Illinois Institute of Technology
  • Chicago, United States
Recent publications
Maximal biclique enumeration (MBE) in bipartite graphs is a fundamental problem in data mining with widespread applications. Many recent works solve this problem based on the set-enumeration (SE) tree, which sequentially traverses vertices to generate the enumeration tree nodes representing distinct bicliques, then checks whether these bicliques are maximal or not. However, existing MBE algorithms only expand bicliques with untraversed vertices to ensure distinction, which often necessitate extensive node checks to eliminate non-maximal bicliques, resulting in significant computational overhead during the enumeration process. To address this issue, we propose an aggressive set-enumeration (ASE) tree that aggressively expands all bicliques to their maximal form, thus avoiding costly node checks on non-maximal bicliques. This aggressive enumeration may produce multiple duplicate maximal bicliques, but we efficiently eliminate these duplicates by lever-aging the connection between parent and child nodes and conducting low-cost node checking. Additionally, we introduce an aggressive merge-based pruning (AMP) approach that aggressively merges vertices sharing the same local neighbors. This helps prune numerous duplicate node generations caused by subsets of merged vertices. We integrate the AMP approach into the ASE tree, and present the Aggressive Maximal Biclique Enumeration Algorithm (AMBEA). Experimental results show that AMBEA is 1.15× to 5.32× faster than its closest competitor and exhibits better scalability and parallelization capabilities on larger bipartite graphs.
The challenges of data privacy and security posed by data outsourcing are becoming increasingly prevalent. Oblivious RAM (ORAM)-based oblivious data storage guarantees data confidentiality through data encryption and access pattern obfuscation. However, it suffers from performance degradation and low throughput. To address these issues, the concurrency of ORAM in a multi-user scenario has been explored. We investigate several existing concurrent oblivious data storage solutions and discover that a trusted proxy is used to serve concurrent accesses between users and storage, with processing locks involved in the proxy to ensure correctness and prevent conflicts. The proxy-based system is inherently prone to pessimistic concurrency control, and as the number of users grows, a proxy might become a performance bottleneck, causing significant delays. In this study, we propose Opca, a novel oblivious data storage framework that enables optimistic concurrent access. Opca refines the proxy design by temporally storing multiple versions of modified data with labeled timestamps, committing only the latest version to the storage during a separate processing period. Opca is implemented and evaluated in different real-world storage backends with a scalable number of users, and its performance is compared to alternative schemes. Opca outperforms the stateof-the-art concurrent oblivious storage system TaoStore, which relies on a similar system setting. Our results show that Opca can improve 3.77x throughput and reduce 73.5% response time
In this paper, we investigate a sink-driven three-layer flow in a radial Hele-Shaw cell. The three fluids are of different viscosities, with one fluid occupying an annulus-like domain, forming two interfaces with the other two fluids. Using a boundary integral method and a semi-implicit time stepping scheme, we alleviate the numerical stiffness in updating the interfaces and achieve spectral accuracy in space. The interaction between the two interfaces introduces novel dynamics leading to rich pattern formation phenomena, manifested by two typical events: either one of the two interfaces reaches the sink faster than the other (forming cusp-like morphology), or they come very close to each other (suggesting a possibility of interface merging). In particular, the inner interface can be wrapped by the other to have both scenarios. We find that multiple parameters contribute to the dynamics, including the width of the annular region, the location of the sink, and the mobilities of the fluids.
This paper is concerned with the mean curvature flow, which describes the dynamics of a hypersurface whose normal velocity is determined by local mean curvature. We present a Cartesian grid-based method for solving mean curvature flows in two and three space dimensions. The present method embeds a closed hypersurface into a fixed Cartesian grid and decomposes it into multiple overlapping subsets. For each subset, extra tangential velocities are introduced such that marker points on the hypersurface only moves along grid lines. By utilizing an alternating direction implicit (ADI)-type time integration method, the subsets are evolved alternately by solving scalar parabolic partial differential equations on planar domains. The method removes the stiffness using a semi-implicit scheme and has no high-order stability constraint on time step size. Numerical examples in two and three space dimensions are presented to validate the proposed method.
