Career Technical Education Adjunct Faculty Teacher Readiness: An Investigation of Teacher Excellence and Variables of Preparedness

The purpose of this research was to examine the relationship between teaching readiness and teaching excellence with three variables of preparedness of adjunct professors teaching career technical education courses through student surveys using a correlational design of two statistical techniques; least-squares regression and one-way analysis of variance. That is, the research tested the relationship between teacher readiness and teacher excellence with the number of years teaching, the number of years of experience in the professional field and exposure to teaching related professional development, referred to as variables of preparedness. The results of the research provided insight to the relationship between the variables of preparedness and student assessment of their adjunct professors. Concerning the years of teaching experience, this research found a negative inverse relationship with how students rated their professors’ teaching readiness and excellence. The research also found no relationship between years of professional experience and the students’ assessment. Lastly, the research found a significant positive relationship between the amount of teaching related professional development taken by an adjunct professor and the students’ assessment in teaching readiness and excellence. This research suggests that policies and practices at colleges should address the professional development needs of adjunct professors. Also, to design a model that meets the practices of inclusion for adjunct faculty and to make professional development a priority within the organization. Lastly, implement that model over time to prepare adjuncts in readiness and excellence.

Comparison and Validation of Tropical Rainfall Measuring Mission (TRMM) Rainfall Algorithms in Tropical Cyclones

Tropical Rainfall Measuring Mission (TRMM) rainfall retrieval algorithms are evaluated in tropical cyclones (TCs). Differences between the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) retrievals are found to be related to the storm region (inner core vs. rainbands) and the convective nature of the precipitation as measured by radar reflectivity and ice scattering signature. In landfalling TCs, the algorithms perform differently depending on whether the rainfall is located over ocean, land, or coastal surfaces. Various statistical techniques are applied to quantify these differences and identify the discrepancies in rainfall detection and intensity. Ground validation is accomplished by comparing the landfalling storms over the Southeast US to the NEXRAD Multisensor Precipitation Estimates (MPE) Stage-IV product. Numerous recommendations are given to algorithm users and developers for applying and interpreting these algorithms in areas of heavy and widespread tropical rainfall such as tropical cyclones.

Big data analytics for proactive and predictive maintenance in electric car battery packs

The idea behind the project is to develop a methodology for analyzing and developing techniques for the diagnosis and the prediction of the state of charge and health of lithium-ion batteries for automotive applications. For lithium-ion batteries, residual functionality is measured in terms of state of health; however, this value cannot be directly associated with a measurable value, so it must be estimated. The development of the algorithms is based on the identification of the causes of battery degradation, in order to model and predict the trend. Therefore, models have been developed that are able to predict the electrical, thermal and aging behavior. In addition to the model, it was necessary to develop algorithms capable of monitoring the state of the battery, online and offline. This was possible with the use of algorithms based on Kalman filters, which allow the estimation of the system status in real time. Through machine learning algorithms, which allow offline analysis of battery deterioration using a statistical approach, it is possible to analyze information from the entire fleet of vehicles. Both systems work in synergy in order to achieve the best performance. Validation was performed with laboratory tests on different batteries and under different conditions. The development of the model allowed to reduce the time of the experimental tests. Some specific phenomena were tested in the laboratory, and the other cases were artificially generated.

Noises: a Nuisance and a Resource. Development of New Decomposition Methods of Noisy Data

Noise is constant presence in measurements. Its origin is related to the microscopic properties of matter. Since the seminal work of Brown in 1828, the study of stochastic processes has gained an increasing interest with the development of new mathematical and analytical tools. In the last decades, the central role that noise plays in chemical and physiological processes has become recognized. The dual role of noise as nuisance/resource pushes towards the development of new decomposition techniques that divide a signal into its deterministic and stochastic components. In this thesis I show how methods based on Singular Spectrum Analysis have the right properties to fulfil the previously mentioned requirement. During my work I applied SSA to different signals of interest in chemistry: I developed a novel iterative procedure for the denoising of powder X-ray diffractograms; I “denoised” bi-dimensional images from experiments of electrochemiluminescence imaging of micro-beads obtaining new insight on ECL mechanism. I also used Principal Component Analysis to investigate the relationship between brain electrophysiological signals and voice emission.

Big Data approaches as a support for precision livestock farming techniques

With the advent of new technologies it is increasingly easier to find data of different nature from even more accurate sensors that measure the most disparate physical quantities and with different methodologies. The collection of data thus becomes progressively important and takes the form of archiving, cataloging and online and offline consultation of information. Over time, the amount of data collected can become so relevant that it contains information that cannot be easily explored manually or with basic statistical techniques. The use of Big Data therefore becomes the object of more advanced investigation techniques, such as Machine Learning and Deep Learning. In this work some applications in the world of precision zootechnics and heat stress accused by dairy cows are described. Experimental Italian and German stables were involved for the training and testing of the Random Forest algorithm, obtaining a prediction of milk production depending on the microclimatic conditions of the previous days with satisfactory accuracy. Furthermore, in order to identify an objective method for identifying production drops, compared to the Wood model, typically used as an analytical model of the lactation curve, a Robust Statistics technique was used. Its application on some sample lactations and the results obtained allow us to be confident about the use of this method in the future.

Data analysis with merge trees

Today’s data are increasingly complex and classical statistical techniques need growingly more refined mathematical tools to be able to model and investigate them. Paradigmatic situations are represented by data which need to be considered up to some kind of trans- formation and all those circumstances in which the analyst finds himself in the need of defining a general concept of shape. Topological Data Analysis (TDA) is a field which is fundamentally contributing to such challenges by extracting topological information from data with a plethora of interpretable and computationally accessible pipelines. We con- tribute to this field by developing a series of novel tools, techniques and applications to work with a particular topological summary called merge tree. To analyze sets of merge trees we introduce a novel metric structure along with an algorithm to compute it, define a framework to compare different functions defined on merge trees and investigate the metric space obtained with the aforementioned metric. Different geometric and topolog- ical properties of the space of merge trees are established, with the aim of obtaining a deeper understanding of such trees. To showcase the effectiveness of the proposed metric, we develop an application in the field of Functional Data Analysis, working with functions up to homeomorphic reparametrization, and in the field of radiomics, where each patient is represented via a clustering dendrogram.

Efficient and low-computational predictive models for spectral sensors

Spectral sensors are a wide class of devices that are extremely useful for detecting essential information of the environment and materials with high degree of selectivity. Recently, they have achieved high degrees of integration and low implementation cost to be suited for fast, small, and non-invasive monitoring systems. However, the useful information is hidden in spectra and it is difficult to decode. So, mathematical algorithms are needed to infer the value of the variables of interest from the acquired data. Between the different families of predictive modeling, Principal Component Analysis and the techniques stemmed from it can provide very good performances, as well as small computational and memory requirements. For these reasons, they allow the implementation of the prediction even in embedded and autonomous devices. In this thesis, I will present 4 practical applications of these algorithms to the prediction of different variables: moisture of soil, moisture of concrete, freshness of anchovies/sardines, and concentration of gasses. In all of these cases, the workflow will be the same. Initially, an acquisition campaign was performed to acquire both spectra and the variables of interest from samples. Then these data are used as input for the creation of the prediction models, to solve both classification and regression problems. From these models, an array of calibration coefficients is derived and used for the implementation of the prediction in an embedded system. The presented results will show that this workflow was successfully applied to very different scientific fields, obtaining autonomous and non-invasive devices able to predict the value of physical parameters of choice from new spectral acquisitions.

Diagnosing criticality in symmetric and chiral clock models

Quantum clock models are statistical mechanical spin models which may be regarded as a sort of bridge between the one-dimensional quantum Ising model and the one-dimensional quantum XY model. This thesis aims to provide an exhaustive review of these models using both analytical and numerical techniques. We present some important duality transformations which allow us to recast clock models into different forms, involving for example parafermions and lattice gauge theories. Thus, the notion of topological order enters into the game opening new scenarios for possible applications, like topological quantum computing. The second part of this thesis is devoted to the numerical analysis of clock models. We explore their phase diagram under different setups, with and without chirality, starting with a transverse field and then adding a longitudinal field as well. The most important observables we take into account for diagnosing criticality are the energy gap, the magnetisation, the entanglement entropy and the correlation functions.

[yoga And The Promotion Of Health].

The scope of this paper is to analyze the self-declared symptoms and state of well-being of participants in the Yoga and Promotion of Health program, which consisted of hatha yoga lessons. It includes body exercises and breathing techniques, as well as ethical and philosophical content, administered to two groups of lecturers, workers and students of a public university in the State of São Paulo from August to December 2011 and March to June 2012. The participants filled out the adapted version of the Measure Yourself Medical Outcome Profile form at the beginning and end of the program. Of the 20 participants in Group 1, eight filled out the form and half of them reported the improvement of self-declared symptoms; as regards the state of well being, three of them felt they had improved. In Group 2, which also had 20 participants, nine completed the program and all of them reported improvements of self-declared symptoms and well-being. In conclusion, yoga is a mind-body practice which exerts an important therapeutic effect on most practitioners and also promotes health for the majority of them, expanding their capacity of self perception and self care. However, it should be noted that it doesn't achieve the same positive effect for all practitioners as some yoga traditions advocate.

