THE EFFECTS OF CHEMICAL HAZARDS IN SUSTAINABLE DEVELOPMENT OF AGRICULTURE USING FUZZY ASSOCIATIVE MEMORIES (FAM)
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The concept of Sustainable development based on an integrated view of environmental policies and development strategies intends to minimize the risks and hazards to the environment. The time has come for efforts to be made on the environmental front towards sustainable development without endangering the ecological assets of the future generation. In this paper we analyze the effects of health hazards in sustainable development of agriculture using Fuzzy Associative Memories (FAM). We arrive at the conclusions by this study how sustainable development is being affected by the pollutions.This paper has four sections. In section one we recall the notion of Fuzzy Associative Memories (FAM) and its properties. In section two we describe the problem. In Section three we adopt FAM to this problem and analyze the problem. Section four gives the conclusions based on our study.
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This document summarizes a research paper on identifying factors related to the adoption of green manufacturing practices among small and medium enterprises (SMEs) in India. It discusses how analytic hierarchy process was used to validate scales for measuring identified factors. The research established that green manufacturing relates to green product design, raw materials, processes, technology, packaging and packaging design. It also reviews prior literature on green manufacturing, identifying gaps such as a lack of empirical studies conducted in India.
Social
Waste management is important from both technical and social perspectives. Effective waste management programs can provide many socio-economic benefits like cheaper products, economic gains from salvaging waste materials, job creation, and a cleaner environment. From a systems viewpoint, waste minimization is complementary to resource management. The paper discusses the key elements of waste management like generation, reduction, collection, recycling and disposal. It emphasizes that professionals should adopt a broader systems approach to waste management to minimize waste and maximize utilization of resources for sustainable development.
A Systemic Approach To Addressing The Complexity Of Energy Problems
A systemic approach is needed to address the complexity of energy problems in a holistic way. Viewing energy only through technical and objective lenses fails to consider important social and cultural factors. A systemic approach views energy development through objective, subjective and intersubjective frameworks. Objectively, it considers the technical aspects of energy interventions. Subjectively, it examines how people perceive development and energy, and how factors like gender and power relations influence outcomes. Intersubjectively, it aims to create mutual understanding between these perspectives through participatory processes. This holistic approach is needed to ensure energy provision improves lives sustainably by accounting for the interconnected social, political, economic and environmental system.
1.1 environmental value systems notes
The document provides an overview of environmental value systems (EVS) and concepts in environmental systems and societies. It discusses how historical events have influenced the development of EVSs and environmental movements. There is a wide spectrum of EVSs from ecocentric to anthropocentric to technocentric. Ecocentric views prioritize nature, education, and self-sufficiency while technocentric views emphasize technological solutions and economic growth to address environmental issues. People's EVS shapes how they perceive and evaluate environmental issues based on cultural, religious, economic and sociopolitical contexts.
Dissertation for Dr. Mike D'Gatlwakdit
This document is a dissertation submitted by Gatluak Miak Deng to Cavendish University in partial fulfillment of a Bachelor's degree in Environmental Health Science. The dissertation examines the impact of solid waste management on disease prevalence in Nakawa Division, Kampala City. It provides background on solid waste management challenges due to urbanization and population growth. The study aims to investigate why disease prevalence has increased despite solid waste management policies being in place. The dissertation will analyze the relationship between implementation of solid waste management policies and reported cases of malaria and diarrhea. It will make recommendations on improving policy implementation and waste management.
A meta-analysis: Risk through Wald versus Laplace perspective in hydrop...
Report from a personal project in the course of Water, Food, and Energy Security at Uppsala University. The project aims to evaluate the role of small methodology choices on the output of bigger evaluation of water project. The project takes into consideration a small literature review and at a simple Montecarlo experiment. While, due to time and resource limitation, I suggest caution on the use of the results of this work I consider the topic of really high interest. In the appendix of the work is possible to find the code that I have written for this specific project.
A Case Study Of Sustainable Urban Planning Principles In Curitiba (Brazil) An...
This document presents a case study comparing principles of sustainable urban planning in Curitiba, Brazil and their applicability in Shiraz, Iran. It analyzes how Curitiba has implemented sustainability strategies since the 1960s through integrated approaches combining decision making, education, transportation, public welfare, heritage conservation, and waste management. While every urban context has unique opportunities and constraints, the study argues many lessons can be learned from Curitiba's success that could apply to improving sustainability in Shiraz if adapted appropriately to its local conditions.
