A Dual Active-Set Algorithm for Regularized Monotonic Regression

Monotonic (isotonic) regression is a powerful tool used for solving a wide range of important applied problems. One of its features, which poses a limitation on its use in some areas, is that it produces a piecewise constant fitted response. For smoothing the fitted response, we introduce a regularization term in the monotonic regression, formulated as a least distance problem with monotonicity constraints. The resulting smoothed monotonic regression is a convex quadratic optimization problem. We focus on the case, where the set of observations is completely (linearly) ordered. Our smoothed pool-adjacent-violators algorithm is designed for solving the regularized problem. It belongs to the class of dual active-set algorithms. We prove that it converges to the optimal solution in a finite number of iterations that does not exceed the problem size. One of its advantages is that the active set is progressively enlarging by including one or, typically, more constraints per iteration. This resulted in solving large-scale test problems in a few iterations, whereas the size of that problems was prohibitively too large for the conventional quadratic optimization solvers. Although the complexity of our algorithm grows quadratically with the problem size, we found its running time to grow almost linearly in our computational experiments

Formation of public strategic planning in Ukraine

It is sometimes the case that a theory proposes that the population means on two variables should have the same rank order across a set of experimental conditions. This paper presents a test of this hypothesis. The test statistic is based on the coupled monotonic regression algorithm developed by the authors. The significance of the test statistic is determined by comparison to an empirical distribution specific to each case, obtained via non-parametric or semi-parametric bootstrap. We present an analysis of the power and Type I error control of the test based on numerical simulation. Partial order constraints placed on the variables may sometimes be theoretically justified. These constraints are easily incorporated into the computation of the test statistic and are shown to have substantial effects on power. The test can be applied to any form of data, as long as an appropriate statistical model can be specified.free access is valid until January 8, 2016:http://authors.elsevier.com/a/1S3XC53naPWGhFunding agencies: Australian Research Council [0877510, 0878630, 110100751, 130101535]; National Science Foundation [1256959]; Linkoping University</p

Adaptation to Digitalization in Supply Chain Management

Abstract- The purpose of the study was to find out the possibilities of adapting states to global trends in the digital transformation of the main spheres of life for survival and development in an emerging multi-polar world. The work was done as part of a grant from the Russian Foundation for Basic Research and discloses the results of the initial stage of its implementation. Our task was to develop a conceptual vision for solving the problems of adapting states to global trends in digital transformation and to justify the mechanisms for its implementation in practice. Information for the study was compiled from scientific literature, the Internet, statistical reports, and other open sources available for use. In the theoretical part of the study, we needed to clarify such concepts as “digitalization in supply chain management ” and “adaptation”, justify the manifestation of their basic functions, identify and describe such new global trends in digitalization in supply chain management  that affect adaptation, as the dominant role of states in this issue over other participants in digital transformations; their massive, comprehensive nature, high speed and irreversibility of digital transformation; recognition of intellectual capital as the undivided dominant power of digital transformation and the displacement of cultural and spiritual factors of human development into the background. Contrary to expectations, we came to the conclusion that the adaptation of states to the global trends of digital transformation in the main areas of life is facilitated by the timely identification, understanding of global changes and the implementation of strategies for adapting institutions, business entities, the population and society to future changes using special rules, mechanisms and decisions set out in the paper. The recommendations arising from this study can be applied at the state and interstate levels of government when developing strategies, programs, regulatory documents, regulations and standards governing adaptation to digitalization in supply chain management. They are useful for business corporations and public organizations which professional interests extend to solving the problems of socialization and adaptation of people, taking into account the diversity of cultures and national identity of citizens

scDrugPrio: a framework for the analysis of single-cell transcriptomics to address multiple problems in precision medicine in immune-mediated inflammatory diseases

