University of California, Merced
  • Merced, California, United States
Recent publications
Background Identification of widespread biases present in reported research findings in many scientific disciplines, including psychology, such as failures to replicate and the likely extensive application of questionable research practices, has raised serious concerns over the reliability and trustworthiness of scientific research. This has led to the development of, and advocacy for, ‘open science’ practices, including data, materials, analysis, and output sharing, pre-registration of study predictions and analysis plans, and increased access to published research findings. Implementation of such practices has been enthusiastic in some quarters, but literacy in, and adoption of, these practices has lagged behind among many researchers in the scientific community. Advances In the current article I propose that researchers adopt an open science ‘mindset’, a comprehensive approach to open science predicated on researchers’ operating under the basic assumption that, wherever possible, open science practices will be a central component of all steps of their research projects. The primary, defining feature of the mindset is a commitment to open science principles in all research projects from inception to dissemination. Other features of the mindset include the assumption that all components of research projects (e.g. pre-registered hypotheses, protocols, materials, analysis plans, data, and output) will be accessible broadly; pro-active selection of open fora to disseminate research components and findings; open and transparent dissemination of reports of the research findings in advance of, and after, formal publication; and active promotion of open science practices through education, modeling, and advocacy. Conclusion The open science mindset is a ‘farm to fork’ approach to open science aimed at promoting comprehensive quality in application of open science, and widening participation in open science practices so that they become the norm in research in health psychology and behavioral medicine going forward.
Pyrogenic organic carbon (PyC) is found in soils as a heterogeneous mixture of thermally altered plant residues that range in their susceptibility to losses via mineralization, leaching, and erosion. Leaching of PyC as DOC (DPyC) within the soil profile is likely influenced by the chemical composition of solid PyC and the dominant soil processes and properties at a particular depth. Here we report the results of a 2-year laboratory decomposition and leaching study designed to investigate the interactive effects of pyrolysis temperature levels (no pyrolysis, 300 °C, and 450 °C) and soil depth (surface soil, 0–10 cm depth; subsurface soil, 50–70 cm depth) on losses of ¹³C-labeled jack pine (Pinus banksiana) wood, wood pyrolyzed at 300 °C (PyC300) and wood pyrolyzed at 450 °C (PyC450) as dissolved organic carbon (DOC). Losses of wood and PyC in the ¹³C- DOC pool were measured in leachates drained from soils once a month over the course of 1 year, and at one single leaching event after 2 years. We found that pyrolysis temperature levels interacted with time and soil depth to affect losses of wood and PyC as DOC throughout the 1-year incubation and leaching study, with greater DOC losses from wood in surface soil (0.73 ± 0.076% of added C) than in subsurface soil (0.40 ± 0.063% of added C) averaged across sampling time. Monthly DOC losses from PyC were not affected by soil depth. Cumulative data indicated a small contribution of wood (2.86 ± 0.07%), PyC300 (0.40 ± 0.04%), and PyC450 (0.16 ± 0.01%) to total DOC leached from soils. DOC losses from wood and PyC300 (as a proportion of added C) were greater in surface soil than in subsurface soil, whereas DOC losses from PyC450 were unaffected by differences between surface and subsurface soil. Losses of DOC were greater from PyC300 than from PyC450 in surface soil, with no significant differences in DOC losses between PyC300 and PyC450 in subsurface soil. One single leaching event at the end of the 2-year decomposition study resulted in higher DOC losses from wood in subsurface soil than in surface soil likely due to desorption, and no differences in DOC losses between PyC300 and PyC450 regardless of soil depth. Our results suggest strong interactions between the initial physicochemical composition of organic C inputs and soil properties (soil depth as a proxy) that control the mobility and transport of PyC and should be better represented in Earth system models.
Active disturbance rejection control (ADRC) is getting explosive attention with many advantages. This paper proposes a synthesis method for the first-order ADRC based on the existing PI controller. Firstly, the relationship between the first-order ADRC and PI controller is derived. Then the initial parameters of ADRC can be obtained directly from the existing PI parameters and the synthesis procedure is summarized. Moreover, the parameter constraints to obtain better control performance are acquired based on theoretical analyses and ADRC parameters can be optimized based on these parameter constraints. The effectiveness of the proposed ADRC synthesis method and the parameter optimization method is validated by simulations and comparative experiments. Finally, the proposed methods are applied to the secondary air system of a power plant and running data indicate that ADRC can improve the control performance evidently.
