Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of reanalysis forcing fields on ozone trends and age of air from a chemical transport model

Abstract. We use TOMCAT, a 3-dimensional (3D) offline chemical transport model (CTM) forced by two different meteorological reanalysis data sets (ERA-Interim and ERA5) from the European Centre for Medium-Range weather Forecasts (ECMWF) to analyse seasonal behaviour and long-term trends in stratospheric ozone and mean age of air. The model-simulated ozone variations are evaluated against two observation-based data sets. For total column ozone (TCO) comparisons, we use the Copernicus Climate Change Service (C3S) data (1979–2019), while for ozone profiles we use the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) data set (1984–2019). We find that the CTM simulations forced by ERA-Interim (A_ERAI) and ERA5 (B_ERA5) can both successfully reproduce the spatial and temporal variations in stratospheric ozone. Also, modelled TCO anomalies from B_ERA5 show better agreement with C3S than A_ERAI, especially in Northern Hemisphere (NH) mid latitudes, except that it gives somewhat larger positive biases (> 15 DU, Dobson units) during winter–spring seasons. Ozone profile comparisons against SWOOSH data show larger differences between the two simulations. In the lower stratosphere, ozone differences can be directly attributed to the representation of dynamical processes, whereas in the upper stratosphere they can be directly linked to the differences in temperatures between ERAI and ERA5 data sets. Although TCO anomalies from B_ERA5 show relatively better agreement with C3S compared to A_ERAI, a comparison with SWOOSH data does not confirm that B_ERA5 performs better at simulating the variations in the stratospheric ozone profiles. We employ a multivariate regression model to quantify the TCO and ozone profile trends before and after peak stratospheric halogen loading in 1997. Our results show that, compared to C3S, TCO recovery trends (since 1998) in simulation B_ERA5 are significantly overestimated in the Southern Hemisphere (SH) mid latitudes, while for A_ERAI in the NH mid latitudes, simulated ozone trends remain negative. Similarly, in the lower stratosphere, B_ERA5 shows positive ozone recovery trends for both NH and SH mid latitudes. In contrast, both SWOOSH and A_ERAI show opposite (negative) trends in the NH mid latitudes. Furthermore, we analyse age of air (AoA) trends to diagnose transport differences between the two reanalysis data sets. Simulation B_ERA5 shows a positive AoA trend after 1998 and somewhat older age in the NH lower stratosphere compared to A_ERAI, indicating that a slower Brewer–Dobson circulation does not translate into reduced wintertime ozone buildup in the NH extratropical lower stratosphere. Overall, our results show that models forced by the most recent ERA5 reanalyses may not yet be capable of reproducing observed changes in stratospheric ozone, particularly in the lower stratosphere.
Establishing National Carbon Emission Prices for China

The purpose of the paper is to establish national carbon emissions prices for the People's Republic of China, which is one of the world's largest producers of carbon emissions. Several measures have been undertaken to address climate change in China, including the establishment of a carbon trading system. Since 2013, eight regional carbon emissions markets have been established, namely Beijing, Shanghai, Guangdong, Shenzhen, Tianjin, Chongqing, Hubei and Fujian. The Central Government announced a national carbon emissions market, with power generation as the first industry to be considered. However, as carbon emissions prices in the eight regional markets are very different, for a variety of administrative reasons, it is essential to create a procedure for establishing a national carbon emissions price. The regional markets are pioneers, and their experience will play important roles in establishing a national carbon emissions market, with national prices based on regional prices, turnovers and volumes. The paper considers two sources of regional data for China's carbon allowances, which are based on primary and secondary data sources, and compares their relative strengths and weaknesses. The paper establishes national carbon emissions prices based on the primary and secondary regional prices, for the first time, and compares both national prices and regional prices against each other. The carbon emission prices in Hubei, Guangdong, Shenzhen and Tianjin are highly correlated with the national prices based on the primary and secondary sources. Establishing national carbon emissions prices should be very helpful for the national carbon emissions market that is under construction in China, as well as for other regions and countries worldwide.
Data-Driven Control Techniques for Renewable Energy Conversion Systems: Wind Turbine and Hydroelectric Plants

