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Important concepts from the diverse fields of physics, mathematics, engineering and computer science coalesce in this foundational text on the cutting-edge field of quantum information. Designed for undergraduate and graduate students with any STEM background, and written by a highly experienced author team, this textbook draws on quantum mechanics, number theory, computer science technologies, and more, to delve deeply into learning about qubits, the building blocks of quantum information, and how they are used in quantum computing and quantum algorithms. The pedagogical structure of the chapters features exercises after each section as well as focus boxes, giving students the benefit of additional background and applications without losing sight of the big picture. Recommended further reading and answers to select exercises further support learning. Written in approachable and conversational prose, this text offers a comprehensive treatment of the exciting field of quantum information while remaining accessible to students and researchers within all STEM disciplines.
Pre-pregnancy obesity (ppOB) is linked to pregnancy complications and abnormal fetal growth through placental mechanisms, and long non-coding RNAs (lncRNAs) may play an epigenetic role in these processes. We investigated overall and sex-specific associations of pre-pregnancy body mass index (ppBMI), ppOB, and birthweight with placental lncRNA transcripts in two birth cohorts. Study participants were mother-child dyads recruited to the CANDLE (Memphis, TN)(n = 725) and GAPPS (Seattle and Yakima, WA)(n = 159) cohorts. Maternal ppBMI was assessed at enrollment using interviewer-administered questionnaires. LncRNAs (1,077 and 1,033 for CANDLE and GAPPS, respectively) were sequenced from placental samples collected at birth. Placental lncRNA was regressed on ppBMI, ppOB (ppBMI ≥30kg/m2), or continuous birthweight in cohort-specific weighted linear models controlling for a priori-specified confounders and experimental variables. Potential effect modification by infant-sex was examined in sex-stratified analyses and models including BMI-infant-sex interaction terms. No lncRNA transcripts were significantly associated with ppBMI, ppOB, or birthweight in primary models. Among male infants in CANDLE, expression of three lncRNA transcripts (ERVH48-1, AC139099.1, CEBPA-DT) was associated with ppBMI and one transcript (AC104083.1) with birthweight. In GAPPS, ppBMI was associated with two lncRNA transcripts (AP000879.1 and AL365203.2) among males, and birthweight was associated with 17 lncRNA transcripts (including LINC02709, KANSL1-AS1, DANCR, EPB41L4A-AS1, and GABPB1-AS1) among females. No BMI-infant-sex interactions were observed. Though many of these potential associations are for uncharacterized transcripts, several identified lncRNAs (e.g., ERVH48-1 and CEBPA-DT) have been linked to pathways controlling cancer or placental growth, trophoblast differentiation, and gene expression. These associations warrant validation in future studies.
It remains unclear which individuals with subthreshold depression benefit most from psychological intervention, and what long-term effects this has on symptom deterioration, response and remission.
Aims
To synthesise psychological intervention benefits in adults with subthreshold depression up to 2 years, and explore participant-level effect-modifiers.
Method
Randomised trials comparing psychological intervention with inactive control were identified via systematic search. Authors were contacted to obtain individual participant data (IPD), analysed using Bayesian one-stage meta-analysis. Treatment–covariate interactions were added to examine moderators. Hierarchical-additive models were used to explore treatment benefits conditional on baseline Patient Health Questionnaire 9 (PHQ-9) values.
Results
IPD of 10 671 individuals (50 studies) could be included. We found significant effects on depressive symptom severity up to 12 months (standardised mean-difference [s.m.d.] = −0.48 to −0.27). Effects could not be ascertained up to 24 months (s.m.d. = −0.18). Similar findings emerged for 50% symptom reduction (relative risk = 1.27–2.79), reliable improvement (relative risk = 1.38–3.17), deterioration (relative risk = 0.67–0.54) and close-to-symptom-free status (relative risk = 1.41–2.80). Among participant-level moderators, only initial depression and anxiety severity were highly credible (P > 0.99). Predicted treatment benefits decreased with lower symptom severity but remained minimally important even for very mild symptoms (s.m.d. = −0.33 for PHQ-9 = 5).