Along with the increase in the frequency of disastrous wildfires and bushfires around the world during the recent decades, scholarly research efforts have also intensified in this domain. This work investigates divisions and trends of the domain of wildfire/bushfire research. Results show that this research domain has been growing exponentially. It is estimated that the field, as of 2021, it has grown to larger than 13,000 research items, with an excess of 1,200 new articles appearing every year. It also exhibits distinct characteristics of a multidisciplinary research domain. Analyses of the underlying studies reveal that the field is made up of five major divisions. These divisions embody research activities around (i) forest ecology and climate, (ii) fire detection and mapping technologies, (iii) community risk mitigation and planning, (iv) soil and water ecology, and (v) atmospheric science. Research into the sub-topics of reciprocal effects between climate change and fire activities, fire risk modelling/mapping (including burned area modelling), wildfire impact on organic matter, biomass burning, and human health impacts currently constitute trending areas of this field. Amongst these, the climate cluster showed an explosion of activities in 2020 while the human health cluster is identified as the most recent emerging topic of this domain. On the other hand, dimensions of wildfire research related to human behaviour—particularly issues of emergency training, risk perception and wildfire hazard education—seem to be notably underdeveloped in this field, making this one of its most apparent knowledge gaps. A scoping review of all reviews and meta-analysis of this field demonstrates that this sub-topic is also virtually non-existent on the research synthesis front. This meta-synthesis further reveals how a western, deductive view excludes socioecological and traditional knowledge of fire.
Thermal energy storage (TES) for a cooling plant is a crucial resource for load flexibility. Traditionally, simple, heuristic control approaches, such as the storage priority control which charges TES during the nighttime and discharges during the daytime, have been widely used in practice, and shown reasonable performance in the past benefiting both the grid and the end-users such as buildings and district energy systems. However, the increasing penetration of renewables changes the situation, exposing the grid to a growing duck curve, which encourages the consumption of more energy in the daytime, and volatile renewable generation which requires dynamic planning. The growing pressure of diminishing greenhouse gas emissions also increases the complexity of cooling TES plant operations as different control strategies may apply to optimize operations for energy cost or carbon emissions. This paper presents a model predictive control (MPC), site demonstration and evaluation results of optimal operation of a chiller plant, TES and behind-meter photovoltaics for a campus-level district cooling system. The MPC was formulated as a mixed-integer linear program for better numerical and control properties. Compared with baseline rule-based controls, the MPC results show reductions of the excess PV power by around 25%, of the greenhouse gas emission by 10%, and of peak electricity demand by 10%.
The high energy requirement of hydrogen generation via water splitting has motivated the development of acid-alkaline electrolyzers, which have a lower thermodynamic voltage requirement than conventional electrolyzers. Proton exchange membrane acid-alkaline electrolyzers have been reported in literature, but its reactions and ion transport mechanisms are still unknown. In this work, we developed a multiphysics model of a proton exchange membrane acid-alkaline electrolyzer to elucidate the mechanism of operation. The model showed that Na⁺ crossover from the anolyte to the catholyte is the primary mechanism for retaining electroneutrality, in contrast with the prevailing hypothesis that H⁺ is the primary charge carrier. Moreover, we found that H⁺ is transported from the catholyte to the anolyte, which is counterproductive towards maintaining electroneutrality and results in the undesired acid-base neutralization reaction. Increasing the applied current reduces H⁺ crossover, thereby demonstrating a tradeoff between power consumption and side reaction minimization. As the cell is operated, the catholyte composition changes from H2SO4 to a mixture of NaHSO4 and Na2SO4, which in turn reduces the overall efficiency. Therefore, in addition to water, proton exchange membrane acid-alkaline electrolyzers will require constant feeding of fresh electrolyte to maintain its performance, and this poses a barrier towards its practical use.
