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This paper examines the role of the landscape of the American West, both literal and literary, in relocating a mythical Chinese American past in two recent novels, How Much of These Hills is Gold by C Pam Zhang and The Thousand Crimes of Ming Tsu by Tom Lin. Though the two novels differ from each other radically in many ways, their uses and subversions of the conventions and expectations of the Western genre create an expansive literary space of discovery and invention. In rejecting colonial narratives of places and their histories, these historical fictions forge new pathways for Asian American identity formation and posit a theory of embodied geographical belonging that resists the dehumanization of normative modes of identity definition. Through a comparative analysis of Zhang’s and Lin’s works within the frameworks of Asian American and Western genre literary criticism, this project uncovers the interdependency of language, history, and identity, and their embodiment within the unnarratable relation between landscape and its inhabitants.

Hot QCD physics studies the nuclear strong force under extreme temperature and densities. Experimentally these conditions are achieved via high-energy collisions of heavy ions at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). In the past decade, a unique and substantial suite of data was collected at RHIC and the LHC, probing hydrodynamics at the nucleon scale, the temperature dependence of the transport properties of quark-gluon plasma, the phase diagram of nuclear matter, the interaction of quarks and gluons at different scales and much more. This document, as part of the 2023 nuclear science long range planning process, was written to review the progress in hot QCD since the 2015 Long Range Plan for Nuclear Science, as well as highlight the realization of previous recommendations, and present opportunities for the next decade, building on the accomplishments and investments made in theoretical developments and the construction of new detectors. Furthermore, this document provides additional context to support the recommendations voted on at the Joint Hot and Cold QCD Town Hall Meeting, which are reported in a separate document.

Soil structure is a key attribute of soil quality and health that significantly impacts water infiltration. Structure can be significantly altered by natural or anthropogenic drivers including soil management practices and can in turn impact soil infiltration. Those changes in soil structure are often complex to quantify and can lead to conflicting impacts on water infiltration into soils. Here, we present a narrative systematic review (SR) of the impacts of soil structure on water infiltration. Based on inclusion and exclusion criteria, as well as defined methods for literature search and data extraction, our systematic review led to a total of 153 papers divided into two sets: experimental (131) and theoretical (22) papers. That implied a significant number of in-situ and field experiments that were conducted to assess the impacts of soil structure on water infiltration under the influence of different land uses and soil practices. Analysis of the metadata extracted from the collected papers revealed significant impacts of soil structure on water infiltration. Those effects were further attributed to land use and management, where we demonstrate the impact of three unique categories: soil amendments, crop management and tillage. Furthermore, significant correlations were established between infiltration rate and soil structural properties, with R2 values ranging from 0.51 to 0.80 and for saturated hydraulic conductivity and soil structural properties, with R2 values ranging from 0.21 to 0.78. Finally, our review highlighted the significant absence of and the need for theoretical frameworks studying the impacts of soil structure on water infiltration.

This research paper investigates the role of technology in the caregiving experiences of Blind or Low Vision (BLV) parents for their child(ren). Initially, the study aimed to explore the assumed use of assistive technologies (ATs) through analysis of YouTube videos, expecting to find a significant reliance on these technologies in BLV parenting. However, the findings reveal a nuanced perspective. Technology is found to play a supplementary rather than central role in BLV parenting. BLV parents exhibit active adaptation and innovation in their caregiving approaches, focusing on developing personalized systems and solutions. Predominantly mainstream technology is creatively repurposed to cater to their specific needs, a practice akin to life hacking. The research emphasizes that BLV parents prioritize their child(ren)'s health, safety, and well-being, fostering a nourishing environment through their resourceful caregiving strategies.

This dissertation comprises three papers examining how the environment or context in which a decision is made affects choices.Chapter 1 investigates how the presence of seemingly irrelevant alternatives in an assortment can systematically affect people’s choices. We analyze a large dataset of real-world purchase decisions in an online marketplace and find evidence for the asymmetric dominance effect, whereby the inclusion of an option that is inferior to another one in the assortment leads to a preference shift towards the superior option. This work sheds light on where, when, and why this effect occurs. We identify a novel moderator of the effect – the ability to sample or experience the options available – and find evidence consistent with a perceptual mechanism underlying the effect. Chapter 2 explores how people make allocations between themselves and others in highly polarized environments (e.g., abortion, gun control, political parties) using a novel paradigm. In two large nationally representative samples, we asked participants to make lose-lose decisions: either subtract funds from their side of an issue or add funds to the opposing side. Strikingly, individuals were so averse to supporting opposing groups that they preferred to enact equivalent or greater financial harm to their own group instead – a preference that cannot be explained by existing theories. Instead, this work highlights the important role that identity plays in decision-making in polarized environments, underscoring the psychological barriers that impede the advancement of important causes. Finally, chapter 3 reveals how financial generosity is affected by crises, specifically the COVID-19 pandemic. While psychological theories have supported the possibility that both increased selfishness and increased generosity may emerge in these situations, we find convergent evidence from both a dataset capturing real-world donations and a 6-month longitudinal study that individuals exhibited greater

This paper uses data from limited HL-2A Ohmic-plasma to answer the question of how turbulent transport broadens the heat flux width. A key issue in this study is the determination of the origin of SOL turbulence. We develop the concept of the energy production ratio R_a, which compares the flux of turbulence energy across the LCFS to the net, integrated energy production in the SOL. The flux of turbulence energy (i.e., spreading) is measured directly, using Langmuir probes. Experimental data is used to evaluate R_a. Results show that usually R_a>1, indicating that SOL turbulence is energized primarily by edge turbulence spreading. The exceptions – cases where R_a<1 – are those with relatively stronger E×B shear near the LCFS. The latter inhibits both turbulence spreading and local SOL production, but has greater effects on spreading. High blob fraction in the turbulence correlates with large values of R_a. The implications for heat flux width physics are discussed.

The purpose of our research study was to determine the social and ethical aspects of genetic engineering. What originally began as a way to decrease an embryo's risk of genetic diseases has now become a way to alter its appearance; this paper aims to challenge the risks of genetic engineering. To dive deeper into our research question, we were able to examine sources on a global level to determine the perspectives of genetic engineering in different parts of the world. As the current field of genetic engineering is under speculation by many providers, evaluating the pros and cons of each scenario can determine the efficacy of genetic engineering. Employing clinical technology and socially ethical framework were two main criterias which were used in determining the parameters in understanding if genetic engineering is a viable treatment option. The research examined explains any known sideaffects, while also bringing to light the unknown side effects that can result from genetic alterations of an embryo. In summation, this paper aims to highlight embryonic effects and how genetic engineering could challenge their integration into society itself.

