Searching for anomalous photon and dark-sector e+e- pairs in the MicroBooNE detector
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Esse documento regulamenta o Estatuto e o Regimento Interno da Revista Verde, fundada por iniciativa do Programa Escola Verde e do Grupo de Pesquisa em Educação Ambiental Interdisciplinar, os quais estão vinculados à Universidade Federal do Vale do São Francisco (UNIVASF), Universidade de Pernambuco (UPE), Universidade do Estado da Bahia (UNEB), Faculdade de Petrolina (FACAPE) e Instituto Federal do Sertão Pernambucano (IFSertãoPE). A Revista Verde foi criada em Outubro de 2021, com o objetivo de ser uma publicação científica internacional, editada pelo Programa Escola Verde e o Grupo de Pesquisa em Educação Ambiental Interdisciplinar, para contribuir com a divulgação das novas discussões acadêmicas e científicas, resultadas de atividades de extensão e de pesquisas relacionadas a temas socioambientais e da sustentabilidade ambiental. O foco temático da revista são as problemáticas socioambientais, assim como os grandes debates acadêmicos técnicos e políticos em torno desses temas. As abordagens da revista são plurais, interdisciplinares ou específicas de uma área, desde que sobre dimensões essenciais da sustentabilidade, relativas ao meio ambiente e que estimulem o pensamento interdisciplinar. Nessa perspectiva, a revista pretende contribuir no processo de fortalecimento de um espaço de diálogo acadêmico, político e de intercâmbio de ideias e conhecimentos que permita acompanhar as pesquisas de ponta, colaborando com a sistematização e indexação de conhecimentos que podem ser fundamentais para a elaboração de políticas públicas a favor da sustentabilidade no Brasil e no mundo. A meta é constituir um periódico científico de impacto e excelência acadêmica e relevância social, reconhecida pelos pares, no Brasil e internacionalmente.
Personal micromobility modes such as bicycles, e-bikes and scooters offer low- or zero-emission transportation alternatives to single occupancy vehicles (SOVs). However, the lack of supporting data has led to a dearth of data-driven research on the usage of personally owned e-bikes, including variations due to weather, geography and demographics. In this paper, we present an overview of the longitudinal findings from the CanBikeCO program, focused on e-bike adoption and use rates across different demographics, trip characteristics, and geographies. The CanBikeCO program recorded travel survey data from late July 2021 to December 31, 2022, from low-income Colorado households who were provided with e-bikes for personal use by the Colorado Energy Office (CEO). This data was collected in six different communities across Colorado following the mini-pilot program that was conducted in Fall 2020. To collect data for the survey, the program used the NREL OpenPATH application, which combines passive data collection with semantic information such as trip mode and purpose labels. To the best of our knowledge, there is no prior travel survey data on personally owned e-bikes with this range and scope. This unique dataset yielded several insights. One is that commute trips among participants had nearly 17% higher shares of e-bikes than all trips combined. E-bikes were stated to most often replace cars (34% of e-bike trips) and personal micromobility (22%). Participants favored walking for trips less than 1 mile, e-bikes for trips 1-3 miles, and e-bikes, cars or shared rides for trips 3-20 miles. Seasonality accounted for a 10% decrease and subsequent recovery in e-bike mileage on a per user basis. E-bikes are also appealing across age groups, even among older individuals, and see decreased utilization similar to regular bikes or walking during winter months. We also find that e-bike use may be related to characteristics of land use and urban form, occupation and income as well as household car ownership. We conclude that, for this population, who are mainly part of low-income households, the emissions added by the use of e-bikes (in the case of replacement of non-motorized modes) are outweighed by the strong single occupancy vehicle (SOV) travel replacement. As a whole, our findings suggest a considerable potential for energy savings and emissions reductions from personal e-bike ownership.
Personal micromobility devices like bicycles, e-bikes, and scooters are low- or zero-energy alternatives to single-occupancy vehicles. However, a lack of data has led to a dearth of data-driven research on personally owned e-bike usage. We present longitudinal findings from the CanBikeCO program, focused on e-bike adoption and use across demographics, trip characteristics, and geographies in the state of Colorado. CanBikeCO recorded travel survey data from low-income individuals provided with personal e-bikes by the Colorado Energy Office in six communities across Colorado from July 2021 to December 2022. The data were collected using a custom instance of the National Renewable Energy Laboratory OpenPATH platform, which combines passive data collection with semantic information such as trip mode and purpose labels. To our knowledge, there are no prior travel survey data on personally owned e-bikes with this range and scope. Insights from this unique dataset include: (i) work trips were 17% more likely than average trips to be taken on an e-bike, (ii) e-bikes were most often reported to replace cars (34% of e-bike trips) and other personal micromobility devices (22%), and (iii) participants favored walking for trips less than 1 mile, e-bikes for trips of 1-3 miles, and e-bikes, cars, or shared rides for trips of 3-20 miles. The data used to generate these results have been made available in the Transportation Secure Data Center. We find e-bike use is appealing across age groups and may be related to characteristics of land use, urban form, occupation, income, and car ownership. We conclude for this population that the energy demand added by e-bike use (induced demand and replacing non-motorized modes) is outweighed by the reduction in energy demand from replacement of single-occupancy vehicle trips with e-bike trips. Our findings suggest considerable potential for energy savings from personal e-bike ownership.
