Anomalous heavy-fermion and ordered states in the filled skutterudite PrFe4P12

Specific heat and magnetization measurements have been performed on high-quality single crystals of filled-skutterudite PrFe_4P_{12} in order to study the high-field heavy-fermion state (HFS) and low-field ordered state (ODS). From a broad hump observed in C/T vs T in HFS for magnetic fields applied along the direction, the Kondo temperature of ~ 9 K and the existence of ferromagnetic Pr-Pr interactions are deduced. The {141}-Pr nuclear Schottky contribution, which works as a highly-sensitive on-site probe for the Pr magnetic moment, sets an upper bound for the ordered moment as ~ 0.03 \mu_B/Pr-ion. This fact strongly indicates that the primary order parameter in the ODS is nonmagnetic and most probably of quadrupolar origin, combined with other experimental facts. Significantly suppressed heavy-fermion behavior in the ODS suggests a possibility that the quadrupolar degrees of freedom is essential for the heavy quasiparticle band formation in the HFS. Possible crystalline-electric-field level schemes estimated from the anisotropy in the magnetization are consistent with this conjecture.Comment: 7 pages and 7 figures. Accepted for publication in Phys. Rev.

Relative Equilibria in the Four-Vortex Problem with Two Pairs of Equal Vorticities

We examine in detail the relative equilibria in the four-vortex problem where two pairs of vortices have equal strength, that is, \Gamma_1 = \Gamma_2 = 1 and \Gamma_3 = \Gamma_4 = m where m is a nonzero real parameter. One main result is that for m > 0, the convex configurations all contain a line of symmetry, forming a rhombus or an isosceles trapezoid. The rhombus solutions exist for all m but the isosceles trapezoid case exists only when m is positive. In fact, there exist asymmetric convex configurations when m < 0. In contrast to the Newtonian four-body problem with two equal pairs of masses, where the symmetry of all convex central configurations is unproven, the equations in the vortex case are easier to handle, allowing for a complete classification of all solutions. Precise counts on the number and type of solutions (equivalence classes) for different values of m, as well as a description of some of the bifurcations that occur, are provided. Our techniques involve a combination of analysis and modern and computational algebraic geometry

Innovations in air sampling to detect plant pathogens

Many innovations in the development and use of air sampling devices have occurred in plant pathology since the first description of the Hirst spore trap. These include improvements in capture efficiency at relatively high air-volume collection rates, methods to enhance the ease of sample processing with downstream diagnostic methods and even full automation of sampling, diagnosis and wireless reporting of results. Other innovations have been to mount air samplers on mobile platforms such as UAVs and ground vehicles to allow sampling at different altitudes and locations in a short space of time to identify potential sources and population structure. Geographical Information Systems and the application to a network of samplers can allow a greater prediction of airborne inoculum and dispersal dynamics. This field of technology is now developing quickly as novel diagnostic methods allow increasingly rapid and accurate quantifications of airborne species and genetic traits. Sampling and interpretation of results, particularly action-thresholds, is improved by understanding components of air dispersal and dilution processes and can add greater precision in the application of crop protection products as part of integrated pest and disease management decisions. The applications of air samplers are likely to increase, with much greater adoption by growers or industry support workers to aid in crop protection decisions. The same devices are likely to improve information available for detection of allergens causing hay fever and asthma or provide valuable metadata for regional plant disease dynamics

Annual Research Review: interparental conflict and youth psychopathology: an evidence review and practice focused update