The purpose of this paper is to identify likely pathogenic non-coding variants in inherited retinal dystrophy (IRD) genes, using genome sequencing (GS). Patients with IRD were recruited to the study and underwent comprehensive ophthalmological evaluation and GS. The results of GS were investigated through virtual gene panel analysis, and plausible pathogenic variants and clinical phenotype evaluated by the multidisciplinary team (MDT) discussion. For unsolved patients in whom a specific gene was suspected to harbor a missed pathogenic variant, targeted re-analysis of non-coding regions was performed on GS data. Candidate variants were functionally tested by messenger RNA analysis, minigene or luciferase reporter assays. Previously unreported, likely pathogenic, non-coding variants in 7 genes (PRPF31, NDP, IFT140, CRB1, USH2A, BBS10 and GUCY2D), were identified in 11 patients. These were shown to lead to mis-splicing (PRPF31, IFT140, CRB1 and USH2A) or altered transcription levels (BBS10 and GUCY2D). MDT-led, phenotype-driven, non-coding variant re-analysis of GS is effective in identifying the missing causative alleles.

Deep learning algorithms are increasingly popular for complex prediction and classification tasks, and hyperparameter configurations play an important role in algorithm performance. However, the best hyperparameter tuning strategy still remain unresolved. While grid search and random search can be used to detect better hyperparameters, they are costly for big deep learning algorithms and may not produce the optimal result. Bayesian Optimization balancing the exploration and exploitation trade-off shows significant improvement over grid search and random search in both efficiency and accuracy, but the algorithm makes computation on the entire domain, which can be still costly especially in higher dimension settings. In this paper, we propose a space adjustment algorithm selecting top percent points at each iteration that can be incorporated in additional to Bayesian Optimization framework to further reduce experimental cost and improve optimization efficiency. We show our algorithm’s adaptable nature to the response surface of hyperparameter configuration space. We demonstrate our algorithm’s outstanding performance compared with Efficient Global Optimization through a variety of test functions and an application to machine learning datasets.

The Sustainable Development Goals (SDGs) are a set of 17 benchmarks developed by the United Nations in 2015. The intent of the SDG framework is to bring sustainable prosperity to all people on Earth by the year 2030. As of June 2022, we are halfway through the period the SDG framework was designed to study and there have been countless papers published documenting the progress of these goals and their interactions. We performed a systematic review of 690 papers that document one or more SDG and analyzed research patterns and trends within this corpus, including: frequency of SDGs studied across time, geographic scale, SDG interactions, interactions interpreted by researchers as important or significant, and commonly used keywords corresponding with SDG research. In addition to analyzing overall SDG trends, our team aims to further analyze the SDG 2 within the context of the food-energy-water (FEW) nexus, which highlights the authoring team’s areas of expertise and interest. The emphasis on the FEW nexus may serve as a demonstration of how trends in SDG research can shed light on the interdisciplinary relationships across sectors. Our team acknowledges that we are not experts on all 17 of the SDG realms and encourage other authors to use our open-source data to analyze other goals in a deeper way than we are capable.

The US HL-LHC Accelerator Upgrade Project (AUP) is building Nb3Sn quadrupole magnets, called MQXFA, with plans to install 16 of them in the HL-LHC Interaction Regions. Variability in coil size must be dealt with at the assembly level, which requires timely and repeatable measurement of each coil. In this paper we will present the methodology used for coil measurements and the geometrical size data for the coils that have been measured thus far. We will also show the coil measurements of 8 coils before and after cold test. The Leica AT960-MR laser tracker with Spatial Analyzer software acquired to achieve these measurements has been used elsewhere in the project to great effect.

Cold atmospheric plasmas (CAPs) are increasingly used for applications requiring the processing of heat- and pressure-sensitive (bio)materials. A key challenge in model-based control of CAPs arises from the high computational requirements of theoretical plasma models as well as lack of mechanistic understanding of plasma-surface interactions. Thus, control strategies that rely on simple, physics-based models that can be adapted to mitigate plant-model mismatch will be particularly advantageous for CAP applications. This paper presents an optimal control approach for controlling the nonlinear and cumulative effects of CAPs delivered to a target surface using a simple system model. Through parsimonious input parameterization, the solution to the optimal control problem (OCP) is given by an arc sequence that does not include any singular arcs. A data-driven adaptive algorithm based on modifier adaptation is proposed to deal with the structural plant-model mismatch by estimating the mismatch in the cost and constraints of the OCP. The adaptive approach is shown to converge to a Karush-Kuhn-Tucker (KKT) point of the OCP for the true system. Moreover, a control strategy based on feedback linearization and derivative estimation is proposed for online tracking of path constraints in the presence of disturbances and model uncertainty. The proposed approach is demonstrated by simulations and real-time control experiments on a kHz-excited atmospheric pressure plasma jet in Helium, in which the plasma treatment time is minimized while delivering a desired amount of nonlinear thermal effects to the target surface.

In this paper, we present a notion of differential privacy (DP) for data that comes from different classes. Here, the class-membership is private information that needs to be protected. The proposed method is an output perturbation mechanism that adds noise to the release of query response such that the analyst is unable to infer the underlying class-label. The proposed DP method is capable of not only protecting the privacy of class-based data but also meets quality metrics of accuracy and is computationally efficient and practical. We illustrate the efficacy of the proposed method empirically while outperforming the baseline additive Gaussian noise mechanism.We also examine a real-world application and apply the proposed DP method to the autoregression and moving average (ARMA) forecasting method, protecting the privacy of the underlying data source. Case studies on the real-world advanced metering infrastructure (AMI) measurements of household power consumption validate the excellent performance of the proposed DP method while also satisfying the accuracy of forecasted power consumption measurements.

Prostate cancer is the second leading cause of cancer death among men in the United States. The diagnosis of prostate MRI often relies on accurate prostate zonal segmentation. However, state-of-the-art automatic segmentation methods often fail to produce well-contained volumetric segmentation of the prostate zones since certain slices of prostate MRI, such as base and apex slices, are harder to segment than other slices. This difficulty can be overcome by leveraging important multi-scale image-based information from adjacent slices, but current methods do not fully learn and exploit such cross-slice information. In this paper, we propose a novel cross-slice attention mechanism, which we use in a Transformer module to systematically learn cross-slice information at multiple scales. The module can be utilized in any existing deep-learning-based segmentation framework with skip connections. Experiments show that our cross-slice attention is able to capture cross-slice information significant for prostate zonal segmentation in order to improve the performance of current state-of-the-art methods. Cross-slice attention improves segmentation accuracy in the peripheral zones, such that segmentation results are consistent across all the prostate slices (apex, mid-gland, and base). The code for the proposed model is available at https://bit.ly/CAT-Net.

