The Effects of Changing Attention and Context in an Awake Offline Processing Period on Visual Long-Term Memory

There is accumulating evidence that sleep as well as awake offline processing is important for the transformation of new experiences into long-term memory (LTM). Yet much remains to be understood about how various cognitive factors influence the efficiency of awake offline processing. In the present study we investigated how changes in attention and context in the immediate period after exposure to new visual information influences LTM consolidation. After presentation of multiple naturalistic scenes within a working memory paradigm, recognition was assessed 30 min and 24 h later in three groups of subjects. One group of subjects engaged in a focused attention task [the Revised Attentional Network Task (R-ANT)] in the 30 min after exposure to the scenes. Another group of subjects remained in the testing room during the 30 min after scene exposure and engaged in no goal- or task-directed activities. A third group of subjects left the testing room and returned 30 min later. A signal detection analysis revealed no significant differences among the three groups in hits, false alarms, or sensitivity on the 30-min recognition task. At the 24-h recognition test, the group that performed the R-ANT made significantly fewer hits compared to the group that left the testing room and did not perform the attention ask. The group that performed the R-ANT and the group that remained in the testing room during the 30-min post-exposure interval made significantly fewer false alarms on the 24-h recognition test compared to the group that left the testing room. The group that stayed in the testing room and engaged in no goal- or task-directed activities exhibited significantly higher sensitivity (d′) compared to the group that left the testing room and the group that performed the R-ANT task. Staying in the same context after exposure to new information and resting quietly with minimal engagement of attention results in the best ability to distinguish old from novel visual stimuli after 24 h. These findings suggest that changes in attentional demands and context during an immediate post-exposure offline processing interval modulate visual memory consolidation in a subtle but significant manner

Real-time context-based sound and color extraction from text

Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (page 69).Narratarium is a system that uses English text or voice input, provided either realtime or off-line, to generate context-specific colors and sound effects. It accomplishes this by employing a variety of machine learning approaches, including commonsense reasoning and natural language processing. It can be highly customized to prioritize different performance metrics, most importantly accuracy and latency, and can be used with any tagged sound corpus. The final product allows users to tell a story in an immersive environment that augments the story-telling experience with thematic colors and background sounds. In this thesis, we present the back-end logic that generates best guesses for contextual colors and sound using text input. We evaluate the performance of these algorithms under different configurations, and demonstrate that performance is acceptable for realistic user scenarios. We also discuss Narratarium's overall design.by Timothy Peng.M. Eng

LecTix : a lecture-multimedia player

Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.Includes bibliographical references (p. 81-85).LecTix 2.0 is a multimedia player designed specifically for the playback of recorded classroom lectures. LecTix 2.0 plays multimedia consisting of synchronized audio, video, and PowerPoint-style slides. In addition to controls commonly found in multi-media players, LecTix 2.0 features controls designed specifically for lecture-multimedia playback such as customizable skip, variable-speed playback with pitch-normalization, and a browsable timeline of slides. LecTix 2.0's features contribute to its being usable, widely available, and extensible. LecTix 2.0's automatic media synchronization and large, externally consistent controls for navigation make for a learnable, memorable, and efficient user interface. LecTix 2.0's open-source implementation using the Java Media Framework allows it to be freely distributable, portable, and convenient to use without a network connection. LecTix 2.0's media class hierarchy, events, and lecture description result in a modular player that can be extended to support new media types without recompilation of the player's core. In addition to presenting LecTix 2.0, this thesis reviews seven players in use today. I compare them to LecTix 2.0 in terms of usability, availability, and extensibility. I also present a case study of the production of lecture multimedia and the use of an early version of LecTix in an introductory algorithms course.by Timothy D. Olsen.M.Eng

Test Characteristics of Urinary Lipoarabinomannan and Predictors of Mortality among Hospitalized HIV-Infected Tuberculosis Suspects in Tanzania.

Tuberculosis is the most common cause of death among patients with HIV infection living in tuberculosis endemic countries, but many cases are not diagnosed pre-mortem. We assessed the test characteristics of urinary lipoarabinomannan (LAM) and predictors of mortality among HIV-associated tuberculosis suspects in Tanzania. We prospectively enrolled hospitalized HIV-infected patients in Dar es Salaam, with ≥2 weeks of cough or fever, or weight loss. Subjects gave 2 mLs of urine to test for LAM using a commercially available ELISA, ≥2 sputum specimens for concentrated AFB smear and solid media culture, and 40 mLs of blood for culture. Among 212 evaluable subjects, 143 (68%) were female; mean age was 36 years; and the median CD4 count 86 cells/mm(3). 69 subjects (33%) had culture confirmation of tuberculosis and 65 (31%) were LAM positive. For 69 cases of sputum or blood culture-confirmed tuberculosis, LAM sensitivity was 65% and specificity 86% compared to 36% and 98% for sputum smear. LAM test characteristics were not different in patients with bacteremia but showed higher sensitivity and lower specificity with decreasing CD4 cell count. Two month mortality was 64 (53%) of 121 with outcomes available. In multivariate analysis there was significant association of mortality with absence of anti-retroviral therapy (p = 0.004) and a trend toward association with a positive urine LAM (p = 0.16). Among culture-negative patients mortality was 9 (75%) of 12 in LAM positive patients and 27 (38%) of 71 in LAM negative patients (p = 0.02). Urine LAM is more sensitive than sputum smear and has utility for the rapid diagnosis of culture-confirmed tuberculosis in this high-risk population. Mortality data raise the possibility that urine LAM may also be a marker for culture-negative tuberculosis

