Differentiation of Agaricus species and other homobasidiomycetes based on volatile production patterns using an electronic nose system

Comparisons of the qualitative volatile production patterns between seven species of Agaricus, and between two of Volvariella and Pleurotus and one Coprinus species when grown at 25°C on agar media for 14d were made. There was good reproducibility between the volatile production patterns of the same species using an electronic nose unit with a 14 conducting sensor polymer array. Principle Component Analysis (PCA) showed that it was possible to discriminate between five of the seven Agaricus species, but that some overlap occurred between the others. Cluster analysis showed that there was also overlap between some species with the tropical collection of A. bitorquis separating out from the others. The volatile production profile of the commercial A. bisporus was close to that of a wild species, A. campestris. A. bisporus could be readily differentiated from other non-Agaricus species. This study demonstrates the potential for using electronic nose systems to rapidly differentiate mycelial cultures of homobasidiomycete mushrooms

Essays in Basketball Analytics

With the increasing popularity and competition in professional basketball in the past decade, data driven decision has emerged as a big competitive edge. The advent of high frequency player tracking data from SportVU has enabled a rigorous analysis of player abilities and interactions that was not possible before. The tracking data records two-dimensional x-y coordinates of 10 players on the court as well as the x-y-z coordinates of the ball at a resolution of 25 frames per second, yielding over 1 billion space-time observations over the course of a full season. This dissertation offers a collection of spatio-temporal models and player evaluation metrics that provide insight into the player interactions and their performance, hence allowing the teams to make better decisions. Conventional approaches to simulate matches have ignored that in basketball the dynamics of ball movement is very sensitive to the lineups on the court and unique identities of players on both offense and defense sides. In chapter 2, we propose the simulation infrastructure that can bridge the gap between player identity and team level network. We model the progression of a basketball match using a probabilistic graphical model. We model every touch event in a game as a sequence of transitions between discrete states. We treat the progression of a match as a graph, where each node represents the network structure of players on the court, their actions, events, etc., and edges denote possible moves in the game flow. Our results show that either changes in the team lineup or changes in the opponent team lineup significantly affects the dynamics of a match progression. Evaluation on the match data for the 2013-16 NBA season suggests that the graphical model approach is appropriate for modeling a basketball match. NBA teams value players who can ``stretch'' the floor, i.e. create space on the court by drawing their defender(s) closer to themselves. Clearly, this ability to attract defenders varies across players, and furthermore, this effect may also vary by the court location of the offensive player, and whether or not the player is the ball handler. For instance, a ball-handler near the basket attracts a defender more when compared to a non ball-handler at the 3 point line. This has a significant effect on the defensive assignment. This is particularly important because defensive assignment has become the cornerstone of all tracking data based player evaluation models. In chapter 3, we propose a new model to learn player and court location specific offensive attraction. We show that offensive players indeed have varying ability to attract the defender in different parts of the court. Using this metric, teams can evaluate players to construct a roster or lineup which maximizes spacing. We also improve upon the existing defensive matchup inference algorithm for SportVU data. While the ultimate goal of the offense is to shoot the ball, the strategy lies in creating good shot opportunities. Offensive play event detection has been a topic of research interest. Current research in this area have used a supervised learning approach to detect and classify such events. We took an unsupervised learning approach to detect these events. This has two inherent benefits: first, there is no need for pretagged data to learn identifying these events which is a lobor intensive and error prone task; second, an unsupervised approach allows us to detect events that has not been tagged yet i.e. novel events. We use a HMM based approach to detect these events at any point in the time during a possession by specifying the functional form of the prior distribution on the player movement data. We test our framework on detecting ball screen, post up, and drive. However, it can be easily extended to events like isolation or a new event that has certain distinct defensive matchup or player movement feature compared to a non event. This is the topic for chapter 4. Accurate estimation of the offensive and the defensive abilities of players in the NBA plays a crucial role in player selection and ranking. A typical approach to estimate players' defensive and offensive abilities is to learn the defensive assignment for each shot and then use a random effects model to estimate the offensive and defensive abilities for each player. The scalar estimate from the random effects model can then be used to rank player. In this approach, a shot has a binary outcome, either it is made or it is a miss. This approach is not able to take advantage of the “quality” of the shot trajectory. In chapter 5, we propose a new method for ranking players that infers the quality of a shot trajectory using a deep recurrent neural network, and then uses this quality measure in a random effects model to rank players taking defensive matchup into account. We show that the quality information significantly improves the player ranking. We also show that including the quality of shots increases the separation between the learned random effect coefficients, and thus, allows for a better differentiation of player abilities. Further, we show that we are able to infer changes in the player's ability on a game-by-game basis when using a trajectory based model. A shot based model does not have enough information to detect changes in player's ability on a game-by-game basis. A good defensive player prevents its opponent from making a shot, attempting a good shot, making an easy pass, or scoring events, eventually leading to wasted shot clock time. The salient feature here is that a good defender prevents events. Consequently, event driven metrics, such as box scores, cannot measure defensive abilities. Conventional wisdom in basketball is that ``pesky'' defenders continuously maintain a close distance to the ball handler. A closely guarded offensive player is less likely to take or make a shot, less likely to pass, and more likely to lose the ball. In chapter 6, we introduce Defensive Efficiency Rating (DER), a new statistic that measures the defensive effectiveness of a player. DER is the effective distance a defender maintains with the ball handler during an interaction where we control for the identity and wingspan of the the defender, the shot efficiency of the ball handler, and the zone on the court. DER allows us to quantify the quality of defensive interaction without being limited by the occurrence of discrete and infrequent events like shots and rebounds. We show that the ranking from this statistic naturally picks out defenders known to perform well in particular zones