Cytogenetic And Morphologic Approaches Of Hybrids From Experimental Crosses Between Triatoma Lenti Sherlock & Serafim, 1967 And T. Sherlocki Papa Et Al., 2002 (hemiptera: Reduviidae).

The reproductive capacity between Triatoma lenti and Triatoma sherlocki was observed in order to verify the fertility and viability of the offspring. Cytogenetic, morphological and morphometric approaches were used to analyze the differences that were inherited. Experimental crosses were performed in both directions. The fertility rate of the eggs in crosses involving T. sherlocki females was 65% and 90% in F1 and F2 offspring, respectively. In reciprocal crosses, it was 7% and 25% in F1 and F2 offspring, respectively. The cytogenetic analyses of the male meiotic process of the hybrids were performed using lacto-acetic orcein, C-banding and Feulgen techniques. The male F1 offspring presented normal chromosome behavior, a finding that was similar to those reported in parental species. However, cytogenetic analysis of F2 offspring showed errors in chromosome pairing. This post-zygotic isolation, which prevents hybrids in nature, may represent the collapse of the hybrid. This phenomenon is due to a genetic dysregulation that occurs in the chromosomes of F1. The results were similar in the hybrids from both crosses. Morphological features, such as color and size of connexive and the presence of red-orange rings on the femora, were similar to T. sherlocki, while wins size was similar to T. lenti in F1 offspring. The eggshells showed characteristics that were similar to species of origin, whereas the median process of the pygophore resulted in intermediate characteristics in the F1 and a segregating pattern in F2 offspring. Geometric morphometric techniques used on the wings showed that both F1 and F2 offspring were similar to T. lenti. These studies on the reproductive capacity between T. lenti and T. sherlocki confirm that both species are evolutionarily closed; hence, they are included in the brasiliensis subcomplex. The extremely reduced fertility observed in the F2 hybrids confirmed the specific status of the species that were analyzed.

Chitosan Nanoparticles Loaded The Herbicide Paraquat: The Influence Of The Aquatic Humic Substances On The Colloidal Stability And Toxicity.

Polymeric nanoparticles have been developed for several applications, among them as carrier system of pesticides. However, few studies have investigated the fate of these materials in the environment in relation to colloidal stability and toxicity. In nature, humic substances are the main agents responsible for complexation with metals and organic compounds, as well as responsible for the dynamics of these nanoparticles in aquatic and terrestrial environments. In this context, the evaluation of the influence of aquatic humic substances (AHS) on the colloidal stability and toxicity of polymeric nanoparticles of chitosan/tripolyphosphate with or without paraquat was performed. In this study, the nanoparticles were prepared by the ionic gelation method and characterized by size distribution measurements (DLS and NTA), zeta potential, infrared and fluorescence spectroscopy. Allium cepa genotoxicity studies and ecotoxicity assays with the alga Pseudokirchneriella subcapitata were used to investigate the effect of aquatic humic substances (AHS) on the toxicity of this delivery system. No changes were observed in the physical-chemical stability of the nanoparticles due to the presence of AHS using DLS and NTA techniques. However some evidence of interaction between the nanoparticles and AHS was observed by infrared and fluorescence spectroscopies. The ecotoxicity and genotoxicity assays showed that humic substances can decrease the toxic effects of nanoparticles containing paraquat. These results are interesting because they are important for understanding the interaction of these nanostructured carrier systems with species present in aquatic ecosystems such as humic substances, and in this way, opening new perspectives for studies on the dynamics of these carrier systems in the ecosystem.

Métodos probabilístico e determinístico para diagnóstico da necessidade de subsolagem de solos agrícolas

This paper presents two techniques to evaluate soil mechanical resistance to penetration as an auxiliary method to help in a decision-making in subsoiling operations. The decision is based on the volume of soil mobilized as a function of the considered critical soil resistance to penetration in each case. The first method, probabilistic, uses statistical techniques to define the volume of soil to be mobilized. The other method, deterministic, determines the percentage of soil to be mobilized and its spatial distribution. Both cases plot the percentage curves of experimental data related to the soil mechanical resistance to penetration equal or larger to the established critical level and the volume of soil to be mobilized as a function of critical level. The deterministic method plots showed the spatial distribution of the data with resistance to penetration equal or large than the critical level. The comparison between mobilized soil curves as a function of critical level using both methods showed that they can be considered equivalent. The deterministic method has the advantage of showing the spatial distribution of the critical points.