Depression Detection in Tweets using Logistic Regression Model
In the growing world of modernization, mental health issues like depression, anxiety and stress are very normal among people and social media like Facebook, Instagram and Twitter have boosted the growth of such mental health. Everything has its legitimacy and negative mark. During this pandemic, people are more likely to suffer from mental health issues, they are available 24 7 and are cut off from the real world. Past examinations have shown that individuals who invest more energy via online media are bound to be depressed. In this project, we find out people who are depressed based on their tweets, followers, following and many other factors. For this, I have trained and tested our text classifier, which will distinguish between the user who is depressed or not depressed. Rahul Kumar Sharma | Vijayakumar A "Depression Detection in Tweets using Logistic Regression Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd41284.pdf Paper URL: https://www.ijtsrd.comcomputer-science/data-miining/41284/depression-detection-in-tweets-using-logistic-regression-model/rahul-kumar-sharma
9 prashant kumar astalin final paper_54-62
This study examines the relationship between environmental awareness and awareness of social duty among higher secondary students, and how certain educational factors affect these levels of awareness. The researcher administered surveys to 608 students to measure their environmental awareness and awareness of social duty. Statistical analysis found a positive relationship between the two awareness levels. Specifically, awareness of social duty accounted for 35.3% of students' environmental awareness scores. Certain educational factors like grade level, field of study, type of school, and parents' education level accounted for 41% of students' environmental awareness when considered alongside their social duty awareness scores. The study aims to predict environmental awareness based on social duty awareness and these educational characteristics.
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SPSS: An Effective Tool to Compute Learning Outcomes in Acadamics
OBJECTIVES: To determine how SPSS can be a useful tool to evaluate Course Learning Outcomes and analyze student's performance with the help of KS test, histogram and skewness of the tool. It is also contributing to facilitate Deep learning amongst students with the help of achievement of normal distribution of grades. METHODS: Comparative analysis is done using course specification, syllabus, assessment method(Final Exam Question paper is taken as tool) and result statistics for the course of STATISTICAL PROGRAMMING (217 CSM), 3rd year (level 5 course) that is part of BCS curriculum in department of Computer Science, College of computer Science in King Khalid University. Teaching strategies are compared for two years. i.e; 2013 and 2014. Moreover the research inferences the relevance of application of NCAAA standards in meeting Learning outcomes of any module for department of Computer Science, CCS, KKU. RESULTS: Comparison of question papers depict that now students are motivated to have deep learning in terms of understanding, solving, reasoning based questions as contrast to shallow learning (memorized questions) in the past. It is indeed improving Learning domains too (Knowledge, Cognitive, Interpersonal and Communication skills) more effectively than in the past. Also grade distribution is Normal with well-defined curve for 2014 as compared to 2013 having variation in Standard deviation too. Teacher centered learning lead to surface learning. After NCAA standards implementation, there is more focus on learned centered teaching. Design of learning assessments is in such a way that it should meet learning outcomes successfully. CONCLUSIONS: The research is contributing in flourishing the personality of the students to produce qualified graduates with excellence in communication, logically and technically capable enough to share their knowledge nationally and internationally with much more confidence at any platform. Also it is opening door for researchers to evaluate their performance with the help of SPSS in academics or anywhere where we want to gather.
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining Approach
Detection of software bugs and its occurrences, repudiation and its root cause is a very difficult process in large multi threaded applications. It is a must for a software developer or software organization to identify bugs in their applications and to remove or overcome them. The application should be protected from malfunctioning. Many of the compilers and Integrated Development Environments are effectively identifying errors and bugs in applications while running or compiling, but they fail in detecting actual cause for the bugs in the running applications. The developer has to reframe or recreate the package with the new one without bugs. It is time consuming and effort is wasted in Software Development Life Cycle. There is a possibility to use graph mining techniques in detecting software bugs. But there are many problems in using graph mining techniques. Managing large graph data, processing nodes with links and processing subgraphs are the problems to be faced in graph mining approach. This paper presents a novel algorithm named BugLoc which is capable of detecting bugs from the multi threaded software application. The BugLoc uses object template to store graph data which reduces graph management complexities. It also uses substring analysis method in detecting frequent subgraphs. The BugLoc then analyses frequent subgraphs to detect exact location of the software bugs. The experimental results show that the algorithm is very efficient, accurate and scalable for large graph dataset.
