scholarly journals Prediction and Remediation of Groundwater Pollution in a Dynamic and Complex Hydrologic Environment of an Illegal Waste Dumping Site

2021 ◽  
Vol 11 (19) ◽  
pp. 9229
Author(s):  
Thatthep Pongritsakda ◽  
Kengo Nakamura ◽  
Jiajie Wang ◽  
Noriaki Watanabe ◽  
Takeshi Komai
Keyword(s):  
Groundwater Pollution ◽  
Numerical Study ◽  
Pollutant Transport ◽  
Pollutant Removal ◽  
Complex Nature ◽  
Multiple Sources ◽  
Dumping Site ◽  
Naturally Occurring ◽  
Concentration Changes ◽  
Illegal Waste

The characteristics of groundwater pollution caused by illegal waste dumping and methods for predicting and remediating it are still poorly understood. Serious 1,4-dioxane groundwater pollution—which has multiple sources—has been occurring at an illegal waste dumping site in the Tohoku region of Japan. So far, anti-pollution countermeasures have been taken including the installation of an impermeable wall and the excavation of soils and waste as well as the monitoring of contamination concentrations. The objective of this numerical study was to clarify the possibility of predicting pollutant transport in such dynamic and complex hydrologic environments, and to investigate the characteristics of pollutant transport under both naturally occurring and artificially induced groundwater flow (i.e., pumping for remediation). We first tried to reproduce the changes in 1,4-dioxane concentrations in groundwater observed in monitoring wells using a quasi-3D flow and transport simulation considering the multiple sources and spatiotemporal changes in hydrologic conditions. Consequently, we were able to reproduce the long-term trends of concentration changes in each monitoring well. With the predicted pollutant distribution, we conducted simulations for remediation such as pollutant removal using pumping wells. The results of the prediction and remediation simulations revealed the highly complex nature of 1,4-dioxane transport in the dumping site under both naturally occurring and artificially induced groundwater flows. The present study suggests possibilities for the prediction and remediation of pollution at illegal waste dumping sites, but further extensive studies are encouraged for better prediction and remediation.

The Entextualization of Ayurveda as Intellectual Property

2012 ◽  
Vol 19 (3) ◽  
pp. 313-343 ◽  
Author(s):  
Matthew Wolfgram
Keyword(s):  
Intellectual Property ◽  
Global Economy ◽  
Medical Knowledge ◽  
Linguistic Anthropology ◽  
Medical Discourse ◽  
Complex Nature ◽  
Multiple Sources ◽  
The Social ◽  
Rights Discourse ◽  
The Individual

AbstractThis article documents the practices of pharmaceutical creativity in Ayurveda, focusing in particular on how practitioners appropriate multiple sources to innovate medical knowledge. Drawing on research in linguistic anthropology on the social circulation of discourse—a process calledentextualization—I describe how the ways in which Ayurveda practitioners innovate medical knowledge confounds the dichotomous logic of intellectual property (IP) rights discourse, which opposes traditional collective knowledge and modern individual innovation. While it is clear that these categories do not comprehend the complex nature of creativity in Ayurveda, I also use the concept of entextualization to describe how recent historical shifts in the circulation of discourse have caused a partial entailment of this opposition between the individual and the collectivity. Ultimately, I argue that the method exemplified in this article of tracking the social circulation of medical discourse highlights both the empirical complexity of so-called traditional creativity, and the politics of imposing the categories of IP rights discourse upon that creativity, situated as it often is, at the margins of the global economy.

scholarly journals Evaluation of serum MMP-2 and MMP-3, synovial fluid IL-8, MCP-1, and KC concentrations as biomarkers of stifle osteoarthritis associated with naturally occurring cranial cruciate ligament rupture in dogs

PLoS ONE ◽  
2020 ◽  
Vol 15 (11) ◽  
pp. e0242614
Author(s):  
Sarah Malek ◽  
Hsin-Yi Weng ◽  
Shannon A. Martinson ◽  
Mark C. Rochat ◽  
Romain Béraud ◽  
...  
Keyword(s):  
Synovial Fluid ◽  
Linear Regression ◽  
Cruciate Ligament ◽  
Discriminative Ability ◽  
Cranial Cruciate Ligament ◽  
Discriminative Performance ◽  
Naturally Occurring ◽  
Veterinary Pathologist ◽  
Concentration Changes ◽  
And Control

