Search results for: deep soil

Authors: Hussein Bizimana, Osman Sönmez

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Constructed wetlands are current the most widely recognized waste water treatment option, especially in developing countries where they have the potential for improving water quality and creating valuable wildlife habitat in ecosystem with treatment requirement relatively simple for operation and maintenance cost. Lack of grey waste water treatment facilities in Kigali İnstitute of Science and Technology in Rwanda, causes pollution in the surrounding localities of Rugunga sector, where already a problem of poor sanitation is found. In order to treat grey water produced at Kigali İnstitute of Science and Technology, with high BOD concentration, high nutrients concentration and high alkalinity; a Horizontal Sub-surface Flow pilot-scale constructed wetland was designed and can operate in Kigali İnstitute of Science and Technology. The study was carried out in a sedimentation tank of 5.5 m x 1.42 m x 1.2 m deep and a Horizontal Sub-surface constructed wetland of 4.5 m x 2.5 m x 1.42 m deep. The grey waste water flow rate of 2.5 m3/d flew through vegetated wetland and sandy pilot plant. The filter media consisted of 0.6 to 2 mm of coarse sand, 0.00003472 m/s of hydraulic conductivity and cattails (Typha latifolia spp) were used as plants species. The effluent flow rate of the plant is designed to be 1.5 m3/ day and the retention time will be 24 hrs. 72% to 79% of BOD, COD, and TSS removals are estimated to be achieved, while the nutrients (Nitrogen and Phosphate) removal is estimated to be in the range of 34% to 53%. Every effluent characteristic will meet exactly the Rwanda Utility Regulatory Agency guidelines primarily because the retention time allowed is enough to make the reduction of contaminants within effluent raw waste water. Treated water reuse system was developed where water will be used in the campus irrigation system again.

Keywords: constructed wetlands, hydraulic conductivity, grey waste water, cattails

Procedia PDF Downloads 603

Authors: Waqed H. Almohammed, Mohammed Y. Fattah, Sajjad E. Rasheed

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Dynamic traffic loads cause deformation of underground pipes, resulting in vehicle discomfort. This makes it necessary to reinforce the layers of soil above underground pipes. In this study, the subbase layer was reinforced. Finite element software (PLAXIS 3D) was used to in the simulation, which includes geocell reinforcement, vehicle loading, soil layers and Glass Fiber Reinforced Plastic (GRP) pipe. Geocell reinforcement was modeled using a geogrid element, which was defined as a slender structure element that has the ability to withstand axial stresses but not to resist bending. Geogrids cannot withstand compression but they can withstand tensile forces. Comparisons have been made between the numerical models and experimental works, and a good agreement was obtained. Using the mathematical model, the performance of three different pipes of diameter 600 mm, 800 mm, and 1000 mm, and three different vehicular speeds of 20 km/h, 40 km/h, and 60 km/h, was examined to determine their impact on surface settlement and vertical pressure at the pipe crown for two cases: with and without geocell reinforcement. The results showed that, for a pipe diameter of 600 mm under geocell reinforcement, surface settlement decreases by 94 % when the speed of the vehicle is 20 km/h and by 98% when the speed of the vehicle is 60 km/h. Vertical pressure decreases by 81 % when the diameter of the pipe is 600 mm, while the value decreases to 58 % for a pipe with diameter 1000 mm. The results show that geocell reinforcement causes a significant and positive reduction in surface settlement and vertical stress above the pipe crown, leading to an increase in pipe safety.

Keywords: dynamic loading, finite element, geocell-reinforcement, GRP pipe, PLAXIS 3D, surface settlement

Procedia PDF Downloads 243

Authors: Seema Garcha, Sheetal Chopra, Navraj Sarao

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Plant hormones play a role in internal colonization by beneficial microbes and also systemic acquired resistance. They define qualitative and quantitative nature of root microbiome and also influence dynamics of root rhizospheric soil. The present study is an attempt to relate salicylic acid (signal molecule) content and qualitative nature of root endophytes at various stages in the growth of rice varieties of commercial value- Parmal 121 and Basmati 1121. Root seedlings of these varieties were raised using tissue culture techniques and then they were transplanted in the fields. Cultivation was done using conventional methods in agriculture. Field soil contained 0.39% N, 75.12 Kg/hectare of phosphorus and 163.0 Kg/hectare of potassium. Microfloral profiling of the root tissue was done using the selective microbiological medium. The salicylic acid content was estimated using HPLC-Agilent 1100 HPLC Series. Salicylic acid level of Basmati 1121 remained relatively low at the time of transplant and 90 days after transplant. It increased marginally at 60 days. A similar trend was observed with Parmal 121 as well. However, Parmal variety recorded 0.935 ug/g of salicylic acid at 60 days after transplant. Salicylic acid content decreased after 90 days as both the rice varieties remained disease free. The endophytic root microflora was established by 60 days after transplant in both the varieties after which their population became constant. Rhizobium spp dominated over Azotobacter spp. Genetic profiling of endophytes for nitrogen-fixing ability is underway.

Keywords: plant-microbe interaction, rice, root microbiome, salicylic acid

Procedia PDF Downloads 198

Authors: Angelica Salmeron Alcocer, Deifilia Ahuatzi Chacon, Felipe Rodriguez Casasola

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Polycyclic aromatic hydrocarbons (PAHs) are produced naturally (forest fires, volcanic eruptions) and human activity (burning fossil fuels). Concern for PAHs is due to their toxic, mutagenic and carcinogenic effects and so pose a potential risk to human health and ecology. Therefore these are considered the most toxic components of oil, they are highly hydrophobic, making them easily depositable on the floor, air and water. One method of removing PAHs of contaminated soil used surfactants such as Tween 80, which it has been reported as less toxic and also increases the solubility of the PAH compared to other surfactants, fluoranthene is a PAH with molecular formula C16H10, its name derives from the fluorescence which presents to UV light. In this paper, a study of the fluoranthene removal solubilized with Tween 80 in synthetic wastewater using a microbial community (isolated from soil of coffee plantations in the state of Veracruz, Mexico) and Fenton oxidation method was performed. The microbial community was able to use both tween 80 and fluoranthene as carbon sources for growth, when the biological treatment in batch culture was applied, 100% of fluoranthene was mineralized, this only occurred at an initial concentration of 100 ppm, but by increasing the initial concentration of fluoranthene the removal efficiencies decay and degradation time increases due to the accumulation of byproducts more toxic or less biodegradable, however when the Fenton oxidation was previously applied to the biological treatment, it was observed that removal of fluoranthene improved because it is consumed approximately 2.4 times faster.

