Miracle-dz/UniFAR-FTUs huggingface dataset:
The effectiveness of China’s regional carbon market pilots in reducing firm emissions

Significance The emission trading system (ETS) is an important policy instrument for China to achieve its climate targets. However, the effectiveness of ETS in emission reductions and its economic consequences are unknown. Using a unique dataset of firm tax records, we comprehensively assess the impacts of China’s regional ETS pilots, taking advantage of the policy experiments in certain sectors across seven jurisdictions. We demonstrate unambiguous evidence that China’s ETS leads to a reduction in carbon emissions despite low carbon prices and infrequent trading. We also identify the channels through which firms respond to ETS by adjusting energy consumption and sources, employment, capital, and productivity. The lessons learned from the regional pilots shed light on the design of China’s national carbon ETS. China has implemented an emission trading system (ETS) to reduce its ever-increasing greenhouse gas emissions while maintaining rapid economic growth. With low carbon prices and infrequent allowance trading, whether China’s ETS is an effective approach for climate mitigation has entered the center of the policy and research debate. Utilizing China’s regional ETS pilots as a quasi-natural experiment, we provide a comprehensive assessment of the effects of ETS on firm carbon emissions and economic outcomes by means of a matched difference-in-differences (DID) approach. The empirical analysis is based on a unique panel dataset of firm tax records in the manufacturing and public utility sectors during 2009 to 2015. We show unambiguous evidence that the regional ETS pilots are effective in reducing firm emissions, leading to a 16.7% reduction in total emissions and a 9.7% reduction in emission intensity. Regulated firms achieve emission abatement through conserving energy consumption and switching to low-carbon fuels. The economic consequences of the ETS are mixed. On one hand, the ETS has a negative impact on employment and capital input; on the other hand, the ETS incentivizes regulated firms to improve productivity. In the aggregate, the ETS does not exhibit statistically significant effects on output and export. We also find that the ETS displays notable heterogeneity across pilots. Mass-based allowance allocation rules, higher carbon prices, and active allowance trading contribute to more pronounced effects in emission abatement.
Computational basis of decision-making impairment in multiple sclerosis

Background: Multiple sclerosis (MS) is commonly associated with decision-making, neurocognitive impairments, and mood and motivational symptoms. However, their relationship may be obscured by traditional scoring methods. Objectives: To study the computational basis underlying decision-making impairments in MS and their interaction with neurocognitive and neuropsychiatric measures. Methods: Twenty-nine MS patients and 26 matched control subjects completed a computer version of the Iowa Gambling Task (IGT). Participants underwent neurocognitive evaluation using an expanded version of the Brief Repeatable Battery. Hierarchical Bayesian Analysis was used to estimate three established computational models to compare parameters between groups. Results: Patients showed increased learning rate and reduced loss-aversion during decision-making relative to control subjects. These alterations were associated with: (1) reduced net gains in the IGT; (2) processing speed, executive functioning and memory impairments; and (3) higher levels of depression and current apathy. Conclusion: Decision-making deficits in MS patients could be described by the interplay between latent computational processes, neurocognitive impairments, and mood/motivational symptoms.
Modeling and canceling tremor in human-machine interfaces

Zero-phase modeling and canceling of tremor can improve precision in human-machine control applications. Past methods of tremor suppression have been hindered by feedback delays due to phase lag and by the inability to track tremor frequency over time. The weighted-frequency Fourier linear combiner (WFLC) is an adaptive noise canceller that precisely models tremor with zero phase lag. This article briefly presents the WFLC algorithm and describes its application to computer input filtering, clinical tremor quantification, and active tremor canceling for microsurgery.
An effective peak stress formula for concrete confined with carbon fiber reinforced plastics

The uniaxial compression test results of three different strengths and three different sizes of concrete cylinders confined with different layers of carbon fiber reinforced plastics (CFRP) are used to develop an effective peak stress formula for predicting the strength of confined concrete. The theory of this peak stress formula was based on the triaxial confined test of soil and rock, and the lateral confinement of the concrete was assumed to be due to the CFRP. The peak stress of the confined concrete can be explicitly expressed as a function of the unconfined concrete strength and the lateral CFRP confined strength. Experiments were done on 108 concrete cylinders, and the test results show the accuracy and effectiveness of this peak stress formulation of confined concrete.Key words: confined concrete, peak stress, carbon fiber reinforced plastics.
Model-based incremental validity.