The purpose of this study was to evaluate matrix metalloproteinases (MMP) -2 and MMP-3 in serum, and keratinocyte-derived chemoattractant (KC), interleukin 8 (IL-8) and monocyte chemoattractant 1 (MCP-1) in synovial fluid (SF) as stifle osteoarthritis (OA) biomarkers in dogs. Dogs with naturally occurring cranial cruciate ligament (CrCL) rupture (OA group) and healthy controls were recruited. Stifles with CrCL deficiency were surgically stabilized. Serum, SF, and synovial biopsy samples were collected from the OA group preoperatively, whereas samples were collected once from control dogs. A blinded veterinary pathologist graded synovial biopsies. Serum and SF analyses were performed using xMAP technology. General linear regression was used for statistical comparisons of serum biomarkers, and mixed linear regression for SF biomarkers and temporal concentration changes. The overall discriminative ability was quantified using area under curve (AUC). Spearman’s correlation coefficient was used to assess correlations between synovial histology grades and the biomarkers. Samples from 62 dogs in the OA group and 50 controls were included. The MMP-2 and MMP-3 concentrations between the OA and control groups were not significantly different, and both with an AUC indicating a poor discriminative ability. All three SF biomarker concentrations were significantly different between the OA group and controls (P <0.05). The MCP-1 was the only biomarker showing an acceptable discriminative performance with an AUC of 0.91 (95% confidence interval: 0.83–0.98). The sum of the inflammatory infiltrate score was significantly correlated with all three SF biomarkers (P <0.01). Summed synovial stroma, and all scores combined were significantly correlated with IL-8 and MCP-1 concentrations (P <0.003), and the summed synoviocyte scores were significantly correlated with MCP-1 concentrations (P <0.001). Correlations between MCP-1 concentrations and synovial histopathologic grading and its discriminative ability suggest its potential as a synovitis biomarker in canine stifle OA associated with CrCL rupture.

Quantifying Discrete Seismic Responses to Mining

2020 ◽  
Author(s):  
Laura G Brown
Keyword(s):  
Sensor Array ◽  
Underground Mining ◽  
Complex Nature ◽  
Seismic Responses ◽  
Mining Operations ◽  
Analysis Techniques ◽  
Naturally Occurring ◽  
Single Link ◽  
Rock Mass Failure ◽  
Temporal Windows

Applying analysis techniques developed for naturally occurring earthquakes to mine seismicity is common practice, however, these methodologies rarely consider the influence of blasting on the dynamic rock mass failure processes observed in mines. Due to the complex nature of bulk orebody extraction at depth, quantifying discrete seismic responses to mining can be challenging. This paper identifies seismic responses to mining by pairing single-link clustering with finite temporal windows bound by mine blasting practices. A methodology is presented to quantify the space-time characteristics of these responses using four Seismic Response Parameters (SRP’s): Distance to Blast, Distance to Centroid, Time After Blast and Time Between Events. Using SRP’s, seismic responses to mining can be quantitatively classified as induced, complex or triggered (with respect to discrete mine blasting). Because these response parameters do not require an extensive and/or triaxial dense sensor array, they are applicable to a variety of underground mining operations. In this work, SRP’s are applied to 189 discrete seismic responses occurring over two months of active mining, and a two week shutdown period, at Agnico Eagle’s LaRonde Mine.

Prediction of Heart Disease Using Random Forest and Rough Set Based Feature Selection

2018 ◽  
Vol 3 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Indu Yekkala ◽  
Sunanda Dixit
Keyword(s):  
Feature Selection ◽  
Heart Disease ◽  
Random Forest ◽  
Causes Of Death ◽  
Electronic Records ◽  
Complex Nature ◽  
Random Forest Algorithm ◽  
Multiple Sources ◽  
Artery Disease ◽  
Single Data

Data is generated by the medical industry. Often this data is of very complex nature—electronic records, handwritten scripts, etc.—since it is generated from multiple sources. Due to the Complexity and sheer volume of this data necessitates techniques that can extract insight from this data in a quick and efficient way. These insights not only diagnose the diseases but also predict and can prevent disease. One such use of these techniques is cardiovascular diseases. Heart disease or coronary artery disease (CAD) is one of the major causes of death all over the world. Comprehensive research using single data mining techniques have not resulted in an acceptable accuracy. Further research is being carried out on the effectiveness of hybridizing more than one technique for increasing accuracy in the diagnosis of heart disease. In this article, the authors worked on heart stalog dataset collected from the UCI repository, used the Random Forest algorithm and Feature Selection using rough sets to accurately predict the occurrence of heart disease

Performing Effective Drug Delivery and Hyperthermia Based on Biological and Treatment Parameters: A Comprehensive Eulerian-Lagrangian Approach

2016 ◽  
Vol 13 (10) ◽  
pp. 6628-6641 ◽  
Author(s):  
Reza Roohi ◽  
Homayoun Emdad ◽  
Khosrow Jafarpur
Keyword(s):  
Treatment Process ◽  
Numerical Study ◽  
Numerical Data ◽  
Complex Nature ◽  
Second Phase ◽  
Hyperthermia Treatment ◽  
Zone Formation ◽  
Energy Equations ◽  
Thermal Phenomena ◽  
Alternating Magnetic Fields

