HAWKS: Evolving Challenging Benchmark Sets for Cluster Analysis

Comprehensive benchmarking of clustering algorithms is rendered difficult by two key factors: (i) the elusiveness of a unique mathematical definition of this unsupervised learning approach and (ii) dependencies between the generating models or clustering criteria adopted by some clustering algorithms and indices for internal cluster validation. Consequently, there is no consensus regarding the best practice for rigorous benchmarking, and whether this is possible at all outside the context of a given application. Here, we argue that synthetic datasets must continue to play an important role in the evaluation of clustering algorithms, but that this necessitates constructing benchmarks that appropriately cover the diverse set of properties that impact clustering algorithm performance. Through our framework, HAWKS, we demonstrate the important role evolutionary algorithms play to support flexible generation of such benchmarks, allowing simple modification and extension. We illustrate two possible uses of our framework: (i) the evolution of benchmark data consistent with a set of hand-derived properties and (ii) the generation of datasets that tease out performance differences between a given pair of algorithms. Our work has implications for the design of clustering benchmarks that sufficiently challenge a broad range of algorithms, and for furthering insight into the strengths and weaknesses of specific approaches

pySuStaIn: A Python implementation of the Subtype and Stage Inference algorithm

Progressive disorders are highly heterogeneous. Symptom-based clinical classification of these disorders may not reflect the underlying pathobiology. Data-driven subtyping and staging of patients has the potential to disentangle the complex spatiotemporal patterns of disease progression. Tools that enable this are in high demand from clinical and treatment-development communities. Here we describe the pySuStaIn software package, a Python-based implementation of the Subtype and Stage Inference (SuStaIn) algorithm. SuStaIn unravels the complexity of heterogeneous diseases by inferring multiple disease progression patterns (subtypes) and individual severity (stages) from cross-sectional data. The primary aims of pySuStaIn are to enable widespread application and translation of SuStaIn via an accessible Python package that supports simple extension and generalization to novel modeling situations within a single, consistent architecture

Sensitive SERS nanotags for use with 1550 nm (retina-safe) laser excitation

Chalcogenopyrylium nanotags demonstrate an unprecedented SERS performance with a retina safe, 1550 nm laser excitation. These unique nanotags consisting of chalcogenopyrylium dyes and 100 nm gold nanoparticles produce exceptional SERS signals with picomolar detection limits obtained at this extremely red-shifted and eye-safe laser excitation

Core excitations across the neutron shell gap in ²⁰⁷Tl

The single closed-neutron-shell, one proton-hole nucleus 207Tl was populated in deep-inelastic collisions of a 208Pb beam with a 208Pb target. The yrast and near-yrast level scheme has been established up to high excitation energy, comprising an octupol

Sensitive SERS nanotags for use with a hand-held 1064 nm Raman spectrometer

This is the first report of the use of a hand-held 1064 nm Raman spectrometer combined with red shifted surface enhanced Raman scattering (SERS) nanotags to provide an unprecedented performance in the short-wave infrared (SWIR) region. A library consisting of 17 chalcogenopyrylium nanotags produce extraordinary SERS responses with femtomolar detection limits being obtained using the portable instrument. This is well beyond previous SERS detection limits at this far red shifted wavelength and opens up new options for SERS sensors in the SWIR region of the electromagnetic spectrum (between 950-1700 nm)