Keywords: fluoranthene, polycyclic aromatic hydrocarbons, biological treatment, fenton oxidation

Procedia PDF Downloads 236

Authors: Hamid Fallah

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Undoubtedly, flood is known as a natural disaster, and in practice, flood is considered the most terrible natural disaster in the world both in terms of loss of life and financial losses. From 1988 to 1997, about 390,000 people were killed by natural disasters in the world, 58% of which were related to floods, 26% due to earthquakes, and 16% due to storms and other disasters. The total damages in these 10 years were about 700 billion dollars, which were 33, 29, 28% related to floods, storms and earthquakes, respectively. In this regard, the worrisome point has been the increasing trend of flood deaths and damages in the world in recent decades. The increase in population and assets in flood plains, changes in hydro systems and the destructive effects of human activities have been the main reasons for this increase. During rain and snow, some of the water is absorbed by the soil and plants. A percentage evaporates and the rest flows and is called runoff. Floods occur when the soil and plants cannot absorb the rainfall, and as a result, the natural river channel does not have the capacity to pass the generated runoff. On average, almost 30% of precipitation is converted into runoff, which increases with snow melting. Floods that occur differently create an area called flood plain around the river. River floods are often caused by heavy rains, which in some cases are accompanied by snow melt. A flood that flows in a river without warning or with little warning is called a flash flood. The casualties of these rapid floods that occur in small watersheds are generally more than the casualties of large river floods. Coastal areas are also subject to flooding caused by waves caused by strong storms on the surface of the oceans or waves caused by underground earthquakes. Floods not only cause damage to property and endanger the lives of humans and animals, but also leave other effects. Runoff caused by heavy rains causes soil erosion in the upstream and sedimentation problems in the downstream. The habitats of fish and other animals are often destroyed by floods. The high speed of the current increases the damage. Long-term floods stop traffic and prevent drainage and economic use of land. The supports of bridges, river banks, sewage outlets and other structures are damaged, and there is a disruption in shipping and hydropower generation. The economic losses of floods in the world are estimated at tens of billions of dollars annually.

Keywords: flood, hydrological engineering, gis, dam, small hydropower, suitablity

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Authors: Reza Mehrafarin, Nafiseh Mirshekari

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The Sistan plain has always been a site for the settlement of various human societies, thanks to its favorable environmental conditions, such as abundant water from the Hirmand River and fertile sedimentary soil. Consequently, there was a need for a systematic archaeological investigation in the area. The survey had multiple objectives, with the most significant ones being the creation of an archaeological map and the identification and documentation of all ancient sites to establish their records and chronology. The survey was carried out in two phases, with each phase covering half of the area. The research method involved fieldwork, with two teams of professional archaeologists conducting a comprehensive survey of each of the 22 areas in Sistan. Once an area was identified, various recording, scientific, and field operations were executed to study the site. In the first phase (2007), an intensive field survey focused on the residential area of Sistan, including its northern and eastern regions. This phase resulted in the identification of 808 sites in eleven selected areas. In the second phase (2009), the desert area of Sistan, or its southern half, was surveyed, leading to the identification of approximately 853 sites. Overall, these surveys resulted in the identification of 1661 sites in Sistan. Among these sites, approximately 899 belong to the Bronze Age (late 4th millennium BCE to early 2nd millennium BCE). Of these sites, around 501 date back to the historical period, while nearly 590 sites pertain to the Islamic period. The archaeological investigations of both phases revealed that Sistan has consistently possessed fertile soil, abundant water, and a skilled workforce, making it capable of becoming Iran's granary and the center of the East once again if these conditions are restored.

Keywords: sistan, field surveys, archaeology, archaeological map

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Authors: Alireza Nejadmohammad Namaghi

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Investigators have reported that mulches increase production potential in arid and semi arid lands. Mulches are covering materials that are used on soil surface for efficiency irrigation, erosion control, weed control, evaporation decrease and improvement of water perpetration. Our aim and local situation determine the kind of material that we can use. In this research we used different mulches including chemical mulch (M1), Aquasorb polymer, manure mulch (M2), Residue mulch (M3) and polyethylene mulch (M4), with control treatment (M0), without usage of mulch, on germination, biomass dry matter and cottonseed yield (Varamin variety) in Kashan area. Randomized complete block (RCB) design have measured the cotton yield with 3 replications for measuring the biomass dry matter and 4 replication in tow irrigation periods as 7 and 14 days. Germination percentage for M0, M1, M2, M3 and M4 treatment were receptivity 64, 65, 76, 57 and 72% Biomass dry matter average for M0, M1, M2, M3 and M4 treatment were receptivity 276, 306, 426, 403 and 476 gram per plot. M4 treatment (polyethylene Mulch) had the most effect, M2 and M3 had no significant as well as M0 and M1. Total yield average with respect to 7 days irrigation for M0, M1, M2, M3 and M4 treatment were receptivity 700, 725, 857, 1057 and 1273 gram per plot. Dunken ne multiple showed no significant different among M0, M1, M2, and M3, but M4 ahs the most effect on yield. Total yield average with respect to 14 days irrigation for M0, M1, M2, M3 and M4 treatment were receptivity 535, 507, 690, 957 and 1047 gram per plot. These were significant difference between all treatments and control treatment. Results showed that used different mulches with water decrease in dry situation can increase the yield significantly.