The quality of the interparental relationship is recognized as an important influence on child and adolescent psychopathology. Historically, clinically-oriented research on this topic has focused on the impacts of parental divorce and domestic violence as primary interparental relationship influences on child outcomes, to the relative neglect of dimensional or qualitative features of the couple/interparental relationship for youth (child and adolescent) psychopathology. Recent research has highlighted that children are affected by attributes of interparental conflict, specifically how parents express and manage conflicts in their relationship, across a continuum of expressed severity and negativity – ranging from silence to violence. Further, new evidence highlights that children’s emotional, behavioral, social, academic outcomes and future interpersonal relationships are adversely affected by conflict between parents/carers whether adults are living together or not (i.e. married or separated), or where children are or are not genetically related to their rearing parents (e.g. adoption). We review evidence and present an integrated theoretical model, highlighting how children are affected by interparental conflict and what this evidence base means for effective intervention and prevention program development, as well as the development of possible cost-benefit models. Additionally, we review policy implications of this research and highlight some very recent examples of UK-based policy focusing on addressing the interparental relationship and its impact on youth psychopathology

Parity nonconserving cold neutron-parahydrogen interactions

Three pion dominated observables of the parity nonconserving interactions between the cold neutrons and parahydrogen are calculated. The transversely polarized neutron spin rotation, unpolarized neutron longitudinal polarization, and photon-asymmetry of the radiative polarized neutron capture are considered. For the numerical evaluation of the observables, the strong interactions are taken into account by the Reid93 potential and the parity nonconserving interactions by the DDH model along with the two-pion exchange.Comment: 17 pages, 2 figure

Characterisation and calibration of low-cost PM sensors at high temporal resolution to reference-grade performance

Particulate Matter (PM) low-cost sensors (LCS) present a cost-effective opportunity to improve the spatiotemporal resolution of airborne PM data. Previous studies focused on PM-LCS-reported hourly data and identified, without fully addressing, their limitations. However, PM-LCS provide measurements at finer temporal resolutions. Furthermore, government bodies have developed certifications to accompany new uses of these sensors, but these certifications have shortcomings. To address these knowledge gaps, PM-LCS of two models, 8 Sensirion SPS30 and 8 Plantower PMS5003, were collocated for one year with a Fidas 200S, MCERTS-certified PM monitor and were characterised at 2 min resolution, enabling replication of certification processes, and highlighting their limitations and improvements. Robust linear models using sensor-reported particle number concentrations and relative humidity, coupled with 2-week biannual calibration campaigns, achieved reference-grade performance, at median PM2.5 background concentration of 5.5 μg/m3, demonstrating that, with careful calibration, PM-LCS may cost-effectively supplement reference equipment in multi-nodes networks with fine spatiotemporality

Geographies of responsibility

Issues of space, place and politics run deep. There is a long history of the entanglement of the conceptualisation of space and place with the framing of political positions. The injunction to think space relationally is a very general one and, as this collection indicates, can lead in many directions. The particular avenue to be explored in this paper concerns the relationship between identity and responsibility, and the potential georaphies of both

CP Violation in Supersymmetric U(1)' Models

The supersymmetric CP problem is studied within superstring-motivated extensions of the MSSM with an additional U(1)' gauge symmetry broken at the TeV scale. This class of models offers an attractive solution to the mu problem of the MSSM, in which U(1)' gauge invariance forbids the bare mu term, but an effective mu parameter is generated by the vacuum expectation value of a Standard Model singlet S which has superpotential coupling of the form SH_uH_d to the electroweak Higgs doublets. The effective mu parameter is thus dynamically determined as a function of the soft supersymmetry breaking parameters, and can be complex if the soft parameters have nontrivial CP-violating phases. We examine the phenomenological constraints on the reparameterization invariant phase combinations within this framework, and find that the supersymmetric CP problem can be greatly alleviated in models in which the phase of the SU(2) gaugino mass parameter is aligned with the soft trilinear scalar mass parameter associated with the SH_uH_d coupling. We also study how the phases filter into the Higgs sector, and find that while the Higgs sector conserves CP at the renormalizable level to all orders of perturbation theory, CP violation can enter at the nonrenormalizable level at one-loop order. In the majority of the parameter space, the lightest Higgs boson remains essentially CP even but the heavier Higgs bosons can exhibit large CP-violating mixings, similar to the CP-violating MSSM with large mu parameter.Comment: 29 pp, 3 figs, 2 table

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization