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A variety of scattering-based, microscopy-based, and mobility-based methods are frequently used to probe the size distributions of colloidal nanoparticles with transmission electron microscopy (TEM) often considered to be the "gold standard". Charge detection mass spectrometry (CDMS) is an alternative method for nanoparticle characterization that can rapidly measure the mass and charge of individual nanoparticle ions with high accuracy. Two low polydispersity, ∼100 nm diameter nanoparticle size standards with different compositions (polymethyl methacrylate/polystyrene copolymer and 100% polystyrene) were characterized using both TEM and CDMS to explore the merits and complementary aspects of both methods. Mass and diameter distributions are rapidly obtained from CDMS measurements of thousands of individual ions of known spherical shape, requiring less time than TEM sample preparation and image analysis. TEM image-to-image variations resulted in a ∼1-2 nm range in the determined mean diameters whereas the CDMS mass precision of ∼1% in these experiments leads to a diameter uncertainty of just 0.3 nm. For the 100% polystyrene nanoparticles with known density, the CDMS and TEM particle diameter distributions were in excellent agreement. For the copolymer nanoparticles with unknown density, the diameter from TEM measurements combined with the mass from CDMS measurements enabled an accurate measurement of nanoparticle density. Differing extents of charging for the two nanoparticle standards measured by CDMS show that charging is sensitive to nanoparticle surface properties. A mixture of the two samples was separated based on their different extents of charging despite having overlapping mass distributions centered at 341.5 and 331.0 MDa.

Before one can address the pressing questions within any discipline, it is worth investigating the narratives and assumptions that undergird the answers. In Chinese archaeology, there have been observable points in time where politics have exerted significant force on academic opinions - certain political epochs correspond to homogeneity in opinion. This begs the question: in the context of Chinese archaeology, how exactly has politics affected archaeological interpretations of discoveries and theoretical frameworks? Within the modern era, I look to three major eras that have well-documented effects on Chinese archaeology to chart the changes in the discipline over time: 1) the Republican era, 2) the Maoist era, and 3) the post-reform period (i.e., 1978 and onwards). In interpreting these broad eras and the political views that characterize them, I will appeal to Michel Foucault’s concept of the episteme. That is, the underlying assumptions that ground the way people understand the world and their surroundings. I find that, regardless of what political narratives become dominant, nationalism is always a core fixture of these interpretations. Further, I also find that nationalism did not appear as a spontaneous phenomenon but served a very specific purpose: to counter the Western colonization of the discipline.

Research assessing personality traits and religiosity across cultures has typically neglected variation across religious affiliations and has been limited to a small number of personality traits. This study examines the relationship between the Big Five personality traits and their facets, two theoretically distinct measures of religiosity, and twelve other personality traits across seven religious affiliations and 61 countries/regions. The proportion of participants following a religion varied substantially across countries (e.g., Indonesia = 99%; Estonia = 7%). Both measures of religiosity were related to agreeableness, conscientiousness, happiness, and fairness; however; relations with religiosity as a social axiom were stronger and less variable across religious affiliations. Additionally, personality-religiosity links were more robust in low-development, high-conflict, and collectivist nations.

About 40 transneptunian binaries (TNBs) have fully determined orbits with about 10 others being solved except for breaking the mirror ambiguity. Despite decades of study almost all TNBs have only ever been analyzed with a model that assumes perfect Keplerian motion (e.g., two point masses). In reality, all TNB systems are non-Keplerian due to non-spherical shapes, possible presence of undetected system components, and/or solar perturbations. In this work, we focus on identifying candidates for detectable non-Keplerian motion based on sample of 45 well-characterized binaries. We use MultiMoon, a non-Keplerian Bayesian inference tool, to analyze published relative astrometry allowing for non-spherical shapes of each TNB system's primary. We first reproduce the results of previous Keplerian fitting efforts with MultiMoon, which serves as a comparison for the non-Keplerian fits and confirms that these fits are not biased by the assumption of a Keplerian orbit. We unambiguously detect non-Keplerian motion in 8 TNB systems across a range of primary radii, mutual orbit separations, and system masses. As a proof of concept for non-Keplerian fitting, we perform detailed fits for (66652) Borasisi-Pabu, possibly revealing a $J_2 \approx 0.44$, implying Borasisi (and/or Pabu) may be a contact binary or an unresolved compact binary. However, full confirmation of this result will require new observations. This work begins the next generation of TNB analyses that go beyond the point mass assumption to provide unique and valuable information on the physical properties of TNBs with implications for their formation and evolution., Comment: Accepted to AJ

While recent advances in approaches for control of humanoid robot systems show promising results, consideration of fully integrated humanoid systems for solving complex tasks, such as disaster response, has only recently gained focus. In this paper, a software framework for humanoid disaster response robots is introduced. It provides newcomers as well as experienced researchers in humanoid robotics a comprehensive system comprising open source packages for locomotion, manipulation, perception, world modeling, behavior control, and operator interaction. The system uses the Robot Operating System (ROS) as a middleware, which has emerged as a de facto standard in robotics research in recent years. The described architecture and components allow for flexible interaction between operator(s) and robot from teleoperation to remotely supervised autonomous operation while considering bandwidth constraints. The components are self-contained and can be used either in combination with others or standalone. They have been developed and evaluated during participation in the DARPA Robotics Challenge, and their use for different tasks and parts of this competition are described.

Lattice gauge theories (LGTs) can be employed to understand a wide range of phenomena, from elementary particle scattering in high-energy physics to effective descriptions of many-body interactions in materials. Studying dynamical properties of emergent phases can be challenging as it requires solving many-body problems that are generally beyond perturbative limits. We investigate the dynamics of local excitations in a $\mathbb{Z}_2$ LGT using a two-dimensional lattice of superconducting qubits. We first construct a simple variational circuit which prepares low-energy states that have a large overlap with the ground state; then we create particles with local gates and simulate their quantum dynamics via a discretized time evolution. As the effective magnetic field is increased, our measurements show signatures of transitioning from deconfined to confined dynamics. For confined excitations, the magnetic field induces a tension in the string connecting them. Our method allows us to experimentally image string dynamics in a (2+1)D LGT from which we uncover two distinct regimes inside the confining phase: for weak confinement the string fluctuates strongly in the transverse direction, while for strong confinement transverse fluctuations are effectively frozen. In addition, we demonstrate a resonance condition at which dynamical string breaking is facilitated. Our LGT implementation on a quantum processor presents a novel set of techniques for investigating emergent particle and string dynamics.