Image reconstruction of low-count positron emission tomography (PET) data is challenging. Kernel methods address the challenge by incorporating image prior information in the forward model of iterative PET image reconstruction. The kernelized expectation-maximization (KEM) algorithm has been developed and demonstrated to be effective and easy to implement. A common approach for a further improvement of the kernel method would be adding an explicit regularization, which however leads to a complex optimization problem. In this paper, we propose an implicit regularization for the kernel method by using a deep coefficient prior, which represents the kernel coefficient image in the PET forward model using a convolutional neural-network. To solve the maximum-likelihood neural network-based reconstruction problem, we apply the principle of optimization transfer to derive a neural KEM algorithm. Each iteration of the algorithm consists of two separate steps: a KEM step for image update from the projection data and a deep-learning step in the image domain for updating the kernel coefficient image using the neural network. This optimization algorithm is guaranteed to monotonically increase the data likelihood. The results from computer simulations and real patient data have demonstrated that the neural KEM can outperform existing KEM and deep image prior methods.

Associated Particle Imaging utilizes the inelastic scattering of neutrons produced in deuterium-tritium fusion reactions to obtain 3D isotopic distributions within an object. The locations of the inelastic scattering centers are calculated by measuring the arrival time and position of the associated alpha particle produced in the fusion reactions, and the arrival time of the prompt gamma created in the neutron scattering event. While the neutron and its associated particle move in opposite directions in the center-of-mass (COM) system, in the laboratory system the angle is slightly less than 180 degrees, and the COM movement must be taken into account in the reconstruction of the scattering location. Furthermore, the fusion reactions are produced by ions of different momenta, and thus the COM velocity varies, resulting in an uncertainty in the reconstructed positions. In this paper, we analyze the COM corrections to this reconstruction by simulating the energy loss of beam ions in the target material and identifying sources of uncertainty in these corrections. We show that an average COM velocity calculated using the ion beam direction and energy can be used in the reconstruction and discuss errors as a function of ion beam energy, composition, and alpha detection location. When accounting for the COM effect, the mean of the reconstructed locations can be considered a correctable systematic error leading to a shift/tilt in the reconstruction. However, the distribution of reconstructed locations also have a spread that will introduce an error in the reconstruction that cannot be corrected. In this paper, we will use the known stopping powers of ions in materials and reaction cross-sections to examine the reconstruction uncertainties. We also discuss the impact of this effect on our API system.

Distribution grid reliability and resilience has become a major topic of concern for utilities and their regulators. In particular, with the increase in severity of extreme events, utilities are considering major investments in distribution grid assets to mitigate the damage of highly impactful outages. Communicating the overall economic and risk-mitigation benefits of these investments to regulators is an important element of the approval process. Today, industry reliability and resilience planning practices are based largely on methods that do not take explicit account of risk. This paper proposes a practical method for identifying optimal combinations of investments in new line segments and storage devices while considering the balance between the risk associated with high impact and low probability (HILP) events and the reliability related to routine failures. We show that this method can be scaled to address large scale networks and demonstrate its benefits using a Target Feeder from the Commonwealth Edison Reliability Program.

The COVID-19 pandemic presented an unprecedented challenge to public transit systems worldwide, testing the ability of transit agencies to make swift and difficult decisions. Balancing the need to provide essential workers with reliable transportation options while dealing with suddenly reduced revenue and increased operational costs forced many agencies to reduce transit services, making life difficult for countless commuters relying on transit. While the pandemic spotlighted the importance of decisive action during times of crisis, disruptions to public transit systems are a regular occurrence. Disruptions vary significantly in time, duration, location, scope, frequency, and impact. Terrorist attacks, the aftermath of violent protests, and natural disasters are a few examples that can drastically change the transit system and our travel needs. Responding quickly and effectively to these disruptions by making informed decisions is crucial not only for minimizing the impact of the disruption, but also for maintaining the reliability of public transit systems for those who depend on them, ensuring they remain available and accessible when needed most. In recent years, transit agencies have increasingly begun to adopt automated fare collections (AFC) systems, also known as smartcards, to collect fares, making valuable data readily available for analysis. In response, the research community has proposed a number of inferential methods and predictive models to analyze transit patterns. More than 300 research papers have been published on short-term ridership prediction models in the last decade. Despite the abundance of literature, we, the research community, have yet to generate practical knowledge for decision-making. Lack of reproducibility due to inadequate documentation, inaccessible tools and resources, and code and data-sharing issues are prevalent; hindering our ability to create collective wisdom. The problem is further compounded by the lack of rigorous statis

Illegal: the Theater of the Angel Island Immigration Station’s Paper Sons | Skyler Chin, Jeffrey Lo, and Sita Sunil (Fall 2022 Speaker Series)Lecture, 73 minutes; Part of the Fall 2022 Speaker Series (Landscapes of Migration, Incarceration and Resistance)Click the title and scroll to the gray box below to access the video.Recording of presentation at @BAMPFA Osher Theater; free and open to the public Friday, October 21, 2022Speakers: Skyler Chin and Sita Sunil, Playwrights of Illegal; Jeffrey Lo, Director of The Paper Dreams of Harry Chin, PlaywrightOne island, two plays: Skyler Chin and Sita Sunil will discuss their new musical Illegal with Filipino-American playwright Jeffrey Lo, who recently directed The Paper Dreams of Harry Chin, which like Illegal dramatizes the family traumas created by racially exclusionary policies carried out at Angel Island. Skyler Chin was inspired to co-write Illegal by his own ancestors’ experiences at Angel Island, and Sita Sunil’s work as an artist is also shaped by her family’s history of immigration. In addition to his directing work, Jeffrey Lo’s playwriting often deals with issues of Asian American identity. This will be a stimulating conversation across generations and genres.UC @Berkeley Arts + Design Fridays: Landscapes of Migration, Incarceration, and Resistance is a lively series of talks by artists, performers, scholars, and activists exploring themes of global and US migration, exclusion, and belonging. It is also a UC Berkeley course offered as Humanities 20: Explorations of Art + Design. Organized by Susan Moffat, Creative Director of Future Histories Lab and Executive Director of the Global Urban Humanities Initiative and by Lisa Wymore, Professor of Theater, Dance and Performance Studies and Faculty Advisor of Berkeley Arts + Design. Hosted by Susan Moffat.--This speaker series is part of a program of music and dance performances, exhibitions, public conversations, and courses called A Year on Angel

