The commercial bark harvest of the African cherry (Prunus africana) on Mount Oku, Cameroon: Effects on traditional uses and population dynamics

Bark extracts of the African cherry (Prunus africana) are used to treat benign prostatic hyperplasia. This study examined the effects of commercial bark harvest on population dynamics in the Kilum-Ijim Forest Preserve on Mount Oku, Cameroon and on traditional uses. P. africana is valued for its timber and as fuel although its greatest value is as a traditional medicine for human and animal ailments. Harvest has depleted the resource and has eroded traditional forest protection practices. I constructed matrix models to examine the effects of bark harvest on population structure and on population dynamics in harvested and unharvested populations. Harvesting simulations examined the effect on the population growth rate (λ) with differing levels of mortality of harvest-sized and large trees and differing harvest frequencies. Size class frequencies for the entire forest decreased in a reverse j-shaped curve, indicating adequate recruitment in the absence of harvest. Individual plots showed differences from the overall forest data, suggesting effects of natural and man-made perturbations, particularly due to bark harvest. One plot (harvested in the 1980s) showed a temporal difference in λ and fluctuated around one, due to alternating high and low fruiting years; other unharvested plots showed smaller temporal differences. Harvested plots (harvested illegally in 1997) had values of λ less than one and showed small temporal differences. The control plot also showed λ less than one, due to poor recruitment in the closed canopy forest. The value of λ for the combined data was 0.9931 suggesting a slightly declining population. The elasticity matrix for the combined data indicated the population growth rate was most sensitive to the survival of the large reproductive trees (42.5% of the elasticity). In perturbation analyses, reducing the survival of the large trees caused the largest reductions in λ. Simulations involving harvesting frequency indicated λ returns to pre-harvest conditions if trees are re-harvested after 10–15 years, but only if the large trees are left unharvested. Management scenarios suggest harvest can be sustainable if seedlings and small saplings are planted in the forest and actively managed, although large-scale plantations may be the only feasible option to meet market demand. ^

Human impacts on pig frog (Rana grylio) populations in south Florida wetlands: Harvest, water management and mercury contamination

This study investigated how harvest and water management affected the ecology of the Pig Frog, Rana grylio. It also examined how mercury levels in leg muscle tissue vary spatially across the Everglades. Rana grylio is an intermediate link in the Everglades food web. Although common, this inconspicuous species can be affected by three forms of anthropogenic disturbance: harvest, water management and mercury contamination. This frog is harvested both commercially and recreationally for its legs, is aquatic and thus may be susceptible to water management practices, and can transfer mercury throughout the Everglades food web. ^ This two-year study took place in three major regions: Everglades National Park (ENP), Water Conservation Areas 3A (A), and Water Conservation Area 3B (B). The study categorized the three sites by their relative harvest level and hydroperiod. During the spring of 2001, areas of the Everglades dried completely. On a regional and local scale Pig Frog abundance was highest in Site A, the longest hydroperiod, heavily harvested site, followed by ENP and B. More frogs were found along survey transects and in capture-recapture plots before the dry-down than after the dry-down in Sites ENP and B. Individual growth patterns were similar across all sites, suggesting differences in body size may be due to selective harvest. Frogs from Site A, the flooded and harvested site, had no differences in survival rates between adults and juveniles. Site B populations shifted from a juvenile to adult dominated population after the dry-down. Dry-downs appeared to affect survival rates more than harvest. ^ Total mercury in frog leg tissue was highest in protected areas of Everglades National Park with a maximum concentration of 2.3 mg/kg wet mass where harvesting is prohibited. Similar spatial patterns in mercury levels were found among pig frogs and other wildlife throughout parts of the Everglades. Pig Frogs may be transferring substantial levels of mercury to other wildlife species in ENP. ^ In summary, although it was found that abundance and survival were reduced by dry-down, lack of adult size classes in Site A, suggest harvest also plays a role in regulating population structure. ^