Keywords: mulch, cotton, arid land management, irrigation systems

Procedia PDF Downloads 80

Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

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Authors: Abbas Raza Ali

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Big Data technology is gradually becoming a dire need of large enterprises. These enterprises are generating massively large amount of off-line and streaming data in both structured and unstructured formats on daily basis. It is a challenging task to effectively extract useful insights from the large scale datasets, even though sometimes it becomes a technology constraint to manage transactional data history of more than a few months. This paper presents a framework to efficiently manage massively large and complex datasets. The framework has been tested on a communication service provider producing massively large complex streaming data in binary format. The communication industry is bound by the regulators to manage history of their subscribers’ call records where every action of a subscriber generates a record. Also, managing and analyzing transactional data allows service providers to better understand their customers’ behavior, for example, deep packet inspection requires transactional internet usage data to explain internet usage behaviour of the subscribers. However, current relational database systems limit service providers to only maintain history at semantic level which is aggregated at subscriber level. The framework addresses these challenges by leveraging Big Data technology which optimally manages and allows deep analysis of complex datasets. The framework has been applied to offload existing Intelligent Network Mediation and relational Data Warehouse of the service provider on Big Data. The service provider has 50+ million subscriber-base with yearly growth of 7-10%. The end-to-end process takes not more than 10 minutes which involves binary to ASCII decoding of call detail records, stitching of all the interrogations against a call (transformations) and aggregations of all the call records of a subscriber.

Keywords: big data, communication service providers, enterprise data warehouse, stream computing, Telco IN Mediation

Procedia PDF Downloads 173

Authors: Taramani Yadav, Gajender Kumar, R.K. Yadav, H.S. Jat

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Soil Salinity and irrigation water salinity is critical threat to enhance agricultural food production to full fill the demand of billion plus people worldwide. Salt affected soils covers 6.73 Mha in India and ~1000 Mha area around the world. Irrigation scheduling of saline water is the way to ensure food security in salt affected areas. Research experiment was conducted at ICAR-Central Soil Salinity Research Institute, Experimental Farm, Nain, Haryana, India with 36 treatment combinations in double split plot design. Three sets of treatments consisted of (i) three regimes of irrigation viz., 60, 80 and 100% (I1, I2 and I3, respectively) of crop ETc (crop evapotranspiration at identified respective stages) in main plot; (ii) four levels of irrigation water salinity (sub plot treatments) viz., 2, 4, 8 and 12 dS m-1 (iii) applications of two PBRs along with control (without PBRs) i.e. salicylic acid (G1; 1 mM) and thiourea (G2; 500 ppm) as sub-sub plot treatments. Grain yield of wheat (Triticum aestivum) was increased with less amount of high salt loaded irrigation water at the same level of salinity (2 dS m-1), the trend was I3>I2>I1 at 2 dS m-1 with 8.10 and 17.07% increase at 80 and 100% ETc, respectively compared to 60% ETc. But contrary results were obtained by increasing amount of irrigation water at same level of highest salinity (12 dS m-1) showing following trend; I1>I2>I3 at 12 dS m-1 with 9.35 and 12.26% increase at 80 and 60% ETc compared to 100% ETc. Enhancement in grain yield of wheat (Triticum aestivum) is not need to increase amount of irrigation water under saline condition, with salty irrigation water less amount of irrigation water gave the maximum wheat (Triticum aestivum) grain yield.

Keywords: Irrigation, Salinity, Wheat, Yield

Procedia PDF Downloads 163

Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

Procedia PDF Downloads 188

Authors: Mohammed Abu Shquier

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This paper introduces a word segmentation method using the novel BP-LSTM-CRF architecture for processing semantic output training. The objective of web morphological analysis tools is to link a formal morpho-syntactic description to a lemma, along with morpho-syntactic information, a vocalized form, a vocalized analysis with morpho-syntactic information, and a list of paradigms. A key objective is to continuously enhance the proposed system through an inductive learning approach that considers semantic influences. The system is currently under construction and development based on data-driven learning. To evaluate the tool, an experiment on homograph analysis was conducted. The tool also encompasses the assumption of deep binary segmentation hypotheses, the arbitrary choice of trigram or n-gram continuation probabilities, language limitations, and morphology for both Modern Standard Arabic (MSA) and Dialectal Arabic (DA), which provide justification for updating this system. Most Arabic word analysis systems are based on the phonotactic morpho-syntactic analysis of a word transmitted using lexical rules, which are mainly used in MENA language technology tools, without taking into account contextual or semantic morphological implications. Therefore, it is necessary to have an automatic analysis tool taking into account the word sense and not only the morpho-syntactic category. Moreover, they are also based on statistical/stochastic models. These stochastic models, such as HMMs, have shown their effectiveness in different NLP applications: part-of-speech tagging, machine translation, speech recognition, etc. As an extension, we focus on language modeling using Recurrent Neural Network (RNN); given that morphological analysis coverage was very low in dialectal Arabic, it is significantly important to investigate deeply how the dialect data influence the accuracy of these approaches by developing dialectal morphological processing tools to show that dialectal variability can support to improve analysis.