Measurement and Analysis of Power in Hybrid System

Application with renewable energy  sources  such   as solar cell array, wind turbines, or fuel cells have increased significantly during the past decade. To obtain the clean energy, we are using the hybrid solar-wind power generation. Consumers prefer quality power from suppliers. The quality of power can be measured by using parameters such as voltage sag, harmonic and power factor.   To   obtain   quality   power   we   have different topologies. In our paper we present a new possible topology which improves power quality. This paper presents modeling analysis and design of a pulse width modulation voltage source inverter (PWM-VSI) to be connected between sources, which supplies energy from a hybrid solar wind energy system to the ac grid. The objective of this paper is to show that, with an adequate control, the converter not only can transfer the dc from hybrid solar wind energy system, but also can improve the power factor and quality power of electrical system. Whenever a disturbance occurs on load side, this disturbance can be minimized using open loop and closed loop control systems

re-Wildin Detroit: Return of a blighted city back to nature

Detroit’s complicated history of corruption, racial tensions and economic decline have made conventional strategies for growth, repopulation and infill inadequate for dealing with ongoing and overwhelming urban vacancy. Dealing with voids within shrinking cities have been difficult because it lies outside the existing experience and vocabulary of urban planning, architecture and socioeconomics. Most have failed to recognize that voids are not useless and there is potential value in keeping them as voids. What is the current conditions of these voids? How do we make use of it without erasing it? How can we revisit ideas of a city that embraces its existing voids? How do cities retreat and reorganize in a productive ways? What agency does design have in a void, if any at all? Allowing nature to reclaim the voids of a blighted city could generate tensions that allow for a new kind of ecological urbanism. We propose a future for the city of Detroit that lets nature take its course by rewilding remains of a post industrial city. By using current contextual logic we speculate on reorganizing the city into nodes of urban villages and allowing the voids in between them to be spaces of regeneration for communities within Detroit and greater ecologies. We consider the qualities of the disregarded to claim that something can be made out of nothing. We explore how boundaries can work to let the urban and the natural coexist. We are also critical of the viability of landscape architecture’s solutions to remaking urban land into large parks. While the practice of landscape architecture offers compelling design solutions from an urban and ecological perspective, it often resolves itself in form of expensive parks which are not a replicable model. The idea of rewilding is taken very literally. While we understand landscape architecture as crafting nature, we understand rewilding as letting nature have its own agency. We are more interested in the idea of doing nothing and the work it takes for rewilding to take place on its own. In resolving the system for rewilding to take place we have the opportunity to revisit the place of architecture

A Method for Determination of Protein Concentration in a Given Unknown Sample Using Absorbance Difference Between 205 nm and 280 nm