We present a novel application of a qubit-coupled phonon detector to search for new physics, e.g., ultralight dark matter (DM) and high-frequency gravitational waves. The detector, motivated by recent advances in quantum acoustics, is composed of superconducting transmon qubits coupled to high-overtone bulk acoustic resonators ($h$BARs) and operates in the GHz - 10 GHz frequency range. New physics can excite $O(10 \, \mu \text{eV})$ phonons within the $h$BAR, which are then converted to qubit excitations via a transducer. We detail the design, operation, backgrounds, and expected sensitivity of a prototype detector, as well as a next-generation detector optimized for new physics signals. We find that a future detector can complement current haloscope experiments in the search for both dark photon DM and high-frequency gravitational waves. Lastly we comment on such a detector's ability to operate as a $10 \, \mu\text{eV}$ threshold athermal phonon sensor for sub-GeV DM detection., Comment: 17 pages main text, 8 pages appendices, 5 pages references, 10 Figures

Protein aggregation is involved in many human diseases, but characterizing the sizes and shapes of intermediate oligomers (∼10-100 nm) that are important to the formation of macroscale aggregates like amyloid fibrils is a significant analytical challenge. Here, charge detection mass spectrometry (CDMS) is used to characterize individual conformational states of bovine serum albumin oligomers with up to ∼225 molecules (15 MDa). Elongated, partially folded, and globular conformational families for each oligomer can be readily distinguished based on the extent of charging. The abundances of individual conformers vary with changes in the monomer concentration or by adding aggregation inhibitors, such as SDS, heparin, or MgCl2. These results show the potential of CDMS for investigating intermediate oligomers in protein aggregation processes that are important for understanding aggregate formation and inhibition mechanisms and could accelerate formulation buffer development to prevent the aggregation of biotherapeutics.

Mutualistic interactions between species are widespread and important for community structure and ecosystem function. In a changing environment, the proximate mechanisms that maintain mutualisms affect their stability and susceptibility to perturbation. In ant-plant mutualisms, ants defend their host plants against herbivores or competing plants in exchange for housing or food. While the phenomenon of species exchanging services for resources is well documented, how such arrangements are maintained is not. There are at least four hypothesized mechanisms through which plants use sugar to induce ant defense against herbivores. Three such hypotheses (“deficit”, “fuel for foraging”, “predictable rewards”) predict that the appearance of a new sugar source near the host plant would increase the rate of ant attacks against herbivores, but the fourth hypothesis (“attract and distract”) predicts the opposite. To examine how the mutualism between Triplaris americana and Pseudomyrmex dendroicus would be affected, we simulated the appearance of a novel sugar source at a random half of 34 T. americana trees with P. dendroicus colonies. Compared to control colonies, those with access to the sugar source were less likely to attack herbivorous insects (Nasutitermes sp. termites). Thus, our findings support the “attract and distract” hypothesis. We infer that this ant-plant mutualism could be destabilized by the appearance of an alternative sugar source, such as a nectar-producing plant or honeydew-excreting insect. More broadly, we conclude that the mechanisms responsible for maintaining mutualistic relationships are relevant for understanding how ecological communities are affected by environmental change. Abstract in Spanish is available with online material.

Introduction: Emergency doctors routinely face uncertainty-they work with limited patient information, under tight time constraints and receive minimal post-discharge feedback. While higher uncertainty tolerance (UT) among staff is linked with reduced resource use and improved well-being in various specialties, its impact in emergency settings is underexplored. We aimed to develop a UT measure and assess associations with doctor-related factors (eg, experience), patient outcomes (eg, reattendance) and resource use (eg, episode costs). Methods: From May 2021 to February 2022, emergency doctors (specialty trainee 3 and above) from five Yorkshire (UK) departments completed an online questionnaire. This included a novel UT measure-an adapted Physicians' Reaction to Uncertainty scale collaboratively modified within our team according to Hillen et al's (2017) UT model. The questionnaire also included well-being-related measures (eg, Brief Resilience Scale) and assessed factors like doctors' seniority. Patient encounters involving prespecified 'uncertainty-inducing' problems (eg, headache) were analysed. Multilevel regression explored associations between doctor-level factors, resource use and patient outcomes. Results: 39 doctors were matched with 384 patients. The UT measure demonstrated high reliability (Cronbach's alpha=0.92) and higher UT was significantly associated with better psychological well-being including greater resilience (Pearson's r=0.56; 95% CI=0.30 to 0.74) and lower burnout (eg, Cohen's d=-2.98; -4.62 to -1.33; mean UT difference for 'no' vs 'moderate/high' burnout). UT was not significantly associated with resource use (eg, episode costs: beta=-0.07; -0.32 to 0.18) or patient outcomes including 30-day readmission (eg, OR=0.82; 0.28 to 2.35). Conclusions: We developed a reliable UT measure for emergency medicine. While higher UT was linked to doctor well-being, its impact on resource use and patient outcomes remains unclear. Further measure validation a, CC BY 4.0Correspondence to Dr Luke Budworth; l.w.budworth@leeds.ac.ukThis report is independent research funded by the National Institute for Health and Care Research Yorkshire and Humber Applied Research Collaboration (ARC) (NIHR200166) and the National Institute for Health and Care Research Yorkshire and Humber Patient Safety Research Collaboration (PSRC). The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. ADS is funded by a postdoctoral fellowship from THIS Institute, NIHR (AI_AWARD01864 and COV-LT-0009), UKRI (Horizon Europe Guarantee for DataTools4Heart) and British Heart Foundation Accelerator Award (AA/18/6/24223).

AIMS: The purpose of this study is to evaluate the accuracy and validity of the determination of cause of death (COD) and manner of death (MOD) at the completion of the forensic autopsy prosection. METHODS: We analysed 952 autopsy cases conducted from 2019 to 2020 and compared every patients COD, other significant contributing factors to death (OSC), and MOD after prosection to their COD, OSC and MOD after completion of the final autopsy report. RESULTS: We found that 83% of cases (790 patients) did not have an unexpected change and 17% of cases (162 patients) exhibited a true change in their final diagnosis; the relationship between age and changes in COD and MOD was significant. CONCLUSIONS: Our findings indicate that in the majority of forensic autopsy cases, medical professionals can reasonably complete death certification after the autopsy prosection. In addition to improving the accuracy of COD and MOD, advances in this field will enhance timely decedent affairs management, timely investigations of crimes and timely closure to families who have lost loved ones. We recommend implementing combined interventional education and consultation with expert pathologists, and a well-followed structured method of death classification as the best course of practice.

Aggregation of protein-based therapeutics can occur during development, production, or storage and can lead to loss of efficacy and potential toxicity. Native mass spectrometry of a covalently linked pentameric monoclonal antibody complex with a mass of ∼800 kDa reveals several distinct conformations, smaller complexes, and abundant higher-order aggregates of the pentameric species. Charge detection mass spectrometry (CDMS) reveals individual oligomers up to the pentamer mAb trimer (15 individual mAb molecules; ∼2.4 MDa) whereas intermediate aggregates composed of 6-9 mAb molecules and aggregates larger than the pentameric dimer (1.6 MDa) were not detected/resolved by standard mass spectrometry, size exclusion chromatography (SEC), capillary electrophoresis (CE-SDS), or by mass photometry. Conventional quadrupole time-of-flight mass spectrometry (QTOF MS), mass photometry, SEC, and CE-SDS did not resolve partially or more fully unfolded conformations of each oligomer that were readily identified using CDMS by their significantly higher extents of charging. Trends in the charge-state distributions of individual oligomers provides detailed insight into how the structures of compact and elongated mAb aggregates change as a function of aggregate size. These results demonstrate the advantages of CDMS for obtaining accurate masses and information about the conformations of large antibody aggregates despite extensive overlapping m/z values. These results open up the ability to investigate structural changes that occur in small, soluble oligomers during the earliest stages of aggregation for antibodies or other proteins.