Motion Object Detection Using BGS Technique
The detection of moving object is an important in many applications such as a vehicle identification in a traffic monitoring system,human detection in a crime branch.In this paper we identify a vehicle in a video sequence.This paper briefly explain the detection of moving vehicle in a video.We introduce a new algorithm BGS for idntifying vehicle in a video sequence. First, we differentiate the foreground from background in frames by learning the background. Then, the image is divided into many small nonoverlapped frames. The candidates of the vehicle part can be found from the frames if there is some change in gray level between the current image and the background. The extracted background subtraction method is used in subsequent analysis to detect a vehicle and classify moving vehicle.
Analysis of Women Harassment in Villages Using CETD Matrix Modal
It is commonly understood that misbehavior intends to upset .Law says , the repeated intentional misbehavior towards women is an offensive. The main concept of this paper can find something interesting that will make us reflect on what is done by women’s rights and gender equality. To solve such problem, in this paper we are interested to adopt CETD matrix.
Solving Assignment Problem Using L-R Fuzzy Numbers
In this paper we determine a new method to solving assignment problem using L-R fuzzy parameters. This method requires finding out the minimal cost reach optimality compared to the existing methods available in the literature. Numerical examples show that the fuzzy assignment ranking method offers an effective way for handling the fuzzy assignment problem.
Fuzzy Chroamtic Number of Line Graph using α-Cuts
In this paper, we introduce chromatic number of line graph using α-cuts. The concept of chromatic number of fuzzy graphs was introduced by Munoz et.al, later Eslahchi and onagh. They are defined by the fuzzy chromatic number of complete graphs (kn), cycle graph (cn), star graph (sn), wheel graph (wn), and line graph are found and results are summarized.
A Study on the Exposures of Rag- Pickers Using Induced Neutrosophic Cognitive...
In this paper, using a new Fuzzy bimodal called Induced Neutrosophic Cognitive Relational Maps (INCRM) we analyse the Socio-Economic problem faced by Rag-Pickers. Based on the study, conclusions and some remedial measures are stated.
Dual Trapezoidal Fuzzy Number and its Applications
In this Paper, we introduce Convergence of α-Cut. We define at Which point the α-Cut converges to the fuzzy numbers and it will be illustrated by example using dual trapezoidal fuzzy number and some mensuration problems are illustrated with approximated values.
Developing and Porting multi-grid solver for CFD application on Intel-MIC pla...
This paper presents an implementation of one dimensional Burgers equation using implicit method with Intel Xeon Phi Coprocessor. In particular, we used MAGMA MIC library which is an open source high performance library for solving a systems of non-linear equations. Further for high performance computation we consider offload mode as the primary mode of operation for Intel Xeon phi coprocessor. The result obtained from implicit scheme is then compared with the exact values and it’s seen that the results obtained are approximate and reliable. The result table showed that the proposed scheme achieved higher performance on Intel MIC platform.
Saturation Index of π(D(r,s))
Adin and Roichman [1] introduced the concept of permutation graphs and Peter Keevash, Po-Shen Loh and Benny Sudakov [2] identified some permutation graphs with maximum number of edges. Ryuhei Uehara, Gabriel Valiente, discussed on Linear structure of Bipartite Permutation Graphs and the Longest Path Problem [3]. If i, j belongs to a permutation on p symbols {1, 2, …, p} and i is less than j then there is an edge between i and j in the permutation graph if i appears after j in the sequence of permutation. So the line of i crosses the line of j in the permutation. Hence there is a one to one correspondence between crossing of lines in the permutation and the edges of the corresponding permutation graph. In this paper we found the conditions for a permutation to realize a double star and comprehend the algorithm to determine the satuation index of the permutation. AMS Subject Classification (2010): 05C35, 05C69, 20B30.
Classification and Prediction of Heart Disease from Diabetes Patients using H...
