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Background: The outbreak of COVID-19 overlaps with the usual flu season, and the main signs, symptoms and imaging manifestations in COVID-19 and flu infections share similarity. This study is aimed to constructed an accurate and robust model for initial screening and differential diagnosis of COVID-19 and influenza A, so as to provide an effective tool for global prevention and control of COVID-19 outbreak. Methods: The 151 COVID-19 infections patients and 155 influenza A patients in Fuyang No.2 People's Hospital were included and randomly assigned in a 4:1 ratio to train set and test set. Univariate logistic regression analysis was conducted between two diseases. The predictor variables were selected by variables importance assessed by random forest algorithms and were analyzed in train set to develop classification and regression tree models. The validity of the model was tested using data from test set. Findings: Recursive partitioning of the train set indicated that the optimal model for prediction was model A (signs and symptoms+ serum biochemistry), in which the best single predictor for COVID-19 patients was normal or high level of LDL-c, followed by low level of CK, then by frequency of respiratory symptom less than 3 times, and last by highest temperature on the first day of admission less than 38℃. The AUC, sensitivity, specificity was 93%, 100%, 87% respectively. The Suboptimal model was model B (signs and symptoms+ routine blood), in which the best single predictor for COVID-19 patients was low level of EO#, followed by normal level of MONO%, then by normal level of HCT, next by highest temperature on the first day of admission less than 37℃, and last by frequency of respiratory symptom less than 1 times. The AUC, sensitivity, specificity was 87%, 73%, 100% respectively. Interpretation: The two models that we created provides clinicians with a rapid triage tool and identification means for quickly identifying and screening pneumonia caused by COVID-19 and seasonal influenza. The optimal model can be applied to developed countries/regions and major hospitals, and the suboptimal one can be used in grass-roots areas, underdeveloped regions and small hospitals. Funding Statement: This work is supported by Shanghai Municipal Science and Technology Major Project (No.2018SHZDZX01) and ZJ Lab; the Shanghai Municipal Commission of Health and the Family Foundation for Young Talents (2017YQ023). Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: This study was approved by the Ethics Committee of the Fuyang No.2 People's Hospital, Anhui Province.

We observe that combining the techniques of Arora, Rao, and Vazirani, with the rounding algorithm of Rao and Richa yields an O(√logn log logn)-approximation for the minimum-linear arrangement problem. This improves over the O(logn)-approximation of Rao and Richa.

We define a natural notion of efficiency for approximate nearest-neighbor (ANN) search in general n-point metric spaces, namely the existence of a randomized algorithm which answers (1 + e)-ANN queries in polylog(n) time using only polynomial space. We then study which families of metric spaces admit efficient ANN schemes in the black-box model, where only oracle access to the distance function is given, and any query consistent with the triangle inequality may be asked.For e < 2/5, we offer a complete answer to this problem. Using the notion of metric dimension defined in [A. Gupta, et al., Bounded geometries, fractals, and low-distortion embeddings, in: 44th Annu. IEEE Symp. on Foundations of Computer Science, 2003, pp. 534-543] (a la [P. Assouad, Plongements lipschitziens dans Rn, Bull. Soc. Math. France 111 (4) (1983) 429-448]), we show that a metric space X admits an efficient (1+e)-ANN scheme for any e < 2/5 if and only if dim(X) = O(log log n). For coarser approximations, clearly the upper bound continues to hold, but there is a threshold at which our lower bound breaks down--this is precisely when points in the "ambient space" may begin to affect the complexity of "hard" subspaces S ⊆ X. Indeed, we give examples which show that dim(X) does not characterize the black-box complexity of ANN above the threshold.Our scheme for ANN in low-dimensional metric spaces is the first to yield efficient algorithms without relying on any additional assumptions on the input. In previous approaches (e.g., [K.L. Clarkson, Nearest neighbor queries in metric spaces, Discrete Comput. Geom. 22(1) (1999) 63-93; D. Karger, M. Ruhl, Finding nearest neighbors in growth-restricted metrics, in: 34th Annu. ACM Symp. on the Theory of Computing, 2002, pp. 63-66; R. Krauthgamer, J.R. Lee, Navigating nets: simple algorithms for proximity search, in: 15th Annu. ACM-SIAM Symp. on Discrete Algorithms, 2004, pp. 791-801; K. Hildrum, et al., A note on finding nearest neighbors in growth-restricted metrics, in: Proc. of the 15th Annu. ACM-SIAM Symp. on Discrete Algorithms, 2004, pp. 560-561]), even spaces with dim(X) = O(1) sometimes required Ω(n) query times.

We study the metric properties of finite subsets of L1. The analysis of such metrics is central to a number of important algorithmic problems involving the cut structure of weighted graphs, including the Sparsest Cut Problem, one of the most compelling open problems in the field of approximation algorithms. Additionally, many open questions in geometric non-linear functional analysis involve the properties of finite subsets of L1.We present some new observations concerning the relation of L1 to dimension, topology, and Euclidean distortion. We show that every n-point subset of L1 embeds into L2 with average distortion O(√log n), yielding the first evidence that the conjectured worst-case bound of O(√log n) is valid. We also address the issue of dimension reduction in Lp for p ∈ (1, 2). We resolve a question left open by M. Charikar and A. Sahai [Dimension reduction in the l1 norm, in: Proceedings of the 43rd Annual IEEE Conference on Foundations of Computer Science, ACM, 2002, pp. 251-260] concerning the impossibility of dimension reduction with a linear map in the above cases, and we show that a natural variant of the recent example of Brinkman and Charikar [On the impossibility of dimension reduction in l1, in: Proceedings of the 44th Annual IEEE Conference on Foundations of Computer Science, ACM, 2003, pp. 514-523], cannot be used to prove a lower bound for the non-linear case. This is acomplished by exhibiting constant-distortion embeddings of snowflaked planar metrics into Euclidean space.

A metric space X is said to be absolutely Lipschitz extendable if every Lipschitz function f from X into any Banach space Z can be extended to any containing space Y⊇X, where the loss in the Lipschitz constant in the extension is independent of Y,Z, and f. We show that various classes of natural metric spaces are absolutely Lipschitz extendable. To cite this article: J.R. Lee, A. Naor, C. R. Acad. Sci. Paris, Ser. I 338 (2004).

Upon induction of a bacteriophage λ lysogen, a site-specific recombination reaction excises the phage genome from the chromosome of its bacterial host. A critical regulator of this process is the phage-encoded excisionase (Xis) protein, which functions both as a DNA architectural factor and by cooperatively recruiting integrase to an adjacent binding site specifically required for excision. Here we present the three-dimensional structure of Xis and the results of a structure-based mutagenesis study to define the molecular basis of its function. Xis adopts an unusual “winged”-helix motif that is modeled to interact with the major- and minor-grooves of its binding site through a single α-helix and loop structure (“wing”), respectively. The C-terminal tail of Xis, which is required for cooperative binding with integrase, is unstructured in the absence of DNA. We propose that asymmetric bending of DNA by Xis positions its unstructured C-terminal tail for direct contacts with the N-terminal DNA-binding domain of integrase and that an ensuing disordered to ordered transition of the tail may act to stabilize the formation of the tripartite integrase–Xis–DNA complex required for phage excision.

This paper analyzes 79 categorical case studies in trade and the environment to determine basic attributes of the field. It intends to describe these attributes, organized into four intellectual clusters, in order to set some basic standards for measuring trends and making initial quantitative generalizations about policy in the trade and environment field. This general review and categorization is a necessary step in the development of any field of study and absolutely critical to building a basis for cumulative research and advancement of knowledge. The findings suggest that the data mirror general beliefs about trade and environment with respect to the types of problems, actors involved, remedies, industries and other key attributes. Notably, the findings highlight the difference between process and product in environmental cases and the relation between rich and poor countries in trade and environment issues.

The authors conducted a retrospective study of acute-care hospitalization over a 2-year period for patients diagnosed with Alzheimer's disease (AD). These patients were compared to an age- and gender-matched group of non-AD patients. AD patients had fewer admissions and fewer comorbid medical diagnoses, but had a significantly longer total length of hospital stay. Possible explanations for the increased length of stay and suggestions for further research are discussed.

Introduction: Massachusetts was an early adopter of the Accountable Care Organization payment model. In response, Healthcare systems have been under pressure to reduce costs and evaluate resource allocation to optimize patient care. In the Cytopathology laboratory, we hypothesized that changing from reflex cellblock (RCB) preparation for fluids (FL) to a selective CB (SCB) preparation method would reduce cost without compromising care. Materials and Methods: Two FL cohorts were analyzed and compared for utility and cost of specimen preparation for diagnosis. The RCB group was composed of all FL cases from 2009 when CBs were prepared for all FL specimens to supplement the SurePath slide. The SCB group was from 2011, when the workflow was modified to prepare CB only on those cases where cytological evaluation of the SurePath slide indicated a need for ancillary testing. Cost for cellblock preparation was estimated to be $20 for technical charges for preparing a CB. Results: The RCB groups consisted of 951 CB from 951 FL (100%). A negative interpretationwasmade on both SurePath andCB in 73%of cases, and a malignant diagnosis without ancillary testing was made on both in 13% of cases. Ancillary testing, contributing to final diagnosis was performed on 16% of the CB. The SCB consisted of 261 CB from 1386 FL (19%); a reduction of CBpreparations of 81%.Anegative interpretationwasmade on both SurePath and CB in 30% of cases. A malignant diagnosis that did not need ancillary testing was made on both in 30% of cases. Ancillary testing, contributing to the final diagnosis was performed on 41% of the SCB cases. An estimation of savings from the modified workflow was $22,500 not including pathologist charge and ancillary testing. Conclusions: Selectively processing CB from FL reduces laboratory costs without compromising patient care.