Image deblurring is a classic problem in low-level computer vision with the aim to recover a sharp image from a blurred input image. Advances in deep learning have led to significant progress in solving this problem, and a large number of deblurring networks have been proposed. This paper presents a comprehensive and timely survey of recently published deep-learning based image deblurring approaches, aiming to serve the community as a useful literature review. We start by discussing common causes of image blur, introduce benchmark datasets and performance metrics, and summarize different problem formulations. Next, we present a taxonomy of methods using convolutional neural networks (CNN) based on architecture, loss function, and application, offering a detailed review and comparison. In addition, we discuss some domain-specific deblurring applications including face images, text, and stereo image pairs. We conclude by discussing key challenges and future research directions.
Space is a limited resource in which many animals need to perform basic functions such as feeding and reproducing. Competition over access to space can induce a variety of behaviours that may result in differential access to crucial resources related to survival and fitness. The Aegean wall lizard, Podarcis erhardii, is a colour-polymorphic lizard that inhabits dry stone walls where they access food, safely thermoregulate, shelter from predators and interact with other lizards. Many colour-polymorphic species have morphs with distinct behavioural strategies, which may play a role in morph evolution and maintenance. Here, we conducted the first behavioural experiments on P. erhardii colour morphs. Our goal was to compare morph competitive ability and characterize morph differences in social behaviours using laboratory contest experiments over limited heated space on a stone wall in a neutral arena. Contest experiments revealed that colour morph, not size, predicted intermorph contest outcomes. White and yellow morphs were associated with winning and the orange morph was associated with losing contests. Male colour morphs exhibited different levels of aggressive, boldness, chemical signalling and visual signalling behaviours depending on which morph they were in contest with. White morphs always performed aggressive and scent-marking behaviours more frequently during contests with other morphs. Yellow morphs performed aggressive, bold, chemical signalling and visual signalling behaviours at intermediate frequencies relative to other morphs. Orange morphs performed aggressive behaviours equally often when in contest with yellow morphs but performed all other behaviours less frequently against yellow and white morphs. Considering these results, behavioural variation among P. erhardii colour morphs may promote morph maintenance.
High-intensity wildfires alter the chemical composition of organic matter, which is expected to be distinctly different from low-intensity prescribed fires. Herein, we used pyrolysis gas chromatography/mass spectrometry (Py-GC/ MS), in conjunction with solid-state 13 C nuclear magnetic resonance (NMR) and Fourier transform infrared (FT-IR) spectroscopy, to assess chemical alterations from three wildfires and a long-term frequent prescribed fire site. Our results showed that black ash formed under moderate intensity burns contained less aromatic (ArH), polyaromatic hydrocarbon (PAH), and nitrogen-containing compounds (Ntg) but more lignin (LgC) and phenol compounds (PhC), compared to white ash formed under high intensity burns. Both 13 C NMR and FT-IR confirmed a higher relative percentage of carboxyl carbon in white ash, indicating the potential for higher water solubility and more mobile carbon, relative to black ash. Compared to wildfires, ash from low-intensity prescribed fire contained less ArH, PAH, and Ntg and more LgC and PhC. Controlled laboratory burning trials indicated that organic matter alteration was sensitive to the burn temperature, but not related to the fuel type (pine vs fir) nor oxygen absence/presence at high burn temperatures. This study concludes that higher burn temperatures resulted in higher (poly)aromatic carbon/nitrogen and lower lignin/phenol compounds.
The California ribbed mussel, Mytilus californianus, is an ecosystem engineer crucial for the survival of many marine species inhabiting the intertidal zone of California. Here, we describe the first reference genome for M. californianus and compare it to previously published genomes from three other Mytilus species: M. edulis, M. coruscus, and M. galloprovincialis. The M. californianus reference genome is 1.65 Gb in length, with N50 sequence length of 118Mb, and an estimated 86.0% complete single copy genes. Compared to the other three Mytilus species, the M. californianus genome assembly is the longest, has the highest N50 value, and the highest percentage complete single copy genes. This high-quality genome assembly provides a foundation for population genetic analyses that will give insight into future conservation work along the coast of California.