The complex nature of involved biomechanical/thermal phenomena, clearly highlights the necessity of a comprehensive numerical modeling of the treatment process. The present numerical study is performed in two main phases: first the magnetic nanoparticles distribution is calculated throughout the cancerous tissue by application of Eulerian-Lagrangian method. To simulate the bio-system behavior as realistic as possible several parameters and phenomena are numerically modeled such as: Lorentz and Magnetization forces, non-Newtonian blood behavior, tissue multi-zone formation, capillary vessels blood delivery, lymphatic blood drainage and dominant actuating forces for the particles movement. In the second phase, two coupled energy equations for blood and tissues are solved numerically to determine the temperature distribution in the presence of an external alternating magnetic field (AMF). The effect of several parameters including flow Re number, strength of static and alternating magnetic fields are investigated, as well. Based on the obtained numerical data, there exists an optimum Mn number to maximize the deposition percentage for various simulated Re number, in addition to the fact that hyperthermia treatment is more feasible and practical for tissues with high Re number.

Natural Convection in Shallow, Horizontal Air Layers Encountered in Electronic Cooling

1995 ◽  
Vol 117 (4) ◽  
pp. 307-316 ◽  
Author(s):  
Elias Papanicolaou ◽  
Sridhar Gopalakrishna
Keyword(s):  
Heat Transfer ◽  
Natural Convection ◽  
Aspect Ratio ◽  
Numerical Study ◽  
Constant Heat Flux ◽  
Bottom Surface ◽  
Multiple Sources ◽  
Critical Dimensions ◽  
Convection Regime ◽  
Air Layers

A numerical study of natural convection induced in a horizontal, enclosed air layer due to a discrete, constant heat flux source at the bottom surface is carried out in this paper. The nature of the transition from conduction to a cellular convection regime for this discrete-heating case is characterized. Multiple sources are also considered and the results are compared to those for a single source. The governing equations of continuity, momentum, and energy conservation are formulated for a two-dimensional layer. The important parameters are the overall aspect ratio (length/height of the layer), the ratio of source length to total length, and the Rayleigh number. The effect of varying these parameters is investigated, and heat transfer correlations are derived, for both single and multiple sources, in the form Nus ∝ C (Ra)c>, where Nus is the Nusselt number averaged over each source. The value of C is found to depend strongly on the aspect ratio and the source size. Based on the heat transfer results, the tendency of each geometric configuration to fully attain transition to the convection regime is evaluated. This can provide guidelines for maintaining certain critical dimensions that best exploit natural convection effects, in systems where fan-driven cooling is not available.

scholarly journals Arsenic and other heavy metals in the rivers of central Nepal

1970 ◽  
Vol 31 ◽  
pp. 11-18 ◽  
Author(s):  
Steven H Emerman
Keyword(s):  
Heavy Metals ◽  
Kathmandu Valley ◽  
Bed Sediment ◽  
Multiple Sources ◽  
Central Nepal ◽  
Naturally Occurring ◽  
River Bed ◽  
Organic Complexation ◽  
Positively Charged ◽  
River Bed Sediment

The objective of this study was to measure fluvial As, Co, Cu, Fe, and Zn in order to determine whether central Nepal has a geographically-limited source of As. Seventeen rivers in central Nepal outside and eight rivers inside the heavily polluted Kathmandu valley were sampled monthly for six months. Outside the Kathmandu valley, fluvial As (11 ± 1 mg/l), Co (110 ± 30 mg/l), Cu (93 ± 4 mg/l), Fe (550 ± 80 mg/l), and Ni (50 ± 3 mg/l) were over 5, 550, 13, and 13 times the global averages for each respective element, while Zn (27 ± 4 mg/l) was very close to the global average. The only statistically significant differences between inside and outside the Kathmandu valley were pH (inside: 7.13 ± 0.06, outside: 8.13 ± 0.06), Fe (inside: 1060 ± 90 mg/l) and Cu (inside: 70 ± 10 mg/l) so that Co, Cu, Ni, and Zn levels inside the Kathmandu valley were all naturally occurring. Fluvial As was correlated both in space and time with pH. Outside the Kathmandu valley, fluvial As decreased when pH decreased, due to the increase in the number of positively-charged sorption sites on river bed sediment. Inside the polluted Kathmandu valley, fluvial As increased when pH decreased, due to the organic complexation of As and the negative correlation between organic matter and pH. Central Nepal has multiple sources of As associated with mineralisation of Co, Cu, Fe, and Ni, but not Pb-Zn.

Sign in / Sign up

Export Citation Format

Share Document