The multi-factorial chronicle, severe disease among human is diabetes. As a result of abnormal level of glucose in body leads to heart attack, kidney disease, renal failure, Hyperglycemia and also cancer in organs like liver and pancreas. Many studies have been proved that several types of heart diseases are possible in diabetic patients having a high blood sugar. Many approaches were proposed to diagnose both Diabetes and heart diseases. Most of the diabetes people can also have heart diseases called as Diabetic Cardiomyopathy. The earliest manifestation of diabetic cardiomyopathy is needed certain processes. The objective of the study is to examine the association of heart disease and diabetes. The relationship between diabetes and cardiovascular diseases are examined by taking into account of age, sex and associated diabetic and cardiovascular risk factors. The data are collected from patients with diabetes. From these data, features are selected by ant colony optimization and those selected features are given to hybrid PSO-LIBSVM to classify abnormal and normal data. This performance is evaluated using performance metrics and proved this classifiers efficiency for detection of Diabetic Cardiomyopathy.
Format Preserving Encryption for Small Domain
Cryptography is important in communicating secured information that is vulnerable to distortion. The main goal of this paper is encrypting the small arbitrary length data without any changes in the length and data type. We propose a flexible arbitrary length small domain block cipher (FPESD). FPESD is based on AES Algorithm. The resulting cipher text is the same as input plaintext. Here, we use Galois finite field GF (28) and format preserving key to implement FPE. For decryption format preserving key is used along with cipher text and secret key.
Intuitionistic Double Layered Fuzzy Graph and its Cartesian Product Vertex De...
The intuitionistic double layered fuzzy graph gives a 3-D structural view to a fuzzy graph. To find the cartesian product of two intuitionistic double layered fuzzy graphsis a challenging one. In this paper under some condition,a simple method to find the vertex degree of cartesian product of two IDLFG without the cartesianproduct structure is given.
Clustering and Classification in Support of Climatology to mine Weather Data ...
Knowledge of climate data of region is essential for business, society, agriculture, pollution and energy applications. Climate is not fixed, the fluctuation in the climate can be seen from year to year.The data mining application help meteorological scientists to predictaccurate weather forecast and decisions and also provide more performance and reliability than any other methods. The data mining techniques applied on weather data are efficient when compare to the mathematical models used. Various techniques of data mining are applied on climate data to support weather forecasting, climate scientists, agriculture, vegetation, water resources and tourism. The aim of this paper is to provide a review report on various data mining techniques applied on weather data set in support of weather prediction and climate analysis.
Test Suite Reduction Based on Fault Detection with Cost Optimization
Test Suite Reduction is an optimization technique to identify the minimally sized subset of test cases with enforced constraints involved. The main purpose of test suite reduction is to deduce increased number of test cases that in turn increase the time and cost involved in execution. Fault Detection is the method of identifying the faults that affect the outcome of the system either logically or syntactically. This paper focuses on the reduction of the test suite that has high fault identification rates and also incurs low cost of execution of test cases. The proposed approach includes a new parameter Fault Detection Effectiveness to identify fault rates of test suite; an algorithm for test suite reduction based on priority of requirements; a low cost framework to identify the execution of test cases with minimum budget. Thus, the proposed work defines a test suite that has high fault detection effectiveness providing maximum coverage to requirements at minimum cost of execution.
Artifact Facet Ranking and It’s Applications
As the e-commerce is gaining popularity various customer surveys of objects are currently accessible on the Internet. These surveys are frequently disordered, prompting challenges in knowledge discovery and object assessment. This article proposes an object feature positioning skeleton, which consequently recognizes the critical features of an object from online customer surveys. The critical object features are recognized focused around two perceptions: 1) they are normally commented extensively by customers and 2) customer suppositions on the critical feature significantly impact their general assessments on the object. Specifically, given the customer surveys of an item, we first extract the object feature by a shallow reliance parser and focus customer suppositions on these features through an opinion characterizer. We then create a probabilistic object feature positioning calculation to identify the criticalness of perspectives by at the same time considering feature recurrence and the impact of customer opinion given to every feature over their general opinion. The experimental results on 3 popular products demonstrate the effectiveness of our approach.
