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Effect Of Graded Levels Of Condensed Tannin (Ct) From Mimosa Pudica On In-Vitro Methane Production, P. K. Malik, R. Bhatta, N. Ravi, M. Saravanan, L. Baruah 2020 National Institute of Animal Nutrition and Physiology, India

Effect Of Graded Levels Of Condensed Tannin (Ct) From Mimosa Pudica On In-Vitro Methane Production, P. K. Malik, R. Bhatta, N. Ravi, M. Saravanan, L. Baruah

International Grassland Congress Proceedings

Livestock in the country are primarily being fed on fibrous feed resulted in high enteric methane (CH4) emission along with low nutrients availability to host animal. Rumen methano genesis is necessary for the host system as this process ensure the removal of fermentative H2 through the reduction of CO2 into CH4. At the same time this process is wasteful because the emission also represents a loss of dietary energy (6-12% of gross energy intake) apart from contributing to global warming.

Worldwide livestock contribute around 90-95 Tg methane to the pool with a contribution of 12-13% from ...


Gross Biomass And Root/Shoot Ratio Mediated Drought Sensitivities Of Ecosystem Carbon Exchange In A Meadow Steppe, Yunbo Wang, Wei Sun, Deli Wang 2020 Northeast Normal University, China

Gross Biomass And Root/Shoot Ratio Mediated Drought Sensitivities Of Ecosystem Carbon Exchange In A Meadow Steppe, Yunbo Wang, Wei Sun, Deli Wang

International Grassland Congress Proceedings

According to IPCC’s Report (2007), global precipitation regimes will change largely in the future, with more annual precipitation at the mid-latitude regions. Simultaneously, due to the accelerating industrialization and use of nitrogen (N) fertilizer, significant increase in nitrogen deposition has been widely documented (Liu et al., 2013).

Water and nitrogen are the two most important limiting factors for the ecological processes of arid and semi-arid grassland ecosystems; therefore, altered precipitation regimes and enhanced nitrogen deposition are likely to change vegetation composition, ecosystem productivity, and aboveground vs belowground biomass distribution.

In addition to these long-term changes, short-term climate extremes, such ...


Spatial Heterogeneity Of Soil And Vegetation Characteristics And Soil-Vegetation Relationships Along An Ecotone In Southern Mu Us Sandy Land, China, Yingzhong Xie, Kaiyang Qiu, Dongmei Xu, Richard Pott 2020 Ningxia University, China

Spatial Heterogeneity Of Soil And Vegetation Characteristics And Soil-Vegetation Relationships Along An Ecotone In Southern Mu Us Sandy Land, China, Yingzhong Xie, Kaiyang Qiu, Dongmei Xu, Richard Pott

International Grassland Congress Proceedings

Spatial pattern analysis is an essential component of spatial heterogeneity studies on soil properties and vegetation characteristics. It was conducted in several studies for both soil and vegetation characteristics (Strand et al., 2007; Dick and Gilliam, 2007; Zuo et al., 2010). This study aims to examine the changes in the spatial heterogeneity of soil properties at different soil layers, the spatial heterogeneity of soil and vegetation characteristics along an ecotone, and soil-vegetation relationships along the ecotone in a critical area of desertification.


Evaluate The Interactions Between Grassland Ecosystems And Precipitation Anomalies Under Changing Grazing Intensity In Central Asia, Dildora Aralova, Babatunde A. Osunmadewa, Toderich Kristina, Dilshod Gafurov, Elmar Csaplovics 2020 Technical University of Dresden, Germany

Evaluate The Interactions Between Grassland Ecosystems And Precipitation Anomalies Under Changing Grazing Intensity In Central Asia, Dildora Aralova, Babatunde A. Osunmadewa, Toderich Kristina, Dilshod Gafurov, Elmar Csaplovics

International Grassland Congress Proceedings

Long term monitoring of grassland being the largest ecosystem on earth plays an important role in understanding its productivity and transformation (changes) over time. With the availability of remote sensing data, most ecological and environmental problems caused either by human activities such as extensive agriculture, pastoralism which might lead to desertification, land degradation, loss of biodiversity and climate change amongst others can be monitored. For this study, vegetation cover was selected as the main source of examination and subsets of area covered with grasslands were profiled for further monitoring of grassland increasing and decreasing trends in selected areas of Central ...