As an important facet of construct validity, incremental validity has been the focus of many applied investigations across a wide array of disciplines. Unfortunately, traditional methodological approaches for studying incremental validity, typically rooted in multiple regression, have many limitations that can hinder such assessments. In the current work, a strategy based in structural equation modeling is offered that greatly expands researchers' ability to investigate incremental validity of multiple individual predictors or blocks of predictors all within a single structural model. Models for four different research scenarios are presented, where the predictors of focal interest are: (a) individual measured predictors, (b) individual latent predictors, (c) blocks of measured predictors, and (d) blocks of latent predictors. Technical details of model specifications and model constraints are provided, and flexible extensions to other interesting questions (e.g., comparisons across populations) are discussed. Two empirical examples are included to illustrate the application of the proposed methods in different applied settings; complete Mplus and R syntax for both illustrative examples is supplied. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Nonclassical autophagy activation pathways are essential for production of infectious Influenza A virus in vitro

Autophagy is a critical mechanism deployed by eukaryotic cells in response to stress, including viral infection, to boost the innate antimicrobial responses. However, an increasing number of pathogens hijack the autophagic machinery to facilitate their own replication. Influenza A virus (IAV), responsible for several global pandemics, has an intricate dependence on autophagy for successful replication in mammalian cells. To elucidate key chokepoints in the host stress responses facilitating IAV replication, we constructed a meta‐transcriptome of IAV and host gene expression dynamics during early (1–3 hpi), mid (4–6 hpi), and late (8–12 hpi) stages of the viral replication cycle at two multiplicities of infection (MOI): 1 and 5. We supplemented the global transcriptome study with phosphoproteomic analysis of stress‐activated protein kinase (SAPK/JNK) signaling in lung carcinoma (predominantly used as an in vitro model of IAV replication) and normal human bronchial epithelial cells. We report significant differences in the activation profiles of autophagy regulating genes upon IAV infection at the two MOI as well as divergent dependence on ULK1 signaling within the normal and cancer cells. Regardless of the cell model, JNK‐Thr187 signaling was crucial for the production of infectious viral particles.
Integrative Review of Programs to Improve Outcomes for Children With Comorbid Asthma and Anxiety/Depressive Symptoms

Asthma is one of the most common pediatric chronic physical conditions. Youth with comorbid asthma and anxiety/depressive symptoms tend to have less controlled asthma and an increased use of health services in schools. The purpose of this integrative review was to examine the literature on educational and behavioral/ cognitive behavioral skills interventions for children with asthma and anxiety/depressive symptoms. Five electronic databases and forward/backward citations were searched. Eleven peer reviewed articles were retained for review. Main findings of the limited evidence suggest that educational and behavioral/cognitive behavioral skills programs may increase asthma knowledge and asthma-related self-efficacy while reducing anxiety/depressive symptoms. One study showed a decrease in use of quick relief inhalers and another had increased adherence to asthma controller medication. The literature indicates that educational and cognitive behavioral skills programs can have a positive impact on children with asthma and symptoms of anxiety/depression. School-based skills programs had better retention than outpatient programs.
Escape from recognition of SARS-CoV-2 Beta variant spike epitopes but overall preservation of T cell immunity