Nowadays, determining the protein content of a sample is a common experiment that is conducted in laboratories. Although there are several ways to measure protein content, dye-based spectrophotometric methods are most frequently used in laboratories. In dye-based approaches, protein assays are mostly carried out at a certain wavelength. Protein concentration tests like Lowry’s take a long time; whereas Bradford’s is quick but requires expensive chemicals. In order to reduce the usage of time and money associated with protein assay, we first looked into and then proposed an easy, affordable, and more accurate technique of determining protein concentration that uses standard curves but doesn’t use any dyes. The difference of two UV wavelength absorbance values at 205 nm and 280 nm was used to determine the protein concentration where one absorbance was recorded for the presence of peptide bonds and another for aromatic proteins. The proposed method has many advantages as it consumes minimum time and chemicals but the major setback is anionic detergents, which can shift the absorbance spectra abruptly

Studies on the effect of sodium arsenate & cadmium chloride on Pithophora oedogonia (Mont.) Wittrock 1877

Cadmium and Arsenic are heavy metals although not common in our environment, its threat in certain places are aggravated due to anthropogenic factors. To know its critical role on plants the investigation was made using Na2HAsO4 and CdCl2 treatment on Pithophora oedogonia (Mont.) Wittrock 1877. The observations were made after 14 days of treatment. The changes were noted. In both cases, the treated cells exhibited gradual disruption of cell wall and cell membrane. The chlorophyll content initially increased and finally decreased due to the notable destruction of chloroplasts in both treated cells. A profuse number of akinetes were observed at 100 ppm and 150 ppm of Na2HAsO4 and CdCl2 treated media. Decrease in protein content was started at 100 ppm in both cases. The lipid content initially decreased at 50 ppm and at 100 ppm lipid profile increased in terms of toleration to the Na2HAsO4 and CdCl2 stress. Pithophora oedogonia (Mont.) Wittrock 1877 exhibited more sensitivity to CdCl2 stress & showing abrupt changes in chlorophyll-a and chlorophyll-b production. The carotenoid production shown more sensitivity in Na2HAsO4 stress. Total phenol production was decreased initially and at 200 ppm CdCl2 stress had shown significant enhancement than the control set but at the 200 ppm of Na2HAsO4 shown inhibitory effect

ISOLATION AND IDENTIFICATION OF BACTERIOCIN PRODUCING MICROBES USING BIOCHEMICAL AND MOLECULAR TOOLS AND ANALYSIS OF ITS BIOPRESERVATION POTENTIAL

ABSTRACTObjective: Food safety is a matter of utmost importance in developing countries as well as in developed countries, so keeping this in mind this researchwork deals with the identification and characterization of bacteriocin producing microbes by using biochemical and molecular characterization. This study has also covered the biopreservation potential of bacteriocin produced by these microbes against sapodilla, tomato and banana as well.Methods: For the purpose of sample collection and isolation, samples of milk, curd and gangajal water were taken and bacteriocin producing microbes were isolated by using serial dilution method. Screening of bacteriocin producing microbe was done by antibacterial sensitivity test using agar well diffusion method against Bacillus amyloliquefaciens, Escherichia Coli, Staphylococcus aureus and Pseudomonas aeruginosa by determining their zone of inhibition. Biochemical characterization was done by using different tests, such as, catalase test, mannitol test, citrate test, gelatin test, maltose test, indole test, urease test, lactose test etc. Molecular characterization was done by using 16S rRNA gene sequencing. Preservative action of bacteriocinwas observed on fruits that comprise sapodilla, tomato and banana by spraying bacteriocin on them and analyzing their activities shows for at least10 days.Results: Microbes were found to be Enterococcus faecalis (Accession number KX011874) and Bacillus cereus (Accession number KX011875). Periodicobservatory studies reflect that using bacteriocin, banana can be preserved for nearly 6-7 days while sapodilla for 8-9 days and tomato for 9-10 days.Conclusion: From present study we would like to conclude that bacteriocins produced by microbes which is found in milk or curd can also be used asbiopreservatives for these defined fruits that is sapodilla, tomato and banana.Keywords: Bacteriocin, Biopreservation, 16S rRNA analysis

Facial Expression Recognition System Using Facial Characteristic Points And ID3

Facial expression is one of the most powerful, natural, and abrupt means for human beings which have the knack to communicate emotion and regulate inter-personal behaviour. In this paper we present a novel approach for facial expression detection using decision tree. Facial expression information is mostly concentrate on facial expression information regions, so the mouth, eye and eyebrow regions are segmented from the facial expression images firstly. Using these templates we calculate 30 facial characteristics points (FCP’s). These facial characteristic points describe the position and shape of the above three organs to find diverse parameters which are input to the decision tree for recognizing different facial expression