Effect Of Climate Change In 50-Years Period On Grassland Productivity In Central Poland, Piotr Goliñski, Marek Czerwinski, Barbara Golinska 2020 Poznan University of Life Sciences, Poland

Effect Of Climate Change In 50-Years Period On Grassland Productivity In Central Poland, Piotr Goliñski, Marek Czerwinski, Barbara Golinska

International Grassland Congress Proceedings

In Central Europe, the climate change is predicted to bring more rainfall in winter, less rainfall in summer, and an increased drought risk (Trnka et al., 2011). Smit et al., (2008) reported that significant drops in grassland productivity can usually be attributed to drier summers. Also in Poland, the most important abiotic factor limiting grassland productivity is water shortage and its distribution during vegetative season. Indicating the influence of climate on grass vegetation growth could be an important tool in grassland management on the national, regional and single grassland scales. The aim of the study was to evaluate the effect ...


Climate Change Adaptation In Vulnerable Crop And Livestock Production Systems In Mgeta, Tanzania, Leif Jarle Asheim, Zabron C. Nziku, Lars O. Eik, Dismas Mwaseba, George C. Kifaro 2020 Norwegian Agricultural Economics Research Institute, Norway

Climate Change Adaptation In Vulnerable Crop And Livestock Production Systems In Mgeta, Tanzania, Leif Jarle Asheim, Zabron C. Nziku, Lars O. Eik, Dismas Mwaseba, George C. Kifaro

International Grassland Congress Proceedings

Awareness regarding effects of climate change on the environment and livelihoods is becoming more apparent than at any time before (Elisha, 2006). Among the farming systems that have attracted the attention in Tanzania, are those in Mgeta in thehigh altitude water catchment area in the Uluguru Mountains. Land degradation have been widely reported in Mgeta (Ponte, 2001), and is currently threatening the source of water for domestic use and livelihoods of the local communities. Increased occurrence of droughts and dry spells during the growing seasons might reinforce the problem. A robust cropping system toreplace the erosion vulnerable vegetables seems needed ...


On Statistical Significance Of Discriminant Function Coefficients, Tolulope T. Sajobi, Gordon H. Fick, Lisa M. Lix 2020 University of Calgary

On Statistical Significance Of Discriminant Function Coefficients, Tolulope T. Sajobi, Gordon H. Fick, Lisa M. Lix

Journal of Modern Applied Statistical Methods

Discriminant function coefficients are useful for describing group differences and identifying variables that distinguish between groups. Test procedures were compared based on asymptotically approximations, empirical, and exact distributions for testing hypotheses about discriminant function coefficients. These tests are useful for assessing variable importance in multivariate group designs.


Evidence-Based Detection Of Pancreatic Canc, Rajeshwari Deepak Chandratre 2020 San Jose State University

Evidence-Based Detection Of Pancreatic Canc, Rajeshwari Deepak Chandratre

Master's Projects

This study is an effort to develop a tool for early detection of pancreatic cancer using evidential reasoning. An evidential reasoning model predicts the likelihood of an individual developing pancreatic cancer by processing the outputs of a Support Vector Classifier, and other input factors such as smoking history, drinking history, sequencing reads, biopsy location, family and personal health history. Certain features of the genomic data along with the mutated gene sequence of pancreatic cancer patients was obtained from the National Cancer Institute (NIH) Genomic Data Commons (GDC). This data was used to train the SVC. A prediction accuracy of ~85 ...


