University of South Florida

An approach to the construction of classifiers from imbalanced datasets is described. A dataset is imbalanced if the classification categories are not approximately equally represented. Often real-world data sets are predominately composed of ``normal'' examples with only a small percentage of ``abnormal'' or ``interesting'' examples. It is also the case that the cost of misclassifying an abnormal (interesting) example as a normal example is often much higher than the cost of the reverse error. Under-sampling of the majority (normal) class has been proposed as a good means of increasing the sensitivity of a classifier to the minority class. This paper shows that a combination of our method of over-sampling the minority (abnormal) class and under-sampling the majority (normal) class can achieve better classifier performance (in ROC space) than only under-sampling the majority class. This paper also shows that a combination of our method of over-sampling the minority class and under-sampling the majority class can achieve better classifier performance (in ROC space) than varying the loss ratios in Ripper or class priors in Naive Bayes. Our method of over-sampling the minority class involves creating synthetic minority class examples. Experiments are performed using C4.5, Ripper and a Naive Bayes classifier. The method is evaluated using the area under the Receiver Operating Characteristic curve (AUC) and the ROC convex hull strategy.

The purposes of this article are to position mixed methods research ( mixed research is a synonym) as the natural complement to traditional qualitative and quantitative research, to present pragmatism as offering an attractive philosophical partner for mixed methods research, and to provide a framework for designing and conducting mixed methods research. In doing this, we briefly review the paradigm “wars” and incompatibility thesis, we show some commonalities between quantitative and qualitative research, we explain the tenets of pragmatism, we explain the fundamental principle of mixed research and how to apply it, we provide specific sets of designs for the two major types of mixed methods research ( mixed-model designs and mixed-method designs), and, finally, we explain mixed methods research as following (recursively) an eight-step process. A key feature of mixed methods research is its methodological pluralism or eclecticism, which frequently results in superior research (compared to monomethod research). Mixed methods research will be successful as more investigators study and help advance its concepts and as they regularly practice it.

Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior. The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts. Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology. Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research. In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact. Three recent exemplars in the research literature are used to demonstrate the application of these guidelines. We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community.

BACKGROUND: We aimed to investigate the influence of oligomeric forms of β-amyloid (Aβ) and the influence of the duration of exposure on the development of tau phosphorylation. METHODS: Aβ oligomers were injected intracranially either acutely into 5-month-old rTg4510 mice and tissue was collected 3 days later, or chronically into 3-month-old mice and tissue was collected 2 months later. Several forms of phosphorylated tau (p-tau), GSK3 (glycogen synthase kinase-3) and microglial and astrocyte activation were measured. RESULTS: Acute injections of Aβ oligomers had no effect on p-tau epitopes but did result in elevation of phosphorylated/activated GSK3 (pGSK3). Chronic infusion of Aβ oligomers into the right hippocampus resulted in 3- to 4-fold elevations in several p-tau isoforms with no changes in total tau levels. A significant elevation in pGSK3 accompanied these changes. Microglial staining with CD68 paralleled the increase in tau phosphorylation, however, CD45 staining was unaffected by Aβ. Control experiments revealed that the infusion of Aβ from the minipumps was largely complete by 10 days after implantation. Thus, the elevation in p-tau 2 months after implantation implies that the changes are quite persistent. CONCLUSION: Soluble Aβ(1-42) oligomers have long-lasting effects on tau phosphorylation in the rTg4510 model, possibly due to elevations in GSK3. These data suggest that even brief elevations in Aβ production, may have enduring impact on the risk for tauopathy.

The Mini-International Neuropsychiatric Interview (M.I.N.I.) is a short structured diagnostic interview, developed jointly by psychiatrists and clinicians in the United States and Europe, for DSM-IV and ICD-10 psychiatric disorders. With an administration time of approximately 15 minutes, it was designed to meet the need for a short but accurate structured psychiatric interview for multicenter clinical trials and epidemiology studies and to be used as a first step in outcome tracking in nonresearch clinical settings. The authors describe the development of the M.I.N.I. and its family of interviews: the M.I.N.I.-Screen, the M.I.N.I.-Plus, and the M.I.N.I.-Kid. They report on validation of the M.I.N.I. in relation to the Structured Clinical Interview for DSM-III-R, Patient Version, the Composite International Diagnostic Interview, and expert professional opinion, and they comment on potential applications for this interview.

