Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods

In this paper, we study matrix scaling and balancing, which are fundamental problems in scientific computing, with a long line of work on them that dates back to the 1960s. We provide algorithms for both these problems that, ignoring logarithmic factors involving the dimension of the input matrix and the size of its entries, both run in time $\widetilde{O}\left(m\log \kappa \log^2 (1/\epsilon)\right)$ where $\epsilon$ is the amount of error we are willing to tolerate. Here, $\kappa$ represents the ratio between the largest and the smallest entries of the optimal scalings. This implies that our algorithms run in nearly-linear time whenever $\kappa$ is quasi-polynomial, which includes, in particular, the case of strictly positive matrices. We complement our results by providing a separate algorithm that uses an interior-point method and runs in time $\widetilde{O}(m^{3/2} \log (1/\epsilon))$. In order to establish these results, we develop a new second-order optimization framework that enables us to treat both problems in a unified and principled manner. This framework identifies a certain generalization of linear system solving that we can use to efficiently minimize a broad class of functions, which we call second-order robust. We then show that in the context of the specific functions capturing matrix scaling and balancing, we can leverage and generalize the work on Laplacian system solving to make the algorithms obtained via this framework very efficient.Comment: To appear in FOCS 201

Influence of Substrate Temperature on Structural and Morphological Properties of SnO2 Nanostructured Thin Films

SnO2 nanostructures thin films with thickness of 500 nm were prepared by electron beam-physical vapor deposition on glass substrate at temperature of 300, 373, 443, and 583 K. Structural and morphological properties of these nanostructured thin films were studied by Scanning and Transmission Electron Microscopy (SEM, TEM) and Atomic Force Microscope (AFM) methods. The changes in structural and morphological properties are found at different temperatures. Increase temperature causes important change of the structural and morphological properties. The sample prepared at 300 K has crystalline structure and the sample prepared at 583 K has amorphous structure. Roughness parameters have low values at 300, 373, 443 K as opposed to the values obtained at 583 K. This different behavior may be due to the amorphous structure of the sample that was observed in the TEM analysis

Healable Cellulose Iontronic Hydrogel Stickers for Sustainable Electronics on Paper

The authors acknowledge the support from FCT - Portuguese Foundation for Science and Technology through the Ph.D. scholarships SFRH/BD/126409/2016 (I.C.) and SFRH/BD/122286/2016 (J.M.). The authors would like to acknowledge the European Commission under project NewFun (ERC-StG-2014, GA 640598) and project SYNERGY (H2020-WIDESPREAD-2020-5, CSA, proposal no 952169). This work was also supported by the FEDER funds through the COMPETE 2020 Program and the National Funds through the FCT - Portuguese Foundation for Science and Technology under the Project No. POCI-01-0145-FEDER-007688, reference UID/CTM/50025, project CHIHC, reference PTDC/NAN-MAT/32558/2017. The authors would also like to thank their colleagues Daniela Gomes and Ana Pimentel from CENIMAT/i3N for the SEM and DSC-TGA measurements, respectively.Novel nature-based engineered functional materials combined with sustainable and economically efficient processes are among the great challenges for the future of mankind. In this context, this work presents a new generation of versatile flexible and highly conformable regenerated cellulose hydrogel electrolytes with high ionic conductivity and self-healing ability, capable of being (re)used in electrical and electrochemical devices. They can be provided in the form of stickers and easily applied as gate dielectric onto flexible indium–gallium–zinc oxide transistors, decreasing the manufacturing complexity. Flexible and low-voltage (<2.5 V) circuits can be handwritten on-demand on paper transistors for patterning of conductive/resistive lines. This user-friendly and simplified manufacturing approach holds potential for fast production of low-cost, portable, disposable/recyclable, and low-power ion-controlled electronics on paper, making it attractive for application in sensors and concepts such as the “Internet-on-Things.”.publishersversionpublishe

“Control-Alt-Delete”: Rebooting Solutions for the E-Waste Problem

A number of efforts have been launched to solve the global electronic waste (e-waste) problem. The efficiency of e-waste recycling is subject to variable national legislation, technical capacity, consumer participation, and even detoxification. E-waste management activities result in procedural irregularities and risk disparities across national boundaries. We review these variables to reveal opportunities for research and policy to reduce the risks from accumulating e-waste and ineffective recycling. Full regulation and consumer participation should be controlled and reinforced to improve local e-waste system. Aiming at standardizing best practice, we alter and identify modular recycling process and infrastructure in eco-industrial parks that will be expectantly effective in countries and regions to handle the similar e-waste stream. Toxicity can be deleted through material substitution and detoxification during the life cycle of electronics. Based on the idea of "Control-Alt-Delete", four patterns of the way forward for global e-waste recycling are proposed to meet a variety of local situations

Impact of Intermediate Hyperglycemia and Diabetes on Immune Dysfunction in Tuberculosis