The asymmetric Hubbard dimer is a model that allows for explicit expressions of the Hartree–Fock (HF) and Kohn–Sham (KS) states as analytical functions of the external potential, Δ v, and of the interaction strength, U. We use this unique circumstance to establish a rigorous comparison between the individual contributions to the correlation energies stemming from the two theories in the { U, Δ v} parameter space. Within this analysis of the Hubbard dimer, we observe a change in the sign of the HF kinetic correlation energy, compare the indirect repulsion energies, and derive an expression for the “traditional” correlation energy, i.e., the one that corrects the HF estimate, in a pure site-occupation function theory spirit [Eq. (45) ]. Next, we test the performances of the Liu–Burke and the Seidl–Perdew–Levy functionals, which model the correlation energy based on its weak- and strong-interaction limit expansions and can be used for both the traditional and the KS correlation energies. Our results show that, in the Hubbard dimer setting, they typically work better for the HF reference, despite having been originally devised for KS. These conclusions are somewhat in line with prior assessments of these functionals on various chemical datasets. However, the Hubbard dimer model allows us to show the extent of the error that may occur in using the strong-interaction ingredient for the KS reference in place of the one for the HF reference, as has been carried out in most of the prior assessments.
Incidence rates of type 1 diabetes are increasing faster in Latinx youth than other ethnic groups, yet this population remains understudied. The current study (1) tested differences in division of diabetes-related responsibility (adolescent alone, mother alone, and shared) across Latinx and non-Latinx White families (N = 118 mother-adolescent dyads, 56 = Latinx dyads, Mage=13.24 years), and (2) examined associations between diabetes responsibility and adolescent health (HbA1c, diabetes self-management behaviors, and depressive symptoms). Latina mothers reported more shared and less adolescent responsibility than non-Latinx White mothers, but there were no ethnic differences in adolescent reports of responsibility. Independent of demographic and illness-related characteristics, mother- and adolescent-reports of shared responsibility were associated with higher self-management behaviors, while individual responsibility (adolescent or mother alone) was generally associated with lower self-management behaviors. Shared responsibility associations with higher mother-reported self-management behaviors occurred among Latinx families, but not non-Latinx White families. Shared and individual responsibility were not associated with HbA1c or depressive symptoms. The findings suggest the importance of shared responsibility for diabetes management in adolescence, particularly in Latinx families.
The AuTi gaseous molecule was for the first time identified in vapors produced at high temperature from a gold-titanium alloy. The homogeneous equilibria AuTi(g) = Au(g) + Ti(g) (direct dissociation) and AuTi(g) + Au(g) = Au 2 (g) + Ti(g) (isomolecular exchange) were studied by Knudsen Effusion Mass Spectrometry (KEMS) in the temperature range 2111 -2229 K. The so determined equilibrium constants were treated by the "third-law method" of thermodynamic analysis, integrated with theoretical calculations, and the dissociation energy at 0 K was derived as (AuTi) = 241.0 {plus minus} 5.2 kJ/mol. A similar investigation was carried out for the AuSc and AuFe species, whose dissociation energies were previously reported with large uncertainties. The direct dissociation and the isomolecular exchange with the Au 2 dimer were studied in the 1969-2274 and 1842-2092 K ranges for AuSc and AuFe, respectively, and the dissociation energies derived as (AuSc) = 240.4 {plus minus} 6.0 and (AuFe) = 186.2 {plus minus} 4.2 kJ/mol. The experimental bond energies are compared with those calculated here by CCSD(T) with the correlation-consistent basis sets cc-pVXZ(-PP) and cc-pwCVXZ(-PP) (with X = T,Q,5), also in the limit of complete basis set, and with those from CASSCF-MRCI calculations, recently available in the literature. The stronger bond of AuTi compared to AuFe parallels the trend observed in monochlorides. This analogy is shown to be more generally observed in the AuM and MCl diatomic series (with M = first-row transition metal), in accordance with a picture of "pseudo-halogen" bonding behaviour of gold.
