The development of a structured methodology for the construction and integrity control of spreadsheet models

Numerous studies and reported cases have established the seriousness of the frequency and impact of user-generated spreadsheet errors. This thesis presents a structured methodology for spreadsheet model development, which enables improved integrity control of the models. The proposed methodology has the potential to ensure consistency in the development process and produce more comprehensible, reliable and maintainable models, which can reduce the occurrence of user-generated errors. An insight into the nature and properties of spreadsheet errors is essential for the development of a methodology for controlling the integrity of spreadsheet models. An important by-product of the research is the development of a comprehensive classification or taxonomy of the different types of user-generated spreadsheet errors based on a rational taxonomic scheme. Research on the phenomenon of spreadsheet errors has revealed the need to adopt a software engineering based methodology as a framework for spreadsheet development in practical situations. The proposed methodology represents a new approach to the provision of a structured, software engineering based discipline for the development of spreadsheet models. It is established in this thesis that software engineering principles can in fact be applied to the process of spreadsheet model building to help improve the quality of the models. The methodology uses Jackson structures to produce the logical design of the spreadsheet model. This is followed by a technique to derive the physical model, which is then implemented as a spreadsheet. The methodology’s potential for improving the quality of spreadsheet models is demonstrated. In order to evaluate the effectiveness of the proposed framework, the various features of the proposed structured methodology are tested on a range of spreadsheet models through a series of experiments. The results of the tests provide adequate evidence of the methodology’s potential to reduce the occurrence of user-generated errors and enhance the comprehensibility of the models

How does the primate ventral visual stream causally support core object recognition?

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Brain and Cognitive Sciences, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 161-173).Primates are able to rapidly, accurately and effortlessly perform the computationally difficult visual task of invariant object recognition - the ability to discriminate between different objects in the face of high variation in object viewing parameters and background conditions. This ability is thought to rely on the ventral visual stream, a hierarchy of visual cortical areas culminating in inferior temporal (IT) cortex. In particular, decades of research strongly suggests that the population of neurons in IT supports invariant object recognition behavior. However, direct causal evidence for this decoding hypothesis has been equivocal to date, especially beyond the specific case of face-selective sub-regions of IT. This research aims to directly test the general causal role of IT in invariant object recognition. To do so, we first characterized human and macaque monkey behavior over a large behavioral domain consisting of binary discriminations between images of basic-level objects, establishing behavioral metrics and benchmarks for computational models of this behavior. This work suggests that, in the domain of basic-level core object recognition, humans and monkeys are remarkably similar in their behavioral responses, while leading models of the visual system significantly diverge from primate behavior. We then reversibly inactivated individual, millimeter-scale regions of IT via injection of muscimol while monkeys performed several interleaved binary object discrimination tasks. We found that inactivating different millimeter-scale regions of primate IT resulted in different patterns of object recognition deficits, each predicted by the local region's neuronal selectivity. Our results provide causal evidence that IT directly underlies primate object recognition behavior in a topographically organized manner. Taken together, these results establish quantitative experimental constraints for computational models of the ventral visual stream and object recognition behavior.by Rishi Rajalingham.Ph. D

Screening hybrid poplar clones for resistance to the forest tent caterpillar, Malacosoma disstria

Susceptibility of various hybrid poplar clones to attack by Malacosoma disstria larvae was assessed. No-choice experiments were conducted on one week old foliage using first instar larvae. Performance of larvae on each hybrid was also determined. Clones 3389 (DxB), 3729 (NxM), 505508 (MxDT), 750316 (MxT), and 915320 (MxB) were found to be highly resistant to attack by first instar larvae. Susceptible clones were found to belong to the P. x euramericana and P. x generosa Henry crosses. Hybrids with a P. maximowiczii or P. balsamifera parent were found to be consumed at intermediate levels. Consumption was found to be positively correlated to survivorship and negatively correlated to instar duration; instar duration was negatively correlated to survivorship