This dataset contains photographs, thermogravimetric analysis (TGA) profiles, Fourier transform infrared (FTIR) spectra, and nuclear magnetic resonance (NMR) spectra of samples of poly(styrene sulfonate), poly(diallyldimethylammonium), potassium bromide, and water reported in the authors' manuscript "Segregative Phase Separation of Strong Polyelectrolyte Complexes at High Salt and High Polymer Concentrations."

This dataset contains thermogravimetric analysis (TGA) profiles, turbidity data, and nuclear magnetic resonance (NMR) spectra of samples of poly(styrene sulfonate), poly(diallyldimethylammonium), and poly(2-acrylamido-2-methyl-1-propanesulfonic acid) prepared with lithium bromide, sodium bromide, and/or potassium bromide, and water, reported in the authors' manuscript "Effect of Cation-pi Interactions on the Phase Behavior and Viscoelastic Properties of Polyelectrolyte Complexes."

In “Racial Prejudice and Friction,” John Dewey writes: “Too often we try to discuss race prejudice morally before we have dealt with it scientifically. That is, we justify or condemn it before we understand it.” Dewey’s remark applies well to contemporary work on the epistemology of prejudiced belief, in which there are dueling tendencies either to condemn or to justify these beliefs without sufficient care. In this dissertation, I chart a middle path between these extremes. I first critique Amia Srinivasan’s radical epistemology, according to which judgments about the epistemic status of morally and politically problematic beliefs should be guided by considerations of moral and political utility. I argue instead that we must uphold the priority of the epistemic, keeping separate epistemic evaluations of problematic beliefs and concerns about the utility of our epistemological judgments. I then examine the role of testimony in the formation of prejudiced belief. I defend testimonial reductionism, which holds that hearers must have sufficient positive reasons to regard speakers as trustworthy in order to be justified in believing what they say. I then argue that while prejudiced testimonial beliefs can be epistemically justified, this is true most often when these beliefs are formed in highly isolated and evidentially impoverished environments. Most prejudiced agents in societies like our own, however, are not in such dire epistemic straits. So, although perhaps not all prejudiced beliefs are epistemically unjustified, there is prima facie reason to regard such beliefs with suspicion. Finally, I discuss prejudiced beliefs based on biased perceptual experiences, disputing Susanna Siegel’s position that biased experiences can be irrational and, when they are, this irrationality transmits to beliefs formed on their basis. Drawing on Anil Gupta’s Conscious Experience, I present a coherentist account on which the epistemic status of an agent’s perceptual beliefs depends o

Introduction: Emergency doctors routinely face uncertainty-they work with limited patient information, under tight time constraints and receive minimal post-discharge feedback. While higher uncertainty tolerance (UT) among staff is linked with reduced resource use and improved well-being in various specialties, its impact in emergency settings is underexplored. We aimed to develop a UT measure and assess associations with doctor-related factors (eg, experience), patient outcomes (eg, reattendance) and resource use (eg, episode costs). Methods: From May 2021 to February 2022, emergency doctors (specialty trainee 3 and above) from five Yorkshire (UK) departments completed an online questionnaire. This included a novel UT measure-an adapted Physicians' Reaction to Uncertainty scale collaboratively modified within our team according to Hillen et al's (2017) UT model. The questionnaire also included well-being-related measures (eg, Brief Resilience Scale) and assessed factors like doctors' seniority. Patient encounters involving prespecified 'uncertainty-inducing' problems (eg, headache) were analysed. Multilevel regression explored associations between doctor-level factors, resource use and patient outcomes. Results: 39 doctors were matched with 384 patients. The UT measure demonstrated high reliability (Cronbach's alpha=0.92) and higher UT was significantly associated with better psychological well-being including greater resilience (Pearson's r=0.56; 95% CI=0.30 to 0.74) and lower burnout (eg, Cohen's d=-2.98; -4.62 to -1.33; mean UT difference for 'no' vs 'moderate/high' burnout). UT was not significantly associated with resource use (eg, episode costs: beta=-0.07; -0.32 to 0.18) or patient outcomes including 30-day readmission (eg, OR=0.82; 0.28 to 2.35). Conclusions: We developed a reliable UT measure for emergency medicine. While higher UT was linked to doctor well-being, its impact on resource use and patient outcomes remains unclear. Further measure validation a, CC BY 4.0Correspondence to Dr Luke Budworth; l.w.budworth@leeds.ac.ukThis report is independent research funded by the National Institute for Health and Care Research Yorkshire and Humber Applied Research Collaboration (ARC) (NIHR200166) and the National Institute for Health and Care Research Yorkshire and Humber Patient Safety Research Collaboration (PSRC). The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. ADS is funded by a postdoctoral fellowship from THIS Institute, NIHR (AI_AWARD01864 and COV-LT-0009), UKRI (Horizon Europe Guarantee for DataTools4Heart) and British Heart Foundation Accelerator Award (AA/18/6/24223).

Introduction: Emergency doctors routinely face uncertainty-they work with limited patient information, under tight time constraints and receive minimal post-discharge feedback. While higher uncertainty tolerance (UT) among staff is linked with reduced resource use and improved well-being in various specialties, its impact in emergency settings is underexplored. We aimed to develop a UT measure and assess associations with doctor-related factors (eg, experience), patient outcomes (eg, reattendance) and resource use (eg, episode costs). Methods: From May 2021 to February 2022, emergency doctors (specialty trainee 3 and above) from five Yorkshire (UK) departments completed an online questionnaire. This included a novel UT measure-an adapted Physicians' Reaction to Uncertainty scale collaboratively modified within our team according to Hillen et al's (2017) UT model. The questionnaire also included well-being-related measures (eg, Brief Resilience Scale) and assessed factors like doctors' seniority. Patient encounters involving prespecified 'uncertainty-inducing' problems (eg, headache) were analysed. Multilevel regression explored associations between doctor-level factors, resource use and patient outcomes. Results: 39 doctors were matched with 384 patients. The UT measure demonstrated high reliability (Cronbach's alpha=0.92) and higher UT was significantly associated with better psychological well-being including greater resilience (Pearson's r=0.56; 95% CI=0.30 to 0.74) and lower burnout (eg, Cohen's d=-2.98; -4.62 to -1.33; mean UT difference for 'no' vs 'moderate/high' burnout). UT was not significantly associated with resource use (eg, episode costs: beta=-0.07; -0.32 to 0.18) or patient outcomes including 30-day readmission (eg, OR=0.82; 0.28 to 2.35). Conclusions: We developed a reliable UT measure for emergency medicine. While higher UT was linked to doctor well-being, its impact on resource use and patient outcomes remains unclear. Further measure validation a, CC BY 4.0Correspondence to Dr Luke Budworth; l.w.budworth@leeds.ac.ukThis report is independent research funded by the National Institute for Health and Care Research Yorkshire and Humber Applied Research Collaboration (ARC) (NIHR200166) and the National Institute for Health and Care Research Yorkshire and Humber Patient Safety Research Collaboration (PSRC). The views expressed in this publication are those of the author(s) and not necessarily those of the National Institute for Health Research or the Department of Health and Social Care. ADS is funded by a postdoctoral fellowship from THIS Institute, NIHR (AI_AWARD01864 and COV-LT-0009), UKRI (Horizon Europe Guarantee for DataTools4Heart) and British Heart Foundation Accelerator Award (AA/18/6/24223).

