1,244 research outputs found
Immigrant Workers in the Cleaning Industry: The Experience of Boston\u27s Central Americans
This study has two objectives: to describe Central Americans\u27 employment experience in the Boston area by focusing on cleaning workers and to explore the reasons why Central Americans in particular, and immigrants in general, become concentrated in industries like cleaning. The study highlights a number of characteristics of immigrant workers and of cleaning work that contribute to employment in the industry. Recent immigrants need jobs that do not require English skills or formal training, can be accessed informally, and offer schedules that allow them to take on additional work. Cleaning companies, in turn, need a constant source of reliable workers who are willing to do work that many consider undesirable in return for relatively low wages. The study suggests that the key factor linking Central American workers with cleaning is the formation of social networks in immigrant communities, which aid in transmitting employment information. The results also suggest that although they view cleaning jobs as temporary, many Central Americans remain in the industry for long periods because they lack better employment opportunities
Cosmological Constraints from Hubble Parameter versus Redshift Data
We use the Simon, Verde, & Jimenez (2005) determination of the redshift
dependence of the Hubble parameter to constrain cosmological parameters in
three dark energy cosmological models. We consider the standard CDM
model, the XCDM parameterization of the dark energy equation of state, and a
slowly rolling dark energy scalar field with an inverse power-law potential.
The constraints are restrictive, consistent with those derived from Type Ia
supernova redshift-magnitude data, and complement those from galaxy cluster gas
mass fraction versus redshift data.Comment: Minor changes, including an estimate for H_0. ApJL, in pres
Behavioural loyalty towards store brands.
This paper applies a consumer brand choice model to measure store brand (SB) loyalty. The aim of this paper is to examine whether SB loyalty is different across categories, and we focus on risk perception as an explanatory variable. The model is estimated using ACNielsen Spanish household scanner panel data on two laundry detergent categories over a 2 year period for more than 1107 households. Loyalty, price, socio demographics and shopping behaviour variables are included. The discrete choice model formulation is the logit modelStore brands; National brands; Brand loyalty; Logit model; Household scanner panel;
Brucellosis in Terekeka County, Central Equatoria State, Southern Sudan
Objectives: To identify factors associated with Brucellosis in patients attending Terekeka Health Facility, Terekeka County, Central Equatoria State, Southern Sudan and to evaluate the utility of the rapid test kit Euracil®.Design: A facility based case-control study.Setting: Terekeka Health Facility, Terekeka County, Central Equatoria State, Southern Sudan.Subjects: Cases were patients presenting at the Terekeka Health Facility with clinical symptoms suggestive of Brucellosis and tested positive for Brucellosis by rapid antigen test while controls were selected from individuals attending Terekeka Health facility with health problems unrelated to brucellosis or febrile illness.Results: A total of fifty eight cases with clinical symptoms suggestive of and tested positive for Brucellosis by rapid antigen test presented. A total of 116 consented controls were recruited into the study. Males accounted for 52% of the cases and 53% of the controls. The mean age was 31 years for both groups. Cases without formal education were 84% while 40% had no source of income, 20% of the cases and 14% of the controls were cattle keepers while 5% of the cases and 13% of the controls were students. In multivariate analysis there were many factors associated with Brucellosislike consumption of raw meat, living with animals at the same place, raising of goats, farm cleaning contact, eating of aborted and wild animals. Logistic regression revealed two factors associated with the disease; consumption of raw milk (OR=3.9, P-value 0.001, 95% CI 1.6666 - 9.0700) was a risk factor while drinking boiled milk was protective(OR= 0.09, p- value 0.000, 95% CI, 0.1 - 0.2).Conclusions: The main age-groups affected were 20 – 30 years with males being affected more than females. Drinking of raw milk was significantly associated with Brucellosis while drinking boiled milk was protective. There should be active public health education on the benefits of boiling milk before consumption. Further studies to elucidate the extent and epidemiology of brucellosis in humans and animals in Southern Sudan are recommended
Evaluation of community-based surveillance for Guinea worm, South Sudan, 2006
