Consistency Cuts for Dantzig-Wolfe Reformulations

A New Family of Valid-Inequalities for Dantzig-Wolfe Reformulation of Mixed Integer Linear Programs In “Consistency Cuts for Dantzig-Wolfe Reformulation,” Jens Vinther Clausen, Richard Lusby, and Stefan Ropke present a new family of valid inequalities to be applied to Dantzig-Wolfe reformulations with binary linking variables. They show that, for Dantzig-Wolfe reformulations of mixed integer linear programs that satisfy certain properties, it is enough to solve the linear programming relaxation of the Dantzig-Wolfe reformulation with all consistency cuts to obtain integer solutions. An example of this is the temporal knapsack problem; the effectiveness of the cuts is tested on a set of 200 instances of this problem, and the results are state-of-the-art solution times. For problems that do not satisfy these conditions, the cuts can still be used in a branch-and-cut-and-price framework. In order to show this, the cuts are applied to a set of generic mixed linear integer programs from the online library MIPLIB. These tests show the applicability of the cuts in general.

Impact of COVID-19 Pandemic on Utilization of Facility-Based Essential Maternal and Child Health Services in North Shewa Zone, Ethiopia

Introduction: Ethiopia registered its first case of COVID-19 on March 13, 2020. We aimed to assess maternal, newborn, and child health care (MNCH) utilization during the first six months of the COVID-19 pandemic, as well as potential barriers and enablers of service utilization from health care providers and clients. Methods: Mixed study design was conducted as part of the Birhan Health and Demographic Surveillance System in Ethiopia. The trend of service utilization during the first six months of COVID-19 was compared to corresponding time and data points of the preceding year. Result: Service utilization of new family planning visits (43.2 to 28.5/month, p = 0.014) and sick under five child visits (225.0 to 139.8/month, P = 007) declined during the initial six months of the pandemic compared to the same period in the preceding year. Antenatal and postnatal care visits, facility delivery rates, and child routine immunization visits also decreased although this did not reach statistical significance. Interviews with health care providers and clients highlighted several barriers to service utilization during COVID-19, including fear of disease transmission, economic hardship, and transport service disruptions and restrictions. Enablers of service utilization included communities' decreased fear of COVID-19, and awareness-raising activities. Conclusion: Provision of essential MNCH services is crucial to ascertain favorable maternal and child health outcomes. In low- and middle-income country settings like Ethiopia, health systems might be fragile to withstand the caseloads and priority setting due to the pandemic. Our study presents early findings on the utilization of MNCH services that were maintained except sick child and new family planning visits. Government leaders, policy makers, and clinicians who wish to improve the resilience of their health system will need to continuously monitor service utilization and clients' evolving concerns during the pandemic to prevent increases in maternal and child morbidity and mortality.

Aberrant Structure MRI in Parkinson’s Disease and Comorbidity with Depression Based on Multinomial Tensor Regression Analysis

Background: Depression is a prominent and highly prevalent nonmotor feature in patients with Parkinson’s disease (PD). The neural and pathophysiologic mechanisms of PD with depression (DPD) remain unclear. The current diagnosis of DPD largely depends on clinical evaluation. Methods: We proposed a new family of multinomial tensor regressions that leveraged whole-brain structural magnetic resonance imaging (MRI) data to discriminate among 196 non-depressed PD (NDPD) patients, 84 DPD patients, 200 healthy controls (HC), and to assess the special brain microstructures in NDPD and DPD. The method of maximum likelihood estimation coupled with state-of-art gradient descent algorithms was used to predict the individual diagnosis of PD and the development of DPD in PD patients. Results: The results reveal that the proposed efficient approach not only achieved a high prediction accuracy (0.94) with a multi-class AUC (0.98) for distinguishing between NDPD, DPD, and HC on the testing set but also located the most discriminative regions for NDPD and DPD, including cortical regions, the cerebellum, the brainstem, the bilateral basal ganglia, and the thalamus and limbic regions. Conclusions: The proposed imaging technique based on tensor regression performs well without any prior feature information, facilitates a deeper understanding into the abnormalities in DPD and PD, and plays an essential role in the statistical analysis of high-dimensional complex MRI imaging data to support the radiological diagnosis of comorbidity of depression with PD.