Conclusions
Psychological intervention reduces the symptom burden in individuals with subthreshold depression up to 1 year, and protects against symptom deterioration. Benefits up to 2 years are less certain. We find strong support for intervention in subthreshold depression, particularly with PHQ-9 scores ≥ 10. For very mild symptoms, scalable treatments could be an attractive option.
The Hierarchical Taxonomy of Psychopathology (HiTOP) and Research Domain Criteria (RDoC) frameworks emphasize transdiagnostic and mechanistic aspects of psychopathology. We used a multi-omics approach to examine how HiTOP’s psychopathology spectra (externalizing [EXT], internalizing [INT], and shared EXT + INT) map onto RDoC’s units of analysis.
Methods
We conducted analyses across five RDoC units of analysis: genes, molecules, cells, circuits, and physiology. Using genome-wide association studies from the companion Part I article, we identified genes and tissue-specific expression patterns. We used drug repurposing analyses that integrate gene annotations to identify potential therapeutic targets and single-cell RNA sequencing data to implicate brain cell types. We then used magnetic resonance imaging data to examine brain regions and circuits associated with psychopathology. Finally, we tested causal relationships between each spectrum and physical health conditions.
Results
Using five gene identification methods, EXT was associated with 1,759 genes, INT with 454 genes, and EXT + INT with 1,138 genes. Drug repurposing analyses identified potential therapeutic targets, including those that affect dopamine and serotonin pathways. Expression of EXT genes was enriched in GABAergic, cortical, and hippocampal neurons, while INT genes were more narrowly linked to GABAergic neurons. EXT + INT liability was associated with reduced gray matter volume in the amygdala and subcallosal cortex. INT genetic liability showed stronger causal effects on physical health – including chronic pain and cardiovascular diseases – than EXT.
Conclusions
Our findings revealed shared and distinct pathways underlying psychopathology. Integrating genomic insights with the RDoC and HiTOP frameworks advanced our understanding of mechanisms that underlie EXT and INT psychopathology.
There is considerable comorbidity between externalizing (EXT) and internalizing (INT) psychopathology. Understanding the shared genetic underpinnings of these spectra is crucial for advancing knowledge of their biological bases and informing empirical models like the Research Domain Criteria (RDoC) and Hierarchical Taxonomy of Psychopathology (HiTOP).
Methods
We applied genomic structural equation modeling to summary statistics from 16 EXT and INT traits in individuals genetically similar to European reference panels (EUR-like; n = 16,400 to 1,074,629). Traits included clinical (e.g. major depressive disorder, alcohol use disorder) and subclinical measures (e.g. risk tolerance, irritability). We tested five confirmatory factor models to identify the best fitting and most parsimonious genetic architecture and then conducted multivariate genome-wide association studies (GWAS) of the resulting latent factors.
Results
A two-factor correlated model, representing EXT and INT spectra, provided the best fit to the data. There was a moderate genetic correlation between EXT and INT (r = 0.37, SE = 0.02), with bivariate causal mixture models showing extensive overlap in causal variants across the two spectra (94.64%, SE = 3.27). Multivariate GWAS identified 409 lead genetic variants for EXT, 85 for INT, and 256 for the shared traits.
Conclusions
The shared genetic liabilities for EXT and INT identified here help to characterize the genetic architecture underlying these frequently comorbid forms of psychopathology. The findings provide a framework for future research aimed at understanding the shared and distinct biological mechanisms underlying psychopathology, which will help to refine psychiatric classification systems and potentially inform treatment approaches.
Borderline personality disorder (BPD) is a debilitating psychiatric illness whose symptoms frequently emerge during adolescence. Critically, self-injury and suicide attempts in BPD are often precipitated by interpersonal discord. Initial studies in adults suggest that the interpersonal difficulties common in BPD may emerge from disrupted processing of socioemotional stimuli. Less is known about these processes in adolescents with BPD symptoms, despite substantial changes in socioemotional processing during this developmental period.