Nina Hein,1 Conner Callaway,2 Devin Ford,2 John C Carlson1 1Ochsner Health System, Department of Allergy and Clinical Immunology, New Orleans, LA, USA; 2Tulane University, School of Medicine, New Orleans, LA, USACorrespondence: John C Carlson, Department of Pediatrics, Ochsner Health System, 1315 Jefferson Hwy, New Orleans, LA, 20121, USA, Tel +1-504-842-3900, Fax +1-504-842-5848, Email john.carlson@ochsner.org

Nanoporous gold (np-Au) has found its use in applications ranging from catalysis to biosensing, where pore morphology plays a critical role in performance. While the morphology evolution of bulk np-Au has been widely studied, knowledge about its thin-film form is limited. This work hypothesizes that the mechanical compliance of the thin film substrate can play a critical role in the morphology evolution. Via experimental and finite-element-analysis approaches, we investigate the morphological variation in np-Au thin films deposited on compliant silicone (PDMS) substrates of a range of thicknesses anchored on rigid glass supports and compare those to the morphology of np-Au deposited on glass. More macroscopic (10 s to 100 s of microns) cracks and discrete islands form in the np-Au films on PDMS compared to on glass. Conversely, uniformly distributed microscopic (100 s of nanometers) cracks form in greater numbers in the np-Au films on glass than those on PDMS, with the cracks located within the discrete islands. The np-Au films on glass also show larger ligament and pore sizes, possibly due to higher residual stresses compared to the np-Au/PDMS films. The effective elastic modulus of the substrate layers decreases with increasing PDMS thickness, resulting in secondary np-Au morphology effects, including a reduction in macroscopic crack-to-crack distance, an increase in microscopic crack coverage, and a widening of the microscopic cracks. However, changes in the ligament/pore widths with PDMS thickness are negligible, allowing for independent optimization for cracking. We expect these results to inform the integration of functional np-Au films on compliant substrates into emerging applications, including flexible electronics.

In group-living species, reproductive variation among individuals of the same sex is widespread. By identifying the mechanisms underlying this reproductive skew, we gain fundamental insights into the evolution and maintenance of sociality. A common mechanism, social control, is typically studied by quantifying dominance, which is one of many attributes of sociality that describes how individuals exert influence on others and is an incomprehensive measure of social control as it accounts only for direct relationships. Here, we use the global reaching centrality (GRC), which quantifies the degree of hierarchy in a social network by accounting for both direct and indirect social relationships. Using a wild, free-living population of adult female yellow-bellied marmots (Marmota flaviventris), we found a positive relationship between the reproductive skew index and GRC: more despotic social groups have higher reproductive skew. The GRC was stronger predictor for skew than traditional measures of social control (i.e. dominance). This allows deeper insights into the diverse ways individuals control other group members reproduction, a core component in the evolution of sociality. Future studies of skew across taxa may profit by using more comprehensive, network-based measures of social control.

Image-based deformation estimation is an important tool used in a variety of engineering problems, including crack propagation, fracture, and fatigue failure. These tools have been important in biomechanics research where measuring in vitro and in vivo tissue deformations are important for evaluating tissue health and disease progression. However, accurately measuring tissue deformation in vivo is particularly challenging due to limited image signal-to-noise ratio. Therefore, we created a novel deep-learning approach for measuring deformation from a sequence of images collected in vivo called StrainNet. Utilizing a training dataset that incorporates image artifacts, StrainNet was designed to maximize performance in challenging, in vivo settings. Artificially generated image sequences of human flexor tendons undergoing known deformations were used to compare benchmark StrainNet against two conventional image-based strain measurement techniques. StrainNet outperformed the traditional techniques by nearly 90%. High-frequency ultrasound imaging was then used to acquire images of the flexor tendons engaged during contraction. Only StrainNet was able to track tissue deformations under the in vivo test conditions. Findings revealed strong correlations between tendon deformation and applied forces, highlighting the potential for StrainNet to be a valuable tool for assessing rehabilitation strategies or disease progression. Additionally, by using real-world data to train our model, StrainNet was able to generalize and reveal important relationships between the effort exerted by the participant and tendon mechanics. Overall, StrainNet demonstrated the effectiveness of using deep learning for image-based strain analysis in vivo.

The sulfur over calcium ratio (S/Ca) in foraminiferal shells was recently proposed as a new and independent proxy for reconstructing marine inorganic carbon chemistry. This new approach assumes that sulfur is incorporated into CaCO3 predominantly in the form of sulfate (SO42−) through lattice substitution for carbonate ions (CO32–), and that S/Ca thus reflects seawater [CO32–]. Although foraminiferal growth experiments validated this approach, field studies showed controversial results suggesting that the potential impact of [CO32–] may be overwritten by one or more parameters. Hence, to better understand the inorganic processes involved, we here investigate S/Ca values in inorganically precipitated CaCO3 (S/Ca(cc)) grown in solutions of CaCl2 − Na2CO3 − Na2SO4 − B(OH)3 − MgCl2. Experimental results indicate the dependence of sulfate partitioning in CaCO3 on the carbon chemistry via changing pH and suggest that faster precipitation rates increase the partition coefficient for sulfur. The S/Ca ratios of our inorganic calcite samples show positive correlation with modelled [CaSO40](aq), but not with the concentration of free SO42− ions. This challenges the traditional model for sulfate incorporation in calcite and implies that the uptake of sulfate potentially occurs via ion-ion pairs rather than being incorporated as single anions. Based on the [Ca2+] dependence via speciation, we here suggest a critical evaluation of this potential proxy. As sulfate complexation seems to control sulfate uptake in inorganic calcite, application as a proxy using foraminiferal calcite may be limited to periods for which seawater chemistry is well-constrained. As foraminiferal calcite growth is modulated by inward

The Theory of Planned Behavior (TPB) is a highly influential and powerful behavior change model that offers promising guidance on promoting urgently needed, pro-environmental action. Recent pro-environmental research has successfully augmented TPB using anticipated emotions-the emotions an individual consciously predicts they will experience in relation to possible outcomes of their decision. However, immediate emotions-the emotions an individual actually experiences during decision-making-have received far less attention. Given that immediate emotions are relevant to pro-environmental decision-making and can address the theoretical and empirical limitations of TPB, we contend that pro-environmental studies should explicitly examine immediate emotions within the TPB framework. This article aims to stimulate rigorous research that enhances pro-environmental communication and policymaking by providing integrative insights into immediate emotions along with recommendations for evaluating immediate emotions in a pro-environmental TPB context.