Drug repurposing; Immune-mediated inflammatory disease; Single-cell RNA sequencingReutilización de medicamentos; Enfermedad inflamatoria inmunomediada; Secuenciación de ARN unicelularReutilització de medicaments; Malaltia inflamatòria immunomediada; Seqüenciació d'ARN unicel·lularBackground Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn’s disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn’s disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusions We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio’s potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package (https://github.com/SDTC-CPMed/scDrugPrio).Open access funding provided by Karolinska Institute. This work was supported by the DocTIS project, which has received funding from the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement N° 848028; Swedish Cancer Society CAN 2017/411; Cocozza Foundation; National Natural Science Foundation of China 82171791, US National Institutes of Health grants HL155107 and HL155096; American Heart Association grant 957729; European Union’s Horizon 2021 Research and Innovation Programme grant 101057619 and Mag-Tarmfonden (grant 1–23). The computations were partially enabled by resources provided by the Swedish National Infrastructure for Computing (SNIC) at Linköping University partially funded by the Swedish Research Council through grant agreement no. 2018–05973

Assessing the Multiple Dimensions of Poverty. Data Mining Approaches to the 2004-14 Health and Demographic Surveillance System in Cuatro Santos, Nicaragua.

We identified clusters of multiple dimensions of poverty according to the capability approach theory by applying data mining approaches to the Cuatro Santos Health and Demographic Surveillance database, Nicaragua. Four municipalities in northern Nicaragua constitute the Cuatro Santos area, with 25,893 inhabitants in 5,966 households (2014). A local process analyzing poverty-related problems, prioritizing suggested actions, was initiated in 1997 and generated a community action plan 2002-2015. Interventions were school breakfasts, environmental protection, water and sanitation, preventive healthcare, home gardening, microcredit, technical training, university education stipends, and use of the Internet. In 2004, a survey of basic health and demographic information was performed in the whole population, followed by surveillance updates in 2007, 2009, and 2014 linking households and individuals. Information included the house material (floor, walls) and services (water, sanitation, electricity) as well as demographic data (birth, deaths, migration). Data on participation in interventions, food security, household assets, and women's self-rated health were collected in 2014. A K-means algorithm was used to cluster the household data (56 variables) in six clusters. The poverty ranking of household clusters using the unsatisfied basic needs index variables changed when including variables describing basic capabilities. The households in the fairly rich cluster with assets such as motorbikes and computers were described as modern. Those in the fairly poor cluster, having different degrees of food insecurity, were labeled vulnerable. Poor and poorest clusters of households were traditional, e.g., in using horses for transport. Results displayed a society transforming from traditional to modern, where the forerunners were not the richest but educated, had more working members in household, had fewer children, and were food secure. Those lagging were the poor, traditional, and food insecure. The approach may be useful for an improved understanding of poverty and to direct local policy and interventions

Peculiarities of growing Ga1–xInxAs solid solutions on GaAs substrates in the field of a temperature gradient through a thin gas zone

Solid solution Ga1–xInxAs is widely used in modern optoelectronics as a material for p-i-n photodetectors, lasers emitting in the spectral range 1.3–1.55 μm. In this paper, the features of obtaining Ga1–xInxAs films by the method of zone recrystallization with a temperature gradient, the essence of which is the sequential recrystallization of parts of the source melt moving under the action of a temperature gradient, are studied. Ga1–xInxAs films on GaAs substrates were obtained in a temperature gradient field through a thin gas zone in a specially designed graphite cassette. The films were prepared at a temperature of 1123 K with a temperature gradient of 30 K/cm. A 1:1 mixture of nitrogen and hydrogen was used as the carrier gas. The thickness of the gas zone between the source and the substrate was 1 mm. The deposition time for all films was 10 min. The growth kinetics, morphology, and structure of the chemical bonds of the obtained films have been studied. Based on the results of theoretical calculations, it was found that an increase in the concentration of indium leads to a decrease in the film growth rate to 0.3137 μm/min. A comparison of the results of theoretical calculations with experimental results showed a discrepancy between the growth rates for films with an indium concentration in the growth source of more than 20 %, which is primarily due to the segregation of indium on the film surface. The films have an RMS roughness from 9.1 to 24.2 nm. It is shown that the content of indium in the growth source significantly affects the properties of the grown films and leads to a decrease in the growth rate, an increase in the elastic stresses in the layer, and a nonstoichiometric composition of the film. It has been established that with an increase in the indium concentration in the film, a significant shift in the frequency of the LO and TO phonon modes of GaAs to the left by 13 and 16 cm–1, respectively, is observed due to the influence of elastic mechanical stresses. The presented results show that Ga1–xInxAs solid solution films with short-range order of chemical bonds were obtained by the method of zone recrystallization in a temperature gradient

