Factors associated with social work student satisfaction with field placements in child welfare

This study was conducted during the 1994-1995 academic year. Seven social work education programs in the state of Florida, all accredited by the Council on Social Work Education, participated in this study. Graduate and undergraduate social work students in child welfare field placements, and their field instructors, were surveyed during the Spring 1995 semester to assess their satisfaction with field placements in this area and the relationship of this satisfaction to employment interests and field placement recommendations.^ The majority of social work students responding to this survey were generally satisfied with several aspects of their field placements--the learning, field work program, field instructor, child welfare agency, and overall field experience. The field instructors were generally more satisfied than the students, but only statistically different from the students in the areas of satisfaction with the field work program and the child welfare agency. Multiple regression analysis revealed that learning assignment opportunities, field instructor relationship characteristics, placement preference, and pre-placement interview contributed to the prediction of student satisfaction.^ Student satisfaction in field placement was significantly related to the acceptance of employment, if offered, and the recommendation of the field placement to other students. Logistic regression analysis revealed that satisfaction with the child welfare agency was the greatest contributor to the prediction of acceptance of employment, and satisfaction with the field work program was the greatest contributor to the prediction of field placement recommendation. ^

Improved sampling and detection of ignitable liquid residues and explosives by mass spectrometry and ion mobility spectrometry

Fire debris evidence is submitted to crime laboratories to determine if an ignitable liquid (IL) accelerant was used to commit arson. An ignitable liquid residue (ILR) may be difficult to analyze due to interferences, complex matrices, degradation, and low concentrations of analytes. Debris from an explosion and pre-detonated explosive compounds are not trivial to detect and identify due to sampling difficulties, complex matrices, and extremely low amounts (nanogram) of material present. The focus of this research is improving the sampling and detection of ILR and explosives through enhanced sensitivity, selectivity, and field portable instrumentation. Solid Phase MicroExtraction (SPME) enhanced the extraction of ILR by two orders of magnitude over conventional activated charcoal strip (ACS) extraction. Gas chromatography tandem mass spectrometry (GC/MS/MS) improved sensitivity of ILR by one order of magnitude and explosives by two orders of magnitude compared to gas chromatography mass spectrometry (GC/MS). Improvements in sensitivity were attributed to enhanced selectivity. An interface joining SPME to ion mobility spectrometry (IMS) has been constructed and evaluated to improve field detection of hidden explosives. The SPME-IMS interface improved the detection of volatile and semi-volatile explosive compounds and successfully adapted the IMS from a particle sampler into a vapor sampler. ^

Intuition and its component parts in the heuristic processing of deception detection: Hunch, *evidence, and reliance on intuitive efficacy

Rated trust in intuitive efficacy (measured as trust, belief, use, accuracy and weighting of intuition) was investigated as a predictor of self-designated use of intuitive (hunch and hunch plus evidential belief) vs. deliberative (evidential belief and evidential belief plus hunch) deception detection judgments and actual accuracy. Twenty-nine student participants were filmed as they made true and deceptive statements about their everyday activities on a given evening (last Friday night), and college students (N=238) judged 20 (10=true, 10=deceptive) of these filmed statements as truthful or deceptive. Participants provided ratings of reliance on hunches vs. evidential belief, confidence in film judgments, intuitive efficacy, accuracy in deception detection, reliance on cues to deception, and experiences with intuition. Generalized estimated equation modeling using binary logistics demonstrated accuracy in identifying true vs. deceptive statements was predicted by film number, hunch-evidence ratings, weighting of intuition, and total cues cited. Weighting of intuition was predictive of accuracy across participants, with higher weighting predictive of higher accuracy in general. Participants who cited evidential belief plus hunch and moderate to high weighting incorrectly reversed their true vs. deceptive judgments. Accuracy for true statements was higher for hunches and hunch plus evidential belief, whereas accuracy for deceptive statements was higher for evidential belief Accuracy for participants who relied on evidential belief plus hunch was at chance. Subjective experiences underlying judgments differed by participant and type of film viewed (true vs. deceptive) and were predicted by hunch-evidence ratings, trust, use, intuitive accuracy, and total cues cited. Trust predicted increases in judging films to be true, whereas use and accuracy predicted increases in judging films as deceptive; none were predictive of accuracy. Increased number of cues cited predicted judgments of deception, whereas decreased number of cues cited predicted truth. The study concluded that participants have the capacity to self-define their judgments as subjectively vs. deliberately based, provide subjective assessments of the influence of intuitive vs. objective information on their judgments, and can apply this self-knowledge, through effective weighting of intuition vs. other types of information, in making accurate judgments of true and deceptive everyday statements.