Factors associated with prompt difficulty in automated essay scoring

This study explores factors related to the prompt difficulty in Automated Essay Scoring. The sample was composed of 6,924 students. For each student, there were 1-4 essays, across 20 different writing prompts, for a total of 20,243 essays. E-rater® v.2 essay scoring engine developed by the Educational Testing Service was used to score the essays. The scoring engine employs a statistical model that incorporates 10 predictors associated with writing characteristics of which 8 were used. The Rasch partial credit analysis was applied to the scores to determine the difficulty levels of prompts. In addition, the scores were used as outcomes in the series of hierarchical linear models (HLM) in which students and prompts constituted the cross-classification levels. This methodology was used to explore the partitioning of the essay score variance.^ The results indicated significant differences in prompt difficulty levels due to genre. Descriptive prompts, as a group, were found to be more difficult than the persuasive prompts. In addition, the essay score variance was partitioned between students and prompts. The amount of the essay score variance that lies between prompts was found to be relatively small (4 to 7 percent). When the essay-level, student-level-and prompt-level predictors were included in the model, it was able to explain almost all variance that lies between prompts. Since in most high-stakes writing assessments only 1-2 prompts per students are used, the essay score variance that lies between prompts represents an undesirable or "noise" variation. Identifying factors associated with this "noise" variance may prove to be important for prompt writing and for constructing Automated Essay Scoring mechanisms for weighting prompt difficulty when assigning essay score.^

Signal processing of physiological signals for automated assessment of stress in computer users

The need to provide computers with the ability to distinguish the affective state of their users is a major requirement for the practical implementation of affective computing concepts. This dissertation proposes the application of signal processing methods on physiological signals to extract from them features that can be processed by learning pattern recognition systems to provide cues about a person's affective state. In particular, combining physiological information sensed from a user's left hand in a non-invasive way with the pupil diameter information from an eye-tracking system may provide a computer with an awareness of its user's affective responses in the course of human-computer interactions. In this study an integrated hardware-software setup was developed to achieve automatic assessment of the affective status of a computer user. A computer-based "Paced Stroop Test" was designed as a stimulus to elicit emotional stress in the subject during the experiment. Four signals: the Galvanic Skin Response (GSR), the Blood Volume Pulse (BVP), the Skin Temperature (ST) and the Pupil Diameter (PD), were monitored and analyzed to differentiate affective states in the user. Several signal processing techniques were applied on the collected signals to extract their most relevant features. These features were analyzed with learning classification systems, to accomplish the affective state identification. Three learning algorithms: Naïve Bayes, Decision Tree and Support Vector Machine were applied to this identification process and their levels of classification accuracy were compared. The results achieved indicate that the physiological signals monitored do, in fact, have a strong correlation with the changes in the emotional states of the experimental subjects. These results also revealed that the inclusion of pupil diameter information significantly improved the performance of the emotion recognition system. ^

Demographic effects of thatch harvest and implications for sustainable use of irapai palm (Lepidocaryum tenue, Mart.), by riverine communities in the Peruvian Amazon

Lepidocaryum tenue Mart. (Arecaceae) is a small, understory palm of terra firme forests of the western and central Amazon basin. Known as irapai, it is used for roof thatch by Amazonian peoples who collect its leaves from the wild and generate income from its fronds and articles fabricated from them. Increasing demand has caused local concern that populations are declining. Cultivation attempts have been unsuccessful. The purpose of this study was to investigate market conditions and quantify population dynamics and demographic responses of harvested and unharvested irapai growing near Iquitos, Peru. ^ Ethnobotanical research included participant surveys to determine movement of thatch tiles, called crisnejas, through Moronacocha Port. I also conducted a seed germination trial, and for four years studied five populations growing in communities with similar topography and soils but different land tenure and management strategies. Stage, survival, leaf production, and reproductive transitions were used to calculate ramet demographic rates and develop population projection matrices. ^ Weavers made an average of 20–30 crisnejas per day (90–130 leaves each), and earned US$0.09 to 0.70 each (US$1.80 to 21.00 per day). Average crisnejas per month sold per vendor was 2,955 with a profit range of US$0.05 to 0.32 per crisneja. Wholesalers worked with capital outlay from US$100 to 400, and an estimated ten to twenty vendors could be found at a given time. Consumers paid between US$0.23 to 1.20 per crisneja. Although differences in demographic rates by location existed, most were not significant enough to attribute to management. ^ After 60 months, mean seed germination rate was 19.5% in all media (37.9% in peat). Seedling survival was less than two percent after twelve months. Annual palm mortality was three percent, and occurred disproportionately in small (<50 cm) palms. Small palms grew more in height. Unharvested palms grew less than harvested palms. Large palms (≥50 cm) produced more leaves, were more likely to reproduce, and collectors harvested them more frequently. Reproductive potentials (sexual and asexual) were low. Population growth rates were greater than or not significantly different from 1.0, indicating populations maintained or increased in size. Current levels of irapai harvest appear sustainable. DNA analysis of stems and recruits is recommended to understand population composition and stage-specific asexual fecundity. ^