Effectual Data Integrity Checking Technique Based on Number Theory
Cloud Computing makes data really mobile and a client can simply access a chosen cloud with any internet accessible device. The espousal and dispersion of Cloud computing are threatened by unresolved security issues that affect both the cloud provider and the cloud user. The integrity of data stored in the cloud is one of the challenges to be addressed before the novel storage model is applied widely. This paper analyses the efficiency issues and security dodge of an existing scheme and proposes an amended data integrity scheme using improved RSA and number theory based concept for cloud archive. This scheme of protecting the integrity of guest virtual machines can be agreed upon by both the cloud and the customer and can be incorporated in the service level agreement (SLA).Based onhypothetical analysis, we demonstrate that the proposedscheme has a provably safe and highly adroit dataintegrity inspection measure.
Micro-Neuro-Sensor Recording of STN Neurons of the Human Brain
What cause to the neurons of the human brain cells when they are damaged. They become inactive. So damage to subthalamiuc nucleus (STN) neurons of the human brain causing larger involuntary movements and thereby attacking the Parkinson’s disease (PD). Deep brain stimulation (DBS) of bilateral sub thalamic nuclei (STN) is an efficient method of rehabilitation technique in subjects with advanced idiopathic Parkinson’s (or Parkinson) disease. Accurate targeting of STN neurons and placement of microelectrodes/ (neurosensors) are paramount importance for optimal results after STN-DBS method.In this paper, microminiaturized electrode recordings (MER) of STN neurons were detected in a mean of 3.5 ±1.1 channels on right hemisphere and 3.6 ±1.04 on left hemisphere.Final channel selected were most commonly central seen in 42.3% followed by anterior in 33.7%. When a high current is delivered to STN or GPi neurons of basal ganglia (a component of human brain), causing their inhibition and improved indication of symptoms. It is now known that there is a significant change in the firing pattern and a reorganization of the entire basal ganglia circuit with DBS. The MER of STN neurons has identified a specific high frequency irregular larger amplitude firing patterns seen only in disease states and hence used to detect the neurons of ST nucleus during functional surgery. Microelectrode recording is so useful to confirm the right path but has to be taken in consideration with effects on macro stimulation.
EDM: Finding Answers to Reduce Dropout Rates in Schools
The focus of this paper is to get a bird's eye view of the various factors that could be analyzed to present schools and governments timely indicators of school dropouts. With the help of EDM, one could have access to enormous amounts of data. The crux of the matter would be to identify the data in line with plans and ideas that would eventually lead to the formulation of policies that enhance the teaching and learning process.
Analysis of Effort Estimation Model in Traditional and Agile (USING METRICS ...
Agile software development has been gaining popularity and replacing the traditional methods of developing software. However, estimating the size and effort in Agile software development still remains a challenge. Measurement practices in agile methods are more important than traditional methods, because lack of appropriate an effective measurement practices will increase the risk of project. This paper discuss about traditional and agile effort estimation model, and analysis done on how the metrics are used in estimation process. The paper also suggeststo use object point and use case point to improve accuracy of effort in agile software development.
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SPSS: An Effective Tool to Compute Learning Outcomes in Acadamics
SPSS: An Effective Tool to Compute Learning Outcomes in Acadamics
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining Approach
BugLoc: Bug Localization in Multi Threaded Application via Graph Mining Approach
Analysis of Women Harassment in Villages Using CETD Matrix Modal
Analysis of Women Harassment in Villages Using CETD Matrix Modal
Solving Assignment Problem Using L-R Fuzzy Numbers
Solving Assignment Problem Using L-R Fuzzy Numbers
A Study on the Exposures of Rag- Pickers Using Induced Neutrosophic Cognitive...
A Study on the Exposures of Rag- Pickers Using Induced Neutrosophic Cognitive...
Dual Trapezoidal Fuzzy Number and its Applications
Dual Trapezoidal Fuzzy Number and its Applications
Developing and Porting multi-grid solver for CFD application on Intel-MIC pla...
Developing and Porting multi-grid solver for CFD application on Intel-MIC pla...
Classification and Prediction of Heart Disease from Diabetes Patients using H...
Classification and Prediction of Heart Disease from Diabetes Patients using H...
Intuitionistic Double Layered Fuzzy Graph and its Cartesian Product Vertex De...
Intuitionistic Double Layered Fuzzy Graph and its Cartesian Product Vertex De...
Clustering and Classification in Support of Climatology to mine Weather Data ...