We investigate the ability of μ → e facilities, Mu2e and COMET, to probe, or discover, new physics with their detector validation datasets. The validation of the detector response may be performed using a dedicated run with μ + , collecting data below the Michel edge, E e ≲ 52 MeV ; an alternative strategy using π + → e + ν e may also be considered. We focus primarily on a search for a monoenergetic e + produced via two-body decays μ + → e + X or π + → e + X , with X a light new physics particle. Mu2e can potentially explore new parameter space beyond present astrophysical and laboratory constraints for a set of well motivated models including axionlike particles with flavor violating couplings ( μ + → e + a ), massive Z ′ bosons ( μ + → Z ′ e + ), and heavy neutral leptons ( π + → e + N ). The projected sensitivities presented herein can be achieved in a matter of days. Published by the American Physical Society 2024
Measurements of the E × B toroidal angular velocity, $\omega_{E \times B}\,=\,E_\mathrm{r}/RB_\theta$ ($E_\mathrm{r}$ is the radial electric field, B θ is the poloidal magnetic field), are made using the Doppler back-scattering (DBS) and charge-exchange recombination (CER) spectroscopy diagnostics. DBS uses the Doppler shift of wavenumber-resolved density fluctuations while CER uses the Doppler shift of impurity emission lines to independently measure plasma parameters for calculating the local radial electric field. DBS and CER profiles of $\omega_{E \times B}$ as a function of normalized toroidal flux (ρ) are compared at various levels of neutral beam applied torque on the plasma. Under standard neoclassical theory $\omega_{E\times B}$ is a flux surface quantity, making it appropriate to compare across diagnostics. DBS and CER generally show good agreement when comparing $\omega_{E \times B}$ profiles at different levels of neutral beam injection-applied torque. Furthermore, the DBS values have close to the same precision as CER values when averaged over a similar time-scale and effects, such as prompt-torque are considered. DBS is able to observe the rapid ($\lt$10 ms) modification of the $E_\mathrm{r}$ profile by the diagnostic neutral beam 'blips'. This modification is most pronounced when the blip applies a large relative change in torque on the plasma. Overall, these results could have implications on transport analysis and suggests using DBS and CER in conjunction to constrain values of the E × B-shear (sometimes called $\gamma_{E \times B}$).
The gyrokinetic particle simulation is a powerful tool for studies of transport, nonlinear phenomenon, and energetic particle physics in tokamak plasmas. While most gyrokinetic simulations make use of the scalar and vector potentials, a new model (GK-E&B) has been developed by using the E and B field in a general form and has been implemented in simulating kinetic Alfvén waves in uniform plasma. In our work, the Chen et al. GK-E&B model has been expressed, in general, tokamak geometry using the local orthogonal coordinates and general tokamak coordinates. Its reduction for uniform plasma is verified, and the numerical results show good agreement with the original work. The theoretical dispersion relation and numerical results in the local model in screw pinch geometry are also in excellent agreement. Numerical results show excellent performance in a realistic parameter regime of burning plasmas with high values of β/(M e k$^{2}_{⊥}$ρ$^{2}_{i}$), which is a challenge for traditional methods due to the “cancellation” problem. As one application, the GK-E&B model is implemented with kinetic electrons in the local single flux surface limit. With the matched International Tokamak Physics Activity-Toroidicity-induced Alfvén Eigenmodes parameters adopted, numerical results show the capability of the GK-E&B in treating the parallel electron Landau damping for realistic tokamak plasma parameters. As another application, the global GK-E&B model has been implemented with the dominant electron contribution in the cold electron limit. Its capability in simulating the finite E || due to the finite electron mass is demonstrated.