The interest in the use of renewable energy resources is increasing, especially towards wind and hydro powers, which should be efficiently converted into electric energy via suitable technology tools. To this end, data-driven control techniques represent viable strategies that can be employed for this purpose, due to the features of these nonlinear dynamic processes of working over a wide range of operating conditions, driven by stochastic inputs, excitations and disturbances. Therefore, the paper aims at providing some guidelines on the design and the application of different data-driven control strategies to a wind turbine benchmark and a hydroelectric simulator. They rely on self-tuning PID, fuzzy logic, adaptive and model predictive control methodologies. Some of the considered methods, such as fuzzy and adaptive controllers, were successfully verified on wind turbine systems, and similar advantages may thus derive from their appropriate implementation and application to hydroelectric plants. These issues represent the key features of the work, which provides some details of the implementation of the proposed control strategies to these energy conversion systems. The simulations will highlight that the fuzzy regulators are able to provide good tracking capabilities, which are outperformed by adaptive and model predictive control schemes. The working conditions of the considered processes will be also taken into account in order to highlight the reliability and robustness characteristics of the developed control strategies, especially interesting for remote and relatively inaccessible location of many plants.
State-of-Charge Estimation for Lithium-Ion Batteries Using Residual Convolutional Neural Networks

State-of-charge (SOC) is a relative quantity that describes the ratio of the remaining capacity to the present maximum available capacity. Accurate SOC estimation is essential for a battery-management system. In addition to informing the user of the expected usage until the next recharge, it is crucial for improving the utilization efficiency and service life of the battery. This study focuses on applying deep-learning techniques, and specifically convolutional residual networks, to estimate the SOC of lithium-ion batteries. By stacking the values of multiple measurable variables taken at many time instants as the model inputs, the process information for the voltage or current generation, and their interrelations, can be effectively extracted using the proposed convolutional residual blocks, and can simultaneously be exploited to regress for accurate SOCs. The performance of the proposed network model was evaluated using the data obtained from a lithium-ion battery (Panasonic NCR18650PF) under nine different driving schedules at five ambient temperatures. The experimental results demonstrated an average mean absolute error of 1.260%, and an average root-mean-square error of 0.998%. The number of floating-point operations required to complete one SOC estimation was 2.24 × 106. These results indicate the efficacy and performance of the proposed approach.
Effects of waste plastics as partial fine-aggregate replacement for reinforced low-carbon concrete pavements

ABSTRACT Using waste plastics as a partial natural aggregate replacement and monitoring strength and workability reduction in pavement structures is vital to net-carbon zero. This study explores the utilisation of waste plastic as a fine aggregate replacement in medium-strength reinforced concrete pavements, for improving plastic aggregate performance and the intrinsic reasoning for observed strength performance. Various weight fractions of fines were substituted by the same weight of plastic aggregates ranging from 5–15% according to the appropriate standards (Eurocodes and British Standards). The physical and mechanical properties of the composites were analysed. The results indicated that the use of polymeric materials as a partial replacement for fines contributed to a decrease in workability, compressive strength and push-out bond between steel reinforcement and concrete. Despite these trends, 5% replacement of fine aggregates with plastic waste surpassed all the feasibility criteria. Furthermore, using 10% of plastic replacement by weight was deemed feasible in non-structural applications such as roads, pavements, and facades. The outputs have demonstrated environmental engineering concepts in tackling plastic waste, providing an alternative to conventional aggregate. Environmental benefits can arise due to the removal of potentially hazardous plastics from entering ecosystems as well as minimising dredging of global sand reserves.
A comparison of triple test cross and model fitting analyses in two spring wheat crosses.

One hundred and twenty triple teat cross families and a set of six basic generations arising from two breadwheat crosses (9 0 x HD 2009, C 591 x WL 711) were grown in three blocks of randomized block design to detect additive, dominance and epistatic components of genetic variation for grain yield and tillers/plant, grains/spike, grain weight, harvest index, spikelets/spike,and spikelength. The results obtained by triple test cross and modelfitting analysis were in agreement with each other. Additive and additive x additive type of gene actions are more predominant in this material.
Optimal Quantum Circuits for General Two-Qubit Gates

In order to demonstrate nontrivial quantum computations experimentally, such as the synthesis of arbitrary entangled states, it will be useful to understand how to decompose a desired quantum computation into the shortestpossible sequence of one-qubit and two-qubit gates. We contribute to this effort by providing a method to construct an optimal quantum circuit for a general two-qubit gate that requires at most 3 controlled-NOT (CNOT) gates and 15 elementary one-qubit gates. Moreover, if the desired two-qubit gate corresponds to a purely real unitary transformation, we provide a construction that requries at most 2 CNOT and 12 one-qubit gates. We then prove that these constructions are optimal with respect to the family of CNOT, y-rotation, z-rotation, and phase gates.
COMIC DEVELOPMENT OF CHILDREN'S STORIES WITH THE THEME OF CLEAN HEALTHY AND BEAUTIFUL ENVIRONMENT FOR READING MATERIALS IN LOWER CLASS