Antinuclear antibodies in primary osteoarthritis of the knee

Objective: Although osteoarthritis (OA) is widely accepted as a degenerative disease, autoimmune processes are believed to be involved in the pathogenesis. There are limited studies in this area and most of them focused on antibodies against chondrocyte membrane. In an attempt to address the paucity of evidence in this regard, we explored the clinical significance of antinuclear antibody (ANA) in primary osteoarthritis of the knee (OAK). Method: We studied 106 patients with primary osteoarthritis of at least 1 knee and 63 healthy controls from two tertiary centres in Malaysia from September 2005 to May 2012. All subjects were tested for ANA by immunofluorescence testing, and a titer of 1:40 and above was considered positive. Besides, the radiographs of bilateral knees were evaluated for grading, tibiofemoral compartment involvement and total knee replacement (TKR) implants. We compared the clinical characteristics between the ANA positive and ANA negative OAK cases. Results: The incidence of ANA positivity among the cases (39.4 %) was higher than the controls (27 %) but this difference was statistically insignificant (p=0.754). ANA positive cases showed significantly higher incidence of bilateral and Grade IV OAK with higher frequency of TKR. In the multiple regression analysis, bilateral OAK (p< 0.0001; odds ratio 9.00), Grade IV OAK (p<0.001, odds ratio 3.44) and TKR (p=0.009; odds ratio 2.97) remained associated with ANA positivity. Conclusions: ANA test is a potential prognostic tool in primary OAK and its positivity is associated with the clinical outcomes of bilateral, Grade IV OAK and TKR

Novel therapeutic targets in rheumatoid arthritis

Rheumatoid arthritis (RA) is the most common chronic systemic autoimmune disease worldwide. Although incurable, there are available therapies to effectively control the disease activity and minimize the joint damage. Numerous cytokines, enzymes and other forms of proteins have been implicated in the disease process of RA. In general, pharmacological therapies in RA target cytokine pathways. Despite a wide variety of disease modifying antirheumatic drugs (DMARD), a significant proportion of patients remain refractory to the available therapies. Hence, the search for newer drugs with different modes of actions is an ongoing process. The present review aimed to explore novel therapeutic targets in RA based on data from the literature. Inhibitors of spleen tyrosine kinase, choline kinase, galectin 3 and hypoxia-inducible factor may have a promising role in thetreatment of RA. Besides, cell based therapies which may enhance the levels of systemic tristetraprolin could be beneficial in RA

Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes

Humans and animals have a rich and flexible understanding of the physical world, which enables them to infer the underlying dynamical trajectories of objects and events, plausible future states, and use that to plan and anticipate the consequences of actions. However, the neural mechanisms underlying these computations are unclear. We combine a goal-driven modeling approach with dense neurophysiological data and high-throughput human behavioral readouts to directly impinge on this question. Specifically, we construct and evaluate several classes of sensory-cognitive networks to predict the future state of rich, ethologically-relevant environments, ranging from self-supervised end-to-end models with pixel-wise or object-centric objectives, to models that future predict in the latent space of purely static image-based or dynamic video-based pretrained foundation models. We find strong differentiation across these model classes in their ability to predict neural and behavioral data both within and across diverse environments. In particular, we find that neural responses are currently best predicted by models trained to predict the future state of their environment in the latent space of pretrained foundation models optimized for dynamic scenes in a self-supervised manner. Notably, models that future predict in the latent space of video foundation models that are optimized to support a diverse range of sensorimotor tasks, reasonably match both human behavioral error patterns and neural dynamics across all environmental scenarios that we were able to test. Overall, these findings suggest that the neural mechanisms and behaviors of primate mental simulation are thus far most consistent with being optimized to future predict on dynamic, reusable visual representations that are useful for embodied AI more generally.Comment: 17 pages, 6 figure

Serum matrix metalloproteinase-3 predicts radiographic joint damage and functional disability in rheumatoid arthritis

The search for novel biomarkers has taken centre stage in the past decades of research in Rheumatoid Arthritis (RA). The purpose of the present study was to determine the correlation of serum matrix metalloproteinase-3 (MMP-3) with disease activity, joint damage and functional disability in patients with RA. We consecutively recruited RA patients who were under follow-up at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC). Information on the RA disease characteristics were obtained from the medical records and all RA patients were assessed for DAS28 (disease activity score based on 28 joints) and Stanford Health Assessment Questionnaire (HAQ) 8-item Disability Index (HAQ-DI). The hand radiographs of the RA patients were assessed for joint damage using the Modified Sharp Score (MSS). Serum MMP-3 levels from RA patients and healthy controls were measured using the ELISA method. We recruited a total of 77 RA patients and 18 healthy controls. The serum MMP-3 levels were significantly higher among the RA patients (p<0.05). There were significant correlations between the serum MMP-3 levels and MSS (r =0.327) and HAQ-DI (r=0.256), both p<0.05. The mean serum MMP levels in RA patients with radiographic joint erosions was significantly higher than in patients without erosions (p<0.05). Likewise, the subjects with significant functional impairment i.e HAQ-DI ≥1; had significantly higher mean MMP-3 levels compared to RA patients without significant disability (p<0.05). Using multivariate analysis, HAQ-DI remained the independent predictor of serum MMP-3 in RA patients. Serum MMP-3 is a potential biomarker and predictor of radiographic joint damage and functional disability in RA