The kinetics of Criegee intermediates are important for atmospheric modeling. However, the quantitative kinetics of Criegee intermediates are still very limited, especially for those with hydroxy groups. Here, we calculate rate constants for the unimolecular reaction of E-glycolaldehyde oxide [E-hydroxyethanal oxide, E-(CH 2 OH)CHOO], for its reactions with H 2 O and (H 2 O) 2 , and for the reaction of the E-(CH 2 OH)CHOO…H 2 O complex with H 2 O. For the highest level of electronic structure, we use W3X-L//CCSD(T)-F12a/cc-pVDZ-F12 for the unimolecular reaction and the reaction with water and W3X-L//DF-CCSD(T)-F12b/jun-cc-pVDZ for the reaction with 2 water molecules. For the dynamics, we use a dual-level strategy that combines conventional transition state theory with the highest level of electronic structure and multistructural canonical variational transition state theory with small-curvature tunneling with a validated density functional for the electronic structure. This dynamical treatment includes high-frequency anharmonicity, torsional anharmonicity, recrossing effects, and tunneling. We find that the unimolecular reaction of E-(CH 2 OH)CHOO depends on both temperature and pressure. The calculated results show that E-(CH 2 OH)CHOO…H 2 O + H 2 O is the dominant entrance channel, while previous investigations only considered Criegee intermediates + (H 2 O) 2 . In addition, we find that the atmospheric lifetime of E-(CH 2 OH)CHOO with respect to 2 water molecules is particularly short with a value of 1.71 × 10 –6 s at 0 km, which is about 2 orders of magnitude shorter than those usually assumed for Criegee intermediate reactions with water dimer. We also find that the OH group in E-(CH 2 OH)CHOO enhances its reactivity.
E-waste from end-of-life electrical and electronic devices is one of the fastest growing waste streams from households and businesses. E-waste recycling yields environmental sustainability and economic benefits. Due to continuous changes in e-waste types and compositions, recycling businesses face challenges to optimize their operational configuration to achieve better economic and environmental performance. To help e-waste recyclers mitigate this problem, we have developed a modular decision support tool called the Comprehensive Manufacturing Assessment Tool (CMAT) that can simulate both e-waste recycling operations and economics. This tool can give valuable insights regarding the profitability of the entire operation and different e-waste types. In addition, a new bio-inspired metaheuristic optimization algorithm, hen-and-chicks optimization (HACO), was developed to assign manpower to different workstations to maximize operational efficiencies. According to the results of our case study, laptops, desktops, and computer peripherals are the three electronic waste products that produce the most profit. Our examination of the sensitivity of material prices shows that the price of steel has the most significant influence on total profit, because it is the most widely used material in the majority of electronic devices. We have released the decision support tool as open-source software under a general public license. It could be customized for other recycling industries beyond e-waste to achieve business sustainability by making their operations more efficient.
Electronic waste, or e-waste, encompasses end-of-life electrical and electronic equipment, including computers, monitors, televisions, printers, cell phones, household appliances with electronic components, and small consumer devices containing batteries or circuitry. E-waste is one of the fastest-growing components of the U.S. waste stream, with nearly 8 million tons generated in 2022. E-waste presents two related public-interest considerations. First, e-waste contains economically and strategically important materials: base metals (copper, aluminum, iron, steel), precious metals (gold, silver, platinum group metals), and critical materials such as rare earth elements, gallium, and indium that appear on the U.S. Geological Survey's (USGS) 2025 List of Critical Minerals. Second, many electronic devices contain hazardous constituents - including lead, mercury, cadmium, and brominated flame retardants - as well as rechargeable batteries that can pose fire risks during handling. Effective management of these constituents helps protect workers, communities, and the environment. In the United States, it is estimated that less than 20% of e-waste is formally collected and recycled, leaving over 6 million tons landfilled or otherwise unrecovered. This fact sheet provides state and local decision-makers an overview of (1) e-waste composition and recoverable materials, (2) technology pathways used to recover those materials, and (3) examples of operational and partnership structures used to provide e-waste recycling capacity in the United States. It is intended to complement existing collection-program guidance available through U.S. Environmental Protection Agency (EPA) and other sources.
Diorganyl dichalcogenides (R–E–E–R; R = organyl, E = S, Se, Te) are widely employed for the polymorphic control of diamond-like crystal structures owing to their tunable C–E bond reactivity. In this work, we extend their application to non-close-packed alkali metal-based chalcogenides by demonstrating the selective synthesis of CsGaE 2 (E = S, Se) polymorphs. Weaker C–E bonds or higher temperatures promote the formation of the thermodynamically stable mC64 phases, while stronger C–E bonds or lower temperatures allow for the isolation of the metastable mC16 phases. Furthermore, heat-treatment studies reveal the pronounced metastability of CsGaSe 2 -mC16 particles and the irreversible phase transition of CsGaS 2 analogous to its bulk counterpart.