Immigrants and their descendants are vital to the fabric of the U.S. and Switzerland. Schools’ importance in fostering immigrant-origin students’ learning while considering their rich cultures, languages, and knowledge is well established. Therefore, this mixed-methods, cross-national, multiple-case dissertation study explores U.S. and Swiss students’ perspectives on their experiences and opportunities in school, social capital, the development of their vocational aspirations, and how the former shapes the latter two. Centering student voice, I draw on social network data and interview data with 22 immigrant-origin middle school students (interviewed 3-4 times each, resulting in 41 hours of interview data), 13 teachers (10.5 hours), and two principals (1.5 hours). Surveys were conducted with 259 students. Findings are presented in three articles focused on (a) immigrant-origin middle school students’ personal support networks and the mobilization of peer social capital, (b) the changes in peer interactions and friendships during the Covid-19 pandemic, and (c) the role of networks and contexts of reception on vocational aspirations. Paper 1 suggests that peers constituted more than half of participants’ personal support networks, whereas schools were critical contexts for adolescents to interact with peers and build friendships. Networks in the U.S. were more dynamic than networks in Switzerland. Shared social background, perceived integrity, and trustworthiness cultivated friendships, whereas those perceptions were shaped by the school contexts. Findings from Paper 2 describes U.S. students’ experienced changes in their peer interactions and friendships. Paper 3 shows how social networks and contexts of reception, including institutional, economic, political, and sociocultural factors, shaped vocational aspirations. However, the degree of different factors’ importance differed across the U.S. and Swiss contexts. The dissertation concludes by discussing implications

Problem: Preoperative education for parents whose children are undergoing an ophthalmic procedure or surgery is critical for a positive surgical experience. Current parent preoperative education practices in a pediatric ophthalmology clinic rely mainly on verbal instruction and can have inconsistent delivery.PICO Question: Among parents of pediatric patients undergoing ophthalmic procedure or surgery (P), how does the utilization of a preoperative educational video (I), compared to the current standard of practice (verbal instruction only) (C), impact surgical day parent satisfaction (O), over a three-month period? Methods: A quality improvement (QI) project was conducted between July 2022 to April 2023. Pre-surgical parents were identified in a pediatric ophthalmology clinic and viewed a 10-minute voice-narrated PowerPoint video containing standard parent education. Parents were given a paper copy of the slides and a QR code as a resource. Parents were asked to 1) evaluate the effectiveness of the video by completing the Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V), 2) answer demographic questions, and 3) complete the Hospital National Research Corporation (NRC) Health parent satisfaction survey. The NRC Health scores were compared three months before and after the preoperative video introduction. Percentages were used to evaluate sample characteristics and compare percentages of parent satisfaction scores pre- and post-video implementation. Results: A total of 43 parents watched the video and answered the PEMAT-A/V questionnaire. PEMAT-A/V scores showed that 93% of participants reported the video as easy to understand and that it acknowledged actionable items needed for day of surgery. Parent satisfaction scores improved from pre-intervention (n=50; 3 months) 87% compared to post-intervention (n=49; 2.5 months) 100%. Conclusion: Preoperative video education can positively impact satisfaction with surgical experience among paren

The COVID-19 pandemic, caused by the SARS-CoV-2 virus, has profoundly affected global health, presenting unprecedented challenges to pregnant women and their offspring. This paper explores the impacts of COVID-19 on maternal, neonatal, and childhood health, shedding light on both short-term and potential long-term consequences. The transmission of the virus from mother to child, though relatively low compared to other vertically transmitted diseases, remains a subject of ongoing study. Maternal COVID-19 infection during pregnancy is linked to adverse outcomes such as preterm delivery, cesarean section, preeclampsia, and gestational diabetes. Additionally, COVID-19 infection appears to influence placental pathology, raising concerns about fetal development and health in the long term. The pandemic has exacerbated maternal mental health challenges, including an increased prevalence of postpartum depression. Infants born to mothers with COVID-19 may experience lower neonatal weight, reduced head circumference, and a heightened risk of complications. Long-term health effects on children, including cardiovascular and respiratory impacts, remain areas of active investigation. Comprehensive research is vital to understand the magnitude of these risks and develop effective strategies for preventing and managing COVID-19 in pregnant women. Prioritizing the health and well-being of pregnant women and their offspring is critical in mitigating the enduring effects of the pandemic on maternal, neonatal, and childhood outcomes.

This paper proposes a new relationship between thermal conductivity and degree of saturation of unsaturated soils, referred to as the thermal conductivity function (TCF). The new sigmoidal relationship between thermal conductivity and degree of saturation was developed so that all parameters have a physical meaning. After calibration of the model using data from the literature and comparison with other available TCFs, the parameters of the new TCF were related to those of the soil-water retention curves for the soils investigated in the calibration process. The linkage between the parameters of the TCF and SWRC indicates that the parameters reflect the point of air entry and pore size distribution of the soil, as well as the maximum and minimum thermal conductivity values encountered at saturated and dry conditions, respectively.

This dissertation consists of three papers. The first is conceptual paper concerned with creating tenets for QuantCrit research titled the Anti-Racist Tenets for Analysis (ARTA), discussing each tenet’s meaning and greater application, as well as providing research reflection questions for each tenet. Researchers may use these reflections along with the general meaning of each tenet to ensure their own research is conducted in a transparent and critical way, considering race and the social impact race has both on variables and equity within their studies. The second paper is an empirical application of the established anti-racist tenets for analysis to quantitative research. Four different ways of including race in quantitative analysis are examined. The first is a traditional multivariate approach with one racial category (White) excluded as a reference group. The second is a moderation approach where race is interacted with a number of other independent variables to represent the pervasiveness of race to lived experiences. The third is a path analysis structural equation model where the dependent variable is regressed on the independent variables which are all in turn regressed upon race, and the fourth is a grouping analysis where each racial group’s analysis is run independently. Results found that traditional multivariate and moderation approaches had the same results, suggesting moderation did not add significantly to the model. The path analysis was found to be more exemplary of the pervasiveness of race and intersectional identities than the first two models, and to be sensitive enough to be useful when race is not a central point of study. However, the grouping model was the only truly anti-racist method, as it eliminated the point of comparison between races as well as exemplifying more clearly the lived experiences of each race as well as intersectional identities. The third study tackles equity between factor analysis groups, by showing how to gender run

Consumer reactions to COVID-19 pandemic disruptions have been varied, including modifications in spending frequency, amount, product categories and delivery channels. This study analyzes spending data from a sample of 720 U.S. households during the start of deconfinement and early vaccine rollout to understand changes in spending and behavior one year into the pandemic. This paper finds that overall spending is similar to pre-pandemic levels, except for a 28% decline in prepared food spending. More educated and higher income households with children have shifted away from in-person spending, whereas politically conservative respondents are more likely to shop in-person and via pickup.