SARS-CoV-2 variants that escape neutralization and potentially affect vaccine efficacy have emerged. T cell responses play a role in protection from reinfection and severe disease, but the potential for spike mutations to affect T cell immunity is incompletely understood. We assessed neutralizing antibody and T cell responses in 44 South African COVID-19 patients either infected with the Beta variant (dominant from November 2020 to May 2021) or infected before its emergence (first wave, Wuhan strain) to provide an overall measure of immune evasion. We show that robust spike-specific CD4 and CD8 T cell responses were detectable in Beta-infected patients, similar to first-wave patients. Using peptides spanning the Beta-mutated regions, we identified CD4 T cell responses targeting the wild-type peptides in 12 of 22 first-wave patients, all of whom failed to recognize corresponding Beta-mutated peptides. However, responses to mutated regions formed only a small proportion (15.7%) of the overall CD4 response, and few patients (3 of 44) mounted CD8 responses that targeted the mutated regions. Among the spike epitopes tested, we identified three epitopes containing the D215, L18, or D80 residues that were specifically recognized by CD4 T cells, and their mutated versions were associated with a loss of response. This study shows that despite loss of recognition of immunogenic CD4 epitopes, CD4 and CD8 T cell responses to Beta are preserved overall. These observations may explain why several vaccines have retained the ability to protect against severe COVID-19 even with substantial loss of neutralizing antibody activity against Beta. Description T cell immunity to SARS-CoV-2 Beta is preserved despite some loss of variant epitope recognition by CD4 T cells. T cells versus SARS-CoV-2 variants Many studies have examined the ability of vaccine-induced antibodies to neutralize SARS-CoV-2 variants of concern but have not looked at T cells. Riou et al. developed a method to study T cell responses to SARS-CoV-2 variants in 44 South African COVID-19 patients infected with first-wave SARS-CoV-2 in early 2020 or the Beta variant, which dominated from November 2020 to May 2021. Beta-infected individuals developed robust spike-specific CD4 and CD8 T cell responses like first-wave infected individuals, and only a small fraction of the overall CD4 and CD8 T cell response targeted regions in spike associated with Beta mutations. This study highlights the preservation of T cell immunity despite a loss of recognition of epitopes altered by mutations and provides insight into sustained vaccine efficacy against some variants.
Defective Allelic Exclusion by IgD in the Absence of Autoantigen

Key Points IgD has the unique ability to neglect weakly interacting autoantigens. IgD has a higher activation threshold than IgM. B cells can adjust their sensitivity to Ag by shifting IgM- to IgD–BCR ratio. A considerable proportion of peripheral B cells is autoreactive, and it is unclear how the activation of such potentially harmful cells is regulated. In this study, we show that the different activation thresholds or IgM and IgD BCRs adjust B cell activation to the diverse requirements during development. We rely on the autoreactive 3-83 model BCR to generate and analyze mice expressing exclusively autoreactive IgD BCRs on two different backgrounds that determine two stages of autoreactivity, depending on the presence or absence of the cognate Ag. By comparing these models with IgM-expressing control mice, we found that, compared with IgM, IgD has a higher activation threshold in vivo, as it requires autoantigen to enable normal B cell development, including allelic exclusion. Our data indicate that IgM provides the high sensitivity required during early developmental stages to trigger editing of any autoreactive specificities, including those enabling weak interaction with autoantigen. In contrast, IgD has the unique ability to neglect weakly interacting autoantigens while retaining reactivity to higher-affinity Ag. This IgD function enables mature B cells to ignore autoantigens while remaining able to efficiently respond to foreign threats.
BCL‐2‐family protein tBID can act as a BAX‐like effector of apoptosis