Methods
Eighty-six adolescents and young adults with and without BPD symptoms completed an emotional interference task involving the identification of a facial emotion expression in the presence of a conflicting or congruent emotion word. We used hierarchical drift diffusion modeling to index speed of processing and decision boundary. Using Bayesian multilevel regression, we characterized age-related differences in facial emotion processing. We examined whether BPD symptom dimensions were associated with alterations in facial emotion processing. To determine the specificity of our effects, we analyzed behavioral data from a corresponding nonemotional interference task.
Results
Emotion-related impulsivity, but not negative affectivity or interpersonal dysfunction, predicted inefficient processing when presented with conflicting negative emotional stimuli. Across both tasks, emotion-related impulsivity in adolescents, but not young adults, was further associated with a lower decision boundary – resulting in fast but inaccurate decisions.
Conclusion
Impulsive adolescents with BPD symptoms are prone to making errors when appraising facial emotion expressions, which may potentiate or worsen interpersonal conflicts. Our findings highlight the role of lower-level social cognitive processes in interpersonal difficulties among vulnerable youth during a sensitive developmental window.
The compromise effect arises when being close to the “middle” of a choice set makes an option more appealing. The compromise effect poses conceptual and practical problems for economic research: by influencing choices, it can bias researchers’ inferences about preference parameters. To study this bias, we conduct an experiment with 550 participants who made choices over lotteries from multiple price lists (MPLs). Following prior work, we manipulate the compromise effect to influence choices by varying the middle options of each MPL. We then estimate risk preferences using a discrete-choice model without a compromise effect embedded in the model. As anticipated, the resulting risk preference parameter estimates are not robust, changing as the compromise effect is manipulated. To disentangle risk preference parameters from the compromise effect and to measure the strength of the compromise effect, we augment our discrete-choice model with additional parameters that represent a rising penalty for expressing an indifference point further from the middle of the ordered MPL. Using this method, we estimate an economically significant magnitude for the compromise effect and generate robust estimates of risk preference parameters that are no longer sensitive to compromise-effect manipulations.
In acute ischemic stroke, a longer time from onset to endovascular treatment (EVT) is associated with worse clinical outcome. We investigated the association of clinical outcome with time from last known well to arrival at the EVT hospital and time from hospital arrival to arterial access for anterior circulation large vessel occlusion patients treated > 6 hours from last known well.
Methods:
Retrospective analysis of the prospective, multicenter cohort study ESCAPE-LATE. Patients presenting > 6 hours after last known well with anterior circulation large vessel occlusion undergoing EVT were included. The primary outcome was the modified Rankin Scale (mRS) score at 90 days. Secondary outcomes were good (mRS 0–2) and poor clinical outcomes (mRS 5–6) at 90 days, as well as the National Institutes of Health Stroke Scale at 24 hours. Associations of time intervals with outcomes were assessed with univariable and multivariable logistic regression.
Results:
Two hundred patients were included in the analysis, of whom 85 (43%) were female. 90-day mRS was available for 141 patients. Of the 150 patients, 135 (90%) had moderate-to-good collaterals, and the median Alberta Stroke Program Early CT Score (ASPECTS) was 8 (IQR = 7–10). No association between ordinal mRS and time from last known well to arrival at the EVT hospital (odds ratio [OR] = 1.01, 95% CI = 1.00–1.02) or time from hospital arrival to arterial access (OR = -0.01, 95% CI = -0.02–0.00) was seen in adjusted regression models.
Conclusion:
No relationship was observed between pre-hospital or in-hospital workflow times and clinical outcomes. Baseline ASPECTS and collateral status were favorable in the majority of patients, suggesting that physicians may have chosen to predominantly treat slow progressors in the late time window, in whom prolonged workflow times have less impact on outcomes.
This letter presents an improved analytical model for analyzing probe-fed microstrip antennas loaded by metallic vias with lumped terminations. The proposed formulation is based on the resonant cavity model and enables efficient analysis of such perturbed radiators for various types of terminations. The model is validated through the analysis of two antennas: one operating in a TM00 mode and the other with four capacitive terminations to produce circular polarization. Moreover, a reconfigurable RHCP/LHCP antenna based on the patch with capacitive terminations has been manufactured and tested, showing a broadside axial ratio below 0.5 dB at 1.575 GHz.