Intermediate labour markets (ILMs) provide fixed-term work opportunities and coaching for people in disadvantaged positions in labour markets. We study 46 sequences from six audio-recorded recruitment interviews for an ILM job targeted at people who have been unemployed for a prolonged period. Using an ethnomethodological approach to identity, membership categorization analysis and conversation analysis, we study how interviewers and candidates construct and negotiate who is fit for the ILM job. We present interactional moves through which the participants jointly construct the 'fit for the ILM job' category and treat the candidate's membership in it as a positive matter. Further, we demonstrate how the candidates are put in an interactionally difficult position in the interview as there are contradictory and ambiguous expectations about the ideal candidate. We discuss the results in relation to the interactional and institutional logics of a recruitment interview and suggest that enhancing the transparency might reinforce ethics of recruitment in ILMs.
We examined support for type 1 diabetes in casual versus committed romantic relationships and links to blood glucose, self-care, and affect in 101 young adults (Mage 18.8). Individuals provided survey and daily measures of support and blood glucose and affect during a 14-day diary period. Survey data indicated individuals viewed partners as helpful, with partners in committed relationships rated more helpful than those in casual relationships. Daily assessments indicated partners were seen as only moderately helpful. Individuals in committed relationships discussed diabetes with partners on more diary days than those in casual relationships. When individuals in any relationship type experienced more helpful partner support than their average, they reported higher positive and lower negative affect. However, those in casual relationships also experienced more negative affect and higher mean blood glucose the next day. Results suggest tradeoffs between immediate benefits and subsequent costs of partner support to adults in casual relationships.
Exponential integrators are a well-known class of time integration methods that have been the subject of many studies and developments in the past two decades. Surprisingly, there have been limited efforts to analyze their stability and efficiency on non-diffusive equations to date. In this paper we apply linear stability analysis to showcase the poor stability properties of exponential integrators on non-diffusive problems. We then propose a simple repartitioning approach that stabilizes the integrators and enables the efficient solution of stiff, non-diffusive equations. To validate the effectiveness of our approach, we perform several numerical experiments that compare partitioned exponential integrators to unmodified ones. We also compare repartitioning to the well-known approach of adding hyperviscosity to the equation right-hand-side. Overall, we find that the repartitioning restores convergence at large timesteps and, unlike hyperviscosity, it does not require the use of high-order spatial derivatives.
The stability and reliability of the power grid are facing great challenges caused by the intermittency and randomness of renewable energy, for example, the frequency variations induced by the load variance. To handle these challenges, the load frequency regulation is becoming a powerful feasible alternative. This paper focuses on the load frequency regulation for multi-area power systems with renewable sources via a cascaded active disturbance rejection control (ADRC) approach. By introducing a multi-area power system with renewable sources, a cascaded ADRC structure is structured for a multi-area power system, which contains a photovoltaic system, a thermal system and a wind system. Based on the ADRC principle and the parameter stability region, a practical and effective design procedure for the proposed cascaded ADRC is provided. Simulations illustrate that the proposed cascaded ADRC can ensure the stronger ability to reject the consumed power compared with other comparative control strategies under different scenarios. Besides, it needs the shortest time to return to the stable state with the smallest overshoot under all operating conditions when the load variance occurs. The successful application of the multi-area power system indicates a promising potential of the proposed cascaded ADRC in the power industry.
Institution pages aggregate content on ResearchGate related to an institution. The members listed on this page have self-identified as being affiliated with this institution. Publications listed on this page were identified by our algorithms as relating to this institution. This page was not created or approved by the institution. If you represent an institution and have questions about these pages or wish to report inaccurate content, you can contact us here.
2,503 members
Mourad Sadqi
  • Department of Bioengineering
Juan C Meza
  • Department of Applied Mathematics
Jitske Tiemensma
  • Psychological Science
Ricardo Castro
  • Department of Mechanical Engineering
Juan Camilo Sánchez-Arcila
  • School of Natural Sciences
Information
Address
5200 North Lake Road Merced, CA 95343, Merced, California, United States
Head of institution
Dorothy Leland, Chancellor
Website
www.ucmerced.edu
Phone
(209) 228-4400