Keywords: NLP, DL, ML, analyser, MSA, RNN, CNN

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Authors: Mehrnaz Mostafavi

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The assessment and categorization of incidental lung nodules present a considerable challenge in healthcare, often necessitating resource-intensive multiple computed tomography (CT) scans for growth confirmation. This research addresses this issue by introducing a distinct computational approach leveraging radiomics and deep-learning methods. However, understanding local services is essential before implementing these advancements. With diverse tracking methods in place, there is a need for efficient and accurate identification approaches, especially in the context of managing lung nodules alongside pre-existing cancer scenarios. This study explores the integration of text-based algorithms in medical data curation, indicating their efficacy in conjunction with machine learning and deep-learning models for identifying lung nodules. Combining medical images with text data has demonstrated superior data retrieval compared to using each modality independently. While deep learning and text analysis show potential in detecting previously missed nodules, challenges persist, such as increased false positives. The presented research introduces a Structured-Query-Language (SQL) algorithm designed for identifying pulmonary nodules in a tertiary cancer center, externally validated at another hospital. Leveraging natural language processing (NLP) and machine learning, the algorithm categorizes lung nodule reports based on sentence features, aiming to facilitate research and assess clinical pathways. The hypothesis posits that the algorithm can accurately identify lung nodule CT scans and predict concerning nodule features using machine-learning classifiers. Through a retrospective observational study spanning a decade, CT scan reports were collected, and an algorithm was developed to extract and classify data. Results underscore the complexity of lung nodule cohorts in cancer centers, emphasizing the importance of careful evaluation before assuming a metastatic origin. The SQL and NLP algorithms demonstrated high accuracy in identifying lung nodule sentences, indicating potential for local service evaluation and research dataset creation. Machine-learning models exhibited strong accuracy in predicting concerning changes in lung nodule scan reports. While limitations include variability in disease group attribution, the potential for correlation rather than causality in clinical findings, and the need for further external validation, the algorithm's accuracy and potential to support clinical decision-making and healthcare automation represent a significant stride in lung nodule management and research.

Keywords: lung cancer diagnosis, structured-query-language (SQL), natural language processing (NLP), machine learning, CT scans

Procedia PDF Downloads 86

Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

Procedia PDF Downloads 92

Authors: Clotilde Guyon, Nada Jmari, Yen-Chin Li, Jean Denoyel, Noriyuki Fujikado, Christophe Blanchet, David Root, Matthieu Giraud

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Aire induces ectopic expression of a large repertoire of tissue-specific antigen (TSA) genes in thymic medullary epithelial cells (MECs), driving immunological self-tolerance in maturing T cells. Although important mechanisms of Aire-induced transcription have recently been disclosed through the identification and the study of Aire’s partners, the fine transcriptional functions underlied by a number of them and conferred to Aire are still unknown. Alternative cleavage and polyadenylation (APA) is an essential mRNA processing step regulated by the termination complex consisting of 85 proteins, 10 of them have been related to Aire. We evaluated APA in MECs in vivo by microarray analysis with mRNA-spanning probes and RNA deep sequencing. We uncovered the preference of Aire-dependent transcripts for short-3’UTR isoforms and for proximal poly(A) site selection marked by the increased binding of the cleavage factor Cstf-64. RNA interference of the 10 Aire-related proteins revealed that Clp1, a member of the core termination complex, exerts a profound effect on short 3’UTR isoform preference. Clp1 is also significantly upregulated in the MECs compared to 25 mouse tissues in which we found that TSA expression is associated with longer 3’UTR isoforms. Aire-dependent transcripts escape a global 3’UTR lengthening associated with MEC differentiation, thereby potentiating the repressive effect of microRNAs that are globally upregulated in mature MECs. Consistent with these findings, RNA deep sequencing of actinomycinD-treated MECs revealed the increased stability of short 3’UTR Aire-induced transcripts, resulting in TSA transcripts accumulation and contributing for their enrichment in the MECs.

Keywords: Aire, central tolerance, miRNAs, transcription termination

Procedia PDF Downloads 380

Authors: Jovana Jankovic Pantic, Dragoslav Rakic, Tina Djuric, Irena Basaric Ikodinovic, Snezana Bogdanovic

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Regardless of the numerous activities undertaken to reduce municipal solid waste, its annual volumes continue to grow. In Serbia, the most common and the only one form of waste disposal is at municipal landfills with daily compaction and soil covering. Municipal waste compacting is one of the basic components of the disposal process. Well compacted waste takes up less volume and allows much safer storage. In order to better predict the behavior of municipal waste at landfills, it is necessary to define compaction parameters: the maximum dry unit weight and optimal moisture content. In current geotechnical practice, the most common method of determination compaction parameters is by the standard method (Proctor compaction test) used in soil mechanics, with an eventual reduction of compaction energy. Although this methodology is accepted in newer geotechnical scientific discipline "waste mechanics", different treatments of municipal waste at the landfill itself (including pretreatment), indicate the need to change this classical approach. The main reason for that is the simulation of the operation of compactors (hedgehogs) at the landfill. Therefore, during the research, various innovative solutions are introduced, such as changing the classic flat Proctor hammer, by adding spikes, whose function is, in addition to compaction, destruction and shredding of municipal waste. The paper presents the behavior of municipal waste for four synthetic waste samples with different waste compositions (Plandište landfill). The samples were tested in standard Proctor apparatus at the same compaction energy, but with two different hammers: standard flat hammer and hammer with spikes.

