Low-carbon fly ash concrete is one of the hottest research topics in the concrete industry. This study proposes a design method for low-carbon fly ash concrete that systematically considers strength, form removal time, and carbonation durability life. The basic steps of this method are as follows: First, based on the experimental results, the strength development formula of fly ash concrete using different mix ratios and different aging periods is obtained through regression. The adopted carbonation depth calculation formula can be used to consider the influence of the curing time and mix ratio on carbonation depth. Second, through the analysis of design cases, the dominant factors in the design of low-carbon fly ash concrete are clarified. For example, strength dominates, demolding time dominates, or carbonation durability dominates. If the concrete is removed from the formwork early, the carbonation resistance is very weak, and a large amount of cementitious material is required in order to meet the carbonation durability requirements. Appropriately extending the removal time of the concrete form can enhance the carbonation durability, reduce the content of cementitious materials, and achieve the goal of low-carbon design. In short, the method proposed in this study can be used as a general method for low-carbon fly ash concrete design, and this method can be extended for use in different countries and regions. Full article

The purpose of this study was to evaluate the effect of fermented mixed feed (FMF) (soybean meal–rapeseed meal–corn bran (6:3:1, m/m/m)) on the growth performance, intestinal microbial communities, and metabolomes of squabs. One hundred and eighty 1-day-old squabs were randomly allocated to two groups, each containing six replicates of fifteen squabs cared for by 60 pairs of breeding pigeons secreting crop milk. Each pair of breeding pigeons cared for three squabs. The control group was fed a basal diet, while the experimental group was fed the basal diet containing 5% FMF. The results showed that daily weight gain, carcass weight, villus height, and the mRNA level of ZO-1 in the ileum were increased in the birds fed FMF compared to the control squabs (p < 0.05). Greater abundances of beneficial bacteria such as Lactobacillus, Bifidobacteria, and Bacillus as well as fewer harmful bacteria (i.e., Enterococcus, Veillonella, and Corynebacterium) in the ilea of squabs fed FMF. Six differential metabolites were identified in the FMF-treated squabs; one metabolite was increased (ω-salicoyisalicin) and five were decreased (3-benzoyloxy-6-oxo-12-ursen-28-oic acid, estradiol-17-phenylpropionate, aminotriazole, phosphatidyl ethanolamine (22:6/0:0), and 1-arachidonoylglycerophosphoinositol). Positive correlations were observed between the abundance of Lactobacillus and villus height. Overall, FMF treatment improved both growth and intestinal health in pigeons, suggesting potential benefits for pigeon production. Full article

Range-spread target (RST) detection is an important issue for high-resolution radar (HRR). Traditional detectors relying on manually designed detection statistics have their performance limitations. Therefore, in this work, two deep learning-based detectors are proposed for RST detection using HRRPs, i.e., an NLS detector and DFCW detector. The NLS detector leverages domain knowledge from the traditional detector, treating the input HRRP as a low-level feature vector for target detection. An interpretable NLS module is designed to perform noise reduction for the input HRRP. The DFCW detector takes advantage of the extracted high-level feature map of the input HRRP to improve detection performance. It incorporates a feature cross-weighting module for element-wise feature weighting within the feature map, considering the channel and spatial information jointly. Additionally, a nonlinear accumulation module is proposed to replace the conventional noncoherent accumulation operation in the double-HRRP detection scenario. Considering the influence of the target spread characteristic on detector performance, signal sparseness is introduced as a measure and used to assist in generating two datasets, i.e., a simulated dataset and measured dataset incorporating real target echoes. Experiments based on the two datasets are conducted to confirm the contribution of the designed modules to detector performance. The effectiveness of the two proposed detectors is verified through performance comparison with traditional and deep learning-based detectors. Full article

Background: The objective of this study was to investigate factors influencing Gallium 68 Prostate Specific Membrane Antigen Positron Emission Tomography (Ga68 PSMA PET-CT) uptake for primary staging in prostate cancer. Methods: Retrospective analysis was conducted on 499 non-metastatic and 243 de novo metastatic prostate cancer cases undergoing Ga68 PSMA PET-CT. Demographic, clinical, and imaging data were collected and analyzed. Multivariate logistic regression determined independent risk factors for metastasis detection on Ga68 PSMA PET-CT. Results: Metastatic cases showed higher levels of total PSA, PSA density (dPSA) and biopsy ISUP grade group compared to non-metastatic cases. Multivariate analysis identified cT2 stage and dPSA as independent predictors of metastasis detection on Ga68 PSMA PET-CT. Conclusions: Ga68 PSMA PET-CT plays a crucial role in prostate cancer staging, with identified factors such as clinical T stage and dPSA significantly impacting its diagnostic accuracy. These findings underscore the importance of Ga68 PSMA PET-CT in refining clinical staging and guiding treatment decisions for prostate cancer patients. Full article