The Theory of Planned Behavior (TPB) is a highly influential and powerful behavior change model that offers promising guidance on promoting urgently needed, pro-environmental action. Recent pro-environmental research has successfully augmented TPB using anticipated emotions-the emotions an individual consciously predicts they will experience in relation to possible outcomes of their decision. However, immediate emotions-the emotions an individual actually experiences during decision-making-have received far less attention. Given that immediate emotions are relevant to pro-environmental decision-making and can address the theoretical and empirical limitations of TPB, we contend that pro-environmental studies should explicitly examine immediate emotions within the TPB framework. This article aims to stimulate rigorous research that enhances pro-environmental communication and policymaking by providing integrative insights into immediate emotions along with recommendations for evaluating immediate emotions in a pro-environmental TPB context.

Sub-Saharan Africa has fewer medical workers per capita than any region of the world, and that shortage has been highlighted consistently as a critical constraint to improving health outcomes in the region. This paper draws on newly available, systematic, comparable data from 10 countries in the region to explore the dimensions of this shortage. We find wide variation in human resources performance metrics, both within and across countries. Many facilities are barely staffed, and effective staffing levels fall further when adjusted for health worker absences. However, caseloads—while also varying widely within and across countries—are also low in many settings, suggesting that even within countries, deployment rather than shortages, together with barriers to demand, may be the principal challenges. Beyond raw numbers, we observe significant proportions of health workers with very low levels of clinical knowledge on standard maternal and child health conditions. This study highlights that countries may need to invest broadly in health workforce deployment, improvements in capacity and performance of the health workforce, and on addressing demand constraints, rather than focusing narrowly on increases in staffing numbers.

The Theory of Planned Behavior (TPB) is a highly influential and powerful behavior change model that offers promising guidance on promoting urgently needed, pro-environmental action. Recent pro-environmental research has successfully augmented TPB using anticipated emotions-the emotions an individual consciously predicts they will experience in relation to possible outcomes of their decision. However, immediate emotions-the emotions an individual actually experiences during decision-making-have received far less attention. Given that immediate emotions are relevant to pro-environmental decision-making and can address the theoretical and empirical limitations of TPB, we contend that pro-environmental studies should explicitly examine immediate emotions within the TPB framework. This article aims to stimulate rigorous research that enhances pro-environmental communication and policymaking by providing integrative insights into immediate emotions along with recommendations for evaluating immediate emotions in a pro-environmental TPB context.

The purpose of this action research project is to design, execute, and evaluate a small group instructional framework that cultivates a missional culture focused on communal discipleship at MVMNT Church, a local church in the Association of Related Churches network, while also addressing a gap in scholarship surrounding the interrelation of discipleship and the missional church. Using a mixed-methods approach, this study leveraged inductive thematic analysis of semi-structured interviews with survey data to validate the lack of discipleship activity at MVMNT Church and moderate-to-low comprehension of topics related to mission, discipleship, and leadership in the church. This project recommended and directed an intervention consisting of an instructional program that targeted seven members of MVMNT Church in formal and informal church leadership to cultivate an environment for learning, knowledge-sharing, and mutual edification in discipleship to address the problem. Longitudinal analysis of survey data collected post-intervention demonstrates the success of the instructional framework in improving comprehension of these topics and the effective catalysis of discipleship. This project proposes an instructional framework bridging the gap between mission and discipleship scholarship, with the potential to improve missional discipleship cultures in many other similar church environments. The project processed the generalizability and transferability of this research and areas warranting more in-depth study.

The Theory of Planned Behavior (TPB) is a highly influential and powerful behavior change model that offers promising guidance on promoting urgently needed, pro-environmental action. Recent pro-environmental research has successfully augmented TPB using anticipated emotions-the emotions an individual consciously predicts they will experience in relation to possible outcomes of their decision. However, immediate emotions-the emotions an individual actually experiences during decision-making-have received far less attention. Given that immediate emotions are relevant to pro-environmental decision-making and can address the theoretical and empirical limitations of TPB, we contend that pro-environmental studies should explicitly examine immediate emotions within the TPB framework. This article aims to stimulate rigorous research that enhances pro-environmental communication and policymaking by providing integrative insights into immediate emotions along with recommendations for evaluating immediate emotions in a pro-environmental TPB context.

While recent advances in approaches for control of humanoid robot systems show promising results, consideration of fully integrated humanoid systems for solving complex tasks, such as disaster response, has only recently gained focus. In this paper, a software framework for humanoid disaster response robots is introduced. It provides newcomers as well as experienced researchers in humanoid robotics a comprehensive system comprising open source packages for locomotion, manipulation, perception, world modeling, behavior control, and operator interaction. The system uses the Robot Operating System (ROS) as a middleware, which has emerged as a de facto standard in robotics research in recent years. The described architecture and components allow for flexible interaction between operator(s) and robot from teleoperation to remotely supervised autonomous operation while considering bandwidth constraints. The components are self-contained and can be used either in combination with others or standalone. They have been developed and evaluated during participation in the DARPA Robotics Challenge, and their use for different tasks and parts of this competition are described.

Introduction: Strong and ever-growing evidence highlights the effectiveness of recovery housing in supporting and sustaining substance use disorder (SUD) recovery, especially when augmented by intensive support that includes assertive linkages to community services. This study aims to evaluate a pilot intensive recovery support (IRS) intervention for individuals (n=175) entering certified Level II and III recovery residences. These individuals met at least three out of five conditions (no health insurance; no driving license; substance use in the last 14 days; current unemployment; possession of less than $75 capital). The study assesses the impact of the IRS on engagement, retention, and changes in recovery capital, compared to the business-as-usual Standard Recovery Support (SRS) approach (n=1,758). Methods: The study employed quasi-experimental techniques to create weighted and balanced counterfactual groups. These groups, derived from the Recovery Capital (REC-CAP) assessment tool, enabled comparison of outcomes between people receiving IRS and those undergoing SRS. Results: After reweighting for resident demographics, service needs, and barriers to recovery, those receiving IRS exhibited improved retention rates, reduced likelihood of disengagement, and growth in recovery capital after living in the residence for 6-9 months. Conclusion: The results from this pilot intervention indicate that intensive recovery support, which integrates assertive community linkages and enhanced recovery coaching, outperforms a balanced counterfactual group in engagement, length of stay, and recovery capital growth. We suggest that this model may be particularly beneficial to those entering Level II and Level III recovery housing with lower levels of recovery capital at admission.