Design of an automated book reader as an assistive technology tool for blind persons

This dissertation introduces a novel automated book reader as an assistive technology tool for persons with blindness. The literature shows extensive work in the area of optical character recognition, but the current methodologies available for the automated reading of books or bound volumes remain inadequate and are severely constrained during document scanning or image acquisition processes. The goal of the book reader design is to automate and simplify the task of reading a book while providing a user-friendly environment with a realistic but affordable system design. This design responds to the main concerns of (a) providing a method of image acquisition that maintains the integrity of the source (b) overcoming optical character recognition errors created by inherent imaging issues such as curvature effects and barrel distortion, and (c) determining a suitable method for accurate recognition of characters that yields an interface with the ability to read from any open book with a high reading accuracy nearing 98%. This research endeavor focuses in its initial aim on the development of an assistive technology tool to help persons with blindness in the reading of books and other bound volumes. But its secondary and broader aim is to also find in this design the perfect platform for the digitization process of bound documentation in line with the mission of the Open Content Alliance (OCA), a nonprofit Alliance at making reading materials available in digital form. The theoretical perspective of this research relates to the mathematical developments that are made in order to resolve both the inherent distortions due to the properties of the camera lens and the anticipated distortions of the changing page curvature as one leafs through the book. This is evidenced by the significant increase of the recognition rate of characters and a high accuracy read-out through text to speech processing. This reasonably priced interface with its high performance results and its compatibility to any computer or laptop through universal serial bus connectors extends greatly the prospects for universal accessibility to documentation.

Automated detection of hematological abnormalities through classification of flow cytometric data patterns

Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^

An automated method for the determination of electroreception thresholds in weakly electric fish

Weakly electric fish produce a dual function electric signal that makes them ideal models for the study of sensory computation and signal evolution. This signal, the electric organ discharge (EOD), is used for communication and navigation. In some families of gymnotiform electric fish, the EOD is a dynamic signal that increases in amplitude during social interactions. Amplitude increase could facilitate communication by increasing the likelihood of being sensed by others or by impressing prospective mates or rivals. Conversely, by increasing its signal amplitude a fish might increase its sensitivity to objects by lowering its electrolocation detection threshold. To determine how EOD modulations elicited in the social context affect electrolocation, I developed an automated and fast method for measuring electroreception thresholds using a classical conditioning paradigm. This method employs a moving shelter tube, which these fish occupy at rest during the day, paired with an electrical stimulus. A custom built and programmed robotic system presents the electrical stimulus to the fish, slides the shelter tube requiring them to follow, and records video of their movements. I trained the electric fish of the genus Sternopygus was trained to respond to a resistive stimulus on this apparatus in 2 days. The motion detection algorithm correctly identifies the responses 91% of the time, with a false positive rate of only 4%. This system allows for a large number of trials, decreasing the amount of time needed to determine behavioral electroreception thresholds. This novel method enables the evaluation the evolutionary interplay between two conflicting sensory forces, social communication and navigation.

Assessing an automated, information -sharing technology in the post "9 -11" era: Do local law enforcement officers think it meets their needs?

In the wake of the “9-11” terrorists' attacks, the U.S. Government has turned to information technology (IT) to address a lack of information sharing among law enforcement agencies. This research determined if and how information-sharing technology helps law enforcement by examining the differences in perception of the value of IT between law enforcement officers who have access to automated regional information sharing and those who do not. It also examined the effect of potential intervening variables such as user characteristics, training, and experience, on the officers' evaluation of IT. The sample was limited to 588 officers from two sheriff's offices; one of them (the study group) uses information sharing technology, the other (the comparison group) does not. Triangulated methodologies included surveys, interviews, direct observation, and a review of agency records. Data analysis involved the following statistical methods: descriptive statistics, Chi-Square, factor analysis, principal component analysis, Cronbach's Alpha, Mann-Whitney tests, analysis of variance (ANOVA), and Scheffe' post hoc analysis. ^ Results indicated a significant difference between groups: the study group perceived information sharing technology as being a greater factor in solving crime and in increasing officer productivity. The study group was more satisfied with the data available to it. As to the number of arrests made, information sharing technology did not make a difference. Analysis of the potential intervening variables revealed several remarkable results. The presence of a strong performance management imperative (in the comparison sheriff's office) appeared to be a factor in case clearances and arrests, technology notwithstanding. As to the influence of user characteristics, level of education did not influence a user's satisfaction with technology, but user-satisfaction scores differed significantly among years of experience as a law enforcement officer and the amount of computer training, suggesting a significant but weak relationship. ^ Therefore, this study finds that information sharing technology assists law enforcement officers in doing their jobs. It also suggests that other variables such as computer training, experience, and management climate should be accounted for when assessing the impact of information technology. ^