Keywords: compaction, hammer with spikes, landfill, municipal solid waste, proctor compaction test

Procedia PDF Downloads 217

Authors: Hardisiswo Soedjana, Inne Caroline

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Deep dermal or full thickness burns are inevitably lead to post-burn contractures. These contractures remain to be one of the most concerning late complications of burn injuries. Surgical management includes releasing the contracture followed by resurfacing the defect accompanied by post-operative rehabilitation. Optimal treatment of post-burn contractures depends on the characteristics of the contractures. This study is aimed to describe clinical characteristics, problems, and management of post-burn contractures in adults and children. A retrospective analysis was conducted from medical records of patients suffered from contractures after burn injuries admitted to Hasan Sadikin general hospital between January 2016 and January 2018. A total of 50 patients with post burn contractures were included in the study. There were 17 adults and 33 children. Most patients were male, whose age range within 15-59 years old and 5-9 years old. Educational background was mostly senior high school among adults, while there was only one third of children who have entered school. Etiology of burns was predominantly flame in adults (82.3%); whereas flame and scald were the leading cause of burn injury in children (11%). Based on anatomical regions, hands were the most common affected both in adults (35.2%) and children (48.5%). Contractures were identified in 6-12 months since the initial burns. Most post-burn hand contractures were resurfaced with full-thickness skin graft (FTSG) both in adults and children. There were 11 patients who presented with recurrent contracture after previous history of contracture release. Post-operative rehabilitation was conducted for all patients; however, it is important to highlight that it is still challenging to control splinting and exercise when patients are discharged and especially the compliance in children. In order to improve quality of life in patients with history of deep burn injuries, prevention of contractures should begin right after acute care has been established. Education for the importance of splinting and exercise should be administered as comprehensible as possible for adult patients and parents of pediatric patients.

Keywords: burn, contracture, education, exercise, splinting

Procedia PDF Downloads 126

Authors: Balakrishna Shetty

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Introduction: Stem Cell Imaging is a challenging field since the advent of Stem Cell treatment in humans. Series of research on tagging and tracking the stem cells has not been very effective. The present study is an effort by the authors to track the stem cells injected into calf muscles by Magnetic Resonance Diffusion Weighted Imaging. Materials and methods: Stem Cell injection deep into the calf muscles of patients with peripheral vascular disease is one of the recent treatment modalities followed in our institution. 5 patients who underwent deep intramuscular injection of stem cells as treatment were included for this study. Pre and two hours Post injection MRI of bilateral calf regions was done using 1.5 T Philips Achieva, 16 channel system using 16 channel torso coils. Axial STIR, Axial Diffusion weighted images with b=0 and b=1000 values with back ground suppression (DWIBS sequence of Philips MR Imaging Systems) were obtained at 5 mm interval covering the entire calf. The invert images were obtained for better visualization. 120ml of autologous bone marrow derived stem cells were processed and enriched under c-GMP conditions and reduced to 40ml solution containing mixture of above stem cells. Approximately 40 to 50 injections, each containing 0.75ml of processed stem cells, was injected with marked grids over the calf region. Around 40 injections, each of 1ml normal saline, is injected into contralateral leg as control. Results: Significant Diffusion hyper intensity is noted at the site of injected stem cells. No hyper intensity noted before the injection and also in the control side where saline was injected conclusion: This is one of the earliest studies in literature showing diffusion hyper intensity in intramuscularly injected stem cells. The advantages and deficiencies in this study will be discussed during the presentation.

Keywords: stem cells, imaging, DWI, peripheral vascular disease

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Authors: Tahani Hallek, Dhaou Akrout, Riadh Ahmadi, Mabrouk Montacer

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The present work is an organic geochemical study of the Fahdene Formation outcrops at the Mahjouba region belonging to the Eastern part of the Kalaat Senan structure in northwestern Tunisia (the Kef-Tedjerouine area). The analytical study of the organic content of the samples collected, allowed us to point out that the Formation in question is characterized by an average to good oil potential. This fossilized organic matter has a mixed origin (type II and III), as indicated by the relatively high values of hydrogen index. This origin is confirmed by the C29 Steranes abundance and also by tricyclic terpanes C19/(C19+C23) and tetracyclic terpanes C24/(C24+C23) ratios, that suggest a marine environment of deposit with high plants contribution. We have demonstrated that the heterogeneity of organic matter between the marine aspect, confirmed by the presence of foraminifera, and the continental contribution, is the result of an episodic anomaly in relation to the sequential stratigraphy. Given that the study area is defined as an outer platform forming a transition zone between a stable continental domain to the south and a deep basin to the north, we have explained the continental contribution by successive forced regressions, having blocked the albian transgression, allowing the installation of the lowstand system tracts. This aspect is represented by the incised valleys filling, in direct contact with the pelagic and deep sea facies. Consequently, the Fahdene Formation, in the Kef-Tedjerouine area, consists of transgressive system tracts (TST) brutally truncated by extras of continental progradation; resulting in a mixed influence deposition having retained a heterogeneous organic material.

Keywords: molecular geochemistry, biomarkers, forced regression, deposit environment, mixed origin, Northern Tunisia

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Authors: Rui Wu

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In the volatile modern manufacturing environment, new orders randomly occur at any time, while the pre-emptive methods are infeasible. This leads to a real-time scheduling method that can produce a reasonably good schedule quickly. The dynamic Flexible Job Shop problem is an NP-hard scheduling problem that hybrid the dynamic Job Shop problem with the Parallel Machine problem. A Flexible Job Shop contains different work centres. Each work centre contains parallel machines that can process certain operations. Many algorithms, such as genetic algorithms or simulated annealing, have been proposed to solve the static Flexible Job Shop problems. However, the time efficiency of these methods is low, and these methods are not feasible in a dynamic scheduling problem. Therefore, a dynamic rule selection scheduling system based on the reinforcement learning method is proposed in this research, in which the dynamic Flexible Job Shop problem is divided into several parallel machine problems to decrease the complexity of the dynamic Flexible Job Shop problem. Firstly, the features of jobs, machines, work centres, and flexible job shops are selected to describe the status of the dynamic Flexible Job Shop problem at each decision point in each work centre. Secondly, a framework of reinforcement learning algorithm using a double-layer deep Q-learning network is applied to select proper composite dispatching rules based on the status of each work centre. Then, based on the selected composite dispatching rule, an available operation is selected from the waiting buffer and assigned to an available machine in each work centre. Finally, the proposed algorithm will be compared with well-known dispatching rules on objectives of mean tardiness, mean flow time, mean waiting time, or mean percentage of waiting time in the real-time Flexible Job Shop problem. The result of the simulations proved that the proposed framework has reasonable performance and time efficiency.