Abstract This study aimed at developing a predictive model that captures the influences of a variety of agricultural and environmental variables and is able to predict the concentrations of enteric bacteria in soil amended with untreated Biological Soil Amendments of Animal Origin (BSAAO) under dynamic conditions. We developed and validated a Random Forest model using data from a longitudinal field study conducted in mid‐Atlantic United States investigating the survival of Escherichia coli O157:H7 and generic E. coli in soils amended with untreated dairy manure, horse manure, or poultry litter. Amendment type, days of rain since the previous sampling day, and soil moisture content were identified as the most influential agricultural and environmental variables impacting concentrations of viable E. coli O157:H7 and generic E. coli recovered from amended soils. Our model results also indicated that E. coli O157:H7 and generic E. coli declined at similar rates in amended soils under dynamic field conditions.The Random Forest model accurately predicted changes in viable E. coli concentrations over time under different agricultural and environmental conditions. Our model also accurately characterized the variability of E. coli concentration in amended soil over time by providing upper and lower prediction bound estimates. Cross‐validation results indicated that our model can be potentially generalized to other geographic regions and incorporated into a risk assessment for evaluating the risks associated with application of untreated BSAAO. Our model can be validated for other regions and predictive performance also can be enhanced when data sets from additional geographic regions become available.
The United States Department of Energy’s (DOE’s) Office of Fossil Energy and the National Energy Technology Laboratory (NETL) developed a suite of screening-level, techno-economic models/tools, known as the CO2_E_EvSystem, to evaluate technical aspects and costs of using carbon dioxide (CO2) enhanced oil recovery (EOR) to store CO2 and produce oil. CO2_E_EvSystem has three software components and several input and output files. The software components are CO2_E_EvTool, CO2_Prophet, and CO2_E_COM. Almost all computational work is performed by CO2_Prophet and CO2_E_COM, which are both Fortran programs. The primary role of CO2_E_EvTool is to manage input and output files for the two programs, run the two programs, allow multiple oilfields to be evaluated in a single run, and generate files that summarize the results for all the oilfields run. This version of the CO2_E_EvSystem includes a residual oil zone dataset from the San Andres formation, Permian Basin, to demonstrate the system and guide users on attributes needed for dataset inputs.
Hydraulic property estimates for the soils, cementitious materials, and waste zones associated with the E-Area low-level radioactive waste disposal units have been provided to support the Performance Assessments (PA) for the E-Area Low-Level Waste Facility (LLWF). Nominal or “best estimate” hydraulic property values for use in the deterministic modeling are provided along with representations of the hydraulic property value uncertainty for use in sensitivity and uncertainty modeling. The hydraulic properties provided for each of the E-Area materials include: porosity ( η ), dry bulk density ( ρ b ), particle density (ρ p ), saturated hydraulic conductivity ( K sat ), characteristic curves (suction head, saturation, and relative permeability), and effective diffusion coefficient ( D e ). A representation of the uncertainty associated with each property, except for the characteristic curves, is provided for each material, except for the E-Area waste zones. These nominal parameter values for each of the E-Area soils, cementitious materials, and waste zones, and, where indicated, parameter uncertainty representations, are based upon the following in order of priority: Site-specific field data, Site-specific laboratory data, Similarity to material with site-specific field or laboratory data, and Literature data. Additionally, a methodology to represent long-term concrete degradation is provided. Finally, because much of the nominal hydraulic property values and uncertainty representations for the E-Area soils, cementitious materials, and waste zones are based on similarity to other materials or literature data, a methodology to prioritize additional work to better define these values and representations is outlined. Prioritization should be based on the importance of the material and/or property to the results of deterministic, sensitivity, and uncertainty modeling. This prioritization should be established through a process of sensitivity modeling. This report supersedes the previous hydraulic properties data package. Revision 1 contains clarifications, updates and corrections to text, figures and tables in a number of places in the report along with some minor editing.
The integration of shared e-scooters with public transit is a promising solution for urban mobility's first/last-mile challenge. This study explores spatiotemporal factors influencing this integration, using 35-day e-scooter trip data from Chicago. Employing a random-effect negative binomial approach, we modeled the frequency of e-scooter trips to access/egress to/from bus stops and train stations. Results indicate that weather conditions, design features like intersection density, and multimodal network density significantly influence usage. The transit system characteristics such as service frequency have a positive effect on the integration of e-scooters and trains while a similar effect for bus and e-scooter integration was not significant. Furthermore, safety-related variables such as accident and crime rates as well as demographic characteristics were also revealed to be significant factors in our study. These findings offer vital insights to urban planners and policymakers for infrastructure, safety enhancements, and interventions to encourage efficient e-scooter-public transit integration.