Database, Features, and Machine Learning Model to Identify Thermally Driven Metal-Insulator Transition Compounds

Metal-insulator transition (MIT) compounds are materials that may exhibit insulating or metallic behavior, depending on the physical conditions, and are of immense fundamental interest owing to their potential applications in emerging microelectronics. There is a dearth of thermally-driven MIT materials, however, which makes delineating these compounds from those that are exclusively insulating or metallic challenging. Here we report a material database comprising temperature-controlled MITs (and metals and insulators with similar chemical composition and stoichiometries to the MIT compounds) from high quality experimental literature, built through a combination of materials-domain knowledge and natural language processing. We featurize the dataset using compositional, structural, and energetic descriptors, including two MIT relevant energy scales, an estimated Hubbard interaction and the charge transfer energy, as well as the structure-bond-stress metric referred to as the global-instability index (GII). We then perform supervised classification, constructing three electronic-state classifiers: metal vs non-metal (M), insulator vs non-insulator (I), and MIT vs non-MIT (T). We identify two important descriptors that separate metals, insulators, and MIT materials in a 2D feature space: the average deviation of the covalent radius and the range of the Mendeleev number. We further elaborate on other important features (GII and Ewald energy), and examine how they affect classification of binary vanadium and titanium oxides. We discuss the relationship of these atomic features to the physical interactions underlying MITs in the rare-earth nickelate family. Last, we implement an online version of the classifiers, enabling quick probabilistic class predictions by uploading a crystallographic structure file

Adaptive Charting Techniques: Literature Review and Extensions

The continuous development of SPC is driven by challenges arising from practical applications across diverse industries. Among others, adaptive charts are becoming more and more popular due to their capability in tackling these challenges by learning unknown shifts and tracking time-varying patterns. This chapter reviews recent development of adaptive charts and classifies them into two categories: those with variable sampling parameters and those with variable design parameters. This review focuses on the latter group and compares their charting performance. As an extension to conventional multivariate charts, this work proposes a double-sided directionally variant chart. The proposed chart is capable of detecting shifts having the same or opposite directions as the reference vector and is more robust to processes with unpredictable shift directions

Evaluation of guided imagery as treatment for recurrent abdominal pain in children: a randomized controlled trial

BACKGROUND: Because of the paucity of effective evidence-based therapies for children with recurrent abdominal pain, we evaluated the therapeutic effect of guided imagery, a well-studied self-regulation technique. METHODS: 22 children, aged 5 – 18 years, were randomized to learn either breathing exercises alone or guided imagery with progressive muscle relaxation. Both groups had 4-weekly sessions with a therapist. Children reported the numbers of days with pain, the pain intensity, and missed activities due to abdominal pain using a daily pain diary collected at baseline and during the intervention. Monthly phone calls to the children reported the number of days with pain and the number of days of missed activities experienced during the month of and month following the intervention. Children with ≤ 4 days of pain/month and no missed activities due to pain were defined as being healed. Depression, anxiety, and somatization were measured in both children and parents at baseline. RESULTS: At baseline the children who received guided imagery had more days of pain during the preceding month (23 vs. 14 days, P = 0.04). There were no differences in the intensity of painful episodes or any baseline psychological factors between the two groups. Children who learned guided imagery with progressive muscle relaxation had significantly greater decrease in the number of days with pain than those learning breathing exercises alone after one (67% vs. 21%, P = 0.05), and two (82% vs. 45%, P < 0.01) months and significantly greater decrease in days with missed activities at one (85% vs. 15%, P = 0.02) and two (95% vs. 77%. P = 0.05) months. During the two months of follow-up, more children who had learned guided imagery met the threshold of ≤ 4 day of pain each month and no missed activities (RR = 7.3, 95%CI [1.1,48.6]) than children who learned only the breathing exercises. CONCLUSION: The therapeutic efficacy of guided imagery with progressive muscle relaxation found in this study is consistent with our present understanding of the pathophysiology of recurrent abdominal pain in children. Although unfamiliar to many pediatricians, guided imagery is a simple, noninvasive therapy with potential benefit for treating children with RAP

Calf health from birth to weaning. III. housing and management of calf pneumonia

Calfhood diseases have a major impact on the economic viability of cattle operations. A three part review series has been developed focusing on calf health from birth to weaning. In this paper, the last of the three part series, we review disease prevention and management with particular reference to pneumonia, focusing primarily on the pre-weaned calf. Pneumonia in recently weaned suckler calves is also considered, where the key risk factors are related to the time of weaning. Weaning of the suckler calf is often combined with additional stressors including a change in nutrition, environmental change, transport and painful husbandry procedures (castration, dehorning). The reduction of the cumulative effects of these multiple stressors around the time of weaning together with vaccination programmes (preconditioning) can reduce subsequent morbidity and mortality in the feedlot. In most studies, calves housed individually and calves housed outdoors with shelter, are associated with decreased risk of disease. Even though it poses greater management challenges, successful group housing of calves is possible. Special emphasis should be given to equal age groups and to keeping groups stable once they are formed. The management of pneumonia in calves is reliant on a sound understanding of aetiology, relevant risk factors, and of effective approaches to diagnosis and treatment. Early signs of pneumonia include increased respiratory rate and fever, followed by depression. The single most important factor determining the success of therapy in calves with pneumonia is early onset of treatment, and subsequent adequate duration of treatment. The efficacy and economical viability of vaccination against respiratory disease in calves remains unclear

Objective–Oriented Sequential Sampling for Simulation Based Robust Design Considering Multiple Sources of Uncertainty

Sequential sampling strategies have been developed for managing complexity when using computationally expensive computer simulations in engineering design. However, much of the literature has focused on objective-oriented sequential sampling methods for deterministic optimization. These methods cannot be directly applied to robust design which must account for uncontrollable variations in certain input variables (i.e., noise variables). Obtaining a robust design that is insensitive to variations in the noise variables is more challenging. Even though methods exist for sequential sampling in design under uncertainty, the majority of the existing literature does not systematically take into account the interpolation uncertainty that results from limitations on the number of simulation runs, the effect of which is inherently more severe than in deterministic design. In this paper, we develop a systematic objective-oriented sequential sampling approach to robust design with consideration of both noise variable uncertainty and interpolation uncertainty. The method uses Gaussian processes to model the costly simulator and quantify the interpolation uncertainty within a robust design objective. We examine several criteria, including our own proposed criteria, for sampling the design and noise variables and provide insight into their performance behaviors. We show that for both of the examples considered in this paper the proposed sequential algorithm is more efficient in finding the robust design solution than a one-shot space filling design.</jats:p