Keywords: dynamic scheduling problem, flexible job shop, dispatching rules, deep reinforcement learning

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Authors: Rona Lee Suelo-Calanao, Mahmoud Loubani

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Objective: Sternal wound infection (SWI) following cardiac operation has a significant impact on patient morbidity and mortality. It also contributes to longer hospital stays and increased treatment costs. SWI management is mainly focused on treatment rather than prevention. This study looks at the effect of closed incision negative pressure therapy (ciNPT) dressing to help reduce the incidence of superficial SWI in high-risk patients after cardiac surgery. The ciNPT dressing was evaluated at 3 cardiac hospitals in the United Kingdom". Methods: All patients who had cardiac surgery from 2013 to 2021 were included in the study. The patients were classed as high risk if they have two or more of the recognised risk factors: obesity, age above 80 years old, diabetes, and chronic obstructive pulmonary disease. Patients receiving standard dressing (SD) and patients using ciNPT were propensity matched, and the Fisher’s exact test (two-tailed) and unpaired T-test were used to analyse categorical and continuous data, respectively. Results: There were 766 matched cases in each group. Total SWI incidences are lower in the ciNPT group compared to the SD group (43 (5.6%) vs 119 (15.5%), P=0.0001). There are fewer deep sternal wound infections (14(1.8%) vs. 31(4.04%), p=0.0149) and fewer superficial infections (29(3.7%) vs. 88 (11.4%), p=0.0001) in the ciNPT group compared to the SD group. However, the ciNPT group showed a longer average length of stay (11.23 ± 13 days versus 9.66 ± 10 days; p=0.0083) and higher mean logistic EuroSCORE (11.143 ± 13 versus 8.094 ± 11; p=0.0001). Conclusion: Utilization of ciNPT as an approach to help reduce the incidence of superficial and deep SWI may be effective in high-risk patients requiring cardiac surgery.

Keywords: closed incision negative pressure therapy, surgical wound infection, cardiac surgery complication, high risk cardiac patients

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Authors: Shailja Thakur

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In this paper it is shown that how farmers are suffering from all sides including vagaries of weather then price fluctuations, demand supply constraints, poor soil health etc. Also the ICT can prove to be of great help if incorporated rightly into Indian agriculture. Some innovative ways to reward farmers and distribution of subsidies to them can improve the current scenario.

Keywords: cost of farming, information and communication technology, innovative steps, roof gardening, vermicomposting

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Authors: Mohammed A. Al-Yafrsi, Fahed A. Al-Mana

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A study was conducted to evaluate the compaction-tolerance ability of some warm season turfgrasses under shade and sunlight conditions in Riyadh, Saudi Arabia. Hybrid bermudagrass (Cynodon dactylon): 'Tifway' and 'Tifsport', seashore paspalum (Paspalum vaginatum) and its cultivar 'Sea Isle 2000' were used. The study area was divided into two sections where one was exposed to sunlight and the other one was maintained under shade using green plastic grille (shade 70%). Turfgrasses were planted by sods in beds containing a mixture of sand, silt, and peat moss (4: 1: 1, v/v). The soil compaction was applied using a locally-made cylindrical roll (weighing 250 kg), passing four times over the growing turfgrasses for 3 days/week. The results revealed that compaction treatment led to a decrease in grass height, and it was the lowest (4.0 cm) for paspalum 'Sea Isle 2000' in February. At the shaded area, paspalum turfgrasses retained its high quality degree (4.0) in April, May, and June. In the sunlight area, the grass quality degree was the greatest (4.0) in 'Sea Isle 2000' and the lowest (3.0) in 'Tifsport'. Paspalum turfgrasses gave higher color degree (4) than bermuda grasses (2.5) in April, May, and June. The compaction also led to a decline in leaf area, fresh and dry weights of all grown turfgrasses. The grass density was high for paspalum turfgrasses indicating that their resistance to compaction was greater than bermudagrasses. It can be concluded that the best compaction and shade tolerant turfgrasses are 'Sea Isle 2000' and seashore paspalum.

Keywords: hybrid bermudagrass, seashore paspalum, soil compaction, shade area, sunlight condition

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Authors: Kamrun N. Keya, Nasrin A. Kona, Ruhul A. Khan

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Sugarcane bagasse (SCB)-reinforced Polypropylene (PP) Based matrix composites (25-45 wt% fiber) were fabricated by a compression molding technique. The SCB surface was chemically modified using 5%-10% sodium hydroxide (NaOH), and after that, mechanical properties, water uptake, and soil degradation of the composites were investigated. Tensile strength (TS), tensile modulus (TM), bending strength (BS), bending modulus (BM) and elongation at break (Eb%) of the 30wt% composites were found to be 35.6 MPa, 10.2 GPa, 56 MPa, 5.6 GPa, and 11%, respectively. The SCB/PP based composites were treated with irradiated under gamma radiation (the source strength 50 kCi Cobalt-60) of various doses (2.5 kGy to 10 kGy). The effect of gamma radiation on the composites was also investigated, and it found that the effect of 5.0 kGy (i.e. units for radiation measurement is 'gray', kGy=kilogray ) gamma dose showed better mechanical properties than other doses. The results revealed that the combination of the chemical modification of the SCB fibers and irradiation of the composites were more effective in compatibility improvement than chemical modification alone. After flexural testing, fracture sides of the untreated and treated both composites were studied by scanning electron microscope (SEM). SEM results of the treated SCB/PP based composites showed better fiber-matrix adhesion than untreated SCB/PP based composites. However, it was found that the treated SCB/PP composite has better mechanical strength, durability, and more receptivity than untreated SCB/PP based composite.