Predicting Students’ Performance By Learning Analytics, Sandeep Subhash Madnaik 2020 San Jose State University

Predicting Students’ Performance By Learning Analytics, Sandeep Subhash Madnaik

Master's Projects

The field of Learning Analytics (LA) has many applications in today’s technology and online driven education. Learning Analytics is a multidisciplinary topic for learn- ing purposes that uses machine learning, statistic, and visualization techniques [1]. We can harness academic performance data of various components in a course, along with the data background of each student (learner), and other features that might affect his/her academic performance. This collected data then can be fed to a sys- tem with the task to predict the final academic performance of the student, e.g., the final grade. Moreover, it allows students to ...


Pattern Analysis And Prediction Of Mild Cognitive Impairment Using The Conn Toolbox, Meenakshi Anbukkarasu 2020 San Jose State University

Pattern Analysis And Prediction Of Mild Cognitive Impairment Using The Conn Toolbox, Meenakshi Anbukkarasu

Master's Projects

Alzheimer's is an irreversible neurodegenerative disorder described by dynamic psychological and memory defalcation. It has been accounted for that the pervasiveness of Alzheimer's is to increase by 4 times in a few years, where one in every 75 people will have this disorder. Hence, there is a critical requirement for the analysis of Alzheimer's at its beginning stage to diminish the difficulty of the overall medical complications. The initial state of Alzheimer’s is called Mild cognitive impairment (MCI), and hence it is a decent target for premature diagnosis and treatment of Alzheimer's. This project focuses ...


Detection Of Mild Cognitive Impairment Using Diffusion Compartment Imaging, Matthew Jones 2020 San Jose State University

Detection Of Mild Cognitive Impairment Using Diffusion Compartment Imaging, Matthew Jones

Master's Projects

The result of applying the Neurite Orientation Density and Dispersion Index (NODDI) algorithm to improve the prediction accuracy for patients diagnosed with MCI is reported. Calculations were carried out using a collection of 68 patients (34 control and 34 with MCI) gathered from the Alzheimer’s Disease Neuroimaging Initiative database (ADNI). Patient data includes the use of high-resolution Magnetic Resonance Images as with as Diffusion Tensor Imaging. A Linear Regression accuracy of 83% was observed using the added NODDI summary statistic: Orientation Dispersion Index (ODI). A statistically significant difference in groups was found between control patients and patients with MCI ...


Probabilistic And Machine Learning Enhancement To Conn Toolbox, Gayathri Hanuma Ravali Kuppachi 2020 San Jose State University

Probabilistic And Machine Learning Enhancement To Conn Toolbox, Gayathri Hanuma Ravali Kuppachi

Master's Projects

Clinical depression is a state of mind where the person suffers from persevering and overpowering sorrow. Existing examinations have exhibited that the course of action of arrangement in the brain of patients with clinical depression has a weird framework topology structure. In the earlier decade, resting-state images of the brain have been under the radar a. Specifically, the topological relationship of the brain aligned with graph hypothesis has discovered a strong connection in patients experiencing clinical depression. However, the systems to break down brain networks still have a couple of issues to be unwound. This paper attempts to give a ...


Biological Physics Student Edition 2020: Chapter 1, Philip C. Nelson 2020 University of Pennsylvania

Biological Physics Student Edition 2020: Chapter 1, Philip C. Nelson

Department of Physics Papers

Chapter 1: What the Ancients Knew


Biological Physics Student Edition 2020: Contents And Prefaces, Philip C. Nelson 2020 University of Pennsylvania

Biological Physics Student Edition 2020: Contents And Prefaces, Philip C. Nelson

Department of Physics Papers

Brief Contents; Detailed Contents; To the Student; To the Instructor


Response Of Dynamic Change Of Vegetation Index To Precipitation Fluctuations In Hulunbeier Typical Steppe, Zhaoyan Diao, Shihai Lu, Zhirong Zheng, Shengxing Ye 2020 Beijing Forestry University, China

