Implementing EM and Viterbi algorithms for Hidden Markov Model in linear memory

<p>Abstract</p> <p>Background</p> <p>The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clustering. A linear memory procedure recently proposed by <it>Miklós, I. and Meyer, I.M. </it>describes a memory sparse version of the Baum-Welch algorithm with modifications to the original probabilistic table topologies to make memory use independent of sequence length (and linearly dependent on state number). The original description of the technique has some errors that we amend. We then compare the corrected implementation on a variety of data sets with conventional and checkpointing implementations.</p> <p>Results</p> <p>We provide a correct recurrence relation for the emission parameter estimate and extend it to parameter estimates of the Normal distribution. To accelerate estimation of the prior state probabilities, and decrease memory use, we reverse the originally proposed forward sweep. We describe different scaling strategies necessary in all real implementations of the algorithm to prevent underflow. In this paper we also describe our approach to a linear memory implementation of the Viterbi decoding algorithm (with linearity in the sequence length, while memory use is approximately independent of state number). We demonstrate the use of the linear memory implementation on an extended Duration Hidden Markov Model (DHMM) and on an HMM with a spike detection topology. Comparing the various implementations of the Baum-Welch procedure we find that the checkpointing algorithm produces the best overall tradeoff between memory use and speed. In cases where sequence length is very large (for Baum-Welch), or state number is very large (for Viterbi), the linear memory methods outlined may offer some utility.</p> <p>Conclusion</p> <p>Our performance-optimized Java implementations of Baum-Welch algorithm are available at <url>http://logos.cs.uno.edu/~achurban</url>. The described method and implementations will aid sequence alignment, gene structure prediction, HMM profile training, nanopore ionic flow blockades analysis and many other domains that require efficient HMM training with EM.</p

Global Impact of the COVID-19 Pandemic on Cerebral Venous Thrombosis and Mortality

Background and purpose: Recent studies suggested an increased incidence of cerebral venous thrombosis (CVT) during the coronavirus disease 2019 (COVID-19) pandemic. We evaluated the volume of CVT hospitalization and in-hospital mortality during the 1st year of the COVID-19 pandemic compared to the preceding year. Methods: We conducted a cross-sectional retrospective study of 171 stroke centers from 49 countries. We recorded COVID-19 admission volumes, CVT hospitalization, and CVT in-hospital mortality from January 1, 2019, to May 31, 2021. CVT diagnoses were identified by International Classification of Disease-10 (ICD-10) codes or stroke databases. We additionally sought to compare the same metrics in the first 5 months of 2021 compared to the corresponding months in 2019 and 2020 (ClinicalTrials.gov Identifier: NCT04934020). Results: There were 2,313 CVT admissions across the 1-year pre-pandemic (2019) and pandemic year (2020); no differences in CVT volume or CVT mortality were observed. During the first 5 months of 2021, there was an increase in CVT volumes compared to 2019 (27.5%; 95% confidence interval [CI], 24.2 to 32.0; P&lt;0.0001) and 2020 (41.4%; 95% CI, 37.0 to 46.0; P&lt;0.0001). A COVID-19 diagnosis was present in 7.6% (132/1,738) of CVT hospitalizations. CVT was present in 0.04% (103/292,080) of COVID-19 hospitalizations. During the first pandemic year, CVT mortality was higher in patients who were COVID positive compared to COVID negative patients (8/53 [15.0%] vs. 41/910 [4.5%], P=0.004). There was an increase in CVT mortality during the first 5 months of pandemic years 2020 and 2021 compared to the first 5 months of the pre-pandemic year 2019 (2019 vs. 2020: 2.26% vs. 4.74%, P=0.05; 2019 vs. 2021: 2.26% vs. 4.99%, P=0.03). In the first 5 months of 2021, there were 26 cases of vaccine-induced immune thrombotic thrombocytopenia (VITT), resulting in six deaths. Conclusions: During the 1st year of the COVID-19 pandemic, CVT hospitalization volume and CVT in-hospital mortality did not change compared to the prior year. COVID-19 diagnosis was associated with higher CVT in-hospital mortality. During the first 5 months of 2021, there was an increase in CVT hospitalization volume and increase in CVT-related mortality, partially attributable to VITT

Global Impact of the COVID-19 Pandemic on Cerebral Venous Thrombosis and Mortality.

BACKGROUND AND PURPOSE: Recent studies suggested an increased incidence of cerebral venous thrombosis (CVT) during the coronavirus disease 2019 (COVID-19) pandemic. We evaluated the volume of CVT hospitalization and in-hospital mortality during the 1st year of the COVID-19 pandemic compared to the preceding year. METHODS: We conducted a cross-sectional retrospective study of 171 stroke centers from 49 countries. We recorded COVID-19 admission volumes, CVT hospitalization, and CVT in-hospital mortality from January 1, 2019, to May 31, 2021. CVT diagnoses were identified by International Classification of Disease-10 (ICD-10) codes or stroke databases. We additionally sought to compare the same metrics in the first 5 months of 2021 compared to the corresponding months in 2019 and 2020 (ClinicalTrials.gov Identifier: NCT04934020). RESULTS: There were 2,313 CVT admissions across the 1-year pre-pandemic (2019) and pandemic year (2020); no differences in CVT volume or CVT mortality were observed. During the first 5 months of 2021, there was an increase in CVT volumes compared to 2019 (27.5%; 95% confidence interval [CI], 24.2 to 32.0; P<0.0001) and 2020 (41.4%; 95% CI, 37.0 to 46.0; P<0.0001). A COVID-19 diagnosis was present in 7.6% (132/1,738) of CVT hospitalizations. CVT was present in 0.04% (103/292,080) of COVID-19 hospitalizations. During the first pandemic year, CVT mortality was higher in patients who were COVID positive compared to COVID negative patients (8/53 [15.0%] vs. 41/910 [4.5%], P=0.004). There was an increase in CVT mortality during the first 5 months of pandemic years 2020 and 2021 compared to the first 5 months of the pre-pandemic year 2019 (2019 vs. 2020: 2.26% vs. 4.74%, P=0.05; 2019 vs. 2021: 2.26% vs. 4.99%, P=0.03). In the first 5 months of 2021, there were 26 cases of vaccine-induced immune thrombotic thrombocytopenia (VITT), resulting in six deaths. CONCLUSIONS: During the 1st year of the COVID-19 pandemic, CVT hospitalization volume and CVT in-hospital mortality did not change compared to the prior year. COVID-19 diagnosis was associated with higher CVT in-hospital mortality. During the first 5 months of 2021, there was an increase in CVT hospitalization volume and increase in CVT-related mortality, partially attributable to VITT

A Morphological Approach to the Voxelization of Solids

In this paper we present a new, morphological criterion for determining whether a geometric solid is suitable for voxelization at a given resolution. The criterion embodies two conditions, namely that the curvature of the solid must be bounded and the critical points of the distance field must be at a certain distance from the boundary of the solid. For solids that fulfill this criterion, we present an analytic and an empirical bound for the trilinear reconstruction error. Additionally, we give a theoretical argument as to why the distance field approach to voxelization is more sound than the prefiltering technique. The essence of the argument is that while sampling and interpolation must always introduce some error, the latter method (but not the former) introduces an error in the surface position independently of the sampling

Caspase-2 and JNK Activated by Saturated Fatty Acids are Not Involved in Apoptosis Induction but Modulate ER Stress in Human Pancreatic β-cells

Background: Fatty acid-induced apoptosis and ER stress of pancreatic β-cells contribute to the development of type 2 diabetes, however, the molecular mechanisms involved are unclear. Aims: In this study we have tested the role of caspase-2 and suggested ER stress mediator JNK in saturated fatty acid-induced apoptosis of the human pancreatic β-cells NES2Y. Results: We found that stearic acid at apoptosis-inducing concentration activated ER stress signaling pathways, i.e. IRE1α, PERK and ATF6 pathways, in NES2Y cells. During stearic acid-induced apoptosis, JNK inhibition did not decrease the rate of apoptosis nor the activation of caspase-8, -9, -7 and -2 and PARP cleavage. In addition, inhibition of JNK activity did not affect CHOP expression although it did decrease the induction of BiP expression after stearic acid treatment. Caspase-2 silencing had no effect on PARP as well as caspase-8, -9 and -7 cleavage and the induction of CHOP expression, however, it also decreased the induction of BiP expression. Surprisingly, caspase-2 silencing was accompanied by increased phosphorylation of c-Jun. Conclusions: We have demonstrated that caspase-2 as well as JNK are not key players in apoptosis induction by saturated fatty acids in human pancreatic β-cells NES2Y. However, they appear to be involved in the modulation of saturated fatty acid-induced ER stress signaling, probably by a mechanism independent of c-Jun phosphorylation

Modelling of NO adsorption in fixed bed on activated carbon

Adsorption experiments of nitric oxide in nitrogen carrier gas were held on activated carbon in a fixed bed flow system. Breakthrough curves describing the dependence of exit concentrations of nitric oxide on time were matched with theoretical response curves calculated from the linear driving force model (LDF). The model assumes Langmuir adsorption isotherm for the description of non-linear equilibrium and overall mass transfer coefficient for mass transfer mechanism. Overall mass transfer coefficients were obtained by the method of least squares for fitting numerically modelled breakthrough curves with experimental breakthrough curves. It was found that LDF model fits all the breakthrough curves and it is a useful tool for modelling purposes.Web of Science32437736

Forest condition monitoring in the Czech Republic:Annual report ICP Forests 2002

In the Year-book there are the methods of evaluation and the results presented, as obtained in assessment of the forest state within the Level I and Level II plots