This study compares the design practices and performance of ChatGPT 4.0, a large language model (LLM), against graduate engineering students in a 48-h prototyping hackathon, based on a dataset comprising more than 100 prototypes. The LLM participated by instructing two participants who executed its instructions and provided objective feedback, generated ideas autonomously and made all design decisions without human intervention. The LLM exhibited similar prototyping practices to human participants and finished second among six teams, successfully designing and providing building instructions for functional prototypes. The LLM’s concept generation capabilities were particularly strong. However, the LLM prematurely abandoned promising concepts when facing minor difficulties, added unnecessary complexity to designs, and experienced design fixation. Communication between the LLM and participants was challenging due to vague or unclear descriptions, and the LLM had difficulty maintaining continuity and relevance in answers. Based on these findings, six recommendations for implementing an LLM like ChatGPT in the design process are proposed, including leveraging it for ideation, ensuring human oversight for key decisions, implementing iterative feedback loops, prompting it to consider alternatives, and assigning specific and manageable tasks at a subsystem level.
This paper examines the writings of socialist scholars who played a pivotal role in shaping Friedrich Hayek’s perspective in The Road to Serfdom, including William Beveridge, Stuart Chase, Henry Dickinson, Hugh Dalton, Evan Durbin, Oskar Lange, Harold Laski, Abba Lerner, Barbara Wootton, and the contributing authors in Findlay MacKenzie’s Planned Society (1937). Many of these socialist thinkers held two main hypotheses. First, industrial concentration was inevitable under capitalism. Second, they argued, government ownership or control of key economic sectors was necessary to protect democracy from industrial consolidation in the capitalist system and to reduce political opposition to complete state ownership or control over the means of production. Despite sharing Hayek’s concern for socialism’s potential erosion of democratic freedoms, these socialist hypotheses have received much less scholarly attention than Hayek’s The Road to Serfdom. We conclude that Hayek formalized socialist scholars’ fears and developed a well-defined hypothesis that central planning could threaten democratic freedoms.
Previous studies identified clusters of first-episode psychosis (FEP) patients based on cognition and premorbid adjustment. This study examined a range of socio-environmental risk factors associated with clusters of FEP, aiming a) to compare clusters of FEP and community controls using the Maudsley Environmental Risk Score for psychosis (ERS), a weighted sum of the following risks: paternal age, childhood adversities, cannabis use, and ethnic minority membership; b) to explore the putative differences in specific environmental risk factors in distinguishing within patient clusters and from controls.
Methods
A univariable general linear model (GLS) compared the ERS between 1,263 community controls and clusters derived from 802 FEP patients, namely, low (n = 223) and high-cognitive-functioning (n = 205), intermediate (n = 224) and deteriorating (n = 150), from the EU-GEI study. A multivariable GLS compared clusters and controls by different exposures included in the ERS.
Results
The ERS was higher in all clusters compared to controls, mostly in the deteriorating (β=2.8, 95% CI 2.3 3.4, η2 = 0.049) and the low-cognitive-functioning cluster (β=2.4, 95% CI 1.9 2.8, η2 = 0.049) and distinguished them from the cluster with high-cognitive-functioning. The deteriorating cluster had higher cannabis exposure (meandifference = 0.48, 95% CI 0.49 0.91) than the intermediate having identical IQ, and more people from an ethnic minority (meandifference = 0.77, 95% CI 0.24 1.29) compared to the high-cognitive-functioning cluster.
Conclusions
High exposure to environmental risk factors might result in cognitive impairment and lower-than-expected functioning in individuals at the onset of psychosis. Some patients’ trajectories involved risk factors that could be modified by tailored interventions.