Keywords: sugarcane bagasse (SCB), polypropylene (PP), mechanical properties, scanning electron microscope (SEM), gamma radiation, water uptake tests and soil degradation

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Authors: Medhat Tawfik, Ezzat Abd El Lateef, Bahr Amany, Mohamed Magda

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Applying organic farming systems in biosaline agriculture is unconventional approach for sustainable use of marginal soil and desert land for planting non-traditional halophytic crops such as Leptochloa fusca, Kochia indica, Sporobolus virginicus and Spartina patens. These plants are highly salt tolerant C4 halophytic forage plants grown well in coastal salt marsh. These halophytic plant will take important place in the farming system, especially in the coastal areas and salt-affected land. We can call it environmentally smart crops because they ensure food security, contribute to energy security, guarantee environmental sustainability, and mitigate the negative impacts of climate change. Organic Agriculture is the most important and widely practiced agro-ecological farming system. It is claimed to be the most sustainable approach and long term adaptation strategy. It promotes soil fertility and diversity at all levels and makes soils less susceptible to erosion. It is also reported to be climate change resilience farming systems as it promotes the proper management of soil, water, biodiversity and local knowledge and provides producers with ecologically sound management decisions. A field experiment was carried out at the Model Farm of National Research Centre, El Tour, South Sinai to study the impact of (Mycorrhiza 1kg/fed., charcoal 4 tons/fed., chicken manure 5 tons/fed., in addition to control treatment) on some growth characters, photosynthetic pigments content, and some physiological aspects i.e. prolind and soluble carbohydrates content, succulence and osmotic pressure values, as well as nutritive values i.e. Crude fat (CF), Acid detergent fiber (ADF), Neutral detergent fiber (NDF), Ether extract (EE) and Nitrogen-free extract (NFE) of five halophytic plant species (Leptochloa fusca, Kochia indica, Sporobolus virginicus and Spartina patens). Our results showed that organic fertilizer treatment enhanced all the previous character as compared with control with superiority to chicken manure over the other treatments.

Keywords: organic agriculture, halophytic plants, saline environment, water security

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Authors: Taramani Yadav, Gajender Kumar, R. K. Yadav, H. S. Jat

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Soil Salinity and irrigation water salinity is critical threat to enhance agricultural food production to full fill the demand of billion plus people worldwide. Salt affected soils covers 6.73 Mha in India and ~1000 Mha area around the world. Irrigation scheduling of saline water is the way to ensure food security in salt affected areas. Research experiment was conducted at ICAR-Central Soil Salinity Research Institute, Experimental Farm, Nain, Haryana, India with 36 treatment combinations in double split plot design. Three sets of treatments consisted of (i) three regimes of irrigation viz., 60, 80 and 100% (I1, I2 and I3, respectively) of crop ETc (crop evapotranspiration at identified respective stages) in main plot; (ii) four levels of irrigation water salinity (sub plot treatments) viz., 2, 4, 8 and 12 dS m-1 (iii) applications of two PBRs along with control (without PBRs) i.e. salicylic acid (G1; 1 mM) and thiourea (G2; 500 ppm) as sub-sub plot treatments. Grain yield of wheat (Triticum aestivum) was increased with less amount of high salt loaded irrigation water at the same level of salinity (2 dS m-1), the trend was I3>I2>I1 at 2 dS m-1 with 8.10 and 17.07% increase at 80 and 100% ETc, respectively compared to 60% ETc. But contrary results were obtained by increasing amount of irrigation water at same level of highest salinity (12 dS m-1) showing following trend; I1>I2>I3 at 12 dS m-1 with 9.35 and 12.26% increase at 80 and 60% ETc compared to 100% ETc. Enhancement in grain yield of wheat (Triticum aestivum) is not need to increase amount of irrigation water under saline condition, with salty irrigation water less amount of irrigation water gave the maximum wheat (Triticum aestivum) grain yield.

Keywords: Irrigation Scheduling, Saline Environment, Triticum aestivum, Yield

Procedia PDF Downloads 139

Authors: Katie-Beth Webster

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Mucormycosis is a rare opportunistic fungal infection that, if left untreated, can cause large scale tissue necrosis and death. There are a number of cases of this in the literature, most commonly in the head and neck region arising from sinuses. It is also usually found in immunocompromised patient subgroups. This study reviewed a number of cases of mucormycosis in previously fit and healthy young trauma patients to assess predisposing factors for infection and adequacy of current treatment paradigms. These trauma patients likely contracted the fungal infection from the soil at the site of the incident. Despite early washout and debridement of the wounds at the scene of the injury and on arrival in hospital, both these patients contracted mucormycosis. It was suspected that inadequate early debridement of soil contaminated limbs was one of the major factors that can lead to catastrophic tissue necrosis. In both cases, this resulted in the patients having a higher level of amputation than would have initially been required based on the level of their injury. This was secondary to cutaneous and soft tissue necrosis secondary to the fungal infiltration leading to osteomyelitis and systemic sepsis. In the literature, it appears diagnosis is often protracted in this condition secondary to inadequate early treatment and long processing times for fungal cultures. If fungal cultures were sent at the time of first assessment and adequate debridements are performed aggressively early, it could lead to these critically unwell trauma patients receiving appropriate antifungal and surgical treatment earlier in their episode of care. This is likely to improve long term outcomes for these patients.

