Bipartite Temporal Graphs and the Parameterized Complexity of Multistage 2-Coloring

We consider the algorithmic complexity of recognizing bipartite temporal graphs. Rather than defining these graphs solely by their underlying graph or individual layers, we define a bipartite temporal graph as one in which every layer can be 2-colored in a way that results in few changes between any two consecutive layers. This approach follows the framework of multistage problems that has received a growing amount of attention in recent years. We investigate the complexity of recognizing these graphs. We show that this problem is NP-hard even if there are only two layers or if only one change is allowed between consecutive layers. We consider the parameterized complexity of the problem with respect to several structural graph parameters, which we transfer from the static to the temporal setting in three different ways. Finally, we consider a version of the problem in which we only restrict the total number of changes throughout the lifetime of the graph. We show that this variant is fixed-parameter tractable with respect to the number of changes

Vertex Cover and Feedback Vertex Set Above and Below Structural Guarantees

Vertex Cover parameterized by the solution size k is the quintessential fixed-parameter tractable problem. FPT algorithms are most interesting when the parameter is small. Several lower bounds on k are well-known, such as the maximum size of a matching. This has led to a line of research on parameterizations of Vertex Cover by the difference of the solution size k and a lower bound. The most prominent cases for such lower bounds for which the problem is FPT are the matching number or the optimal fractional LP solution. We investigate parameterizations by the difference between k and other graph parameters including the feedback vertex number, the degeneracy, cluster deletion number, and treewidth with the goal of finding the border of fixed-parameter tractability for said difference parameterizations. We also consider similar parameterizations of the Feedback Vertex Set problem

Most Classic Problems Remain NP-hard on Relative Neighborhood Graphs and their Relatives

Proximity graphs have been studied for several decades, motivated by applications in computational geometry, geography, data mining, and many other fields. However, the computational complexity of classic graph problems on proximity graphs mostly remained open. We now study 3-Colorability, Dominating Set, Feedback Vertex Set, Hamiltonian Cycle, and Independent Set on the proximity graph classes relative neighborhood graphs, Gabriel graphs, and relatively closest graphs. We prove that all of the problems remain NP-hard on these graphs, except for 3-Colorability and Hamiltonian Cycle on relatively closest graphs, where the former is trivial and the latter is left open. Moreover, for every NP-hard case we additionally show that no $2^{o(n^{1/4})}$-time algorithm exists unless the ETH fails, where n denotes the number of vertices

How the Application of Machine Learning Systems Changes Business Processes: A Multiple Case Study

Machine Learning (ML) systems are applied in organizations to substitute or complement human knowledge work. Although organizations invest heavily in ML, the resulting business benefits often remain unclear. To explain the impact of ML systems, it is necessary to understand how their application changes business processes and affects process performance. In our exploratory multiple case study, we analyze the application of multiple productive ML systems in one organization to (1.) describe how activity composition, allocation, and sequence change in ML-supported processes; (2.) distinguish how the applied ML system type and task characteristics influence process changes; and (3.) explain how process efficiency and quality are affected. As a result, we develop three preliminary change patterns: Lift & Shift, Divide & Conquer, and Expand & Intensify. Our research aims to contribute to the future of work and IS value literature by connecting the emerging knowledge on ML systems to their process-level implications

Beyond immune escape:a variant surface glycoprotein causes suramin resistance in Trypanosoma brucei

Suramin is one of the first drugs developed in a medicinal chemistry program (Bayer, 1916), and it is still the treatment of choice for the hemolymphatic stage of African sleeping sickness caused by Trypanosoma brucei rhodesiense. Cellular uptake of suramin occurs by endocytosis, and reverse genetic studies with T. b. brucei have linked downregulation of the endocytic pathway to suramin resistance. Here we show that forward selection for suramin resistance in T. brucei spp. cultures is fast, highly reproducible and linked to antigenic variation. Bloodstream-form trypanosomes are covered by a dense coat of variant surface glycoprotein (VSG), which protects them from their mammalian hosts' immune defenses. Each T. brucei genome contains over 2000 different VSG genes, but only one is expressed at a time. An expression switch to one particular VSG, termed VSGSur , correlated with suramin resistance. Reintroduction of the originally expressed VSG gene in resistant T. brucei restored suramin susceptibility. This is the first report of a link between antigenic variation and drug resistance in African trypanosomes

Isolation and propagation of Trypanosoma brucei gambiense from sleeping sickness patients in south Sudan

This study aimed at isolating Trypanosoma brucei gambiense from human African trypanosomiasis (HAT) patients from south Sudan. Fifty HAT patients identified during active screening surveys were recruited, most of whom (49/50) were in second-stage disease. Blood and cerebrospinal fluid samples collected from the patients were cryopreserved using Triladyl® as the cryomedium. The samples were stored at −150 °C in liquid nitrogen vapour in a dry shipper. Eighteen patient stabilates could be propagated in immunosuppressed Mastomys natalensis and/or SCID mice. Parasitaemia was highest in SCID mice. Further subpassages in M. natalensis increased the virulence of the trypanosomes and all 18 isolates recovered from M. natalensis or SCID mice became infective to other immunosuppressed mouse breeds. A comparison of immunosuppressed M. natalensis and Swiss White, C57/BL and BALB/c mice demonstrated that all rodent breeds were susceptible after the second subpassage and developed a parasitaemia >106/ml by Day 5 post infection. The highest parasitaemias were achieved in C57/BL and BALB/c mice. These results indicate that propagation of T. b. gambiense isolates after initial isolation in immunosuppressed M. natalensis or SCID mice can be done in a range of immunosuppressed rodent

Augmented Reality-based Robot Control for Laparoscopic Surgery

Minimally invasive surgery is the standard formany abdominal interventions, with an increasing use of tele-manipulated robots. As collaborative robots enter the field ofmedical interventions, their intuitive control needs to be ad-dressed. Augmented reality can thereby support a surgeonby representing the surgical scene in a natural way. In thiswork, an augmented reality based robot control for laparo-scopic cholecystectomy is presented. A user can interact withthe virtual scene to clip the cystic duct and artery as well asto manipulate the deformable gallbladder. An evaluation wasperformed based on the SurgTLX and system usability scale

White-Nose Syndrome Fungus (Geomyces destructans) in Bat, France

White-nose syndrome is caused by the fungus Geomyces destructans and is responsible for the deaths of >1,000,000 bats since 2006. This disease and fungus had been restricted to the northeastern United States. We detected this fungus in a bat in France and assessed the implications of this finding