Factors associated with social work student satisfaction with field placements in child welfare by Diane Elias Alperin.

This study was conducted during the 1994-1995 academic year. Seven social work education programs in the state of Florida, all accredited by the Council on Social Work Education, participated in this study. Graduate and undergraduate social work students in child welfare field placements, and their field instructors, were surveyed during the Spring 1995 semester to assess their satisfaction with field placements ii this area and the relationship of this satisfaction to employment interests and field placement recommendations. The majority of social work students responding to this survey were generally satisfied with several aspects of their field placements--the learning, field work program, field instructor, child welfare agency, and overall field experience. The field instructors were generally more satisfied than the students, but only statistically different from the students in the areas of satisfaction with the field work program and the child welfare agency. Multiple regression analysis revealed that learning assignment opportunities, field instructor relationship characteristics, placement preference, and pre-placement interview contributed to the prediction of student satisfaction. Student satisfaction in field placement was significantly related to the acceptance of employment, if offered, and the recommendation of the field placement to other students. Logistic regression analysis revealed that satisfaction with the child welfare agency was the greatest contributor to the prediction of acceptance of employment, and satisfaction with the field work program was the greatest contributor to the prediction of field placement recommendation.

A research platform for artificial neural networks with applications in pediatric epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and nonepileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that (1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and (2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Improved sampling, pre-concentration, and detection of hidden explosives and illicit drugs by a novel solid phase microextraction geometry coupled to ion mobility spectrometry

The 9/11 Act mandates the inspection of 100% of cargo shipments entering the U.S. by 2012 and 100% inspection of air cargo by March 2010. So far, only 5% of inbound shipping containers are inspected thoroughly while air cargo inspections have fared better at 50%. Government officials have admitted that these milestones cannot be met since the appropriate technology does not exist. This research presents a novel planar solid phase microextraction (PSPME) device with enhanced surface area and capacity for collection of the volatile chemical signatures in air that are emitted from illicit compounds for direct introduction into ion mobility spectrometers (IMS) for detection. These IMS detectors are widely used to detect particles of illicit substances and do not have to be adapted specifically to this technology. For static extractions, PDMS and sol-gel PDMS PSPME devices provide significant increases in sensitivity over conventional fiber SPME. Results show a 50–400 times increase in mass detected of piperonal and a 2–4 times increase for TNT. In a blind study of 6 cases suspected to contain varying amounts of MDMA, PSPME-IMS correctly detected 5 positive cases with no false positives or negatives. One of these cases had minimal amounts of MDMA resulting in a false negative response for fiber SPME-IMS. A La (dihed) phase chemistry has shown an increase in the extraction efficiency of TNT and 2,4-DNT and enhanced retention over time. An alternative PSPME device was also developed for the rapid (seconds) dynamic sampling and preconcentration of large volumes of air for direct thermal desorption into an IMS. This device affords high extraction efficiencies due to strong retention properties under ambient conditions resulting in ppt detection limits when 3.5 L of air are sampled over the course of 10 seconds. Dynamic PSPME was used to sample the headspace over the following: MDMA tablets (12–40 ng detected of piperonal), high explosives (Pentolite) (0.6 ng detected of TNT), and several smokeless powders (26–35 ng of 2,4-DNT and 11–74 ng DPA detected). PSPME-IMS technology is flexible to end-user needs, is low-cost, rapid, sensitive, easy to use, easy to implement, and effective. ^

Development of a dynamic headspace concentration technique for the non-contact sampling of human odor samples and the creation of canine training aids