Supplementary Data: Supplementary materials are available at Clinical Infectious Diseases online at https://academic.oup.com/cid/article/72/1/69/5857148#274319223 . Consisting of data provided by the authors to benefit the reader, the posted materials are not copyedited and are the sole responsibility of the authors, so questions or comments should be addressed to the corresponding author.Copyright © The Author(s) 2020. Background: People with diabetes have an increased risk of developing active tuberculosis (TB) and are more likely to have poor TB-treatment outcomes, which may impact on control of TB as the prevalence of diabetes is increasing worldwide. Blood transcriptomes are altered in patients with active TB relative to healthy individuals. The effects of diabetes and intermediate hyperglycemia (IH) on this transcriptomic signature were investigated to enhance understanding of immunological susceptibility in diabetes-TB comorbidity. Methods: Whole blood samples were collected from active TB patients with diabetes (glycated hemoglobin [HbA1c] ≥6.5%) or IH (HbA1c = 5.7% to <6.5%), TB-only patients, and healthy controls in 4 countries: South Africa, Romania, Indonesia, and Peru. Differential blood gene expression was determined by RNA-seq (n = 249). Results: Diabetes increased the magnitude of gene expression change in the host transcriptome in TB, notably showing an increase in genes associated with innate inflammatory and decrease in adaptive immune responses. Strikingly, patients with IH and TB exhibited blood transcriptomes much more similar to patients with diabetes-TB than to patients with only TB. Both diabetes-TB and IH-TB patients had a decreased type I interferon response relative to TB-only patients. Conclusions: Comorbidity in individuals with both TB and diabetes is associated with altered transcriptomes, with an expected enhanced inflammation in the presence of both conditions, but also reduced type I interferon responses in comorbid patients, suggesting an unexpected uncoupling of the TB transcriptome phenotype. These immunological dysfunctions are also present in individuals with IH, showing that altered immunity to TB may also be present in this group. The TB disease outcomes in individuals with IH diagnosed with TB should be investigated further.European Union’s Seventh Framework Programme (FP7 2007-2013 - Health) under grant agreement No 305279

Matrix Scaling and Balancing via Box Constrained Newton's Method and Interior Point Methods

© 2017 IEEE. In this paper, we study matrix scaling and balancing, which are fundamental problems in scientific computing, with a long line of work on them that dates back to the 1960s. We provide algorithms for both these problems that, ignoring logarithmic factors involving the dimension of the input matrix and the size of its entries, both run in time \widetilde{O}(m\log \kappa \log^2 (1/∈)) where ∈ is the amount of error we are willing to tolerate. Here, \kappa represents the ratio between the largest and the smallest entries of the optimal scalings. This implies that our algorithms run in nearly-linear time whenever \kappa is quasi-polynomial, which includes, in particular, the case of strictly positive matrices. We complement our results by providing a separate algorithm that uses an interior-point method and runs in time \widetilde{O}(m^{3/2} \log (1/∈)).In order to establish these results, we develop a new second-order optimization framework that enables us to treat both problems in a unified and principled manner. This framework identifies a certain generalization of linear system solving that we can use to efficiently minimize a broad class of functions, which we call second-order robust. We then show that in the context of the specific functions capturing matrix scaling and balancing, we can leverage and generalize the work on Laplacian system solving to make the algorithms obtained via this framework very efficient

Negative-Weight shortest paths and unit capacity minimum cost flow in Õ(m[superscript 10/7] log W) Time

In this paper, we study a set of combinatorial optimization problems on weighted graphs: the shortest path problem with negative weights, the weighted perfect bipartite matching problem, the unit-capacity minimum-cost maximum flow problem, and the weighted perfect bipartite b-matching problem under the assumption that ||b||1 = O(m). We show that each of these four problems can be solved in Õ(m[superscript 10/7] log W) time, where W is the absolute maximum weight of an edge in the graph, providing the first polynomial improvement in their sparse-graph time complexity in over 25 years. At a high level, our algorithms build on the interior-point method-based framework developed by Mądry (FOCS 2013) for solving unit-capacity maximum flow problem. We develop a refined way to analyze this framework, as well as provide new variants of the underlying preconditioning and perturbation techniques. Consequently, we are able to extend the whole interior-point method-based approach to make it applicable in the weighted graph regime

AC/DC: Alternating Compressed/DeCompressed training of deep neural networks

The increasing computational requirements of deep neural networks (DNNs) have led to significant interest in obtaining DNN models that are sparse, yet accurate. Recent work has investigated the even harder case of sparse training, where the DNN weights are, for as much as possible, already sparse to reduce computational costs during training. Existing sparse training methods are often empirical and can have lower accuracy relative to the dense baseline. In this paper, we present a general approach called Alternating Compressed/DeCompressed (AC/DC) training of DNNs, demonstrate convergence for a variant of the algorithm, and show that AC/DC outperforms existing sparse training methods in accuracy at similar computational budgets; at high sparsity levels, AC/DC even outperforms existing methods that rely on accurate pre-trained dense models. An important property of AC/DC is that it allows co-training of dense and sparse models, yielding accurate sparse–dense model pairs at the end of the training process. This is useful in practice, where compressed variants may be desirable for deployment in resource-constrained settings without re-doing the entire training flow, and also provides us with insights into the accuracy gap between dense and compressed models. The code is available at: https://github.com/IST-DASLab/ACDC