In this paper, I will discuss the process of developing and pre-visualizing scenic designs for 'Hells Canyon,' produced as part of the 2022 Wagner New Play Festival. In much of my own work that I have created at UCSD, I’ve incorporated both physical modeling techniques as well as digital rendering, using programs such as Vectorworks and SketchUp. Through an analysis of my own work creating the scenic design for 'Hells Canyon,' I will examine where the strengths of these two modes of working lie, and how these two methods ultimately are at their most productive when used in tandem with one another.

This work presents a novel hierarchical approach to increase Battery Electric Buses (BEBs) utilization in transit fleets. The proposed approach relies on three key components. A learning-based BEB digital twin cloud platform is used to accurately predict BEB charge consumption on a per vehicle, per driver, and per route basis, and accurately predict the time-to-charge BEB batteries to any level. These predictions are then used by a Predictive Block Assignment module to maximize the BEB fleet utilization. This module computes the optimal BEB daily assignment and charge management strategy. A Depot Parking and Charging Queue Management module is used to autonomously park and charge the vehicles based on their charging demands. The paper discusses the technical approach and benefits of each level in the architecture and concludes with a realistic simulations study. The study shows that if our approach is employed BEB fleet utilization can increase by a 50% compared to state-of-the-art methods.

A large body of work has linked neural oscillations in the alpha-band (8-13 Hz) to visual perceptual outcomes. In particular, studies have found that alpha phase prior to stimulus onset predicts stimulus detection, and sensory responses and that the frequency of alpha can predict temporal properties of perception. These findings have bolstered the idea that alpha-band oscillations reflect rhythmic sampling of visual information, however the mechanisms of this are unclear. Recently two contrasting hypotheses have been proposed. According to the rhythmic perception account, alpha oscillations impose phasic inhibition on perceptual processing and primarily modulate the amplitude or strength of visual responses and thus the likelihood of stimulus detection. On the other hand, the discrete perception account proposes that alpha activity discretizes perceptual inputs thereby reorganizing the timing (not only the strength) of perceptual and neural processes. In this paper, we sought neural evidence for the discrete perception account by assessing the correlation between individual alpha frequencies (IAF) and the latency of early visual evoked event-related potential (ERP) components. If alpha cycles were responsible for shifting neural events in time, then we may expect higher alpha frequencies to be associated with earlier afferent visual ERPs. Participants viewed large checkerboard stimuli presented to either the upper or lower visual field that were designed to elicit a large C1 ERP response (thought to index feedforward primary visual cortex activation). We found no reliable correlation between IAF and the C1 latency, or subsequent ERP component latencies, suggesting that the timing of these visual-evoked potentials was not modulated by alpha frequency. Our results thus fail to find evidence for discrete perception at the level of early visual responses but leave open the possibility of rhythmic perception.

This paper investigates the energy performance and sizing criteria of 5th generation district heating and cooling (5GDHC) networks as a function of the heat distribution temperature in the building systems connected to the district network. An energy simulation model of a 5GDHC network was developed in Modelica for a case study located in Denmark. Calculations were carried out for four different building heating systems. Simulation results show that reducing the heat distribution temperatures from 70 °C to 23 °C leads to around 40% annual electric energy savings (from 10.4 kWh/m2 to 6.2 kWh/m2) for the operation of the heat pumps. Heat distribution temperatures of 23 °C cause higher water mass flow rates through the network, leading to annual electric energy consumption for the circulation pumps that are almost doubled (from 0.16 kWh/m2 to 0.3 kWh/m2) compared to the reference case at 70 °C. Furthermore, the paper discusses how the results obtained from the Danish case study can be generalized and applied to other cases using a simplified mathematical approach. It is found that about 1.5% of electric energy savings can be achieved for each temperature degree reduction in the heat distribution system.

This paper presents a systematic literature review on the relationship between influencer marketing and parasocial relationships in social media. Influencer marketing has gained significant traction as an effective marketing strategy with the advent of social media platforms. Thus, this study seeks to explore the impact of parasocial relationships between influencers and their followers on consumer trust, purchasing decisions, the factors that influence these relationships, and how influencers can enhance them to optimize marketing outcomes. The review encompasses analysis of five primary research studies, investigating factors such as interpersonal attraction, personal attributes, intimate self-disclosure, and empathy as determinants of parasocial relationships. The findings indicate that parasocial relationships exert a positive influence on consumer trust, purchase intentions, and brand evaluations. Notably, factors such as interpersonal attraction, intimate self-disclosure, and empathy emerge as key drivers in fostering and reinforcing parasocial connections. The paper concludes by discussing practical strategies that influencers can employ, including two-way communication, personal disclosures, advertising transparency, and tailored content, to cultivate and strengthen parasocial relationships, ultimately enhancing marketing effectiveness. The study underscores the need for further research to deepen our understanding of this phenomenon and its implications for influencer marketing.

BACKGROUND AND OBJECTIVES: Given the increase in methodological pluralism in research on brain health, cognitive aging, and neurodegenerative diseases, this scoping review aims to provide a descriptive overview and qualitative content analysis of studies stating the use of participatory research approaches within Alzheimers disease and related dementias (ADRD) literature globally. RESEARCH DESIGN AND METHODS: We conducted a systematic search across four multidisciplinary databases (CINAHL, SCOPUS, PsycInfo, PubMed) for peer-reviewed, English-language studies addressing ADRD that explicitly described their use of a participatory research approach. We employed a systematic process for selecting articles that yielded a final sample of 163 studies. Data from articles were analyzed to chart trends from 1990 to 2022 in terminology, descriptions, application of participatory approaches, and the extent and nature of partnerships with nonacademics. RESULTS: Results demonstrated geographic differences in the use of stated approaches between North America-where community-based participatory research predominates-and Europe, where Action Research is most common. We further found that only 73% of papers in this systematic review had identifiable definitions or descriptions of the participatory approach used. Findings also showed that 14% of articles demonstrated no evidence of engaged partnership beyond activities typical of research participants, while 23% of articles identified partnering with people with dementia, and an additional 16% reported partnerships with members from Indigenous, Black, Asian, or Latinx communities. DISCUSSION AND IMPLICATIONS: This scoping review identifies three areas in need of greater attention in ADRD literature using participatory research approaches. First, findings indicate the importance of strengthening the use, transparency, and rigor of participatory methods. Second, results suggest the need for greater inclusion of historically marginalize

As the prevalence of pediatric diabetes grows and new technologies to manage diabetes emerge, there is increasing concern about consistency in health management across institutional settings, particularly in schools. While much is known about barriers at school, there are still gaps in understanding the institutional dynamics that shape health management in this setting. Using focus groups with 19 youth with type 1 diabetes (T1D) and applying institutional role theory, we find healthcare providers recommendations conflict with school rules and norms, making it difficult to enact both the sick role and the student role. These conflicts elicit negative responses from teachers and peers and stigmatize youth with T1D in school. Caregiver involvement often heightens rather than ameliorates conflict and teachers do not intervene in effective ways. Ultimately, youth must manage conflicts and stigma. By reframing challenges in health management as institutional role conflict, this paper contributes to sociological research by highlighting the importance of institutional roles, especially beyond healthcare. More broadly, the study suggests health research and policy should investigate how to better align institutional roles-rather than relying on youth and their families-to support health management of chronic illnesses across institutional settings.