Human scent and human remains detection canines are used to locate living or deceased humans under many circumstances. Human scent canines locate individual humans on the basis of their unique scent profile, while human remains detection canines locate the general scent of decomposing human remains. Scent evidence is often collected by law enforcement agencies using a Scent Transfer Unit, a dynamic headspace concentration device. The goals of this research were to evaluate the STU-100 for the collection of human scent samples, and to apply this method to the collection of living and deceased human samples, and to the creation of canine training aids. The airflow rate and collection material used with the STU-100 were evaluated using a novel scent delivery method. Controlled Odor Mimic Permeation Systems were created containing representative standard compounds delivered at known rates, improving the reproducibility of optimization experiments. Flow rates and collection materials were compared. Higher air flow rates usually yielded significantly less total volatile compounds due to compound breakthrough through the collection material. Collection from polymer and cellulose-based materials demonstrated that the molecular backbone of the material is a factor in the trapping and releasing of compounds. The weave of the material also affects compound collection, as those materials with a tighter weave demonstrated enhanced collection efficiencies. Using the optimized method, volatiles were efficiently collected from living and deceased humans. Replicates of the living human samples showed good reproducibility; however, the odor profiles from individuals were not always distinguishable from one another. Analysis of the human remains samples revealed similarity in the type and ratio of compounds. Two types of prototype training aids were developed utilizing combinations of pure compounds as well as volatiles from actual human samples concentrated onto sorbents, which were subsequently used in field tests. The pseudo scent aids had moderate success in field tests, and the Odor pad aids had significant success. This research demonstrates that the STU-100 is a valuable tool for dog handlers and as a field instrument; however, modifications are warranted in order to improve its performance as a method for instrumental detection.

Algorithms for efficient transaction management and consistent queries in client -server semantic object-oriented parallel databases

Large read-only or read-write transactions with a large read set and a small write set constitute an important class of transactions used in such applications as data mining, data warehousing, statistical applications, and report generators. Such transactions are best supported with optimistic concurrency, because locking of large amounts of data for extended periods of time is not an acceptable solution. The abort rate in regular optimistic concurrency algorithms increases exponentially with the size of the transaction. The algorithm proposed in this dissertation solves this problem by using a new transaction scheduling technique that allows a large transaction to commit safely with significantly greater probability that can exceed several orders of magnitude versus regular optimistic concurrency algorithms. A performance simulation study and a formal proof of serializability and external consistency of the proposed algorithm are also presented.^ This dissertation also proposes a new query optimization technique (lazy queries). Lazy Queries is an adaptive query execution scheme which optimizes itself as the query runs. Lazy queries can be used to find an intersection of sub-queries in a very efficient way, which does not require full execution of large sub-queries nor does it require any statistical knowledge about the data.^ An efficient optimistic concurrency control algorithm used in a massively parallel B-tree with variable-length keys is introduced. B-trees with variable-length keys can be effectively used in a variety of database types. In particular, we show how such a B-tree was used in our implementation of a semantic object-oriented DBMS. The concurrency control algorithm uses semantically safe optimistic virtual "locks" that achieve very fine granularity in conflict detection. This algorithm ensures serializability and external consistency by using logical clocks and backward validation of transactional queries. A formal proof of correctness of the proposed algorithm is also presented. ^

Slow Isotope Turnover Rates and Low Discrimination Values in the American Alligator: Implications for Interpretation of Ectotherm Stable Isotope Data

Stable isotope analysis has become a standard ecological tool for elucidating feeding relationships of organisms and determining food web structure and connectivity. There remain important questions concerning rates at which stable isotope values are incorporated into tissues (turnover rates) and the change in isotope value between a tissue and a food source (discrimination values). These gaps in our understanding necessitate experimental studies to adequately interpret field data. Tissue turnover rates and discrimination values vary among species and have been investigated in a broad array of taxa. However, little attention has been paid to ectothermic top predators in this regard. We quantified the turnover rates and discrimination values for three tissues (scutes, red blood cells, and plasma) in American alligators (Alligator mississippiensis). Plasma turned over faster than scutes or red blood cells, but turnover rates of all three tissues were very slow in comparison to those in endothermic species. Alligator δ15N discrimination values were surprisingly low in comparison to those of other top predators and varied between experimental and control alligators. The variability of δ15N discrimination values highlights the difficulties in using δ15N to assign absolute and possibly even relative trophic levels in field studies. Our results suggest that interpreting stable isotope data based on parameter estimates from other species can be problematic and that large ectothermic tetrapod tissues may be characterized by unique stable isotope dynamics relative to species occupying lower trophic levels and endothermic tetrapods.