This study aims to produce children's story comics with the theme of a clean, healthy, and beautiful environment for reading materials in lower grades and to determine the feasibility of using children's comics. This development research uses Research and Development research methods with the ADDIE model, namely Analys (analysis), Design (design), Development (development), Implementation (application), Evaluation (evaluation). The development of children's story comics was made using the Clip Studio Paint and Ibis Paint X applications. The comics were validated by design experts, linguists, and field user validators. Based on the results of the feasibility test, the average percentage of results obtained by design experts is 90.63% and linguists 92.7%. Meanwhile, the percentage result by field user validators for comic design was 94.79% and the percentage result for comic language was 93.05%. The results of this development research show that children's story comics with the theme of a clean, healthy, and beautiful environment for reading materials in lower grades are very suitable for use for lower grade students.
Health Expenditures, Health Infrastructure and Health Status in SAARC Countries: A Panel Data Analysis

Scholars in health economics have been studying the relationship between healthcare expenditure and health outcomes for the last half-century. Researchers emphasized the increase of public health expenditure towards providing primary healthcare based on the logic that health expenditure has a direct effect on the health outcomes of the people. However, such studies have a lot of inconsistencies. Given the background, the present study has three research objectives. First, to investigate the effect of healthcare spending on multiple health outcomes in SAARC nations after controlling for country-specific health infrastructures and economic conditions. Second, to undertake a differential analysis of the effect of public and private healthcare spending (both aggregate and out of pocket) on specific health outcomes. Third, to explore the presence (if any) of the differential effect of health expenditure and health infrastructure variables on specific health outcome variables, including mortality and morbidity indicators. Based on a 20-year (1993–2012) panel data from seven SAARC countries, health expenditure was found to influence improved health outcomes in SAARC nations. In addition, the differential effect of public, private and out-of-pocket (OOP) health expenditure was observed on different health outcomes. Thus, OOP expenditures was found to be the major influencer of life expectancy, death rate and TB instances, while public expenditure was found to be influential for improving infant mortality rate (IMR). The present study supports the notion that disaggregated effects of health expenditure (by including the effect of public, private and OOP expenditures) are needed to get a complete understanding of the health expenditure–health outcome linkage. In addition, the findings emphasize on the role of proximal predictors of health outcomes (alongside expenditure variables in the same model) as important inclusion in the health expenditure-health outcome investigation.
Context-Driven Learning From Professional Development: Examining Teacher Knowledge, Instructional Practice, and Student Mathematics Achievement Gains

Professional development (PD) that sets ambitious goals for teacher learning leading to instructional change is in high demand. Even more critical, but somewhat elusive, are PD programs that have a demonstrable effect on teacher knowledge and classroom practice. Supporting teachers to skillfully implement the Common Core State Standards is currently a key focus of many mathematics PD efforts, with an eye towards helping teachers gain mathematical knowledge for teaching and fluency in instructional decision- making that support students’ learning of challenging content. The Learning and Teaching Geometry (LTG) intervention consists of well-specified PD materials that engage teachers in learning complex geometric concepts targeted in the standards through viewing and discussing videocases. This paper describes a group-randomized study to examine the effectiveness of the LTG intervention in two geographic locations. Although the impact of the intervention on teacher s’ knowledge was modest, a stronger effect on their instructional practice emerged which then predicted greater student gains in the targeted content area. Additionally, teachers in the two locations exhibited context-based differences in their learning. This paper explores the gains teachers made, along with possible explanations for the differences between the locations and implications for future research.
The influence of isometrically derived neck muscle spatial tuning patterns on head response in dynamic conditions

The Chalmers AHBM was setup in LS-DYNA to mimic maximum voluntary contraction (MVC) experiments, and to find the optimum cervical muscle activation parameters for a setup using an optimization model in LS-OPT. The setup in LSDYNA incorporated a discrete beam element with a high stiffness, attached to the head of the AHBM, making it resistant to change in length. Pulling against this beam is similar to pushing against a rigid clamp used in the MVC experimental setups with human volunteers. The AHBM head is constrained in 3D space to have small translational and rotational displacements. Hence, it was considered an apt analogy in the numerical simulations of the AHBM, towards obtaining MVC. A linear response surface was used to obtain optimum values for muscle activation parameters in the design space, with sequential domain reduction and tolerance of convergence set to ±1%. The motion of the models was post-processed in LSPrePost. Muscle activation patterns obtained from optimizations for the two models - one with 9 muscle groups and the other with 13 muscle groups in the neck, were compared with the MVC experiment conducted by Siegmund et al. (2007), and later used for simulation of the AHBM with applied dynamic load in 5 different directions, 0, 45, 90, 135 and 180, using a previously implemented 1 DOF PID controller for the AHBM by Osth (2014) as well as a newly developed 3 DOF PID controller, which was based on functions in LS-DYNA. The dynamic spatial tuning patterns for the optimization models were compared to those obtained from the human volunteer sled experiments conducted by Olafsdottir et al. (2015). The muscle activation patterns from the optimizations showed great variation compared to those obtained from the MVC experiments, due to difference in muscle modelling, constraints on the AHBM and the optimization setup. The dynamic spatial tuning patters for the optimization setups with 1 DOF PID controller were scaled in the same directions as the muscles were activated in the MVC optimizations, however, the 3 DOF PID controller behaved differently. Larger translational and rotational head displacements were observed in the optimization models as compared to the experimental model. Models with 3 DOF PID controller resulted in significantly different kinematics as compared to the models with 1 DOF PID controller.
Global quotients among toric Deligne-Mumford stacks

This work characterizes global quotient stacks---smooth stacks associated to a finite group acting a manifold---among smooth quotient stacks $[M/G]$, where $M$ is a smooth manifold equipped with a smooth proper action by a Lie group $G$. The characterization is described in terms of the action of the connected component $G_0$ on $M$ and is related to (stacky) fundamental group and covering theory. This characterization is then applied to smooth toric Deligne-Mumford stacks, and global quotients among toric DM stacks are then characterized in terms of their associated combinatorial data of stacky fans.
T2-A: Developing Engineering Education Products via Project Ownership Oriented Learning in an Undergraduate Mechanics of Materials Course”

Engineering students can experience hands-on learning in laboratory courses. However, running experiments and analyzing data often demand significant student time. Sinking time into these activities is a challenge because while they may induce learning, data collection and processing produce no tangible external benefit. Students value and engage with activities that carry external impacts complimentary to their own learning. Such learning environments are achieved when multi-semester engineering Capstone Design projects are sponsored by industry and students produce working prototype solutions for companies. However, it remains uncertain whether similar learning environments can be created in a single-semester laboratory course. This paper introduces a new pedagogical technique called “Developing Engineering Education Products via Project Ownership Oriented Learning” (DEEP POOL). This approach is predicated on the hypothesis that student engagement, enthusiasm, and interest in laboratory work will increase if the lab is structured so student activities support the development, construction, testing, and commercialization of real products for an engineering education company. Increased student excitement and participation should produce student achievement of Learning Outcomes on par with or better than conventional lab courses. Jacksonville University’s 2017 Fall Mechanics of Materials course pioneered the DEEP POOL pedagogy. This paper describes how the course’s laboratory component was structured to focus student time toward creating, fabricating, testing, and analyzing new and novel sample coupons for the PASCO EX-5515A Materials Stress-Strain Experiment in collaboration with Engineer Inc, an engineering education technology company.
The Price of War: Macroeconomic and Cross-sectional Effects of Sanctions on Russia

How much do sanctions harm the sanctioned economy? We examine the case of Russia, which has faced three major waves of international sanctions over the last decade (in 2014, 2017, and 2022). In a VAR model of the Russian economy, we first apply sign restrictions to isolate shocks to international credit supply to proxy for the financial sanctions shocks. We provide a microeconomic foundation for the sign restriction approach by exploiting the syndicated loan deals in Russia. We then explore the effects of the overall sanctions shocks (financial, trade, technological, etc.) by employing a high-frequency identification (HFI) approach. Our HFI is based on each OFAC/EU sanction announcement and the associated daily changes in the yield-to-maturity of Russia’s US dollar-denominated sovereign bonds. Our macroeconomic estimates indicate that Russia’s GDP may have lost no more than 0.8% due to the financial sanctions shock, and up to 3.2% due to the overall sanctions shock cumulatively over the 2014–2015 period. In 2017, the respective effects are 0 and 0.5%, and in 2022, they are 8 and 12%. Our cross-sectional estimates show that the real income of richer households declines by 1.5–2.0% during the first year after the sanctions shock, whereas the real income of poorer households rises by 1.2% over the same period. Finally, we find that the real total revenue of large firms with high (low) TFPs declines by 2.2 (4.0)% during the first year after the sanctions shock, whereas the effects on small firms are close to zero. Overall, our results indicate heterogeneous effects of sanctions with richer households residing in big cities and larger firms with high TFPs being affected the most. (JEL: F51, E20, E30)