Keywords: mucormycosis, plastic surgery, osteomyelitis, trauma

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Authors: Rajinder Kumar Gupta, Rajni Kant Agrawal, Jaganniwas

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One of the most frightening phenomena of nature is the occurrence of earthquake as it has terrible and disastrous effects. Many earthquakes occur every day worldwide. There is need to have knowledge regarding the trends in earthquake occurrence worldwide. The recoding and interpretation of data obtained from the establishment of the worldwide system of seismological stations made this possible. From the analysis of recorded earthquake data, the earthquake parameters and source parameters can be computed and the earthquake catalogues can be prepared. These catalogues provide information on origin, time, epicenter locations (in term of latitude and longitudes) focal depths, magnitude and other related details of the recorded earthquakes. Theses catalogues are used for seismic hazard estimation. Manual interpretation and analysis of these data is tedious and time consuming. A geographical information system is a computer based system designed to store, analyzes and display geographic information. The implementation of integrated GIS technology provides an approach which permits rapid evaluation of complex inventor database under a variety of earthquake scenario and allows the user to interactively view results almost immediately. GIS technology provides a powerful tool for displaying outputs and permit to users to see graphical distribution of impacts of different earthquake scenarios and assumptions. An endeavor has been made in present study to compile the earthquake data for the whole world in visual Basic on ARC GIS Plate form so that it can be used easily for further analysis to be carried out by earthquake engineers. The basic data on time of occurrence, location and size of earthquake has been compiled for further querying based on various parameters. A preliminary analysis tool is also provided in the user interface to interpret the earthquake recurrence in region. The user interface also includes the seismic hazard information already worked out under GHSAP program. The seismic hazard in terms of probability of exceedance in definite return periods is provided for the world. The seismic zones of the Indian region are included in the user interface from IS 1893-2002 code on earthquake resistant design of buildings. The City wise satellite images has been inserted in Map and based on actual data the following information could be extracted in real time: • Analysis of soil parameters and its effect • Microzonation information • Seismic hazard and strong ground motion • Soil liquefaction and its effect in surrounding area • Impacts of liquefaction on buildings and infrastructure • Occurrence of earthquake in future and effect on existing soil • Propagation of earth vibration due of occurrence of Earthquake GIS based earthquake information system has been prepared for whole world in Visual Basic on ARC GIS Plate form and further extended micro level based on actual soil parameters. Individual tools has been developed for liquefaction, earthquake frequency etc. All information could be used for development of infrastructure i.e. multi story structure, Irrigation Dam & Its components, Hydro-power etc in real time for present and future.

Keywords: GIS based earthquake information system, microzonation, analysis and real time information about liquefaction, infrastructure development

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Authors: Paballo M. Moshupya, Tamiru A. Abiye, Ian Korir

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Mining and processing of naturally occurring radioactive materials could result in elevated levels of natural radionuclides in the environment. The aim of this study was to evaluate the radioactivity levels on a large scale in the West Rand District in South Africa, which is dominated by abandoned gold mine tailings and the consequential radiological exposures to members of the public. The activity concentrations of ²³⁸U, ²³²Th and 40K in mine tailings, soil and rocks were assessed using the BGO Super-Spec (RS-230) gamma spectrometer. The measured activity concentrations for ²³⁸U, ²³²Th and 40K in the studied mine tailings were found to range from 209.95 to 2578.68 Bq/kg, 19.49 to 108.00 Bq/kg and 31.30 to 626.00 Bq/kg, respectively. In surface soils, the overall average activity concentrations were found to be 59.15 Bq/kg, 34.91 and 245.64 Bq/kg for 238U, ²³²Th and 40K, respectively. For the rock samples analyzed, the mean activity concentrations were 32.97 Bq/kg, 32.26 Bq/kg and 351.52 Bg/kg for ²³⁸U, ²³²Th and 40K, respectively. High radioactivity levels were found in mine tailings, with ²³⁸U contributing significantly to the overall activity concentration. The external gamma radiation received from surface soil in the area is generally low, with an average of 0.07 mSv/y. The highest annual effective doses were estimated from the tailings dams and the levels varied between 0.14 mSv/y and 1.09 mSv/y, with an average of 0.51 mSv/y. In certain locations, the recommended dose constraint of 0.25 mSv/y from a single source to the average member of the public within the exposed population was exceeded, indicating the need for further monitoring and regulatory control measures specific to these areas to ensure the protection of resident members of the public.

Keywords: activity concentration, gold mine tailings, in-situ gamma spectrometry, radiological exposures

Procedia PDF Downloads 122

Authors: Samaneh Yavari, Christiane Pferrer, Elisabeth Engelke, Alexander Starke, Juergen Rehage

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Background: Nowadays, bovine limb interventions, especially any claw surgeries, raises selection of the most qualified and appropriate local anesthesia technique applicable for any superficial or deep interventions of the limbs. Currently, two local anesthesia methods of Intravenous Regional Anesthesia (IVRA), as well as Nerve Blocks, have been routine to apply. However, the lack of studies investigating the quality and duration as well as quantity and onset of full (complete) local anesthesia, is noticeable. Therefore, the aim of our study was comparing the onset and quality of both IVRA and our modified NBA at the hind limb of dairy cows. For this abstract, only the onset of full local anesthesia would be consider. Materials and Methods: For that reason, we used six healthy non pregnant non lactating Holestein Frisian cows in a cross-over study design. Those cows divided into two groups to receive IVRA and our modified four-point NBA. For IVRA, 20 ml procaine without epinephrine was injected into the vein digitalis dorsalis communis III and for our modified four-point NBA, 10-15 ml procaine without epinephrine preneurally to the nerves, superficial and deep peroneal as well as lateral and medial branches of metatarsal nerves. For pain stimulation, electrical stimulator Grass S48 was applied. Results: The results of electrical stimuli revealed the faster onset of full local anesthesia (p < 0.05) by application of our modified NBA in comparison to IVRA about 10 minutes. Conclusion and discussion: Despite of available references showing faster onset of foot local anesthesia of IVRA, our study demonstrated that our modified four point NBA not only can be well known as a standard foot local anesthesia method applicable to desensitize the hind limb of dairy cows, but also, selection of this modified validated local anesthesia method can lead to have a faster start of complete desensitization of distal hind limb that is remarkable in any bovine limb interventions under time constraint.

Keywords: IVRA, four point NBA, dairy cow, hind limb, full onset

Procedia PDF Downloads 148