Quality evaluation of DNA obtained from stored human saliva and its applicability to identification in Forensic Dentistry

PURPOSE: This study evaluated the quality of DNA obtained from stored human saliva and its applicability to human identification. METHODS: The saliva samples of 20 subjects, collected in the form of saliva in natura and from mouth swabs and stored at -20ºC, were analyzed. After 7 days, the DNA was extracted from the 40 saliva samples and subjected to PCR and electrophoresis. After 180 days, the technique was repeated with the 20 swab samples. RESULTS: The first-stage results indicated that DNA was successfully extracted in 97.5% of reactions, 95% of saliva in natura and 100% of swab saliva samples, with no statistically significant difference between the forms of saliva. In the second phase, the result was positive for all 20 analyzed samples (100%). Subsequently, in order to analyze the quality of the DNA obtained from human saliva, the SIX3-2 gene was tested on the 20 mouth swab samples, and the PCR products were digested using the MbO1 restriction enzyme to evaluate polymorphisms in the ADRA-2 gene, with positive results for most samples. CONCLUSION: It was concluded that the quantity and quality of DNA from saliva and the techniques employed are adequate for forensic analysis of DNA.

Effect of ageing and immersion in different beverages on properties of denture lining materials

OBJECTIVES: To evaluate the color stability and hardness of two denture liners obtained by direct and indirect techniques, after thermal cycling and immersion in beverages that can cause staining of teeth. MATERIAL AND METHODS: Seventy disc-shaped specimens (18 x 3 mm) processed by direct (DT) and indirect techniques (IT) were made from Elite soft (n=35) and Kooliner (n=35) denture liners. For each material and technique, 10 specimens were subjected to thermal cycling (3,000 cycles) and 25 specimens were stored in water, coffee, tea, soda and red wine for 36 days. The values of color change, Shore A hardness (Elite soft) and Knoop hardness (Kooliner) were obtained. The data were subjected to ANOVA, Tukey's multiple-comparison test, and Kruskal-Wallis test (P<0.05). RESULTS: The thermal cycling promoted a decrease on hardness of Kooliner regardless of the technique used (Initial: 9.09± 1.61; Thermal cycling: 7.77± 1.47) and promoted an increase in the hardness in the DT for Elite Soft (Initial: 40.63± 1.07; Thermal cycling: 43.53± 1.03); hardness of Kooliner (DT: 8.76± 0.95; IT: 7.70± 1.62) and Elite Soft (DT: 42.75± 1.54; IT=39.30± 2.31) from the DT suffered an increase after the immersion in the beverages. The thermal cycling promoted color change only for Kooliner in the IT. Immersion in the beverages did not promote color change for Elite in both techniques. The control group of the DT of Kooliner showed a significant color change. Wine and coffee produced the greatest color change in the DT only for Elite Soft when compared to the other beverages. CONCLUSION: The three variation factors promoted alteration on hardness and color of the tested denture lining materials.

Flexural strength and hardness of direct and indirect composites

The objective of this study was to evaluate the flexural strength (σf) and hardness (H) of direct and indirect composites, testing the hypotheses that direct resin composites produce higher σf and H values than indirect composites and that these properties are positively related. Ten bar-shaped specimens (25 mm x 2 mm x 2 mm) were fabricated for each direct [D250 - Filtek Z250 (3M-Espe) and D350 - Filtek Z350 (3M-Espe)] and indirect [ISin - Sinfony (3M-Espe) and IVM - VitaVM LC (Vita Zahnfabrik)] materials, according to the manufacturer's instructions and ISO4049 specifications. The σf was tested in three-point bending using a universal testing machine (EMIC DL 2000) at a crosshead speed of 0.5 mm/min (ISO4049). Knoop hardness (H) was measured on the specimens' fragments resultant from the σf test and calculated as H = 14.2P/l², where P is the applied load (0.1 kg; dwell time = 15 s) and l is the longest diagonal of the diamond shaped indent (ASTM E384). The data were statistically analyzed using Anova and Tukey tests (α = 0.05). The mean σf and standard deviation values (MPa) and statistical grouping were: D250 - 135.4 ± 17.6a; D350 - 123.7 ± 11.1b; ISin - 98.4 ± 6.4c; IVM - 73.1 ± 4.9d. The mean H and standard deviation values (kg/mm²) and statistical grouping were: D250 - 98.12 ± 1.8a; D350 - 86.5 ± 1.9b; ISin - 28.3 ± 0.9c; IVM - 30.8 ± 1.0c. The direct composite systems examined produce higher mean σf and H values than the indirect composites, and the mean values of these properties were positively correlated (r = 0.91), confirming the study hypotheses.