During apoptosis, the BCL‐2‐family protein tBID promotes mitochondrial permeabilization by activating BAX and BAK and by blocking anti‐apoptotic BCL‐2 members. Here, we report that tBID can also mediate mitochondrial permeabilization by itself, resulting in release of cytochrome c and mitochondrial DNA, caspase activation and apoptosis even in absence of BAX and BAK. This previously unrecognized activity of tBID depends on helix 6, homologous to the pore‐forming regions of BAX and BAK, and can be blocked by pro‐survival BCL‐2 proteins. Importantly, tBID‐mediated mitochondrial permeabilization independent of BAX and BAK is physiologically relevant for SMAC release in the immune response against Shigella infection. Furthermore, it can be exploited to kill leukaemia cells with acquired venetoclax resistance due to lack of active BAX and BAK. Our findings define tBID as an effector of mitochondrial permeabilization in apoptosis and provide a new paradigm for BCL‐2 proteins, with implications for anti‐bacterial immunity and cancer therapy.
Recruitment and Retention of Parents of Adolescents in a Text Messaging Trial (MyTeen): Secondary Analysis From a Randomized Controlled Trial

Background Parenting programs are well established as an effective strategy for enhancing both parenting skills and the well-being of the child. However, recruitment for family programs in clinical and nonclinical settings remains low. Objective This study aims to describe the recruitment and retention methods used in a text messaging program (MyTeen) trial for parents of adolescents (10-15 years) and identify key lessons learned. We aim to provide insights and direction for researchers who seek to recruit parents and build on the limited literature on recruitment and retention strategies for parenting program trials. Methods A recruitment plan was developed, monitored, and modified as needed throughout the course of the project. Strategies to facilitate recruitment were identified (eg, program content and recruitment material, staff characteristics, and study procedures). Traditional and web-based recruitment strategies were used. Results Over a 5-month period, 319 parents or caregivers expressed interest in our study, of which 221 agreed to participate in the study, exceeding our recruitment target of 214 participants. Attrition was low at the 1-month (4.5% overall; intervention group: n=5, 4.6%; control group: n=5, 4.5%) and 3-month follow-ups (9% overall; intervention group: n=10, 9.2%; control group: n=10, 8.9%). Conclusions The use of web-based recruitment strategies appeared to be most effective for recruiting and retaining parents in a text-messaging program trial. However, we encountered recruitment challenges (ie, underrepresentation of ethnic minority groups and fathers) similar to those reported in the literature. Therefore, efforts to engage ethnic minorities and fathers are needed. Trial Registration Australian New Zealand Clinical Trials Registry ACTRN12618000117213; https://www.anzctr. org.au/Trial/Registration/TrialReview.aspx? id=374307
Block copolymer self-assembly assisted fabrication of laterally organized- and stacked- nanoarrays

Block copolymer (BCP) self-assembly processes are often seen as reliable techniques for advanced nanopatterning to achieve functional surfaces and create templates for nanofabrication. By taking advantage of the tunability in pitch, diameter and feature-to-feature separation of the self-assembled BCP features, complex, laterally organized- and stacked- multicomponent nanoarrays comprising of gold and polymer have been fabricated. The approaches not only demonstrate nanopatterning of up to two levels of hierarchy but also investigate how a variation in the feature-to-feature gap at the first hierarchy affects the self-assembly of polymer features at the second. Such BCP self-assembly enabled multicomponent nanoarray configurations are rarely achieved by other nanofabrication approaches and are particularly promising for pushing the boundaries of block copolymer lithography and in creating unique surface architectures and complex morphologies at the nanoscale.
Layover solution in multibaseline SAR interferometry

In this work, spectral estimation techniques are used to exploit baseline diversity of a multichannel interferometric synthetic aperture radar (SAR) system and overcome the layover problem. This problem arises when different height contributions collapse in the same range-azimuth resolution cell, due to the presence of strong terrain slopes or discontinuities in the sensed scene. We propose a multilook approach to counteract the presence of multiplicative noise, which is due to the extended nature of natural targets; to this purpose we extend the RELAX algorithm to the multilook data scenario (M-RELAX). A thorough performance analysis of nonparametric (beamforming and Capon) and parametric (root MUSIC and M-RELAX) techniques is carried out based on Monte Carlo simulations and Cramer-Rao lower bounds (CRLB) calculation. The results suggest the superiority of parametric methods over nonparametric ones.
Adaptive Rate Block Compressive Sensing Based on Statistical Characteristics Estimation

In some video compressive sensing (CS) applications, the sparsity of original signals is unknown to the sampling device. The computing power, memory space and power consumption of the sampling device are also limited, which makes it difficult to achieve adaptive rate compressive sensing (ARCS). A new blocked ARCS method for surveillance videos is proposed, which fully considers the limitations mentioned above. By observing the result of CS measurement, the statistical characteristics of the original signal are estimated. The sparsity of the original signal is reasonably estimated by using these statistical characteristics. Therefore, blocks can be divided into more classes with higher accuracy. The proposed method has the advantages of low computational complexity, small memory footprint and low power consumption, which makes it suitable for implementing in applications such as wireless video sensor networks (WVSN) and single pixel cameras (SPC). The experiment results show that the proposed method can well adapt to the change of sparsity, allocate appropriate sampling rate for each block, effectively reduce the sampling rate, and improve the quality of the reconstructed image. Meanwhile, the amount of calculation in the sampling process is much lower, and the sampling speed is obviously accelerated. The overall performance of the proposed method is better than the previous state-of-the-art method.
Factors Influencing Adoption of Conservation Agriculture: A Case for Increasing Resilience to Climate Change and Variability in Swaziland

Conservation agriculture technologies have been extensively promoted to mitigate against drought as well as improve agriculture productivity for over a decade. Despite the extensive extension and investment Conservation agriculture technologies have been less widely adopted by farmers in Swaziland. Low adoption and lack of continued use of adapted and improved agricultural production technologies amongst farmers has been identified as one of the main reasons for the low agricultural productivity in the country. There is no in-depth analysis of the determinants of Conservation agriculture adoption, this study therefore assessed factors that influenced adoption and continued use of conservation agriculture in the Lowveld agro ecological region of Swaziland Results from 200 farming households practicing conservation agriculture indicated farmer characteristics such as age, gender, levels of education, extension and wealth influence adoption of Conservation agriculture. Likewise, the linear regression model results show that if the household head had some form of education, there were three times more likely to adopt conservation agriculture than a household head without any form of education. As the number of people contributing to agricultural labour increased households there was a 165% chance that these households were more likely to adopt conservation agriculture. Knowing factors that influence adoption will allow development of strategies, policies and plans that take advantage if the main influences of adoption so as to increase adoption and sustainability of use of Conservation agriculture. Keywords: Conservation Agriculture, Technology adoption, Extension, Climate change, Resilience
In situ dynamic properties of an in-service bridge using forced vibration testing

With the use of integrated soil-foundation-structure modeling in seismic bridge design, there is an inherent difficulty in determining the validity of the assumed stiffness and damping of the system and the contribution of various components of the structure and foundation to the overall system response. Validating these assumptions in a laboratory setting is particularly difficult due to problems associated with the appropriate representation of realistic boundary conditions, the variability of soil properties within a bridge site, and scaling of soil-structure systems for laboratory analysis. Some of these problems can be overcome by testing of full scale bridges in the field. This paper provides an overview of the forced vibration testing and computational modeling to determine the in situ dynamic properties of an in-service bridge in Auckland, New Zealand. Testing was performed over two nights with lateral excitation provided by an eccentric mass shaker in transverse axis of the bridge. The bridge-foundation system response was measured with 180 accelerometer channels on the bridge structure. Soils surrounding the piers and abutment were characterized with CPT tests to a depth of 20 m. Natural periods and mode shapes were extracted from the experimental data using a suite of system identification algorithms. Modal properties from both fixed based and a simplified integrated structurefoundation model were compared to those identified from field testing. It was determined that the simple integrated model was able to represent the in situ dynamic properties of the bridge and provided a much better prediction of seismic demand distribution than the fixed base model, which under-predicted the demand on the abutments and over-predicted the demand on the piers.