A Cross-Generational Analysis of Spanish-to-English Lexico-Semantic Phenomena in Emerging Miami English

Sociolinguists have documented the substrate influence of various languages on the formation of dialects in numerous ethnic-regional setting throughout the United States. This literature shows that while phonological and grammatical influences from other languages may be instantiated as durable dialect features, lexical phenomena often fade over time as ethnolinguistic communities assimilate with contiguous dialect groups. In preliminary investigations of emerging Miami Latino English, we have observed that lexical forms based on Spanish lexical forms are not only ubiquitous among the speech of the first generation Cuban Americans but also of the second. Examples, observed in field work, casual observation, and studied formally in an experimental context include the following: “get down from the car,” which derives from the Spanish equivalent, bajar del carro instead of “get out of the car”. The translation task administered to thirty-one participants showed a variety lexical phenomena are still maintained at equal or higher frequencies.

A Research Platform for Artificial Neural Networks with Applications in Pediatric Epilepsy

This dissertation established a state-of-the-art programming tool for designing and training artificial neural networks (ANNs) and showed its applicability to brain research. The developed tool, called NeuralStudio, allows users without programming skills to conduct studies based on ANNs in a powerful and very user friendly interface. A series of unique features has been implemented in NeuralStudio, such as ROC analysis, cross-validation, network averaging, topology optimization, and optimization of the activation function’s slopes. It also included a Support Vector Machines module for comparison purposes. Once the tool was fully developed, it was applied to two studies in brain research. In the first study, the goal was to create and train an ANN to detect epileptic seizures from subdural EEG. This analysis involved extracting features from the spectral power in the gamma frequencies. In the second application, a unique method was devised to link EEG recordings to epileptic and non-epileptic subjects. The contribution of this method consisted of developing a descriptor matrix that can be used to represent any EEG file regarding its duration and the number of electrodes. The first study showed that the inter-electrode mean of the spectral power in the gamma frequencies and its duration above a specific threshold performs better than the other frequencies in seizure detection, exhibiting an accuracy of 95.90%, a sensitivity of 92.59%, and a specificity of 96.84%. The second study yielded that Hjorth’s parameter activity is sufficient to accurately relate EEG to epileptic and non-epileptic subjects. After testing, accuracy, sensitivity and specificity of the classifier were all above 0.9667. Statistical tests measured the superiority of activity at over 99.99 % certainty. It was demonstrated that 1) the spectral power in the gamma frequencies is highly effective in locating seizures from EEG and 2) activity can be used to link EEG recordings to epileptic and non-epileptic subjects. These two studies required high computational load and could be addressed thanks to NeuralStudio. From a medical perspective, both methods proved the merits of NeuralStudio in brain research applications. For its outstanding features, NeuralStudio has been recently awarded a patent (US patent No. 7502763).

Effects of Altered Prenatal Sensory Stimulation on Postnatal Contingency Learning in Bobwhite Quail Neonates (Colinus Virginianus)

Preterm infants are exposed to high levels of modified early sensory experience in the Neonatal Intensive Care Unit (NICU). Reports that preterm infants show deficits in contingency detection and learning when compared to full-term infants (Gekoski, Fagen, & Pearlman, 1984; Haley, Weinberg, & Grunau, 2006) suggest that their exposure to atypical amounts or types of sensory stimulation might contribute to deficits in these critical skills. Experimental modifications of sensory experience are severely limited with human fetuses and preterm infants, and previous studies with precocial bird embryos that develop in ovo have proven useful to assess the effects of modified perinatal sensory experience on subsequent perceptual and cognitive development. In the current study, I assessed whether increasing amounts of prenatal auditory or visual stimulation can interfere with quail neonates’ contingency detection and contingency learning in the days following hatching. Results revealed that augmented prenatal visual stimulation prior to hatching does not disrupt the ability of bobwhite chicks to recognize and prefer information learned in a contingent fashion, whereas augmented prenatal auditory stimulation disrupted the ability of chicks to benefit from contingently presented information. These results suggest that specific types of augmented prenatal stimulation that embryos receive during late prenatal period can impair the ability to learn and remember contingently presented information. These results provide testable developmental hypotheses, with the goal of improving the developmental care and management of preterm neonates in the NICU setting.

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.