Strong Differential Sandwich Results for Bazilevic-Sakaguchi Type Functions Associated with Admissible Functions

In the present article, we define a new family for holomorphic functions (so-called Bazilevic-Sakaguchi type functions) and determinate strong differential subordination and superordination results for these new functions by investigating certain suitable classes of admissible functions. These results are applied to obtain strong differential sandwich results.

Genomic insights into the phylogeny and biomass-degrading enzymes of rumen ciliates

Understanding the biodiversity and genetics of the gut microbiome has important implications for host physiology. One underexplored and elusive group is ciliated protozoa, which play crucial roles in regulating gut microbial interactions. Integrating single-cell sequencing and an assembly-and-identification pipeline, we acquired 52 high-quality ciliate genomes of 22 rumen morphospecies for all major abundant clades. With these genomes, we firstly resolved the taxonomic and phylogenetic framework that reclassified them into 19 species spanning 13 genera and reassigned the genus Dasytricha from Isotrichidae to a new family Dasytrichidae. Via extensive horizontal gene transfer and gene family expansion, rumen ciliates possess a broad array of enzymes to synergistically degrade plant and microbial carbohydrates. In particular, ~80% of the degrading enzymes in Diplodiniinae and Ophryoscolecinae act on plant cell wall, and the high activities of their cellulase, xylanase and lysozyme reflect the potential of ciliate enzymes for biomass-conversion. Additionally, the new ciliate dataset greatly facilitated the rumen metagenomic analyses by allowing ~12% of reads to be classified.

The first epiphytic macrolichen and its implication to the interacting with Mesozoic forest ecosystem

Lichens are well known as pioneer organisms or stress-tolerant extremophiles playing a core role in the early formation of terrestrial ecosystems, of which epiphytic lichens make a distinct contribution to the water-cycle and nutrient cycling in forest ecosystem. But due to the scarcity of relevant fossil records, the evolutionary history of epiphytic lichens is poorly documented. Herein, based on the new material of Daohugouthallus ciliiferus, we demonstrated that the hitherto oldest macrolichen inhabited a gymnosperm branch, representing the first unambiguous Jurassic epiphytic lichen. Combing the fossil and extant macrolichen representatives, we performed the geometric morphometric analysis and comprehensive comparison to infer the systematic status of this rare Jurassic macrolichen. The results declared that D. ciliiferus cannot be assigned to any known macrolichen lineages for its elder age and particular habits, and therefore a new family, Daohugouthallaceae was proposed. This work updated the current knowledge to the historical evolution of epiphytic lichens, implying the macrolichens may have diversified much earlier than the generally accepted K–Pg boundary. In addition, our new finding also provided direct evidence for tracing the continuing joint development of epiphytic lichens and forest ecosystem since the Jurassic of 165 Mya.

Adversarially Robust Learning via Entropic Regularization

In this paper we propose a new family of algorithms, ATENT, for training adversarially robust deep neural networks. We formulate a new loss function that is equipped with an additional entropic regularization. Our loss function considers the contribution of adversarial samples that are drawn from a specially designed distribution in the data space that assigns high probability to points with high loss and in the immediate neighborhood of training samples. Our proposed algorithms optimize this loss to seek adversarially robust valleys of the loss landscape. Our approach achieves competitive (or better) performance in terms of robust classification accuracy as compared to several state-of-the-art robust learning approaches on benchmark datasets such as MNIST and CIFAR-10.

RAA enzyme is a new family of class A extended-spectrum β-lactamase from the Riemerella anatipestifer RCAD0122 strain

Whole genome sequencing of Riemerella anatipestifer isolate RCAD0122 revealed a chromosomally-located β-lactamases gene, bla RAA-1 , which encoded a novel class A extended-spectrum β-lactamases (ESBL), RAA-1. The RAA-1 shared ≤ 65% amino acid sequence identity with other characterized β-lactamases. The kinetic assay of native purified RAA-1 revealed ESBL-like hydrolysis activity. Furthermore, bla RAA-1 could be transferred to a homologous strain by natural transformation. However, the epidemiological study showed that the bla RAA-1 gene is not prevalent currently.