An Explainable Model for Fault Detection in HPC Systems

Large supercomputers are composed of numerous components that risk to break down or behave in unwanted manners. Identifying broken components is a daunting task for system administrators. Hence an automated tool would be a boon for the systems resiliency. The wealth of data available in a supercomputer can be used for this task. In this work we propose an approach to take advantage of holistic data centre monitoring, system administrator node status labeling and an explainable model for fault detection in supercomputing nodes. The proposed model aims at classifying the different states of the computing nodes thanks to the labeled data describing the supercomputer behaviour, data which is typically collected by system administrators but not integrated in holistic monitoring infrastructure for data center automation. In comparison the other method, the one proposed here is robust and provide explainable predictions. The model has been trained and validated on data gathered from a tier-0 supercomputer in production

Effect of vessel wettability on the foamability of "ideal" surfactants and "real-world" beer heads

The ability to tailor the foaming properties of a solution by controlling its chemical composition is highly desirable and has been the subject of extensive research driven by a range of applications. However, the control of foams by varying the wettability of the foaming vessel has been less widely reported. This work investigates the effect of the wettability of the side walls of vessels used for the in situ generation of foam by shaking aqueous solutions of three different types of model surfactant systems (non-ionic, anionic and cationic surfactants) along with four different beers (Guinness Original, Banks’s Bitter, Bass No 1 and Harvest Pale). We found that hydrophilic vials increased the foamability only for the three model systems but increased foam stability for all foams except the model cationic system. We then compared stability of beer foams produced by shaking and pouring and demonstrated weak qualitative agreement between both foam methods. We also showed how wettability of the glass controls bubble nucleation for beers and champagne and used this effect to control exactly where bubbles form using simple wettability patterns

Prediction of Thermal Hazards in a Real Datacenter Room Using Temporal Convolutional Networks

Datacenters play a vital role in today's society. At large, a datacenter room is a complex controlled environment composed of thousands of computing nodes, which consume kW of power. To dissipate the power, forced air/liquid flow is employed, with a cost of millions of euros per year. Reducing this cost involves using free-cooling and average case design, which can create a cooling shortage and thermal hazards. When a thermal hazard happens, the system administrators and the facility manager must stop the production to avoid IT equipment damage and wear-out. In this paper, we study the thermal hazards signatures on a Tier-0 datacenter room's monitored data during a full year of production. We define a set of rules for detecting the thermal hazards based on the inlet and outlet temperature of all nodes of a room. We then propose a custom Temporal Convolutional Network (TCN) to predict the hazards in advance. The results show that our TCN can predict the thermal hazards with an F1-score of 0.98 for a randomly sampled test set. When causality is enforced between the training and validation set the F1-score drops to 0.74, demanding for an in-place online re-training of the network, which motivates further research in this context

The Role of Depression on the Ability to Achieve Smoking Abstinence​

We investigated how depression affects smoking abstinence among cancer patients who participated in MD Anderson Cancer Center\u27s Tobacco Research and Treatment Program (TRTP), assessing outcomes three months post-enrollment. We also compared the likelihood of abstaining from smoking while accounting for nicotine dependence measured by the Fagerström Test for Cigarette Dependence (FTCD). The findings aimed to guide clinical practices in optimizing treatment of tobacco use disorder (TUD) to improve abstinence rates. Integrating comprehensive treatments for depression alongside standard TUD treatment holds promise for improving overall abstinence outcomes.https://openworks.mdanderson.org/stronger24/1005/thumbnail.jp

Impact of Alcohol Use Disorder on Ability to Quit Smoking: A Cohort Study

The study aims to investigate the relationship between alcohol use disorder (DSM-IV alcohol abuse) and ability to quit smoking at the end of treatment among adult cancer patients, who enrolled in MD Anderson Cancer Center’s Tobacco Research and Treatment Program (TRTP). The findings could lead to more effective and integrated treatment strategies and encourage clinicians to include combined pharmacological and behavioral interventions to treat dual substance use.https://openworks.mdanderson.org/stronger24/1004/thumbnail.jp

Comparing the Fagerström Test and Heaviness of Smoking Index in Predicting Smoking Abstinence in Cancer Patients

Introduction: People with cancer who smoke exhibit greater cigarette dependence than people without cancer who smoke, a crucial factor in smoking cessation. Research is limited on the predictive potential of the Fagerström Test for Cigarette Dependence (FTCD) and the Heaviness of Smoking Index (HSI) on smoking abstinence in cancer patients undergoing smoking cessation treatment. Aims and Methods: We analyzed data from 5934 cancer patients seeking smoking cessation treatment at The University of Texas MD Anderson Cancer Center (female 52.08%; Mean age = 55.52, SD = 11.17). We evaluated the predictive accuracy of FTCD and HSI on abstinence at 3, 6, and 9 months from the first consultation, and assessed the concordance between these tools in measuring cigarette dependence using Cohen’s kappa test and different correlation and regression models. We also analyzed variations across sex at birth and race/ethnicity. Results: Both the FTCD and the HSI demonstrated comparable predictive accuracy for smoking cessation at all follow-ups, with neither showing high accuracy (Areas Under the Curve scores around 0.6). Concordance analysis revealed substantial agreement between FTCD and HSI scores (Cohen’s kappa ~ 0.7), particularly at lower levels of dependence. However, this agreement varied by race, with reduced concordance observed in non-Hispanic Blacks. Conclusions: Our results indicate that both the FTCD and HSI are effective tools for predicting smoking cessation in cancer patients, with the HSI offering a less burdensome assessment option. Nevertheless, the findings suggest the need for tailored approaches in assessing cigarette dependence that could predict smoking cessation more accurately, considering racial differences. Implications: The burden of assessing cigarette dependence in cancer care settings can be reduced by using the HSI instead of the FTCD. In addition, both instruments could be substantially interchanged and used for meta-analytic studies examining dependence and abstinence, but race/ethnicity should be considered.publishedVersio

Valorization of byproducts of hemp multipurpose crop: Short non-aligned bast fibers as a source of nanocellulose

Nanocellulose was extracted from short bast fibers, from hemp (Cannabis sativa L.) plants harvested at seed maturity, non-retted, and mechanically decorticated in a defibering apparatus, giving non-aligned fibers. A chemical pretreatment with NaOH and HCl allowed the removal of most of the non-cellulosic components of the fibers. No bleaching was performed. The chemically pretreated fibers were then refined in a beater and treated with a cellulase enzyme, followed by mechanical defibrillation in an ultrafine friction grinder. The fibers were characterized by microscopy, infrared spectroscopy, thermogravimetric analysis and X-ray diffraction after each step of the process to understand the evolution of their morphology and composition. The obtained nanocellulose suspension was composed of short nanofibrils with widths of 5–12 nm, stacks of nanofibrils with widths of 20–200 nm, and some larger fibers. The crystallinity index was found to increase from 74% for the raw fibers to 80% for the nanocellulose. The nanocellulose retained a yellowish color, indicating the presence of some residual lignin. The properties of the nanopaper prepared with the hemp nanocellulose were similar to those of nanopapers prepared with wood pulp-derived rod-like nanofibrils