The need to reduce atmospheric CO2 concentrations necessitates CO2 capture technologies for conversion into stable products or long-term storage. A single pot solution that simultaneously captures and converts CO2 could minimize additional costs and energy demands associated with CO2 transport, compression, and transient storage. While a variety of reduction products exist, currently, only conversion to C2+ products including ethanol and ethylene are economically advantageous. Cu-based catalysts have the best-known performance for CO2 electroreduction to C2+ products. Metal Organic Frameworks (MOFs) are touted for their carbon capture capacity. Thus, integrated Cu-based MOFs could be an ideal candidate for the one-pot capture and conversion. In this paper, we review Cu-based MOFs and MOF derivatives that have been used to synthesize C2+ products with the objective of understanding the mechanisms that enable synergistic capture and conversion. Furthermore, we discuss strategies based on the mechanistic insights that can be used to further enhance production. Finally, we discuss some of the challenges hindering widespread use of Cu-based MOFs and MOF derivatives along with possible solutions to overcome the challenges.

The forthcoming Connected Vehicles (CV) technology promises to substantially aid in managing traffic congestion and improving users’ mobility along transportation corridors. Through CV technology, a global estimate of the corridor’s traffic flow state can be obtained through analyzing data from its constituent components, which can enable globally-optimized traffic management strategies that efficiently utilize existing transportation infrastructure resources. In this paper, we propose a novel integrated corridor management (ICM) methodology that incorporates the underutilized infrastructure of park and ride facilities into its global optimization strategy. Firstly, we discuss how vehicle-to-infrastructure (V2I) communication protocols like basic safety messages (BSM) and traveler information messages (TIM) can be tailored to collect the state of downstream traffic and advertise park and ride advisories to upstream traffic respectively. Then, we model the system in terms of potential delays that can be experienced by vehicles traversing the corridor, and accordingly, we implement a novel centralized deep reinforcement learning (DRL) solution to control how and when such messages are advertised, with the aim of maximizing throughput and minimizing carbon emissions and travel time. We simulate our ICM strategy on a realistic model of Interstate 5 using the Veins simulation software, and the DRL agent converges to a strategy that provides marginal improvement to throughput, freeway travel time, and carbon emissions but at the cost of added travel delay for those using park and ride services.

Antimicrobial resistance (AMR) is a growing global concern that poses significant risks to human, animal, and environmental health. AMR describes organisms, including bacteria, viruses, and fungi, that have become resistant to the drugs used to kill or control them through evolutionary, environmental, or social pressures. The emergence and spread of AMR threaten decades of advancement in reducing morbidity and mortality from many infectious diseases and is one of the most pressing clinical and public health threats. In the United States alone, more than 2.8 million AMR infections occur annually, resulting in over 35,000 deaths and costing the healthcare system over $4.6 billion.Community-acquired Methicillin-resistant Staphylococcus aureus (CA-MRSA) infections are a significant financial burden on healthcare systems and vary across populations. Several studies have documented infection disparities across racial-ethnic categories, economic indicators, and geography. Evidence suggests that differential infection rates are related to social determinants of health such as income, housing, and educational attainment. However, few studies connect infection disparities to the key mechanisms underlying the role of racial-ethnic category, income, or geography in shaping population health. The role of area-based determinants of infection has yet to be thoroughly examined, and addressing the challenges of AMR more broadly will require understanding the social, environmental, and economic processes that shape differential infection incidence. This dissertation explores the systems and determinants associated with disparities in CA-MRSA infection presenting in California emergency departments (ED). The first paper examines the epidemiology of CA-MRSA skin and soft tissue infections (SSTIs) across California from 2016-2019, examining the spatial distribution of infections in a unique neighborhood boundary. CA-MRSA infections are historically associated with densely populated urba

For years researchers have shown the positive role that foreign language courses play in increasing the cultural knowledge and understanding of university students. However, at a time where internationalization is now at the forefront of nearly every major US university, foreign language courses are being cut and defunded at unprecedented levels. Clearly, the cultural benefits that foreign language courses provide are not meeting the standards necessary to be seen as key contributors to the goals of internationalization. Thus, the research presented in this paper is an initial student-centered investigation into the process of cultural learning within foreign language courses. By focusing on how students perceive of and understand the cultural information they are exposed to in the classroom. As a result, the research suggests important areas in which foreign language courses can improve the role they play in facilitating cultural learning, and hopefully, begin to receive the recognition they deserve in improving cultural understanding and awareness.

Since their rise over half a century ago, community archives have filled in the gaps that mainstream archives have knowingly or unknowingly left, preserving the history of typically marginalized groups on their own terms. But it is only in the past decade or two that scholars have begun seriously contending with community archives, a timeline that perhaps not coincidentally overlaps with the archival profession’s increased focus on its own role in perpetuating power relations and systems of oppression. How has the so-called traditional archival community conceived of its relationship to both power and community archives, and what potential do community archives hold to help the archival field rectify its history of exclusion? Through a review of trends in the current literature on the topic, this paper will explore community archives as an alternative to traditional archival practice. Ultimately, this paper will argue for a reconceptualization of community archives as part of the archival continuum rather than as traditional or mainstream archives’ binary opposite. If archives and archival professionals want to begin to grapple with their legacy of power and exclusion, rethinking how we conceptualize archival working taking place outside of the academy and traditional heritage sector is a promising place to begin.

Electric transmission system operators (ISOs, RTOs, and utilities) require large new generators and storage resources seeking to connect to the grid to undergo a series of impact studies before they can be built. This process establishes what new transmission equipment or upgrades may be needed before a project can connect to the system and assigns the costs of that equipment. Berkeley Lab has collected interconnection cost data from interconnection studies from the New York Independent System Operator (NYISO), representing at least 43% of all new unique generation and storage resources requesting interconnection in NYISO from 2003 through 2019. Project-level cost summary data are available for download on this page. We find: -Average interconnection costs have grown as the number of interconnection requests have escalated. -Upgrades both at the point of interconnection and in the broader network have driven cost increases. -Applicants still actively working through the interconnection process have higher interconnection costs than historical projects, but lower costs than projects which have recently withdrawn or been completed. -Solar projects tend to have higher interconnection costs than other resource types. -Larger generators have greater interconnection costs in absolute terms, but economies of scale exist on a per kW basis for solar and wind projects. -Cost estimates increase as projects complete more studies in the interconnection process. Berkeley Lab will publish a series of short analytical papers of generator interconnection costs to the transmission system for MISO, PJM, SPP, ISO-NE and NYISO, which you can find at https://emp.lbl.gov/interconnection_costs.