Perylenetetracarboxylic diimide (PTCDI) is an n-type organic semiconductor molecule that has been widely utilized in numerous applications such as photocatalysis and field-effect transistors. Polarizability and dipole moment, which are inherent properties of molecules, are important parameters that determine their responses to external electric and optical fields, physical properties, and reactivity. These parameters are fundamentally important for the design of innovative materials. In this study, the effects of external electric fields on absorption and fluorescence spectra were investigated to obtain the PTCDI parameters. The PTCDI substituted by an octyl group (N,N′-Dioctyl- 3,4,9,10-perylenedicarboximide) dispersed in a polymethyl methacrylate (PMMA) matrix was studied in this work. The features of vibronic progression in the absorption spectrum were analogous to those observed in solution. The red shift of the absorption band caused by the Stark effect was mainly observed in the presence of an external electric field. Changes in parameters such as the dipole moment and polarizability between the ground and the Franck–Condon excited states of the PTCDI monomer were determined. The fluorescence spectrum shows a contribution from a broad fluorescence band at wavelengths longer than the monomer fluorescence band. This broad fluorescence is ascribed to the excimer-like fluorescence of PTCDI. The effects of the electric field on the fluorescence spectrum, known as the Stark fluorescence or electrofluorescence spectrum, were measured. Fluorescence quenching is observed in the presence of an external electric field. The change in the polarizability of the monomer fluorescence band is in good agreement with that of the electroabsorption spectrum. A larger change in the polarizability was observed for the excimer-like fluorescence band than that for the monomer band. This result is consistent with exciton delocalization between PTCDI molecules in the excimer-like state. Full article

The photo-induced peroxymonosulfate (photo-PMS) reaction is a promising route to eliminate antibiotics from waste water. To achieve excellent photo-PMS activity in Mg–Fe layered double hydroxides (LDHs) for tetracycline hydrochloride (TCH) degradation under simulative solar-light irradiation, Mg–Fe LDHs-loaded polyacrylonitrile (Mg–Fe/PAN) nanofibers were in-situ prepared via the hydrothermal route. For comparison to the photocatalysis and photo-PMS process, the Mg–Fe/PAN-assisted photo-PMS process exhibited a better elimination activity for TCH elimination. In addition, the photo-PMS activities of Mg–Fe/PAN composites were greatly affected by Mg–Fe LDHs content, TCH concentration, pH, and inorganic salts. Among these Mg–Fe/PAN composites, the optimal MgFe₂/PAN with a Mg/Fe molar ratio of 1:2 and a nominal Mg–Fe LDHs content of 2.0 wt. % removed 81.31% TCH solution of 80 mg L⁻¹ TCH within 120 min. This enhanced photo-PMS capacity of MgFe₂/PAN was ascribed to the abundant active sites formed by functional groups and oxygen defects for efficient TCH species adsorption and photon capturing, and the tight interface between Mg–Fe LDHs nanoparticles and PAN nanofibers for the rapid separation and transfer of photoinduced e⁻/h⁺ pairs. SO₄^•− and •O₂⁻ radicals were vital for the MgFe₂/PAN-assisted photo-PMS reaction. Full article

The challenges posed by climate change and global warming loom large, necessitating a critical initial step towards the long-term growth and the enhancement of both environmental and operational efficiency. Within the energy sector, renewable energy sources are gaining increasing prominence. Consequently, traditional oil and gas companies (OGC) are undergoing a gradual transformation into comprehensive energy corporations, aligning themselves with energy transition policies. This paper examines two types of efficiency measures—operational and environmental—for the 20 largest OGC during the period of 2010–2019. Secondly, this research aims to explore the effect of the global energy transition on both environmental and operational efficiency. Based on three estimation methods, two estimation steps are used in this research. In the first step, the True Fixed Effect (TFE) model and the Battese and coelli (1995) SFA model are applied to evaluate, measure and compare the environmental and operational efficiency scores. In the second step, the TFE model and GMM approach for the dynamic panel data model are used to explore, evaluate and verify the effect of global energy transition on the environmental and operational efficiency of the largest 20 OGC in the world. The results reveal that the average operational efficiency of major OGC measured using the BC.95 model and TFE model is 66% and 85%, respectively, and the overall average level of environmental efficiency for OGC over a 10-year period is 31% (based to B.C.95 model) and 13% (based to TFE model). Our findings reveal that biofuels, solar and hydropower contribute to promote the operational and environmental efficiency of the largest 20 OGC. However, the analysis suggests that while the global energy transition significantly influences and bolsters environmental efficiency, its effect on operational efficiency among these major OGC remains less pronounced and insufficient. Full article