Variable sharing is a fundamental property in the static analysis of logic programs, since it is instrumental for ensuring correctness and increasing precision while inferring many useful program properties. Such properties include modes, determinacy, non-failure, cost, etc. This has motivated significant work on developing abstract domains to improve the precision and performance of sharing analyses. Much of this work has centered around the family of set-sharing domains, because of the high precision they offer. However, this comes at a price: their scalability to a wide set of realistic programs remains challenging and this hinders their wider adoption. In this work, rather than defining new sharing abstract domains, we focus instead on developing techniques which can be incorporated in the analyzers to address aspects that are known to affect the efficiency of these domains, such as the number of variables, without affecting precision. These techniques are inspired in others used in the context of compiler optimizations, such as expression reassociation and variable trimming. We present several such techniques and provide an extensive experimental evaluation of over 1100 program modules taken from both production code and classical benchmarks. This includes the Spectector cache analyzer, the s(CASP) system, the libraries of the Ciao system, the LPdoc documenter, the PLAI analyzer itself, etc. The experimental results are quite encouraging: we have obtained significant speedups, and, more importantly, the number of modules that require a timeout was cut in half. As a result, many more programs can be analyzed precisely in reasonable times.
Most studies aiming to quantify carbon stocks in tropical forests have focused on aboveground biomass, omitting carbon in soils and woody debris. Here, we quantified carbon stocks in soils up to 3 m depth, woody debris, and aboveground and belowground tree biomass for the 25-ha Amacayacu Forests Dynamics plot in the northwestern Amazon. Including soils to 3 m depth, total carbon stocks averaged 358.9 ± 24.2 Mg C ha−1, of which soils contributed 53%, biomass 44.2%, and woody debris 2.7%. When only including soils to 0.5 m depth, carbon stocks diminished to 222.1 Mg C ha−1 and biomass became the largest contributor. Among 1-ha subplots, total carbon stocks were correlated with soil carbon stocks at ≥0.5 m depth, belowground biomass of all trees, and aboveground biomass of trees ≥60 cm DBH. Our results support the assumption of biomass as the likely largest carbon source associated with land use change in northwestern Amazonia. However, mining and erosion following land use change could also promote a significant release of carbon from soil, the largest carbon stock. To improve the global carbon balance, we need to better quantify total carbon stocks and dynamics in tropical forests beyond aboveground biomass.
Urgent care centers (UCCs) have reported high rates of antibiotic prescribing for acute respiratory tract infections. Prior UCC studies have generally been limited to single networks. Broadly generalizable stewardship efforts targeting common diagnoses are needed. This study examines the effectiveness of an antibiotic stewardship intervention in reducing inappropriate prescribing for bronchitis and viral upper respiratory tract infections (URTIs) in UCCs.
Design:
A quality improvement study comparing inappropriate antibiotic prescribing rates in UCCs after the introduction of an antibiotic stewardship intervention.
Setting:
Forty-nine UCCs in 27 different networks from 18 states, including 1 telemedicine site.
Participants:
Urgent care clinicians from a national collaborative of UCCs, all members of the Urgent Care Association.
Methods:
The intervention included signing a commitment statement and selecting from 5 different intervention options during 3 plan-do-study-act cycles. The primary outcome was the percentage of urgent care encounters for viral URTIs or bronchitis with inappropriate prescribing, stratified by clinician engagement and diagnosis. A 3-month baseline and 9-month intervention period were compared using a regression model using a generalized estimating equation.
Results:
Among 15,385 encounters, the intervention was associated with decreases in inappropriate antibiotic prescribing for bronchitis (48% relative decrease, aOR = 0.52; 95% CI, 0.33–0.83) and viral URTIs (33%, aOR = 0.67; 95% CI, 0.55–0.82) among actively engaged clinicians compared to baseline. The intervention did not result in significant changes for clinicians not actively engaged.
Conclusions:
This intervention was associated with reductions in inappropriate prescribing among actively engaged clinicians. Implementing stewardship interventions in UCCs may reduce inappropriate antibiotic prescriptions for common diagnoses; however, active clinician engagement may be necessary.
