determining the influence of changes in land cover on the hydrologic response of the catchment.

Keywords: catchment, digital elevation model, hydrological model, routing, runoff

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Authors: A. Fomujong, P. Mobit, A. Ndlovu, R. Teboh

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Purpose: Film’s unique qualities, such as tissue equivalence, high spatial resolution, near energy independence and comparatively less expensive dosimeter, ought to make it the preferred and widely used in radiotherapy centers in low and middle income countries (LMICs). This, however, is not always the case, as other factors that are often maybe taken for granted in advanced radiotherapy centers remain a challenge in LMICs. We explored the unique qualities of film dosimetry that can make it possible for one Institution to benefit from another’s protocols via collaboration. Methods: For simplicity, two Institutions were considered in this work. We used a single batch of films (EBT-XD) and established a calibration protocol, including scan protocols and calibration curves, using the radiotherapy delivery system at Institution A. We then proceeded and performed patient-specific QA for patients treated on system A (PSQA-A-A). Films from the same batch were then sent to a remote center for PSQA on radiotherapy delivery system B. Irradiations were done at Institution B and then returned to Institution A for processing and analysis (PSQA-B-A). The following points were taken into consideration throughout the process (a) A reference film was irradiated to a known dose on the same system irradiating the PSQA film. (b) For calibration, we utilized the one-scan protocol and maintained the same scan orientation of the calibration, PSQA and reference films. Results: Gamma index analysis using a dose threshold of 10% and 3%/2mm criteria showed a gamma passing rate of 99.8% and 100% for the PSQA-A-A and PSQA-B-A, respectively. Conclusion: This work demonstrates that one could use established film dosimetry protocols in one Institution, e.g., an advanced radiotherapy center and apply similar accuracies to irradiations performed at another institution, e.g., a center located in LMIC, which thus encourages collaboration between the two for worldwide patient benefits.

Keywords: collaboration, film dosimetry, LMIC, radiotherapy, calibration

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Authors: M. Sakthivel, A. Devaki, D. Balasubramanyam, P. Kumarasamy, A. Raja, R. Anilkumar, H. Gopi

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The influence of inbreeding on growth traits in the New Zealand White rabbits maintained at Sheep Breeding and Research Station, Sandynallah, The Nilgiris, India was studied in a closed herd. Data were collected over a period of 15 years (1998 to 2012). The traits studied were body weights at weaning (W42), post-weaning (W70) and marketing (W135) age and growth efficiency traits viz., average daily gain (ADG), relative growth rate (RGR) and Kleiber ratio (KR) estimated on a daily basis at different age intervals (1=42 to 70 days; 2=70 to 135 days and 3=42 to 135 days) from weaning to marketing. The effects of inbreeding along with other non-genetic factors (sex of the kit, season and period of birth of the kit) were analyzed using least-squares method. The inbreeding (F) and equivalent inbreeding (EF) coefficients were taken as fixed classes as well as covariates in separate analyses. When taken as covariate, the effect was analyzed as partial regression of respective growth trait on individual inbreeding coefficient (F or EF). The mean body weights at weaning, post-weaning and marketing were 0.715, 1.276 and 2.187 kg, respectively. The maximum growth efficiency was noticed between weaning and post-weaning. Season and period had highly significant influence on all the growth parameters studied and sex of the kit had significant influence on certain growth efficiency traits only. The average coefficients of inbreeding and equivalent inbreeding in the population were 13.233 and 17.585 percent, respectively. About 11.17 percent of total matings were highly inbred in which full-sib, half-sib and parent-offspring matings were 1.20, 6.30 and 3.67 percent, respectively. The regression of body weight traits on F and EF showed negative effect whereas most of the growth efficiency traits showed positive effects. Significant inbreeding depression was observed in W42 and W70. The depression in W42 was 0.214 kg and 0.139 kg and in W70 was 0.269 kg and 0.172 kg for every one unit increase in F and EF, respectively. Though the trait W135 showed positive value and ADG1 showed depression, the effects of inbreeding and equivalent inbreeding were non-significant in these traits. Higher values of inbreeding depression could be due to more variance of F or EF in the population. The analysis of the effect of level of inbreeding on growth traits revealed that the inbreeding class was significant on W70, ADG2, RGR2 and KR2 while EF classes had significant influence only on ADG2, RGR2 and KR2. Obviously, inbreeding does not have a positive effect, therefore, these results suggest that inbreeding had no effect on these traits.

Keywords: growth parameters, equivalent inbreeding, inbreeding effects, rabbit genetics

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