This paper is devoted to the continualization of a diatomic lattice, taking into account natural intervals of wavenumber changes. Continualization refers to the replacement of the original pseudo-differential equations by a system of PDEs that provides a good approximation of the dispersion relations. In this regard, the Padé approximants based on the conditions for matching the values of the dispersion relations of the discrete and continuous models at several characteristic points are utilized. As a result, a sixth-order unconditionally stable system with modified inertia is obtained. Appropriate boundary conditions are formulated. The obtained continuous approximation accurately describes the amplitude ratios of neighboring masses. It is also shown that the resulting continuous system provides a good approximation for the natural frequencies. Full article

Accurate air quality prediction is paramount in safeguarding public health and addressing air pollution control. However, previous studies often ignore the geographic similarity among different monitoring stations and face challenges in dynamically capturing different spatial–temporal relationships between stations. To address this, an air quality predictive learning approach incorporating the Third Law of Geography with SAM–CNN–Transformer is proposed. Firstly, the Third Law of Geography is incorporated to fully consider the geographical similarity among stations via a variogram and spatial clustering. Subsequently, a spatial–temporal attention convolutional network that combines the spatial attention module (SAM) with the convolutional neural network (CNN) and Transformer is designed. The SAM is employed to extract spatial–temporal features from the input data. The CNN is utilized to capture local information and relationships among each input feature. The Transformer is applied to capture time dependencies across long-distance time series. Finally, Shapley’s analysis is employed to interpret the model factors. Numerous experiments with two typical air pollutants (PM_2.5, PM₁₀) in Haikou City show that the proposed approach has better comprehensive performance than baseline models. The proposed approach offers an effective and practical methodology for fine-grained non-stationary air quality predictive learning. Full article

The reasonable and effective application of waste tires and discarded concrete in concrete is an important branch of green concrete development. This paper investigates the effects of the inorganic modification mode on the basic mechanical properties of rubber recycled concrete based on indoor tests. Inorganic modification, such as water washing, acid washing, and alkaline washing modification, was mainly used to treat and modify rubber particles. The factors affecting the compressive strength, the splitting tensile strength, the flexural strength, the axial compressive strength, and the modulus of elasticity of modified rubber recycled concrete were analyzed. The study results show that the incorporation of recycled aggregates and rubber reduced the mechanical properties of concrete, with the compressive and splitting tensile strengths showing the greatest reductions of 27.36% and 27.24%, respectively. Three modification methods significantly improved the mechanical properties of rubber recycled concrete. The alkali washing modification method was the most effective, maximally improving the mechanical properties of rubber recycled concrete by 7.53–15.51%. The effects of the three modifications on the mechanical properties of concrete were ranked as follows: alkali washing > acid washing > water washing. This study provides a data basis for the practical application of rubber recycled concrete in engineering and a test basis for the development of green concrete. Full article

In this work, comprehensive ab initio quantum chemical calculations using the DFT level of theory were performed to characterize the stabilization interactions (H-bonding and hyperconjugation effects) of two stable symmetrical conformations of α-, β-, and γ-cyclodextrins (CDs). For this purpose, we analyzed the electron density using “Atom in molecules” (AIM), “Natural Bond Orbital” (NBO), and energy decomposition method (CECA) in 3D and in Hilbert space. We also calculated the H-bond lengths and OH vibrational frequencies. In every investigated CD, the quantum chemical descriptors characterizing the strength of the interactions between the H-bonds of the primary OH (or hydroxymethyl) and secondary OH groups are examined by comparing the same quantity calculated for ethylene glycol, α-d-glucose (α-d-Glcp) and a water cluster as reference systems. By using these external standards, we can characterize more quantitatively the properties of these bonds (e.g., strength). We have demonstrated that bond critical points (BCP) of intra-unit H-bonds are absent in cyclodextrins, similar to α-d-Glcp and ethylene glycol. In contrast, the CECA analysis showed the existence of an exchange (bond-like) interaction between the interacting O…H atoms. Consequently, the exchange interaction refers to a chemical bond, namely the H-bond between two atoms, unlike BCP, which is not suitable for its detection. Full article