Electric transmission system operators (ISOs, RTOs, or utilities) require new large generators seeking to connect to the grid to undergo a series of impact studies before they can be built. This process establishes what new transmission equipment or upgrades may be needed before a project can connect to the system and assigns the costs of that equipment. Berkeley Lab has collected interconnection cost data from interconnection studies for the PJM Territory, representing nearly 86% of all new unique generators requesting interconnection from 2000 to 2022. Project-level cost summary data are available for download on this page. We find: -Average interconnection costs have grown as the number of interconnection requests have escalated -Projects that have completed all required interconnection studies have the lowest cost compared to applicants still actively working through the interconnection process or those that have withdrawn. -Broader network upgrade costs are the primary driver of recent cost increase. -Potential interconnection costs for wind, storage, and solar are larger than for natural gas -Larger generators have greater interconnection costs in absolute terms, but economies of scale exist on a per kW basis. -Interconnection costs vary by location Berkeley Lab will publish a series of short analytical papers of generator interconnection costs to the transmission system for MISO, PJM, SPP, ISO-NE and NYISO, which you can find at https://emp.lbl.gov/interconnection_costs.

Active, real-time observation of behavior is a time-consuming task, which is heavily resource-limited. At the same time, simultaneous observation of several individuals is often paramount to increase statistical rigor and eliminate potential temporal or environmental bias, especially in natural settings. This paper describes a low-cost video recording system created by using “off-the-shelf” components. The system is easy to use and can automatically record a wide variety of behavior and related ecological interactions and evolutionary processes. The system is sensitive enough to record the behavior of a broad range of animals from planarians, and small insects to humans. It can also be used to measure the behavior of plants. The system will also work during daylight hours or at night and can run continuously and autonomously for 48 hours, or longer if the video capture is motion-triggered or if bigger capacity batteries and data storage facilities are used.

The cap pushing response (CPR) is a free flying technique where honey bees are trained to fly to a target where they push a cap to reveal a hidden food source. In this paper, we report the results of three studies. First, we provide information on three techniques used to shape the CPR. Second, we provide preliminary data suggesting that honey bees can learn the CPR through observing a previously shaped bee. Finally, we provide data on the ability of a honey bee to recall the CPR response. In addition to the three studies, we also continue to advocate for the use of Observation Orientated Modeling (OOM) for comparative investigations.

Studies examining associations between greenspace and Alzheimer's disease and related dementia (ADRD) outcomes are rapidly on the rise, yet no known literature reviews have summarized the racialized/ethnic group and geographic variation of those published studies. This is a significant gap given the known disparities in both greenspace access and ADRD risk between racialized/ethnic groups and between developed versus developing countries. In this rapid literature review, we (1) describe the diversity of published greenspace-brain health studies with respect to racialized/ethnic groups and geographic regions; (2) determine the extent to which published studies have investigated racialized/ethnic group differences in associations; and (3) review methodological issues surrounding studies of racialized/ethnic group disparities in greenspace and brain health associations. Of the 57 papers meeting our inclusion criteria as of 4 March 2022, 21% (n = 12) explicitly identified and included individuals who were Black, Hispanic/Latinx, and/or Asian. Twenty-one percent of studies (n = 12) were conducted in developing countries (e.g., China, Dominican Republic, Mexico), and 7% (n = 4) examined racialized/ethnic group differences in greenspace-brain health associations. None of the studies were framed by health disparities, social/structural determinants of health, or related frameworks, despite the known differences in both greenspace availability/quality and dementia risk by racialized/ethnic group and geography. Studies are needed in developing countries and that directly investigate racialized/ethnic group disparities in greenspace-brain health associations to target and promote health equity.

Anorexia nervosa (AN) usually emerges in adolescence when important changes occur in cognitive, emotional, and social processes. Mentalizing, alexithymia, and impulsiveness represent key dimensions for the understanding and interpretation of psychological difficulties in AN. The outbreak of the COVID-19 pandemic has impacted adolescents with AN, showing a worsening of the disease. The main aims of the present paper are (1) to compare adolescents with AN before and during the COVID-19 pandemic and (2) to explore the relationship between mentalizing, alexithymia, impulsiveness, and psychological difficulties related to eating disorders in adolescents with AN during the COVID-19 pandemic. One hundred and ninety-six AN female adolescents (N = 94 before COVID-19; N = 102 during COVID-19) participated in this study. The results show that adolescents with AN during the COVID-19 pandemic had a more impaired functioning profile than the before COVID-19 group. Mentalizing, alexithymia, and impulsiveness had a predictive role on psychological difficulties related to eating disorders in adolescents with AN during the COVID-19 pandemic. In conclusion, our data reveal that the COVID-19 pandemic has likely represented a stress condition that affects mental health; worsening the severity of adolescents with AN clinical condition. Lastly, predictive patterns suggest the existence of a link between difficulties in the ability to face the problems of the present time using effective strategies and the severity of psychological symptoms.

BACKGROUND AND OBJECTIVES: In Italy, approximately 650 individuals receive a diagnosis of primary progressive aphasia (PPA) every year. Unfortunately, the frequency with which patients are referred to speech-language services is suboptimal, likely due to skepticism regarding the value of speech-language therapy in the context of neurodegeneration. MATERIALS AND METHODS: We conducted a virtual survey of speech and language therapists (SLTs) across Italy, to collect information about the assessment, intervention and management of patients with PPA. To ensure that as many SLTs as possible received the survey, the Italian Federation of SLTs (Federazione Logopedisti Italiani, FLI) aided in disseminating the survey. RESULTS: In total, 336 respondents participated in the online survey, 140 of whom had previous experience with PPA patients. Respondents indicated having seen a total of 428 PPA patients in the previous 24 months (three patients on average, range: 0-40). SLTs who reported never working with PPA identified underdiagnoses, low referral rates and the rarity of the clinical syndrome as major reasons for their lack of experience with PPA. SLTs with experience working with PPA indicated that patients may not have accessed services because of service dysfunction and geographical barriers. Respondents reported using informal interviews during assessments and tests developed for post-stroke aphasia, while impairment-based/restitutive interventions were utilised most often. CONCLUSION: Findings may serve to inform health policy organisations regarding the current shortcomings and needed recommendations for improving the care of individuals with PPA in Italy. Improving awareness of the utility of rehabilitation among SLTs and other clinical service providers may serve to facilitate access to intervention, which in turn will serve to better support individuals living with PPA. WHAT THIS PAPER ADDS: What is already known on the subject Speech and language therapists (SLTs)

Despite the availability of effective treatment, medications for opioid use disorder are underutilized due to a variety of practical, political, and psychological reasons. Digital inequalities, such as limited access to technology, skills to leverage the technology for desirable outcomes, and social resources, may be contributing to negative health outcomes. In addition, broader health literacy plays an integral part in the capacity of individuals to appraise opioid medication-related online information. This paper explores the role of digital inequalities in the uptake of treatment for opioid use disorder. Given the shift toward telemedicine and online counseling for substance use treatment as a consequence of the COVID-19 pandemic, more research into the digital inequalities faced by those who misuse opioids may provide insight into ways of engaging and encouraging this population to utilize treatment.