Clustering and Classification in Support of Climatology to mine Weather Data ...
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Test Suite Reduction Based on Fault Detection with Cost Optimization
Effectual Data Integrity Checking Technique Based on Number Theory
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Micro-Neuro-Sensor Recording of STN Neurons of the Human Brain
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EDM: Finding Answers to Reduce Dropout Rates in Schools
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Storagedeteriorationisanyformoflossinquantityandqualityofbio-materials.
Themajorcausesofdeteriorationinstorage
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•Biological
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Storageonlypreservesquality.Itneverimprovesquality.
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ESR spectroscopy in liquid food and beverages.pptx
With increasing population, people need to rely on packaged food stuffs. Packaging of food materials requires the preservation of food. There are various methods for the treatment of food to preserve them and irradiation treatment of food is one of them. It is the most common and the most harmless method for the food preservation as it does not alter the necessary micronutrients of food materials. Although irradiated food doesn’t cause any harm to the human health but still the quality assessment of food is required to provide consumers with necessary information about the food. ESR spectroscopy is the most sophisticated way to investigate the quality of the food and the free radicals induced during the processing of the food. ESR spin trapping technique is useful for the detection of highly unstable radicals in the food. The antioxidant capability of liquid food and beverages in mainly performed by spin trapping technique.
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
Compexometric titration/Chelatorphy titration/chelating titration
Classification
Metal ion ion indicators
Masking and demasking reagents
Estimation of Magnisium sulphate
Calcium gluconate
Complexometric Titration/ chelatometry titration/chelating titration, introduction, Types-
1.Direct Titration
2.Back Titration
3.Replacement Titration
4.Indirect Titration
Masking agent, Demasking agents
formation of complex
comparition between masking and demasking agents,
Indicators/Metal ion indicators/ Metallochromic indicators/pM indicators,
Visual Technique,PM indicators (metallochromic), Indicators of pH, Redox Indicators
Instrumental Techniques-Photometry
Potentiometry
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Complex titration with EDTA.
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The debris of the ‘last major merger’ is dynamically young
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
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留信网认证的作用:
1:该专业认证可证明留学生真实身份
2:同时对留学生所学专业登记给予评定
3:国家专业人才认证中心颁发入库证书
4:这个认证书并且可以归档倒地方
5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息
6:个人职称评审加20分
7:个人信誉贷款加10分
8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才
The cost of acquiring information by natural selection
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
Micronuclei test.M.sc.zoology.fisheries.
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
Mending Clothing to Support Sustainable Fashion_CIMaR 2024.pdf
Ozturkcan, S., Berndt, A., & Angelakis, A. (2024). Mending clothing to support sustainable fashion. Presented at the 31st Annual Conference by the Consortium for International Marketing Research (CIMaR), 10-13 Jun 2024, University of Gävle, Sweden.
Farming systems analysis: what have we learnt?.pptx
Presentation given at the official farewell of Prof Ken Gillet at Wageningen on 13 June 2024
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THE EFFECTS OF CHEMICAL HAZARDS IN SUSTAINABLE DEVELOPMENT OF AGRICULTURE USING FUZZY ASSOCIATIVE MEMORIES (FAM)
- 1. International Journal of Computing Algorithm, Vol 2(2), December 2013 ISSN(Print):2278-2397 Website: www.ijcoa.com The Effects of Chemical Hazards in Sustainable Development of Agriculture Using Fuzzy Associative Memories (FAM) Charles Robert Kenneth1 , R.C Thivyarathi2 1 Department of Mathematics, Loyola College, Chennai 2 Department 0f Science and Humanities, R.M.D Engineering College, Chennai Abstract The concept of Sustainable development based on an integrated view of environmental policies and development strategies intends to minimize the risks and hazards to the environment. The time has come for efforts to be made on the environmental front towards sustainable development without endangering the ecological assets of the future generation. In this paper we analyze the effects of health hazards in sustainable development of agriculture using Fuzzy Associative Memories (FAM). We arrive at the conclusions by this study how sustainable development is being affected by the pollutions. This paper has four sections. In section one we recall the notion of Fuzzy Associative Memories (FAM) and its properties. In section two we describe the problem. In Section three we adopt FAM to this problem and analyze the problem. Section four gives the conclusions based on our study.