Lake sediment records are of great importance for understanding the evolution of watershed environments. Various studies have been carried out to determine the depositional ages of lake sediments and to examine their physical, chemical, and biological characteristics. The aim is to construct the historical vegetation, environment, and climate patterns in Chinese lake watersheds. In this review, we obtained relevant studies on lake sediment records by searching the key word ‘age-depth’ from the following databases: Web of Science and the China National Knowledge Infrastructure (CNKI, the largest Chinese academic database). We analyzed the literature based on its type (published in a Chinese/English journal or as a Master’s/PhD thesis), period of publication, journal (if published in a journal), key authors, study area, dating scale, and main aims. The results suggest that the lakes in the plateau regions are the most popular research topic, typically covering 100–200 years (short-term) and 500–30,000 years (long-term). The literature focuses on a wide range of topics, from past environmental evolution in watersheds to lake ecology, and it provides a solid foundation for a better understanding of the regional climate change and the preservation of lake environments and ecosystems. In the future, the resulting data obtained from environmental reconstructions with lake sediments will need to be integrated with emerging information processing technologies (e.g., artificial intelligence and meta-analysis) to disentangle the complex interplay between the Earth’s surface processes and global climate change; furthermore, strengthening interdisciplinary collaboration will deepen our comprehension of the man-land relationship and promote the sustainable management of lake ecosystems in the context of global climate change. Full article

The level of difficulty of mathematical test items is a critical aspect for evaluating test quality and educational outcomes. Accurately predicting item difficulty during test creation is thus significantly important for producing effective test papers. This study used more than ten years of content and score data from China’s Henan Provincial College Entrance Examination in Mathematics as an evaluation criterion for test difficulty, and all data were obtained from the Henan Provincial Department of Education. Based on the framework established by the National Center for Education Statistics (NCES) for test item assessment methodology, this paper proposes a new framework containing eight features considering the uniqueness of mathematics. Next, this paper proposes an XGBoost-based SHAP model for analyzing the difficulty of mathematics tests. By coupling the XGBoost method with the SHAP method, the model not only evaluates the difficulty of mathematics tests but also analyzes the contribution of specific features to item difficulty, thereby increasing transparency and mitigating the “black box” nature of machine learning models. The model has a high prediction accuracy of 0.99 for the training set and 0.806 for the test set. With the model, we found that parameter-level features and reasoning-level features are significant factors influencing the difficulty of subjective items in the exam. In addition, we divided senior secondary mathematics knowledge into nine units based on Chinese curriculum standards and found significant differences in the distribution of the eight features across these different knowledge units, which can help teachers place different emphasis on different units during the teaching process. In summary, our proposed approach significantly improves the accuracy of item difficulty prediction, which is crucial for intelligent educational applications such as knowledge tracking, automatic test item generation, and intelligent paper generation. These results provide tools that are better aligned with and responsive to students’ learning needs, thus effectively informing educational practice. Full article

Developments in digital twins are driven by the availability of sensor technologies, big data, first principles knowledge, and advanced analytics. In this paper, we discuss these changes at a conceptual level, presenting a shift from nominal engineering, aiming at design optimisation, to performance engineering, aiming at adaptable monitoring diagnostic, prognostic, and prescriptive capabilities. A key element introduced here is the role of emulators in this transformation. Emulators, also called surrogate models or metamodels, provide monitoring and diagnostic capabilities. In particular, we focus on an optimisation goal combining optimised and robust performance derived from stochastic emulators. We demonstrate the methodology using two open-source examples and show how emulators can be used to complement finite element and computational fluid dynamic models in digital twin frameworks. The case studies consist of a mechanical system and a biological production process. Full article