Response Of Dynamic Change Of Vegetation Index To Precipitation Fluctuations In Hulunbeier Typical Steppe, Zhaoyan Diao, Shihai Lu, Zhirong Zheng, Shengxing Ye

International Grassland Congress Proceedings

In arid and semi-arid regions, precipitation is an important environmental limiting factor for ecosystems, where precipitation characteristic parameters at different time scales have great variability (Mohammad and Howard, 2006), and the small precipitation events (< 5 mm) is the subject of precipitation events (Loik et al., 2004, Sala and Lauenroth, 1982). In this study, we used vegetation index extracted from TM or MODIS image to establish the regression models between vegetation index and precipitation, and then analyzed the response of typical steppe vegetation to precipitation fluctuations. Our result can supply reference for the productivity measurement model in typical steppe.


Effect Of Silting Yield Index On Biomass And Carbon Sequestration Potential Along An Altitudinal Gradient Of Subtropical Chir Pine Forests And Grasslands In North Western Himalaya, India, Debasis Mahato, B. Gupta, Matber Singh 2020 Birsa Agricultural University, India

Effect Of Silting Yield Index On Biomass And Carbon Sequestration Potential Along An Altitudinal Gradient Of Subtropical Chir Pine Forests And Grasslands In North Western Himalaya, India, Debasis Mahato, B. Gupta, Matber Singh

International Grassland Congress Proceedings

Biomass is an important characteristic of vegetation and is regarded as an important indicator of ecological and management processes in the vegetation. Measures of standing crop also reflect the amount of energy stored in the vegetation, which can indicate the potential productivity at the site. Forests are important for carbon sequestration besides playing very important role in the global carbon cycle. They store about 80% of all aboveground and 40% of all belowground terrestrial organic carbon. This study comprises to estimate the biomass and carbon stock of chirpine forests at different altitudinal gradients.


Table Of Contents, 2020 University of South Carolina

Table Of Contents

Journal of the South Carolina Academy of Science

No abstract provided.


Video Synthesis From The Stylegan Latent Space, Lei Zhang 2020 San Jose State University

Video Synthesis From The Stylegan Latent Space, Lei Zhang

Master's Projects

Generative models have shown impressive results in generating synthetic images. However, video synthesis is still difficult to achieve, even for these generative models. The best videos that generative models can currently create are a few seconds long, distorted, and low resolution. For this project, I propose and implement a model to synthesize videos at 1024x1024x32 resolution that include human facial expressions by using static images generated from a Generative Adversarial Network trained on the human facial images. To the best of my knowledge, this is the first work that generates realistic videos that are larger than 256x256 resolution from single ...


Computational Astronomy: Classification Of Celestial Spectra Using Machine Learning Techniques, Gayatri Milind Hungund 2020 San Jose State University

Computational Astronomy: Classification Of Celestial Spectra Using Machine Learning Techniques, Gayatri Milind Hungund

Master's Projects

Lightyears beyond the Planet Earth there exist plenty of unknown and unexplored stars and Galaxies that need to be studied in order to support the Big Bang Theory and also make important astronomical discoveries in quest of knowing the unknown. Sophisticated devices and high-power computational resources are now deployed to make a positive effort towards data gathering and analysis. These devices produce massive amount of data from the astronomical surveys and the data is usually in terabytes or petabytes. It is exhaustive to process this data and determine the findings in short period of time. Many details can be missed ...


Using Deep Learning And Linguistic Analysis To Predict Fake News Within Text, John Nguyen 2020 San Jose State University

Using Deep Learning And Linguistic Analysis To Predict Fake News Within Text, John Nguyen

Master's Projects

The spread of information about current events is a way for everybody in the world to learn and understand what is happening in the world. In essence, the news is an important and powerful tool that could be used by various groups of people to spread awareness and facts for the good of mankind. However, as information becomes easily and readily available for public access, the rise of deceptive news becomes an increasing concern. The reason is due to the fact that it will cause people to be misled and thus could affect the livelihood of themselves or others. The ...


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