[18F]FDG PET/CT and [68Ga]Ga-DOTATATE PET/CT are both used to predict tumor biology in neuroendocrine neoplasms. Although the presence of discordant ([18F]FDG-avid/non–[68Ga]Ga-DOTATATE–avid) disease predicts poor prognosis, the significance of the volume of such discordant disease remains undetermined. The aim of this study is to investigate discordant tumor volume as a potential biomarker in patients with advanced gastroenteropancreatic neuroendocrine neoplasms (GEPNENs). Methods: A multicenter retrospective study in patients with advanced GEPNENs and paired [18F]FDG and [68Ga]Ga-DOTATATE PET/CT no more than 85 d apart was conducted. Patients with discordant disease were identified by the NETPET score, and discordant lesions were contoured with a flat [18F]FDG SUV cutoff of 4. The primary variable of interest was the total discordant volume (TDV), which was the sum of the volumes of discordant lesions. Patients were dichotomized into high- and low-TDV cohorts by the median value. The primary endpoint was overall survival. Results: In total, 44 patients were included (50% men; median age, 60 y), with primary cancers in the pancreas (45%), small bowel (23%), colon (20%), and other (12%). Of the patients, 5% had grade 1 disease, 48% had grade 2 disease, and 48% had grade 3 disease (24% well differentiated, 67% poorly differentiated, 10% unknown within the grade 3 cohort). The overall median survival was 14.1 mo. Overall survival was longer in the low-TDV cohort than in the high-TDV cohort (median volume, 43.7 cm3; survival time, 23.8 mo vs. 9.4 mo; hazard ratio, 0.466 [95% CI, 0.229–0.948]; P 5 0.0221). Patients with no more than 2 discordant intrahepatic lesions survived longer than those with 2 or more lesions (31.8 mo vs. 10.2 mo, respectively; hazard ratio, 0.389 [95% CI, 0.194–0.779]; P 5 0.0049). Conclusion: TDV is a potential prognostic biomarker in GEPNENs and should be investigated in future neuroendocrine neoplasm trials., SCOPUS: ar.j, info:eu-repo/semantics/published

Background: The European Reference Network for rare Inherited Congenital Anomalies, ERNICA, guidelines for gastroschisis cover perinatal period to help teams to improve care. Method: A systematic literature search including 136 publications was conducted. Research findings were assessed following the GRADE methodology. The evidence to decision framework was used to determine the strength and direction of recommendations. Results: The mode or timing of delivery do not impact neonatal mortality, risk of NEC or time on parenteral nutrition (PN). Intra or extra abdominal bowel dilatation predict complex gastroschisis and longer length of hospital stay but not increased perinatal mortality. Outcomes after Bianchi procedure and primary fascia closure under anesthesia are similar. Sutureless closure decreases the rate of surgical site infections and duration of ventilation compared to surgical closure. Silo-staged closure with or without intubation results in similar outcomes. Outcomes of complex gastroschisis (CG) undergoing early or delayed surgical repair are similar. Early enteral feeds starting within 14 days is associated with lower risk of surgical site infection. Recommendations: The panel suggests vaginal birth between 37 and 39 w in cases of uncomplicated gastroschisis. Bianchi’s approach is an option in simple gastroschisis. Sutureless closure is suggested when general anesthesia can be avoided, sutured closure. If anesthesia is required. Silo treatment without ventilation and general anesthesia can be considered. In CG with atresia primary intestinal repair can be attempted if the condition of patient and intestine allows. Enteral feeds for simple gastroschisis should start within 14 days.

The Theory of Planned Behavior (TPB) is a highly influential and powerful behavior change model that offers promising guidance on promoting urgently needed, pro-environmental action. Recent pro-environmental research has successfully augmented TPB using anticipated emotions-the emotions an individual consciously predicts they will experience in relation to possible outcomes of their decision. However, immediate emotions-the emotions an individual actually experiences during decision-making-have received far less attention. Given that immediate emotions are relevant to pro-environmental decision-making and can address the theoretical and empirical limitations of TPB, we contend that pro-environmental studies should explicitly examine immediate emotions within the TPB framework. This article aims to stimulate rigorous research that enhances pro-environmental communication and policymaking by providing integrative insights into immediate emotions along with recommendations for evaluating immediate emotions in a pro-environmental TPB context.

This study determined consumers' attitudes towards physical and mental wellness related to red meat consumption and their willingness to pay (WTP) more for the meat. In 2019, two online surveys of red meat eaters were conducted in the USA (n = 1000) and Australia (n = 523) using commercial platforms. Results showed that over 90% of respondents indicated interest in purchasing red meat to improve their wellness status. Additionally, about 85% indicated their WTP more for red meat for its wellness benefits, with Americans indicating stronger willingness than Australian respondents. The potential of meat consumption to improve overall wellness among red meat eaters was a dominant factor influencing consumers' WTP more. Other factors that increased WTP included frequency of meat consumption, physical exercise, sleep quality, number of children in a household, partnership status, and economic position. Outcomes from this study highlight a unique opportunity for the meat industry to position meat on its qualities that include wellness improvement if backed up with robust scientific evidence., This research was co-funded by Meat & Livestock Australia Donor Company and AgResearch Ltd. Strategic Science Investment Fund, SSIF-A25692 (Consumer Experience: Delivering Customized Food Attributes), Postprint (updated version)

Rocketry has been around for a long time now, however, very few advances have been made. A typical model rocket launch takes between 10 and 60 seconds to reach max altitude. After this, a parachute is ejected from the nose cone and the rocket blows in the wind until landing. The higher the rocket flies, the farther it will land. For the smallest model rockets, this may involve a short walk across a field, however, for larger rockets, it may involve a long search and even loss of the rocket entirely. This project will design a rocket that can safely return to a predetermined location. Having the ability to land the rocket where it started would allow the user to not have to walk to retrieve the rocket. The engineering solution is simply to attach a deployable quad-copter to a rocket that will be used to fly the rocket back to the launchpad after the rocket achieves maximum altitude. This would be achieved via a pilot from the Unmanned Aerial Systems (UAS) club that will fly the rocket to the landing zone. The design consists of four carbon fiber arms attached to the main fuselage of the rocket with motors and propellors on the end of each arm. This will allow for the rocket to be controlled from its peak to the ground, demonstrating the feasibility of the design to develop into a larger project in the future.