FLASH radiation therapy (FLASH-RT), delivered with ultrahigh dose rate (UHDR), may allow patients to be treated with less normal tissue toxicity for a given tumor dose compared with currently used conventional dose rate. Clinical trials are being carried out and are needed to test whether this improved therapeutic ratio can be achieved clinically. During the clinical trials, quality assurance and credentialing of equipment and participating sites, particularly pertaining to UHDR-specific aspects, will be crucial for the validity of the outcomes of such trials. This report represents an initial framework proposed by the NRG Oncology Center for Innovation in Radiation Oncology FLASH working group on quality assurance of potential UHDR clinical trials and reviews current technology gaps to overcome. An important but separate consideration is the appropriate design of trials to most effectively answer clinical and scientific questions about FLASH. This paper begins with an overview of UHDR RT delivery methods. UHDR beam delivery parameters are then covered, with a focus on electron and proton modalities. The definition and control of safe UHDR beam delivery and current and needed dosimetry technologies are reviewed and discussed. System and site credentialing for large, multi-institution trials are reviewed. Quality assurance is then discussed, and new requirements are presented for treatment system standard analysis, patient positioning, and treatment planning. The tables and figures in this paper are meant to serve as reference points as we move toward FLASH-RT clinical trial performance. Some major questions regarding FLASH-RT are discussed, and next steps in this field are proposed. FLASH-RT has potential but is associated with significant risks and complexities. We need to redefine optimization to focus not only on the dose but also on the dose rate in a manner that is robust and understandable and that can be prescribed, validated, and confirmed in real time. Robu

Residential buildings can contribute to save energy and to decrement electricity consumption in the world. On the other hand, the Internet of Things has allowed the implementation of smart homes that can profile the users. Nevertheless, end-users are not accepting the smart homes due to behavioral problems and usability problems with the Human–Machine Interface (HMI) or with the household appliances. As a solution, social products promote the interaction between the smart home and the consumer by including gamification features in the interface. Thus, smart homes can interact and compete with other houses to reduce energy consumption. Therefore, this paper proposes a three-step framework that takes advantage of social products to promote interaction between smart homes within a smart community to reduce electrical energy consumption. The first step collects from the literature review, the characteristics of the end-users, the behavioral and usability problems, and the most common gamification elements that teach, engage and motivate the user to reduce energy consumption. The second step proposes the gamification elements required for a tailored HMI in each social product and smart home through a fuzzy logic decision. The third step evaluates the interaction between social products in smart homes and the users to test which smart home is reducing more energy consumption. Finally, a three-level tailored gamified mock-up is depicted: level 1 for a single social product, level 2 for the smart home, and level three for the smart community. This mock-up can be implemented in small communities as residential complexes.

Evidence-based ADHD interventions such as self-monitoring are scarcely used by educators,especially those teaching in secondary schools (Sibley et al., 2016). Common barriers to intervention use include restricted time, poor knowledge of ADHD, and feelings of frustration and stress associated with teaching students with ADHD (Szép, 2021). Because barriers are often related to stimuli and events that result in increased mental effort, one theoretical lens through which such barriers can be understood is cognitive load. Therefore, in the present research, I used cognitive load theory as a framework to guide the design of a novel, computerbased, self-monitoring intervention intended to reduce barriers to teachers’ intervention use. The purpose was (a) to evaluate the cognitive load experienced by teachers when implementing a self-monitoring intervention, and (b) to explore teachers’ acceptability of the novel, computer-based self-monitoring intervention. To this end, secondary school teachers from the United States read a vignette description of an adolescent with ADHD and were subsequently randomly presented with one of two self-monitoring intervention modalities— computer-based or paper-and-pencil based—to support the student. Then, participants completed rating scales that assessed their likelihood of intervention use and perceived cognitive load associated with the intervention procedures. 336 participants met eligibility criteria to participate, but only 89 were included in the final analysis after listwise deletion of cases that failed to pass the validity check for adequate engagement with the intervention and vignette. Participants’ acceptability ratings for both the computer-based intervention and analog intervention were favorable, and ratings for the computer-based intervention were somewhat higher than their ratings for the analog intervention. However, the difference was not practically significant. Limitations and future directions are discussed.

This research paper foregrounds a bricolage methodology based on autoethnographicwriting and analog collage technique to interweave Arab queerness in migratory contexts. By proceeding as such, the paper seeks to open a space for new modalities of crafting of knowledge; notably by bridging creative visual methodologies with critical theories. It also sketches problemspaces(Grossberg, 2010) of Arab queerness by discussing the different nodal points that shape it.

Because of its simplicity and the ability to produce a stable, slow-propagating crack, the Double-Torsion (DT) method has been used widely for investigating the critical and subcritical propagation of a slow-propagating tensile (mode-I) crack. However, to determine the complex relationship between the crack velocity vc vs. the strain energy release rate G (or the stress intensity factor K) from laboratory measurements, several corrections must be made to account for the impact of sample and crack geometry. Particularly, DT test typically produces a crack with a curved edge profile instead of a straight line, causing the local vc and G vary along the crack front. The experimentally measured vc and G data merely reflect collective, averaged behavior of the crack. This makes inversion for the intrinsic, “true” crack growth kinetics necessary, based upon the knowledge of the crack geometry. Simple and effective correction methods have been proposed and validated for the slow, chemical-reaction-controlled part (Region I) of the vc−G curve. However, reliable methods for the highly nonlinear, transport-dominated part (Region II) and its sudden transition to the dynamic propagation part (Region III) are still lacking. In this paper, we propose a method for determining the intrinsic vc−G relationship across all three Regions based upon DT test data, using a simple model function and its numerical inversion. The performance of this approach is examined and demonstrated using both synthetic and laboratory data for subcritical crack growth in soda lime glass.