Risk factors for human brucellosis in northern Tanzania

Little is known about the epidemiology of human brucellosis in sub-Saharan Africa. This hampers prevention and control efforts at the individual and population levels. To evaluate risk factors for brucellosis in northern Tanzania, we conducted a study of patients presenting with fever to two hospitals in Moshi, Tanzania. Serum taken at enrollment and at 4–6 week follow-up was tested by Brucella microagglutination test. Among participants with a clinically compatible illness, confirmed brucellosis cases were defined as having a ≥ 4-fold rise in agglutination titer between paired sera or a blood culture positive for Brucella spp., and probable brucellosis cases were defined as having a single reciprocal titer ≥ 160. Controls had reciprocal titers < 20 in paired sera. We collected demographic and clinical information and administered a risk factor questionnaire. Of 562 participants in the analysis, 50 (8.9%) had confirmed or probable brucellosis. Multivariable analysis showed that risk factors for brucellosis included assisting goat or sheep births (Odds ratio [OR] 5.9, 95% confidence interval [CI] 1.4, 24.6) and having contact with cattle (OR 1.2, 95% CI 1.0, 1.4). Consuming boiled or pasteurized dairy products was protective against brucellosis (OR 0.12, 95% CI 0.02, 0.93). No participants received a clinical diagnosis of brucellosis from their healthcare providers. The under-recognition of brucellosis by healthcare workers could be addressed with clinician education and better access to brucellosis diagnostic tests. Interventions focused on protecting livestock keepers, especially those who assist goat or sheep births, are needed

Improving actionable observability of large distribution networks for transmission operators to support improved system control, fault detection and mitigation

Copyright © 2017 The Author(s). The widespread introduction of phasor measurement unit (PMUs) in transmission networks is well understood and has improved visibility enhancing grid stability and avoiding low probability events such as blackouts. For many transmission system operators, there is little-to-no visibility of the real-time state of distribution networks beyond the grid supply points. With the increased penetration of distributed energy resources on low- and medium-voltage networks of the state, and thus behaviour, of the distribution network cannot be assumed to follow historical patterns. The future transition to distribution system operator concept requires better visibility, especially around grid supply points, for deploying wide-area control strategies and active network management schemes. This implies active sharing of data between transmission and distribution monitoring systems. There are a number of challenges in extending the use of PMUs to distribution networks. Many of the lessons and best practises at transmission do not translate to the operation of distribution networks, as an exponential increase in network complexity makes it infeasible to perform complex analysis of the complete network model in real time. This paper presents a methodology for addressing the problems faced in deploying microPMUs at the distribution level.Open Grid Systems OGS Studentship

Observation of Low Energy Raman Modes in Twisted Bilayer Graphene

Two new Raman modes below 100 cm^-1 are observed in twisted bilayer graphene grown by chemical vapor deposition. The two modes are observed in a small range of twisting angle at which the intensity of the G Raman peak is strongly enhanced, indicating that these low energy modes and the G Raman mode share the same resonance enhancement mechanism, as a function of twisting angle. The 94 cm^-1 mode (measured with a 532 nm laser excitation) is assigned to the fundamental layer breathing vibration (ZO (prime) mode) mediated by the twisted bilayer graphene lattice, which lacks long-range translational symmetry. The dependence of this modes frequency and linewidth on the rotational angle can be explained by the double resonance Raman process which is different from the previously-identified Raman processes activated by twisted bilayer graphene superlattice. The dependence also reveals the strong impact of electronic-band overlaps of the two graphene layers. Another new mode at 52 cm^-1, not observed previously in the bilayer graphene system, is tentatively attributed to a torsion mode in which the bottom and top graphene layers rotate out-of-phase in the plane.Comment: 12 pages, 5 figures, 14 supp. figures (accepted by Nano Lett

Octupole transitions in the 208Pb region

The 208Pb region is characterised by the existence of collective octupole states. Here we populated such states in 208Pb + 208Pb deep-inelastic reactions. γ-ray angular distribution measurements were used to infer the octupole character of several E3 transitions. The octupole character of the 2318 keV 17− → 14+ in 208Pb, 2485 keV 19/2 − → 13/2 + in 207Pb, 2419 keV 15/2 − → 9/2 + in 209Pb and 2465 keV 17/2 + → 11/2 − in 207Tl transitions was demonstrated for the first time. In addition, shell model calculations were performed using two different sets of two-body matrix elements. Their predictions were compared with emphasis on collective octupole states.This work is supported by the Science and Technology Facilities Council (STFC), UK, US Department of Energy, Office of Nuclear Physics, under Contract No. DEAC02-06CH11357 and DE-FG02-94ER40834, NSF grant PHY-1404442