Multi-view stereo omnidirectional distance estimation usually needs to build a cost volume with many hypothetical distance candidates. The cost volume building process is often computationally heavy considering the limited resources a mobile robot has. We propose a new geometry-informed way of distance candidates selection method which enables the use of a very small number of candidates and reduces the computational cost. We demonstrate the use of the geometry-informed candidates in a set of model variants. We find that by adjusting the candidates during robot deployment, our geometry-informed distance candidates also improve a pre-trained model's accuracy if the extrinsics or the number of cameras changes. Without any re-training or fine-tuning, our models outperform models trained with evenly distributed distance candidates. Models are also released as hardware-accelerated versions with a new dedicated large-scale dataset. The project page, code, and dataset can be found at https://theairlab.org/gicandidates/ .

The sizes and shapes of nanoparticles play a critical role in their chemical and material properties. Common sizing methods based on light scattering or mobility lack individual particle specificity, and microscopy-based methods often require cumbersome sample preparation and image analysis. A promising alternative method for the rapid and accurate characterization of nanoparticle size is charge detection mass spectrometry (CDMS), an emerging technique that measures the masses of individual ions. A recently constructed CDMS instrument designed specifically for high acquisition speed, efficiency, and accuracy is described. This instrument does not rely on an ion energy filter or estimates of ion energy that have been previously required for mass determination, but instead uses direct, in situ measurements. A standardized sample of ∼100 nm diameter polystyrene nanoparticles and ∼50 nm polystyrene nanoparticles with amine-functionalized surfaces are characterized using CDMS and transmission electron microscopy (TEM). Individual nanoparticle masses measured by CDMS are transformed to diameters, and these size distributions are in close agreement with distributions measured by TEM. CDMS analysis also reveals dimerization of ∼100 nm nanoparticles in solution that cannot be determined by TEM due to the tendency of nanoparticles to agglomerate when dried onto a surface. Comparing the acquisition and analysis times of CDMS and TEM shows particle sizing rates up to ∼80× faster are possible using CDMS, even when samples ∼50× more dilute were used. The combination of both high-accuracy individual nanoparticle measurements and fast acquisition rates by CDMS represents an important advance in nanoparticle analysis capabilities.

Ion-ion interactions in charge detection mass spectrometers that use electrostatic traps to measure masses of individual ions have not been reported previously, although ion trajectory simulations have shown that these types of interactions affect ion energies and thereby degrade measurement performance. Here, examples of interactions between simultaneously trapped ions that have masses ranging from ca. 2 to 350 MDa and ca. 100 to 1000 charges are studied in detail using a dynamic measurement method that makes it possible to track the evolution of the mass, charge, and energy of individual ions over their trapping lifetimes. Signals from ions that have similar oscillation frequencies can have overlapping spectral leakage artifacts that result in slightly increased uncertainties in the mass determination, but these effects can be mitigated by the careful choice of parameters used in the short-time Fourier transform analysis. Energy transfers between physically interacting ions are also observed and quantified with individual ion energy measurement resolution as high as ∼950. The mass and charge of interacting ions do not change, and their corresponding measurement uncertainties are equivalent to ions that do not undergo physical interactions. Simultaneous trapping of multiple ions in CDMS can greatly decrease the acquisition time necessary to accumulate a statistically meaningful number of individual ion measurements. These results demonstrate that while ion-ion interactions can occur when multiple ions are trapped, they have negligible effects on mass accuracy when using the dynamic measurement method.

For social animals, group social structure has important consequences for disease and information spread. While prior studies showed individual connectedness within a group has fitness consequences, less is known about the fitness consequences of group social structure for the individuals who comprise the group. Using a long-term dataset on a wild population of facultatively social yellow-bellied marmots (Marmota flaviventer), we showed social structure had largely no relationship with survival, suggesting consequences of individual social phenotypes may not scale to the group social phenotype. An observed relationship for winter survival suggests a potentially contrasting direction of selection between the group and previous research on the individual level; less social individuals, but individuals in more social groups experience greater winter survival. This work provides valuable insights into evolutionary implications across social phenotypic scales.

Marine Protected Areas (MPAs) have been implemented worldwide as a tool for improving the overall health and function of fisheries and marine ecosystems impacted by fishing activity. Monitoring the performance of MPAs in a comprehensive way is crucial for the effective management and thoughtful implementation of new MPAs. In California, mesophotic (30-100m) rocky reef fish communities are a valuable commercial/recreational resource, though the effects of MPAs on this community remain relatively understudied. This is at least partially a result of depth restricted sampling tools that do not typically overlap; SCUBA surveys are generally limited to shallow depths (<30 m) and Remotely Operated Vehicle/Autonomous Underwater Vehicle surveys are often used for deep water (>100m). Additionally, traditional extractive techniques like trawl surveys are limited by their inability to effectively sample high relief rocky habitats, and are not commonly used in MPAs due to their destructive nature. With this study we tested the effects of two MPAs on demersal fish communities living on mesophotic rocky reefs utilizing Baited Remove Underwater Video (BRUV) surveys. We deployed BRUV landers annually from 2019 to 2021 at Anacapa State Marine Reserve/State Marine Conservation Area (SMR/SMCA) and Carrington Pt. SMR. We observed significant positive reserve effects on the total biomass of targeted (i.e., fished) species and on the size structure of individual focal species at both study sites. Relative abundance (MaxN) proved to be a less sensitive metric than biomass for detecting MPA effects, underscoring the utility of a stereo-video camera system that is capable of capturing highly accurate fish measurements. Dissimilar rocky habitat abundance for the deepest depth zones at Anacapa Island, where rockfish (Sebastes spp.) represent the largest proportion of the fish community, is likely one explanation for the negative reserve effect we observed for targeted rockfish abundance

While various forms of artificial intelligence tools and applications have been in development for many years, it is the recent deployment of large language models (LLMs, also referred to here at "advanced AI"), such as OpenAI's ChatGPT, that has sparked both global interest and concern. Although advanced AI has recently captured public attention, other forms of AI—already in use in government and industry—also raise concerns due to their potential to inflict harm. The policy issues and recommendations below apply to currently available automated systems—with special consideration of LLM-based AI applications—and with an eye to other forms of advanced AI on the horizon.President Joe Biden should address the challenges and opportunities of AI with an immediate executive order to implement the Blueprint for an AI Bill of Rights and establish other safeguards to ensure automated systems deliver on their promise to improve lives, expand opportunity, and spur discovery.

The morphological evolution of nanoporous gold is generally believed to be governed by surface diffusion. This work specifically explores the dependence of mass transport by surface diffusion on the curvature of a gold surface. The surface diffusivity is estimated by molecular dynamics simulations for a variety of surfaces of constant mean curvature, eliminating any chemical potential gradients and allowing the possible dependence of the surface diffusivity on mean curvature to be isolated. The apparent surface diffusivity is found to have an activation energy of ∼0.74 eV with a weak dependence on curvature, but is consistent with the values reported in the literature. The apparent concentration of mobile surface atoms is found to be highly variable, having an Arrhenius dependence on temperature with an activation energy that also has a weak curvature dependence. These activation energies depend on curvature in such a way that the rate of mass transport by surface diffusion is nearly independent of curvature, but with a higher activation energy of ∼1.01 eV. The curvature dependencies of the apparent surface diffusivity and concentration of mobile surface atoms is believed to be related to the expected lifetime of a mobile surface atom, and has the practical consequence that a simulation study that does not account for this finite lifetime could underestimate the activation energy for mass transport via surface diffusion by ∼0.27 eV.