Successfully educating urgent care patients on appropriate use and risks of antibiotics can be challenging. We assessed the conscious and subconscious impact various educational materials (informational handout, priming poster, and commitment poster) had on urgent care patients’ knowledge and expectations regarding antibiotics.
Design:
Stratified Block Randomized Control Trial.
Setting:
Urgent care centers (UCCs) in Colorado, Florida, Georgia, and New Jersey.
Participants:
Urgent care patients.
Methods:
We randomized 29 UCCs across six study arms to display specific educational materials (informational handout, priming poster, and commitment poster). The primary intention-to-treat (ITT) analysis evaluated whether the materials impacted patient knowledge or expectations of antibiotic prescribing by assigned study arm. The secondary as-treated analysis evaluated the same outcome comparing patients who recalled seeing the assigned educational material and patients who either did not recall seeing an assigned material or were in the control arm.
Results:
Twenty-seven centers returned 2,919 questionnaires across six study arms. Only 27.2% of participants in the intervention arms recalled seeing any educational materials. In our primary ITT analysis, no difference in knowledge or expectations of antibiotic prescribing was noted between groups. However, in the as-treated analysis, the handout and commitment poster were associated with higher antibiotic knowledge scores.
Conclusions:
Educational materials in UCCs are associated with increased antibiotic-related knowledge among patients when they are seen and recalled; however, most patients do not recall passively displayed materials. More emphasis should be placed on creating and drawing attention to memorable patient educational materials.
Multinomial processing trees (MPTs) are a popular class of cognitive models for categorical data. Typically, researchers compare several MPTs, each equipped with many parameters, especially when the models are implemented in a hierarchical framework. A Bayesian solution is to compute posterior model probabilities and Bayes factors. Both quantities, however, rely on the marginal likelihood, a high-dimensional integral that cannot be evaluated analytically. In this case study, we show how Warp-III bridge sampling can be used to compute the marginal likelihood for hierarchical MPTs. We illustrate the procedure with two published data sets and demonstrate how Warp-III facilitates Bayesian model averaging.
This article considers the application of the simulation-extrapolation (SIMEX) method for measurement error correction when the error variance is a function of the latent variable being measured. Heteroskedasticity of this form arises in educational and psychological applications with ability estimates from item response theory models. We conclude that there is no simple solution for applying SIMEX that generally will yield consistent estimators in this setting. However, we demonstrate that several approximate SIMEX methods can provide useful estimators, leading to recommendations for analysts dealing with this form of error in settings where SIMEX may be the most practical option.
This article devises a Bayesian multivariate formulation for analysis of ordinal data that records teacher classroom performance along multiple dimensions to assess aspects characterizing good instruction. Study designs for scoring teachers seek to measure instructional performance over multiple classroom measurement event sessions at varied occasions using disjoint intervals within each session and employment of multiple ratings on intervals scored by different raters; a design which instantiates a nesting structure with each level contributing a source of variation in recorded scores. We generally possess little a priori knowledge of the existence or form of a sparse generating structure for the multivariate dimensions at any level in the nesting that would permit collapsing over dimensions as is done under univariate modeling. Our approach composes a Bayesian data augmentation scheme that introduces a latent continuous multivariate response linked to the observed ordinal scores with the latent response mean constructed as an additive multivariate decomposition of nested level means that permits the extraction of de-noised continuous teacher-level scores and the associated correlation matrix. A semi-parametric extension facilitates inference for teacher-level dependence among the dimensions of classroom performance under multi-modality induced by sub-groupings of rater perspectives. We next replace an inverse Wishart prior specified for the teacher covariance matrix over dimensions of instruction with a factor analytic structure to allow the simultaneous assessment of an underlying sparse generating structure. Our formulation for Bayesian factor analysis employs parameter expansion with an accompanying post-processing sign re-labeling step of factor loadings that together reduce posterior correlations among sampled parameters to improve parameter mixing in our Markov chain Monte Carlo (MCMC) scheme. We evaluate the performance of our formulation on simulated data and make an application for the assessment of the teacher covariance structure with a dataset derived from a study of middle and high school algebra teachers.