A Study of the (3-He,t) Charge-Exchange Reaction at E(3-He) = 200 MeV

This research was sponsored by the National Science Foundation Grant NSF PHY 87-1440

Near-threshold K+K^{+} Production in Heavy-ion Collisions

Within a hadronic transport model we study in detail contributions to kaon yields and momentum spectra from various baryon (resonance)-baryon (resonance) and $\pi N$ interactions in heavy-ion collisions at beam energies near the free-space kaon production threshold. It is found that the finite lifetime of baryon resonances affects significantly the shape of kaon spectra, and the high energy parts of the kaon spectra are dominated by kaons from $\pi N\rightarrow \Lambda K^{+}$ processes. $N^{*}(1440)$ resonances are found to contribute about 10\% to the kaon yield. Effects of boosting the Fermi momentum distributions of the two colliding nuclei into their center of mass frame, centrality of the reaction as well as the nuclear equation of state on kaon yields and spectra are also discussed. Model calculations on $K^{+}$, $\pi^{+}$ and $\pi^{-}$ spectra for the reaction of Au+Au at $E_{beam}/A= 1.0$ GeV are compared with the experimental data from the KaoS collaboration.Comment: 18 pages, 11 figures available upon request. TAMU preprint #940403

Neutron Decay from Giant Resonances and the Isobaric Analog State in 120-Sb Populated in 120-Sn(3-He,t)120-Sb(n)119-Sb Charge Exchange

This research was sponsored by the National Science Foundation Grant NSF PHY-931478

Modified iterative versus Laplacian Landau gauge in compact U(1) theory

Compact U(1) theory in 4 dimensions is used to compare the modified iterative and the Laplacian fixing to lattice Landau gauge in a controlled setting, since in the Coulomb phase the lattice theory must reproduce the perturbative prediction. It turns out that on either side of the phase transition clear differences show up and in the Coulomb phase the ability to remove double Dirac sheets proves vital on a small lattice.Comment: 14 pages, 8 figures containing 23 graphs, v2: 2 figures removed, 2 references adde

Making things happen : a model of proactive motivation

Being proactive is about making things happen, anticipating and preventing problems, and seizing opportunities. It involves self-initiated efforts to bring about change in the work environment and/or oneself to achieve a different future. The authors develop existing perspectives on this topic by identifying proactivity as a goal-driven process involving both the setting of a proactive goal (proactive goal generation) and striving to achieve that proactive goal (proactive goal striving). The authors identify a range of proactive goals that individuals can pursue in organizations. These vary on two dimensions: the future they aim to bring about (achieving a better personal fit within one’s work environment, improving the organization’s internal functioning, or enhancing the organization’s strategic fit with its environment) and whether the self or situation is being changed. The authors then identify “can do,” “reason to,” and “energized to” motivational states that prompt proactive goal generation and sustain goal striving. Can do motivation arises from perceptions of self-efficacy, control, and (low) cost. Reason to motivation relates to why someone is proactive, including reasons flowing from intrinsic, integrated, and identified motivation. Energized to motivation refers to activated positive affective states that prompt proactive goal processes. The authors suggest more distal antecedents, including individual differences (e.g., personality, values, knowledge and ability) as well as contextual variations in leadership, work design, and interpersonal climate, that influence the proactive motivational states and thereby boost or inhibit proactive goal processes. Finally, the authors summarize priorities for future researc

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Highly-parallelized simulation of a pixelated LArTPC on a GPU

The rapid development of general-purpose computing on graphics processing units (GPGPU) is allowing the implementation of highly-parallelized Monte Carlo simulation chains for particle physics experiments. This technique is particularly suitable for the simulation of a pixelated charge readout for time projection chambers, given the large number of channels that this technology employs. Here we present the first implementation of a full microphysical simulator of a liquid argon time projection chamber (LArTPC) equipped with light readout and pixelated charge readout, developed for the DUNE Near Detector. The software is implemented with an end-to-end set of GPU-optimized algorithms. The algorithms have been written in Python and translated into CUDA kernels using Numba, a just-in-time compiler for a subset of Python and NumPy instructions. The GPU implementation achieves a speed up of four orders of magnitude compared with the equivalent CPU version. The simulation of the current induced on 10^3 pixels takes around 1 ms on the GPU, compared with approximately 10 s on the CPU. The results of the simulation are compared against data from a pixel-readout LArTPC prototype

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities 1,2 . This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity 3�6 . Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55 of the global rise in mean BMI from 1985 to 2017�and more than 80 in some low- and middle-income regions�was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing�and in some countries reversal�of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories. © 2019, The Author(s)