Quantifying Model Complexity via Functional Decomposition for Better Post-Hoc Interpretability

Post-hoc model-agnostic interpretation methods such as partial dependence plots can be employed to interpret complex machine learning models. While these interpretation methods can be applied regardless of model complexity, they can produce misleading and verbose results if the model is too complex, especially w.r.t. feature interactions. To quantify the complexity of arbitrary machine learning models, we propose model-agnostic complexity measures based on functional decomposition: number of features used, interaction strength and main effect complexity. We show that post-hoc interpretation of models that minimize the three measures is more reliable and compact. Furthermore, we demonstrate the application of these measures in a multi-objective optimization approach which simultaneously minimizes loss and complexity

Human Parainfluenza Virus Infection after Hematopoietic Stem Cell Transplantation: Risk Factors, Management, Mortality, and Changes over Time

Human parainfluenza viruses (HPIVs) are uncommon, yet high-risk pathogens after hematopoietic stem cell transplant (HCT). We evaluated 5178 pediatric and adult patients undergoing HCT between 1974 and 2010 to determine the incidence, risk factors, response to treatment, and outcome of HPIV infection as well as any change in frequency or character of HPIV infection over time. HPIV was identified in 173 patients (3.3%); type 3 was most common (66%). HPIV involved upper respiratory tract infection (URTI; 57%), lower respiratory tract infection (LRTI; 9%), and both areas of the respiratory tract (34%), at a median of 62 days after transplantation. In more recent years, HPIV has occurred later after HCT, whereas the proportion with nosocomial infection and mortality decreased. Over the last decade, HPIV was more common in older patients and in those receiving reduced intensity conditioning (RIC). RIC was a significant risk factor for later (beyond day +30). HPIV infections, and this association was strongest in patients with URTI. HCT using a matched unrelated donor (MURD), mismatched related donor (MMRD), age 10 to 19 years, and graft-versus-host disease (GVHD) were all risk factors for HPIV infections. LRTI, early (<30 days), age 10 to 19 years, MMRD, steroid use, and coinfection with other pathogens were risk factors for mortality. The survival of patients with LRTI, especially very early infections, was poor regardless of ribavirin treatment. HPIV incidence remains low, but may have delayed onset associated with RIC regimens and improving survival. Effective prophylaxis and treatment for HPIV are needed

IEC-61850-based communication for integrated EV management in power systems with renewable penetration

As the number of EVs increases, their impact on electrical systems will be substantial. Novel management schemes are needed to manage the electrical load they require when charging. Literature is rich with different techniques to manage and control this effect on the grid by controlling and optimizing power flow. Although these solutions heavily rely on communication lines, they mostly treat communication as a black box. It is important to develop communication solutions that can integrate EVs, charging stations (CSs), and the rest of the grid in an interoperable way. A standard approach would be indispensable as there are different EV models manufactured by different companies. The IEC 61850 standard is a strong tool used for developing communication models for different smart grid components. However, it does not have the necessary models for implementing smart EV management schemes that coordinate between EVs and CSs. In this paper, these missing links are addressed through the development of corresponding models and message mapping. A hardware-in-the-loop test is performed to validate the communication models and cross-platform operation. Then, a co-simulation environment is used to perform a combined study of communication and the power system components. The developed communication model helps integrate the EVs to a centralized, coordinated voltage control scheme. These models can be used to run extensive impact studies where different domains of smart grids need to be considered simultaneously. The main contribution of this paper is the development of smartgrid communication solutions for enabling successful information exchanges

Data Standardization for Smart Infrastructure in First-Access Electricity Systems

Recent developments in renewable energy and Information Technology (IT) fields made it easier to set up power systems at a smaller scale. This proved to be a turning point for developing First-Access Electricity Systems for the underserved locations around the world. However, there are planning and operation challenges due to lack of past data on such places. Deployment of IoT devices and proliferation of smart infrastructures with additional sensors will lead to tremendous opportunities for gathering very useful data. For different stakeholders to access and manage this data, trusted and standardized mechanisms need to be in place. Storing proper data in a well-structured common format allows for collaborative research across disciplines, large-scale analytics, and sharing of algorithms and methodologies, in addition to improved customer service. Data standardization plays a more vital role in the context of electricity access in underdeveloped countries, where there is no past data on generation or consumption as in utility grids. Data collected in a standard structure, be it for a short period of time, facilitates learning from the past experiences, monitoring the current projects and delivering better results in future endeavors. It will result in ways to better assist consumers and help the industry operate more efficiently by sharing data with different stakeholders. It can also enhance competition, thus making electricity accessible faster and to more people. The focus of this paper is data standardization for first-access electricity systems, in general, and renewable energy based microgrids, in particular, different data sources and ways the corresponding data can be exploited, technological and capacity constraints for storage of data, political and governance implications, as well as data security and privacy issues, are examined. The work presented here is relevant to different stake holders such as investors, public utilities, non-governmental organizations (NGOs) and communities. Using the data standardization approach developed here, it is possible to create a much-needed first-access electricity system database. This will provide an important resource for project developers and energy companies to assess the potential of a certain unelectrified site, estimating its demand growth in time and establishing universal control systems that can seamlessly communicate with different components

Seroepidemiology of Toxoplasma gondii infection in patients with liver disease in eastern China

The role of the protozoan parasite Toxoplasma gondii in the pathogenesis of liver disease has recently gained much interest. The aim of this study was to determine the prevalence and risk factors associated with T. gondii infection in patients with liver disease from three cities in Shandong and Henan provinces, China. A case–control study was conducted from December 2014 to November 2015 and included 1142 patients with liver disease and 1142 healthy controls. Serum samples were collected from all individuals and were examined with enzyme-linked immunosorbent assay for the presence of anti-T. gondii IgG and IgM antibodies. Information on the demographics, clinical, and lifestyle characteristics of the participants was collected from the medical records and by the use of a questionnaire. The prevalence of anti-T. gondii IgG was 19·7% in patients with liver disease compared with 12·17% in the controls. Only 13 patients had anti-T. gondii IgM antibodies compared with 12 control individuals (1·14% vs. 1·05%, respectively). The highest seroprevalence was detected in patients with liver cancer (22·13%), followed by hepatitis patients (20·86%), liver cirrhosis patients (20·42%), and steatosis patients (20%). Multivariate logistic regression analysis indicated that consumption of raw meat (odds ratio (OR) = 1·32; 95% confidence interval (CI) 1·01–1·71; P = 0·03) and source of drinking water from wells (OR = 1·56; 95% CI 1·08–2·27; P = 0·01) were independent risk factors for T. gondii infection in liver disease patients. These findings indicate that T. gondii infection is more likely to be present in patients with liver disease. Therefore, efforts should be directed toward health education of populations at high risk of T. gondii infection and measures should be taken to protect vulnerable patients with liver disease

International differences in self-reported health measures in 33 major metropolitan areas in Europe.

The increasing concentration of populations into large conurbations in recent decades has not been matched by international health assessments, which remain largely focused at the country level. We aimed to demonstrate the use of routine survey data to compare the health of large metropolitan centres across Europe and determine the extent to which differences are due to socio-economic factors

Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring.

OBJECTIVE: Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems. METHODS: A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification. FINDINGS: A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach. CONCLUSIONS: The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians