The digital divide and t-government in the United States: using the technology acceptance model to understand usage

This paper applies the technology acceptance model to explore the digital divide and transformational government (t-government) in the United States. Successful t-government is predicated on citizen adoption and usage of e-government services. The contribution of this research is to enhance our understanding of the factors associated with the usage of e-government services among members of a community on the unfortunate side of the divide. A questionnaire was administered to members, of a techno-disadvantaged public housing community and neighboring households, who partook in training or used the community computer lab. The results indicate that perceived access barriers and perceived ease of use (PEOU) are significantly associated with usage, while perceived usefulness (PU) is not. Among the demographic characteristics, educational level, employment status, and household income all have a significant impact on access barriers and employment is significantly associated with PEOU. Finally, PEOU is significantly related to PU. Overall, the results emphasize that t-government cannot cross the digital divide without accompanying employment programs and programs that enhance citizens’ ease in using such services.     

A pattern recognition based intelligent search method and?two?assignment problem case?studies

Numerous papers based on various search methods across a wide variety of applications have appeared in the literature over recent years. Most of these methods apply the following same approach to address the problems at hand: at each iteration of the search, they first apply their search methods to generate new solutions, then they calculate the objective values (or costs) by taking some constraints into account, and finally they use some strategies to determine the acceptance or rejection of these solutions based upon the calculated objective values. However, the premise of this paper is that calculating the exact objective value of every resulting solution is not a must, particularly for highly constrained problems where such a calculation is costly and the feasible regions are small and disconnected. Furthermore, we believe that for newly-generated solutions, evaluating the quality purely by their objective values is sometimes not the most efficient approach. In many combinatorial problems, there are poor-cost solutions where possibly just one component is misplaced and all others work well. Although these poor-cost solutions can be the intermediate states towards the search of a high quality solution, any cost-oriented criteria for solution acceptance would deem them as inferior and consequently probably suggest a rejection. To address the above issues, we propose a pattern recognition-based framework with the target of designing more intelligent and more flexible search systems. The role of pattern recognition is to classify the quality of resulting solutions, based on the solution structure rather than the solution cost. Hence, the general contributions of this work are in the line of “insights” and recommendations. Two real-world cases of the assignment problem, i.e. the hospital personnel scheduling and educational timetabling, are used as the case studies. For each case, we apply neural networks as the tool for pattern recognition. In addition, we present our theoretical and experimental results in terms of runtime speedup.     

Analysis of patients referred to the gastroenterology service of a VA medical center

We recorded clinical information over a 12-month period on consecutive consultations to the gastroenterology service of the Durham VA Medical Center. Of 902 consultations, 789 were prospectively collected. Eighty-five percent of the patients were between 40 and 70 years old. Seventy-five percent of the referrals were from the internal medicine service. The most frequent reasons for consultation were abdominal pain (19%), GI bleeding (active, 16%; occult, 9%), abnormal results of liver tests (18%), and request for a procedure (11%). Diseases of the liver (32%) and "peptic diseases" (30%) were the most common diagnoses. One or more procedures were done in 71% of consultations. When these data are compared with those of a practicing gastroenterologist, using an identical instrument, it is apparent that trainees' experience with structurally identifiable gastroenterologic disease and with a variety of procedures was similar in scope. There were, however, differences in that the physicians at the VA saw substantially fewer patients with so-called "functional" illness. If these data are applicable to other VA Medical Centers, then the training of physicians in gastroenterology at a VA Medical Center should probably be broadened.     

Acute acid-base disorders. 2. Specific disturbances

Evaluation of the acid-base status of the body requires measurement of bicarbonate (total carbon dioxide) concentration, pH, and partial pressure of CO2 in arterial blood. Calculation of standard bicarbonate and base excess or deficit is not necessary. The normal concentration of free hydrogen ions (H+) is approximately 40 millimoles/liter, which is equivalent to a pH of 7.4. The normal load of fixed acids is 50 to 80 millimoles in 24 hours. A steady state is maintained by excretion of an equal amount of H+ by the kidneys, which at the same time regenerate bicarbonate to replenish buffer stores. Renal excretion of H+ is in the form of titratable acid and ammonium. Synthesis of ammonia can increase severalfold under the stimulus of acidosis. This is the chief mechanism of long-term compensation. Metabolic acidosis can be due to an excessive acid load (endogenous or exogenous), impaired renal excretion of H+, or bicarbonate loss. Determination of the "anion gap" (unmeasured anions) helps to establish the mechanism of acidosis. Acidosis with a normal anion gap is due to either bicarbonate loss or ingestion of certain chloride salts. A gap larger than normal indicates the presence in the body of acids other than acidfying chloride salts. Management of metabolic acidosis requires accurate diagnosis, clear understanding of the mechansim, and individualized treatment. Metabloic alkalosis is due to loss of H+ (usually from stomach or kidneys) or ingestion of alkali. Measurement of urinary chloride helps establish the mechanism of alkalosis. In saline-responsive alkalosis, the urinary chloride level is very low. This is usually due to gastric loss of H+, and the condition responds to administration of saline solution. When the urinary chloride level is only moderately low, the alkalosis is probably not due to gastric loss of H+. This form of alkalosis (saline-resistant) does not respond well to administration of saline solution and requires use of potassium in treatment. Apprpriate compensatory responses to acidosis or alkalosis are critical to survival. Compensation for metabloic acidosis consists of hyperventilation and enhanced renal excretion of H+, chiefly as ammonium. In metabolic alkalosis, compensation is mainly renal excretion of bicarbonate. Respiratory acidosis is due to alveolar hypoventilation. In chronic situations, a compensatory rise in serum bicarbonate concentration is expected. Management consists of treatment of the cause of hypoventilation. Respiratory alkalosis is due to hyperventilation. Treatment requires identification and correction of the cause of hyperventilation.     

A kinetic analysis of the changes in fluorescence on the interaction of 8-anilinonaphthalene-1-sulphonate with submitochondrial particles

Residual deficiency of brain performance in chronic alcoholics after a 5-year abstinency. Brain performance of a group of 43 chronic alcoholics abstinent since 5 years was tested. Some aspects of higher intellectual performance were found to be reduced as compared to a control population. The performance was also better than that of a group of chronic alcoholics abstinent for only one year. The residual deficiency of performance could be interpreted as a "functional psychosyndrome", resulting from chronic sensory deprivation on the base of the alcoholism.     

Properties of diagnostic data distributions

In applications of statistical methods to medical diagnosis, information on patients' diseases and symptoms is collected and the resulting data-base is used to diagnose new patients. The data-structure is complicated by a number of factors, two of which are examined here: selection bias and unstable population. Under reasonable conditions, no correction for selection bias is required when assessing probabilities for diseases based on symptom information, and it is suggested that these "diagnostic distributions" should form the principal object of study. Transformation of these distributions under changing population structure is considered and shown to take on a simple form in many situations. It is argued that the prevailing paradigm of diagnostic statistics, which concentrates on incidence of symptoms for given disease, is largely inappropriate and should be replaced by an emphasis on diagnostic distributions. The generalized logistic model is seen to fit naturally into the new framework.     

Quantitative characterization of nanoprecipitates in irradiated low-alloy steels: advances in the application of FEG-STEM quantitative microanalysis to real materials

The characterization of the solute-enriched features (clusters or nanoprecipitates in irradiated low-alloy steels) requires extremely high spatial and elemental resolution, previously necessitating analysis using atom probe field-ion microscopy. In this investigation, field-emission gun-scanning transmission electron microscope (FEG-STEM) quantitative energy dispersive X-ray (EDX) microanalysis (spectrum imaging) has been applied to the characterization of the irradiation-induced nanoprecipitates in a low-alloy forging steel. Refinements in the EDX data have been possible via the application of multivariate statistical analysis (MSA) to the spectrum images, resulting in significantly reduced noise in the images. Most importantly, MSA permitted the clear identification of other elements in these Ni-enriched nanoprecipitates—including Mn and Cu. The processed X-ray spectrum images also provided direct evidence of the preferential formation of these irradiation-induced features along pre-existing dislocations within the steel, as well as the formation of intragranular nanoprecipitates. This research has provided the first direct X-ray spectrum images of irradiation-induced nanoprecipitates in high Ni A508 Gr4N forging steel, and has demonstrated the significant improvements attainable though the application of MSA techniques to the spectrum images. These results independently confirmed the analyses of the Ni-enriched nanoprecipitates previously conducted by 3D-APFIM, with the performance of the FEG-STEM/EDX technique shown to be comparable to that of the 3D-APFIM technique.     

The Problem of Measurement Model Misspecification in Behavioral and Organizational Research and Some Recommended Solutions.

The purpose of this study was to review the distinction between formative- and reflective-indicator measurement models, articulate a set of criteria for deciding whether measures are formative or reflective, illustrate some commonly researched constructs that have formative indicators, empirically test the effects of measurement model misspecification using a Monte Carlo simulation, and recommend new scale development procedures for latent constructs with formative indicators. Results of the Monte Carlo simulation indicated that measurement model misspecification can inflate unstandardized structural parameter estimates by as much as 400% or deflate them by as much as 80% and lead to Type I or Type II errors of inference, depending on whether the exogenous or the endogenous latent construct is misspecified. Implications of this research are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)