Trends and factors related to adolescent pregnancies: an incidence trend and conditional inference trees analysis of northern Nicaragua demographic surveillance data

Background We aimed to identify the 2001-2013 incidence trend, and characteristics associated with adolescent pregnancies reported by 20-24-year-old women. Methods A retrospective analysis of the Cuatro Santos Northern Nicaragua Health and Demographic Surveillance 2004-2014 data on women aged 15-19 and 20-24. To calculate adolescent birth and pregnancy rates, we used the first live birth at ages 10-14 and 15-19 years reported by women aged 15-19 and 20-24 years, respectively, along with estimates of annual incidence rates reported by women aged 20-24 years. We conducted conditional inference tree analyses using 52 variables to identify characteristics associated with adolescent pregnancies. Results The number of first live births reported by women aged 20-24 years was 361 during the study period. Adolescent pregnancies and live births decreased from 2004 to 2009 and thereafter increased up to 2014. The adolescent pregnancy incidence (persons-years) trend dropped from 2001 (75.1 per 1000) to 2007 (27.2 per 1000), followed by a steep upward trend from 2007 to 2008 (19.1 per 1000) that increased in 2013 (26.5 per 1000). Associated factors with adolescent pregnancy were living in low-education households, where most adults in the household were working, and high proportion of adolescent pregnancies in the local community. Wealth was not linked to teenage pregnancies. Conclusions Interventions to prevent adolescent pregnancy are imperative and must bear into account the context that influences the culture of early motherhood and lead to socioeconomic and health gains in resource-poor settings

Relative importance of prenatal and postnatal determinants of stunting: data mining approaches to the MINIMat cohort, Bangladesh.

INTRODUCTION: WHO has set a goal to reduce the prevalence of stunted child growth by 40% by the year 2025. To reach this goal, it is imperative to establish the relative importance of risk factors for stunting to deliver appropriate interventions. Currently, most interventions take place in late infancy and early childhood. This study aimed to identify the most critical prenatal and postnatal determinants of linear growth 0-24 months and the risk factors for stunting at 2 years, and to identify subgroups with different growth trajectories and levels of stunting at 2 years. METHODS: Conditional inference tree-based methods were applied to the extensive Maternal and Infant Nutrition Interventions in Matlab trial database with 309 variables of 2723 children, their parents and living conditions, including socioeconomic, nutritional and other biological characteristics of the parents; maternal exposure to violence; household food security; breast and complementary feeding; and measurements of morbidity of the mothers during pregnancy and repeatedly of their children up to 24 months of age. Child anthropometry was measured monthly from birth to 12 months, thereafter quarterly to 24 months. RESULTS: Birth length and weight were the most critical factors for linear growth 0-24 months and stunting at 2 years, followed by maternal anthropometry and parental education. Conditions after birth, such as feeding practices and morbidity, were less strongly associated with linear growth trajectories and stunting at 2 years. CONCLUSION: The results of this study emphasise the benefit of interventions before conception and during pregnancy to reach a substantial reduction in stunting

Digital twins to personalize medicine

Personalized medicine requires the integration and processing of vast amounts of data. Here, we propose a solution to this challenge that is based on constructing Digital Twins. These are high-resolution models of individual patients that are computationally treated with thousands of drugs to find the drug that is optimal for the patient