The crystal structure of cariprazine dihydrochloride has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Cariprazine dihydrochloride crystallizes in space group P2 1 /n (#14) with a = 27.26430(14), b = 7.29241(1), c = 12.80879(4) Å, β = 99.5963(2)°, V = 2511.038(8) Å ³ , and Z = 4 at 295 K. The crystal structure consists of layers of cations parallel to the bc -plane. The cations stack along the b -axis. Each H atom on the two protonated N atoms participates in a discrete N–H⋯Cl hydrogen bond. One Cl anion acts as an acceptor in two of these bonds, while the other Cl is an acceptor in only one bond. The result is to link the cations and anions into columns parallel to the b -axis. The powder pattern has been submitted to the ICDD for inclusion in the Powder Diffraction File™ (PDF®).
According to the justified true belief (JTB) account of knowledge, people can truly know something only if they have a belief that is both justified and true (i.e., knowledge is JTB). This account was challenged by Gettier, who argued that JTB does not explain knowledge attributions in certain situations, later called “Gettier-type cases,” wherein protagonists are justified in believing something to be true, but their belief was correct only because of luck. Laypeople may not attribute knowledge to protagonists with justified but only luckily true beliefs. Although some research has found evidence for these so-called Gettier intuitions, Turri et al. found no evidence that participants attributed knowledge in a counterfeit-object Gettier-type case differently than in a matched case of JTB. In a large-scale, cross-cultural conceptual replication of Turri and colleagues’ Experiment 1 ( N = 4,724) using a within-participants design and three vignettes across 19 geopolitical regions, we did find evidence for Gettier intuitions; participants were 1.86 times more likely to attribute knowledge to protagonists in standard cases of JTB than to protagonists in Gettier-type cases. These results suggest that Gettier intuitions may be detectable across different scenarios and cultural contexts. However, the size of the Gettier intuition effect did vary by vignette, and the Turri et al. vignette produced the smallest effect, which was similar in size to that observed in the original study. Differences across vignettes suggest that epistemic intuitions may also depend on contextual factors unrelated to the criteria of knowledge, such as the characteristics of the protagonist being evaluated.
Background Self-stigma is associated with low self-esteem, high shame and reduced drinking-refusal self-efficacy in people with alcohol use disorder (AUD). The Self-Stigma in Alcohol-Dependence Scale-Short Form (SSAD-SF) was designed to enable a brief, but valid assessment of AUD self-stigma. Methods We reduced the 64-item SSAD, originally derived from 16 stereotypes towards people with AUD, by removing the most offensive items based on perspectives of people with lived experience. The newly created scale was then assessed and validated in a cross-sectional study involving 156 people reporting alcohol issues in various treatment settings. Results The 20-item SSAD-SF includes five stereotypes, with good internal consistency for each subscale and the overall scale. It reflects the four-stage progressive model of self-stigmatization with decreasing scores over the stages awareness of stereotypes, agreement with stereotypes, self-application of stereotypes, and harmful consequences for self-esteem, and highest correlations between adjacent stages. The subscales apply and harm were associated with internalized stigma, shame, reduced self-esteem, and lower drinking-refusal self-efficacy, as supported by multivariate regression models. Discussion The SSAD-SF is a valid instrument for measuring the process of self-stigmatization in people with AUD. Self-stigma is a consistent predictor of reduced self-esteem, higher shame and lower drinking-refusal self-efficacy in people with AUD. We discuss merits of the progressive model for understanding and addressing self-stigma in AUD.
Objective. Deep learning (DL) is becoming increasingly important in generating attenuation maps for accurate attenuation correction (AC) in cardiac perfusion SPECT imaging. Typically, DL models take inputs from initial reconstructed SPECT images, which are performed on the photopeak window and often also on scatter windows. While prior studies have demonstrated improvements in DL performance when scatter window images are incorporated into the DL input, the comprehensive analysis of the impact of employing different scatter windows remains unassessed. Additionally, existing research mainly focuses on applying DL to SPECT scans obtained at clinical standard count levels. This study aimed to assess utilities of DL from two aspects: (1) investigating the impact when different scatter windows were used as input to DL, and (2) evaluating the performance of DL when applied on SPECT scans acquired at a reduced count level. Approach. We utilized 1517 subjects, with 386 subjects for testing and the remaining 1131 for training and validation. Main results. The results showed that as scatter window width increased from 4% to 30%, a slight improvement was observed in DL estimated attenuation maps. The application of DL models to quarter-count (¼-count) SPECT scans, compared to full-count scans, showed a slight reduction in performance. Nonetheless, discrepancies across different scatter window configurations and between count levels were minimal, with all normalized mean square error (NMSE) values remaining within 2.1% when comparing the different DL attenuation maps to the reference CT maps. For attenuation corrected SPECT slices using DL estimated maps, NMSE values were within 0.5% when compared to CT correction. Significance. This study, leveraging an extensive clinical dataset, showed that the performance of DL seemed to be consistent across the use of varied scatter window settings. Moreover, our investigation into reduced count studies indicated that DL could provide accurate AC even at a ¼-count level.
Veterinary diagnostic laboratories (VDLs) play a critical role in screening both human and animal samples for SARS-CoV-2. To evaluate the SARS-CoV-2 detection methods used by VDLs, a proficiency test was performed by the US Food and Drug Administration’s Veterinary Laboratory and Investigation and Response Network in collaboration with two other organizations. Thirty-two sets of 12 blind-coded samples were prepared by fortifying Molecular Transport Medium (MTM) or feline feces with SARS-CoV-2 Omicron variant or non-SARS-CoV-2 equine coronavirus RNA at various concentrations and shipped to 32 participants for blinded (unbiased) analysis. Results were analyzed according to the principles of International Organization for Standardization 16140-2:2016 using two approaches such as establishing the rate of detection (ROD) and the success rate by applying the analysis of binary outcome by logit approach. ROD provided the overall assessment of laboratories performance, whereas the novel logit approach provided an insight to more specific analysis based on the complexity of each sample. The ROD was 83% and 98% for MTM samples at 200 and 20000 genome copies per 100 µL, respectively. Fecal samples were classified as challenging exploratory, and results were not included in the assessment of performance but discussion purposes only. Fecal samples exhibited matrix interference impacting the performance. The ROD was 44% and 89% for fecal samples at 2000 and 20000 genome copies per 100 µL, respectively. The non-COVID coronavirus RNA, which was used to address the specificity, did not interfere with methods used. Establishing the success rate by evaluating the qualitative results (detected/not detected) applying a logit approach revealed that, out of thirty-two participants, twenty-eight had satisfactory results, one participant had unsatisfactory results, and three participants had questionable results for MTM samples. For fecal samples, three participants out of thirty-two did not meet the expectations at higher concentrations. Lower concentrations of fecal samples were excluded from this analysis. Again, the fecal samples were considered as challenge samples and the results were provided to assist participants in their continuous efforts to improve their performance and not to evaluate their performance.
Background Criminal legal system-involved individuals with serious mental illness (SMI) experience more challenges accessing mental health and other community services than those without a history of criminal legal system involvement. A formative qualitative study was conducted to explore feasibility and acceptability and inform the adaptation of a mental health peer navigation intervention for individuals with SMI reentering the community after jail incarceration. Methods In-depth qualitative interviews and focus-group discussions were conducted with mental health peer navigators (i.e., certified mental health peer support specialists, peer recovery coaches) and individuals with lived experience of SMI and criminal legal system involvement (N = 20 total). Data were analyzed using applied thematic analysis. Results Four major themes emerged: (1) Feasibility and acceptability of peer-provided services: all participants reported that peer navigation services would be feasible and acceptable for individuals with SMI reentering the community after jail incarceration; (2) roles of peer navigators in addressing barriers to care: peers can address barriers to care experienced during community reentry and contribute towards service linkage/engagement; (3) shared identity and combating stigma: having a shared identity with peer navigators may minimize the impact of stigma and make it easier for clients with multiple marginalized identities to seek support; and (4) peer navigator skills and recommendations for the planned program: essential peer navigation skills include authenticity, reliability, active listening, advocacy, trauma-informed care, motivational interviewing, and empathy. Recommendations for the planned program include initiating services while clients are in custody, emphasizing the voluntary nature of peer support, knowing the limits of a peer navigation intervention, and offering support for peer navigators while on the job. Conclusion Participants saw peer navigation services for individuals with SMI with criminal legal system involvement as potentially feasible and acceptable. Such programs may enhance their impact by offering supportive supervision, emphasizing the voluntary nature of the service, and acknowledging recovery as a self-directed endeavor.
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5,466 members
Norma I. Scagnoli
  • Center for Learning Innovations
John Kilbane
  • Division of Biology
Douglas Cork
  • Department of Biological and Chemical Sciences
Fred J Hickernell
  • Department of Applied Mathematics
Rajendra Mehta
  • Department of Biological and Chemical Sciences
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