ASDN : Automated Software Design Notebook tool

Software Engineering is one of the most widely researched areas of Computer Science. The ability to reuse software, much like reuse of hardware components is one of the key issues in software development. The object-oriented programming methodology is revolutionary in that it promotes software reusability. This thesis describes the development of a tool that helps programmers to design and implement software from within the Smalltalk Environment (an Object- Oriented programming environment). The ASDN tool is part of the PEREAM (Programming Environment for the Reuse and Evolution of Abstract Models) system, which advocates incremental development of software. The Asdn tool along with the PEREAM system seeks to enhance the Smalltalk programming environment by providing facilities for structured development of abstractions (concepts). It produces a document that describes the abstractions that are developed using this tool. The features of the ASDN tool are illustrated by an example.

On the Development of an Automated Design Procedure to Design Optimal Robots

The objective in this work is to build a rapid and automated numerical design method that makes optimal design of robots possible. In this work, two classes of optimal robot design problems were specifically addressed: (1) When the objective is to optimize a pre-designed robot, and (2) when the goal is to design an optimal robot from scratch. In the first case, to reach the optimum design some of the critical dimensions or specific measures to optimize (design parameters) are varied within an established range. Then the stress is calculated as a function of the design parameter(s), the design parameter(s) that optimizes a pre-determined performance index provides the optimum design. In the second case, this work focuses on the development of an automated procedure for the optimal design of robotic systems. For this purpose, Pro/Engineer© and MatLab© software packages are integrated to draw the robot parts, optimize them, and then re-draw the optimal system parts.

Electrochemical Immunosensing of Cortisol in an Automated Microfluidic System Towards Point-of-Care Applications

This dissertation describes the development of a label-free, electrochemical immunosensing platform integrated into a low-cost microfluidic system for the sensitive, selective and accurate detection of cortisol, a steroid hormone co-related with many physiological disorders. Abnormal levels of cortisol is indicative of conditions such as Cushing’s syndrome, Addison’s disease, adrenal insufficiencies and more recently post-traumatic stress disorder (PTSD). Electrochemical detection of immuno-complex formation is utilized for the sensitive detection of Cortisol using Anti-Cortisol antibodies immobilized on sensing electrodes. Electrochemical detection techniques such as cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) have been utilized for the characterization and sensing of the label-free detection of Cortisol. The utilization of nanomaterial’s as the immobilizing matrix for Anti-cortisol antibodies that leads to improved sensor response has been explored. A hybrid nano-composite of Polyanaline-Ag/AgO film has been fabricated onto Au substrate using electrophoretic deposition for the preparation of electrochemical immunosening of cortisol. Using a conventional 3-electrode electrochemical cell, a linear sensing range of 1pM to 1µM at a sensitivity of 66µA/M and detection limit of 0.64pg/mL has been demonstrated for detection of cortisol. Alternately, a self-assembled monolayer (SAM) of dithiobis(succinimidylpropionte) (DTSP) has been fabricated for the modification of sensing electrode to immobilize with Anti-Cortisol antibodies. To increase the sensitivity at lower detection limit and to develop a point-of-care sensing platform, the DTSP-SAM has been fabricated on micromachined interdigitated microelectrodes (µIDE). Detection of cortisol is demonstrated at a sensitivity of 20.7µA/M and detection limit of 10pg/mL for a linear sensing range of 10pM to 200nM using the µIDE’s. A simple, low-cost microfluidic system is designed using low-temperature co-fired ceramics (LTCC) technology for the integration of the electrochemical cortisol immunosensor and automation of the immunoassay. For the first time, the non-specific adsorption of analyte on LTCC has been characterized for microfluidic applications. The design, fabrication technique and fluidic characterization of the immunoassay are presented. The DTSP-SAM based electrochemical immunosensor on µIDE is integrated into the LTCC microfluidic system and cortisol detection is achieved in the microfluidic system in a fully automated assay. The fully automated microfluidic immunosensor hold great promise for accurate, sensitive detection of cortisol in point-of-care applications.