Cellular Characterization of SARS Coronavirus Nucleocapsid

The Severe and Acute Respiratory Syndrome coronavirus (SARS CoV) is a newly-emerged virus that caused an outbreak of atypical pneumonia in the winter of 2002-2003. Polyclonal antibodies raised against the nucleocapsid (N) of the SARS CoV showed the localization of N to the cytoplasm and the nucleolus in virus-infected and N-expressing Vero E6 cells. Like other coronavirus N proteins, the SARS N is probably a phosphoprotein. N protein expressed in mammalian cells is apparently able to “spread” to neighboring cells. For N to spread to neighboring cells, it must be exported out of the expressing cells. This is shown by the immunoprecipitation of N from the culture medium of a stable cell line expressing myc-N. Deletion studies showed that the 27 kD C-terminal domain of N (C1/2) is the minimal region of N that can spread to other cells. The nucleolar localization and spreading of N are artefacts of fixation, reminiscent of other protein-transduction domain (PTD)-containing proteinsWeb of Scienc

A Riemann solver at a junction compatible with a homogenization limit

We consider a junction regulated by a traffic lights, with n incoming roads and only one outgoing road. On each road the Phase Transition traffic model, proposed in [6], describes the evolution of car traffic. Such model is an extension of the classic Lighthill-Whitham-Richards one, obtained by assuming that different drivers may have different maximal speed. By sending to infinity the number of cycles of the traffic lights, we obtain a justification of the Riemann solver introduced in [9] and in particular of the rule for determining the maximal speed in the outgoing road.Comment: 19 page

Tracking Cyber Adversaries with Adaptive Indicators of Compromise

A forensics investigation after a breach often uncovers network and host indicators of compromise (IOCs) that can be deployed to sensors to allow early detection of the adversary in the future. Over time, the adversary will change tactics, techniques, and procedures (TTPs), which will also change the data generated. If the IOCs are not kept up-to-date with the adversary's new TTPs, the adversary will no longer be detected once all of the IOCs become invalid. Tracking the Known (TTK) is the problem of keeping IOCs, in this case regular expressions (regexes), up-to-date with a dynamic adversary. Our framework solves the TTK problem in an automated, cyclic fashion to bracket a previously discovered adversary. This tracking is accomplished through a data-driven approach of self-adapting a given model based on its own detection capabilities. In our initial experiments, we found that the true positive rate (TPR) of the adaptive solution degrades much less significantly over time than the naive solution, suggesting that self-updating the model allows the continued detection of positives (i.e., adversaries). The cost for this performance is in the false positive rate (FPR), which increases over time for the adaptive solution, but remains constant for the naive solution. However, the difference in overall detection performance, as measured by the area under the curve (AUC), between the two methods is negligible. This result suggests that self-updating the model over time should be done in practice to continue to detect known, evolving adversaries.Comment: This was presented at the 4th Annual Conf. on Computational Science & Computational Intelligence (CSCI'17) held Dec 14-16, 2017 in Las Vegas, Nevada, US

A Novel Severe Acute Respiratory Syndrome Coronavirus Protein, U274, is transported to the Cell Surface and undergoes Endocytosis

The severe acute respiratory syndrome coronavirus (SARS-CoV) genome contains open reading frames (ORFs) that encode for several genes that are homologous to proteins found in all known coronaviruses. These are the replicase gene 1a/1b and the four structural proteins, nucleocapsid (N), spike (S), membrane (M), and envelope (E), and these proteins are expected to be essential for the replication of the virus. In addition, this genome also contains nine other potential ORFs varying in length from 39 to 274 amino acids. The largest among these is the first ORF of the second longest subgenomic RNA, and this protein (termed U274 in the present study) consists of 274 amino acids and contains three putative transmembrane domains. Using antibody specific for the C terminus of U274, we show U274 to be expressed in SARS-CoV-infected Vero E6 cells and, in addition to the full-length protein, two other processed forms were also detected. By indirect immunofluorescence, U274 was localized to the perinuclear region, as well as to the plasma membrane, in both transfected and infected cells. Using an N terminus myc-tagged U274, the topology of U274 and its expression on the cell surface were confirmed. Deletion of a cytoplasmic domain of U274, which contains Yxx and diacidic motifs, abolished its transport to the cell surface. In addition, U274 expressed on the cell surface can internalize antibodies from the culture medium into the cells. Coimmunoprecipitation experiments also showed that U274 could interact specifically with the M, E, and S structural proteins, as well as with U122, another protein that is unique to SARS-CoV.Web of Scienc