Background: Guinea worm disease (dracunculiasis) is an ancient parasitic disease and is set to be the next disease eradicated from the world and the first to be overcome without a vaccine or treatment. South Sudan and Ghana account for more than 95% of global dracunculiasis.Methods and Materials: We used the Students field guide for surveillance evaluation to assess surveillance objectives, usefulness of the system, operation procedures, costs, and attributes of the South Sudan community based surveillance system.Results: The guinea worm surveillance system has met its objectives; it is active, simple, flexible, sensitive, stable, and moderately acceptable. The data source is slightly biased; the system costs $2,006,610 U.S. dollars a year to operate.Conclusion: Community-based surveillance for guinea worm is a good example of a surveillance system on which an integrated disease surveillance system can be based in countries with poor surveillance capacity. This makes its potential value to public health practice very high.Keywords: Guinea worm, endemic-villages, community-based-surveillance, village volunteers, Integrated Disease surveillance, South Suda
Lee-Yang theory of the two-dimensional quantum Ising model
Determining the phase diagram of interacting quantum many-body systems is an
important task for a wide range of problems such as the understanding and
design of quantum materials. For classical equilibrium systems, the Lee-Yang
formalism provides a rigorous foundation of phase transitions, and these ideas
have also been extended to the quantum realm. Here, we develop a Lee-Yang
theory of quantum phase transitions that can include thermal fluctuations
caused by a finite temperature, and it thereby provides a link between the
classical Lee-Yang formalism and recent theories of phase transitions at zero
temperature. Our methodology exploits analytic properties of the moment
generating function of the order parameter in systems of finite size, and it
can be implemented in combination with tensor-network calculations.
Specifically, the onset of a symmetry-broken phase is signaled by the zeros of
the moment generating function approaching the origin in the complex plane of a
counting field that couples to the order parameter. Moreover, the zeros can be
obtained by measuring or calculating the high cumulants of the order parameter.
We determine the phase diagram of the two-dimensional quantum Ising model and
thereby demonstrate the potential of our method to predict the critical
behavior of two-dimensional quantum systems at finite temperatures.Comment: 10 pages, 6 figure
Lee-Yang theory of quantum phase transitions with neural network quantum states
Predicting the phase diagram of interacting quantum many-body systems is a
central problem in condensed matter physics and related fields. A variety of
quantum many-body systems, ranging from unconventional superconductors to spin
liquids, exhibit complex competing phases whose theoretical description has
been the focus of intense efforts. Here, we show that neural network quantum
states can be combined with a Lee-Yang theory of quantum phase transitions to
predict the critical points of strongly-correlated spin lattices. Specifically,
we implement our approach for quantum phase transitions in the transverse-field
Ising model on different lattice geometries in one, two, and three dimensions.
We show that the Lee-Yang theory combined with neural network quantum states
yields predictions of the critical field, which are consistent with large-scale
quantum many-body methods. As such, our results provide a starting point for
determining the phase diagram of more complex quantum many-body systems,
including frustrated Heisenberg and Hubbard models.Comment: 10 pages, 6 figures, 1 tabl
Emergence of quasiparticle Bloch states in artificial crystals crafted atom-by-atom
The interaction of electrons with a periodic potential of atoms in
crystalline solids gives rise to band structure. The band structure of existing
materials can be measured by photoemission spectroscopy and accurately
understood in terms of the tight-binding model, however not many experimental
approaches exist that allow to tailor artificial crystal lattices using a
bottom-up approach. The ability to engineer and study atomically crafted
designer materials by scanning tunnelling microscopy and spectroscopy (STM/STS)
helps to understand the emergence of material properties. Here, we use atom
manipulation of individual vacancies in a chlorine monolayer on Cu(100) to
construct one- and two-dimensional structures of various densities and sizes.
Local STS measurements reveal the emergence of quasiparticle bands, evidenced
by standing Bloch waves, with tuneable dispersion. The experimental data are
understood in terms of a tight-binding model combined with an additional
broadening term that allows an estimation of the coupling to the underlying
substrate.Comment: 7 figures, 12 pages, main text and supplementary materia
Behavioural loyalty towards store brands
This paper applies a consumer brand choice model to measure store brand (SB) loyalty. The aim of this paper is to examine whether
SB loyalty is different across categories, and we focus on risk perception as an explanatory variable. The model is estimated using
ACNielsen Spanish household scanner panel data on two laundry detergent categories over a 2 year period for more than 1107
households. Loyalty, price, socio demographics and shopping behaviour variables are included. The discrete choice model formulation is
the logit modelThis research was supported by Ministerio de Educación y Ciencia Dir. Gral. de Investigación, Grant SEJ2004-00672Publicad
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