BACKGROUND: Usually the researchers performing meta-analysis of continuous outcomes from clinical trials need their mean value and the variance (or standard deviation) in order to pool data. However, sometimes the published reports of clinical trials only report the median, range and the size of the trial. METHODS: In this article we use simple and elementary inequalities and approximations in order to estimate the mean and the variance for such trials. Our estimation is distribution-free, i.e., it makes no assumption on the distribution of the underlying data. RESULTS: We found two simple formulas that estimate the mean using the values of the median (m), low and high end of the range (a and b, respectively), and n (the sample size). Using simulations, we show that median can be used to estimate mean when the sample size is larger than 25. For smaller samples our new formula, devised in this paper, should be used. We also estimated the variance of an unknown sample using the median, low and high end of the range, and the sample size. Our estimate is performing as the best estimate in our simulations for very small samples (n < or = 15). For moderately sized samples (15 < n < or = 70), our simulations show that the formula range/4 is the best estimator for the standard deviation (variance). For large samples (n > 70), the formula range/6 gives the best estimator for the standard deviation (variance). We also include an illustrative example of the potential value of our method using reports from the Cochrane review on the role of erythropoietin in anemia due to malignancy. CONCLUSION: Using these formulas, we hope to help meta-analysts use clinical trials in their analysis even when not all of the information is available and/or reported.

This paper examines cognitive beliefs and affect influencing one’s intention to continue using (continuance) information systems (IS). Expectation-confirmation theory is adapted from the consumer behavior literature and integrated with theoretical and empirical findings from prior IS usage research to theorize a model of IS continuance. Five research hypotheses derived from this model are empirically validated using a field survey of online banking users. The results suggest that users’ continuance intention is determined by their satisfaction with IS use and perceived usefulness of continued IS use. User satisfaction, in turn, is influenced by their confirmation of expectation from prior IS use and perceived usefulness. Post-acceptance perceived usefulness is influenced by users’ confirmation level. This study draws attention to the substantive differences between acceptance and continuance behaviors, theorizes and validates one of the earliest theoretical models of IS continuance, integrates confirmation and user satisfaction constructs within our current understanding of IS use, conceptualizes and creates an initial scale for measuring IS continuance, and offers an initial explanation for the acceptance-discontinuance anomaly.

Two paradigms characterize much of the research in the Information Systems discipline: behavioral science and design science. The behavioral-science paradigm seeks to develop and verify theories that explain or predict human or organizational behavior. The design-science paradigm seeks to extend the boundaries of human and organizational capabilities by creating new and innovative artifacts. Both paradigms are foundational to the IS discipline, positioned as it is at the confluence of people, organizations, and technology. Our objective is to describe the performance of design-science research in Information Systems via a concise conceptual framework and clear guidelines for understanding, executing, and evaluating the research. In the design-science paradigm, knowledge and understanding of a problem domain and its solution are achieved in the building and application of the designed artifact. Three recent exemplars in the research literature are used to demonstrate the application of these guidelines. We conclude with an analysis of the challenges of performing high-quality design-science research in the context of the broader IS community.

The purpose of this article is to examine how the field of mixed methods currently is being defined. The authors asked many of the current leaders in mixed methods research how they define mixed methods research. The authors provide the leaders' definitions and discuss the content found as they searched for the criteria of demarcation. The authors provide a current answer to the question, What is mixed methods research? They also briefly summarize the recent history of mixed methods and list several issues that need additional work as the field continues to advance. They argue that mixed methods research is one of the three major “research paradigms” (quantitative research, qualitative research, and mixed methods research). The authors hope this article will contribute to the ongoing dialogue about how mixed methods research is defined and conceptualized by its practitioners.

ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTFrom Molecules to Crystal Engineering: Supramolecular Isomerism and Polymorphism in Network SolidsBrian Moulton and Michael J. ZaworotkoView Author Information Department of Chemistry, University of South Florida, 4202 East Fowler Avenue, SCA 400, Tampa, Florida 33620 Cite this: Chem. Rev. 2001, 101, 6, 1629–1658Publication Date (Web):May 12, 2001Publication History Received6 September 2000Published online12 May 2001Published inissue 1 June 2001https://pubs.acs.org/doi/10.1021/cr9900432https://doi.org/10.1021/cr9900432research-articleACS PublicationsCopyright © 2001 American Chemical SocietyRequest reuse permissionsArticle Views21321Altmetric-Citations5872LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Cavities,Chemical structure,Crystal structure,Ligands,Molecular structure Get e-Alerts

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Many materials systems are currently under consideration as potential replacements for SiO2 as the gate dielectric material for sub-0.1 μm complementary metal–oxide–semiconductor (CMOS) technology. A systematic consideration of the required properties of gate dielectrics indicates that the key guidelines for selecting an alternative gate dielectric are (a) permittivity, band gap, and band alignment to silicon, (b) thermodynamic stability, (c) film morphology, (d) interface quality, (e) compatibility with the current or expected materials to be used in processing for CMOS devices, (f) process compatibility, and (g) reliability. Many dielectrics appear favorable in some of these areas, but very few materials are promising with respect to all of these guidelines. A review of current work and literature in the area of alternate gate dielectrics is given. Based on reported results and fundamental considerations, the pseudobinary materials systems offer large flexibility and show the most promise toward successful integration into the expected processing conditions for future CMOS technologies, especially due to their tendency to form at interfaces with Si (e.g. silicates). These pseudobinary systems also thereby enable the use of other high-κ materials by serving as an interfacial high-κ layer. While work is ongoing, much research is still required, as it is clear that any material which is to replace SiO2 as the gate dielectric faces a formidable challenge. The requirements for process integration compatibility are remarkably demanding, and any serious candidates will emerge only through continued, intensive investigation.

Distilling the vast literature on this frequently studied variable in organizational behaviour research, Paul E Spector provides the student and professional with a pithy overview of the application, assessment, causes and consequences of job satisfaction. In addition to discussing the nature of and techniques for assessing job satisfaction, the author summarizes the findings concerning how people feel towards work, including: cultural and gender differences in job satisfaction and personal and organizational causes; and potential consequences of job satisfaction and dissatisfaction. Students and researchers will particularly appreciate the extensive list of references and the Job Satisfaction Survey included in the Appendix.

Metal-organic framework-5 (MOF-5) of composition Zn4O(BDC)3 (BDC = 1,4-benzenedicarboxylate) with a cubic three-dimensional extended porous structure adsorbed hydrogen up to 4.5 weight percent (17.2 hydrogen molecules per formula unit) at 78 kelvin and 1.0 weight percent at room temperature and pressure of 20 bar. Inelastic neutron scattering spectroscopy of the rotational transitions of the adsorbed hydrogen molecules indicates the presence of two well-defined binding sites (termed I and II), which we associate with hydrogen binding to zinc and the BDC linker, respectively. Preliminary studies on topologically similar isoreticular metal-organic framework-6 and -8 (IRMOF-6 and -8) having cyclobutylbenzene and naphthalene linkers, respectively, gave approximately double and quadruple (2.0 weight percent) the uptake found for MOF-5 at room temperature and 10 bar.

The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.

short form 36 questions; SIGN, Scottish intercollegiate network;

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts.

Summary The Mini International Neuropsychiatric Interview (MINI) is a short diagnostic structured interview (DSI) developed in France and the United States to explore 17 disorders according to Diagnostic and Statistical Manual (DSM)-III-R diagnostic criteria. It is fully structured to allow administration by non-specialized interviewers. In order to keep it short it focuses on the existence of current disorders. For each disorder, one or two screening questions rule out the diagnosis when answered negatively. Probes for severity, disability or medically explained symptoms are not explored symptom-by-symptom. Two joint papers present the inter-rater and test-retest reliability of the MINI the validity versus the Composite International Diagnostic Interview (CIDI) (this paper) and the Structured Clinical Interview for DSM-III-R patients (SCID) (joint paper). Three-hundred and forty-six patients (296 psychiatric and 50 non-psychiatric) were administered the MINI and the CIDI ‘gold standard’. Forty two were interviewed by two investigators and 42 interviewed subsequently within two days. Interviewers were trained to use both instruments. The mean duration of the interview was 21 min with the MINI and 92 for corresponding sections of the CIDI. Kappa coefficient, sensitivity and specificity were good or very good for all diagnoses with the exception of generalized anxiety disorder (GAD) (kappa = 0.36), agoraphobia (sensitivity = 0.59) and bulimia (kappa = 0.53). Interrater and test-retest reliability were good. The main reasons for discrepancies were identified. The MINI provided reliable DSM-III-R diagnoses within a short time frame, The study permitted improvements in the formulations for GAD and agoraphobia in the current DSM-IV version of the MINI.

It has become widely accepted that correlations between variables measured with the same method, usually self-report surveys, are inflated due to the action of common method variance (CMV), despite a number of sources that suggest the problem is overstated. The author argues that the popular position suggesting CMV automatically affects variables measured with the same method is a distortion and oversimplification of the true state of affairs, reaching the status of urban legend. Empirical evidence is discussed casting doubt that the method itself produces systematic variance in observations that inflates correlations to any significant degree. It is suggested that the term common method variance be abandoned in favor of a focus on measurement bias that is the product of the interplay of constructs and methods by which they are assessed. A complex approach to dealing with potential biases involves their identification and control to rule them out as explanations for observed relationships using a variety of design strategies.

Importance: Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency. Objective: Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin-stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists' diagnoses in a diagnostic setting. Design, Setting, and Participants: Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC). Exposures: Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation. Main Outcomes and Measures: The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor. Results: The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4% [95% CI, 64.3%-80.4%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P < .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95% CI, 0.927-0.998] for the pathologist WOTC). Conclusions and Relevance: In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.