The extent the evolution of sociality was shaped by multilevel selection – a theoretical framework for natural selection occurring at levels of biological organization other than the gene – is a classic debate in biology. Though common examples are focused on social behavior, we do not know if multilevel selection significantly acts on social behavioral phenotypes in the wild. For multilevel selection to contribute to evolution, social phenotypes must be variable, replicable, and have unique fitness consequences from two or more discrete levels (e.g., the individual and the group). While the individual fitness consequences of the individual social phenotype (e.g., how connected or social an individual is) have been demonstrated, the individual fitness consequences of the group’s social phenotype (e.g., the structure and pattern of all social interactions in the group) for each individual who lives in the group is largely unknown. Here I quantify individual fitness consequences of the group social phenotype, providing evidence that the individual and group social phenotypes are discrete and quantifiable levels of biological organization. Chapters 2 and 3 show how residing in more connected social groups is associated with decreased individual reproductive success but increased individual winter survival in a wild, free-living population yellow-bellied marmots (Marmota flaviventer), a harem polygynous, facultatively social, hibernating rodent with variable and genetically heritable social behaviors. Not only does the type of group an individual resides in have fitness consequences for those individuals, but the fitness consequences of the group social phenotype are different than those of the individual social phenotype (e.g., less social individuals in more connected groups experience higher winter survival). Thus, chapter 3 quantifies the independent contributions of the individual and group social phenotypes to individual fitness by exploring the two phenotypes tog

People in economically advantaged nations tend to evaluate their life as more positive overall and report greater well-being than people in less advantaged nations. But how does positivity manifest in the daily life experiences of individuals around the world? The present study asked 15,244 college students from 62 nations, in 42 languages, to describe a situation they experienced the previous day using the Riverside Situational Q-sort (RSQ). Using expert ratings, the overall positivity of each situation was calculated for both nations and individuals. The positivity of the average situation in each nation was strongly related to the economic development of the nation as measured by the Human Development Index (HDI). For individuals’ daily experiences, the economic status of their nation also predicted the positivity of their experience, even more than their family socioeconomic status. Further analyses revealed the specific characteristics of the average situations for higher HDI nations that make their experiences more positive. Higher HDI was associated with situational experiences involving humor, socializing with others, and the potential to express emotions and fantasies. Lower HDI was associated with an increase in the presence of threats, blame, and hostility, as well as situational experiences consisting of family, religion, and money. Despite the increase in a few negative situational characteristics in lower HDI countries, the overall average experience still ranged from neutral to slightly positive, rather than negative, suggesting that greater HDI may not necessarily increase positive experiences but rather decrease negative experiences. The results illustrate how national economic status influences the lives of individuals even within a single instance of daily life, with large and powerful consequences when accumulated across individuals within each nation.

Optical systems are often comprised of modular arrangements of components, and the improvement of these systems has historically leaned on the precise manufacturing and alignment of the comprising elements. This provides an intuitive pathway to optical design, but ultimately yields systems that are far bulkier than required by the laws of physics. It is often the case that the required degrees of freedom to achieve complex tasks is present within dielectric volumes that are only several wavelengths per side, and these degrees of freedom can be accessed by patterning the dielectric volume with subwavelength resolution. Even in such small volumes, all of the fundamental properties of light (wavelength, polarization, k-vector) can be controlled which opens the possibility for extremely multifunctional, compact image sensor elements. The determination of the refractive index distribution of these devices has historically been a challenging inverse-design problem, and the fabrication of 3D dielectric devices is a challenge unique to different regimes of the electromagnetic spectrum. This thesis utilizes current state-of-the-art optimization techniques to design multifunctional volumetric devices, and theoretically expands upon the techniques to facilitate the optimization of high index contrast structures. Multiple microwave prototypes are measured, devices operating at terahertz frequencies are fabricated using silicon micromachining, and optical devices with resolutions achievable with CMOS processing techniques are studied for next-generation camera sensors.

Enzyme function is ubiquitous in living organisms. Assays and biomarkers utilizing enzyme activity have become a pillar of chemical biology with relevance to the discovery of new biology, clinical diagnostics, and streamlining research and industrial pipelines. This thesis project seeks to develop assays and probes harnessing enzyme activity to expand the current repertoire of biomarkers and inhibitory drugs.Chapter1 describes restricted interaction peptides (RIPs) as a platform technology for tracking protease activity in vivo in real time. We show the proof of concept for this, as we harness the catalytic activity of proteases for tracking various biological events and disease states. This chapter evinces the most characterized and furthest along adaptation of the RIP technology, tracking immune activation via imaging with positron emission tomography (PET) by harnessing granzyme B (GZMB) catalysis Chapter 2 continues the concept of harnessing enzyme activity to aid the field of nuclear medicine and radioimaging by detailing the development of a lipoic acid ligase that conjugates radiofluorine onto proteins of interest that contain a specific peptide substrate sequence. This approach would potentially expand the toolbox and broaden the pipelines of proteins amenable to radioimaging. Chapter 3 describes the inhibition, as opposed to the amplification, of enzyme activity by developing substrates and enzyme functional assays for screening inhibitory drugs against the SARS-CoV-2 major protease (Mpro).

Gad’s Book is a fast-paced, darkly humorous novel that blends philosophical fiction, political satire, and metafiction. The narrative follows an unnamed copywriter and aspiring novelist who—while struggling to navigate the social-technological landscape in present-day Berkeley—unwittingly joins Antifa. When we first meet the narrator, he is awkward, obsessive, and, like so many of his generation, anxious about everything. He (and his counterparts) experience social media anxiety disorder, filter bubbles, the transience of data, the attention deficit, the medicalization of depression, internet culture, the redundancy of technological life, artificial intelligence, and artificial realities. From the very first pages of the novel, the narrator seems to believe that he needs to have an opinion about anything and everything—and, more importantly, that his opinions need to be “correct.” His actions reflect his anxiety: he hides from his ten housemates, whom he has delayed meeting; pretends to smoke cigarettes even when no one is watching; practices making faces on his iPhone camera before going to parties; and spends much of his free time thinking up increasingly bizarre plots for the novel he isn’t writing. And that’s another thing: he’s anxious about (not) writing. Amid growing political tension (it’s an election year), he encounters a cast of characters—enigmatic political activists who offer him an escape from boredom, cynicism, and inertia—and he soon finds himself entangled in dangerous conflicts, complex romantic relationships, and sexual misadventures that first enliven then threaten to destroy his carefully-constructed life.