Background and Objectives: Erdosteine (Erd) is an antioxidant and anti-inflammatory drug. Vitamin B has been reported to exert anti-inflammatory and antioxidant effects. In this study, we investigated the effect of erdosteine and vitamin B complex on a liver ischemia/reperfusion (I/R) model. Materials and Methods: Thirty-two Wistar Albino male rats weighing 350–400 g were used. The animals were randomly selected and divided into four groups. The groups are as follows: first group (Sham), second group (I/R), third group (I/R + vit B), and fourth group (I/R + vit B + Erd). Rats were subjected to 45 min of hepatic ischemia, followed by a 45 min reperfusion period in the I/R and Vitamin B + Erd groups. An amount of 150 mg/kg/day of erdosteine was given orally for 2 days, and 0.05 mL/kg of i.p. vitamin B complex was given 30 min before the reperfusion. Serum biochemical parameters were measured. Serum Total Antioxidant Status (TAS) and Total Oxidant Status (TOS) were measured, and the Oxidative Stress Index (OSI) was calculated. Hepatic tissue samples were taken for the evaluation of histopathological features. Results: In terms of all histopathological parameters, there were significant differences in the I/R + vit B group and I/R + vit B + Erd group compared with the I/R group (p < 0.01). In terms of aspartate aminotransferase (AST), alanine aminotransferase (ALT), lactate dehydrogenase (LDH), TNF-alpha, and IL-6 levels, there were significant differences between the I/R group and treatment groups (p < 0.01). The lowest TOS and OSI levels were obtained in the treatment groups, and these groups had statistically significantly higher TAS levels compared with the sham and I/R groups (p < 0.01). Conclusions: As a preliminary experimental study, our study suggests that these agents may have potential diagnostic and therapeutic implications for both ischemic conditions and liver-related diseases. These results suggest that the combination of vit B + Erd may be used to protect against the devastating effects of I/R injury. Our study needs to be confirmed by clinical studies with large participation. Full article

Glass was introduced as an additive to filaments used for the manufacturing of composite materials, employed by Additive Manufacturing applications. Glass accounts for a large waste electric and electronic equipment (WEEE) percentage, and its recovery and recycling can lead to the production of sustainable composite materials. In this work, poly(lactic acid) (PLA)/commercially available silicon oxide composite filaments were manufactured and their structural, thermal, rheological, and mechanical properties were assessed. Scanning Electron Microscopy confirmed the 1:2 ratio of silicon: oxygen, along with the relatively low adhesion between the filler and the matrix. Differential Scanning Calorimetry presented steady glass transition and melting temperatures of composites, whereas a crystallization temperature of 10% wt. and a crystallinity of 15% wt. composite slightly increased. Rheological analysis showcased that the viscosity of the composite filaments decreased compared to PLA (10–100 compared to 300–400 Pa·s), with a more shear-thinning behavior. Dynamic mechanical analysis exhibited increased elastic, flexural moduli, and flexural strength of composites (up to 16, 23, and 11%, respectively), whereas tensile strength and elongation decreased. The affordability of raw materials (with the future introduction of recycled ones) and the minimal processing steps can lead to the potential scaling up of the study. Full article

The third generation of the BeiDou navigation satellite system (BDS-3) can transmit five-frequency signals. The real-time satellite clock offset of BDS-3 is typically generated utilizing the B1I/B3I combination with the ambiguity-float solutions. By conducting the ambiguity resolution (AR), the reliability of the satellite clock offset can be improved. However, the performance of BDS-3 ambiguity-fixed real-time satellite clock offset with B1C/B2a signals remains unknown and unrevealed. In this contribution, the performance of the BDS-3 ambiguity-fixed satellite clock offset with the new B1C/B2a signals is investigated. One week of observation data from 85 stations was used to perform ambiguity-fixed satellite clock offset estimation. For B1I/B3I and B1C/B2a signals, the wide-lane (WL) uncalibrated phase delay (UPD) on the satellite end is fairly stable for one day, while the narrow-lane (NL) UPD standard deviation (STD) amounts to 0.122 and 0.081 cycles, respectively. The mean ambiguity fixing rate is 80.7% and 78.0% for these two signal combinations, and the time to first fix (TTFF) for the B1C/B2a signals is remarkably shorter than that of the B1I/B3I signals. The STDs of the ambiguity-float and -fixed satellite clock offsets are 0.033 and 0.026 ns, respectively, for the B1I/B3I combination, and it is reduced to 0.024 and 0.023 ns for B1C/B2a signals, respectively. Using the estimated UPD and clock offset products, the positioning performance of the kinematic Precise Point Positioning (PPP)-AR results amounts to 1.56, 1.23, and 4.46 cm in the east, north, and up directions for B1I/B3I signals, respectively. It is improved to 1.36, 1.16, and 4.25 cm using the products estimated with the B1C/B2a signals, with improvements of 12.8%, 5.7%, and 4.7% in three directions, respectively. The experiments showed that the performances of the ambiguity-fixed satellite clock offsets and the PPP-AR results using B1C/B2a signals are better than those of B1I/B3I. Full article

The paper compares the performance of two bio-ester and two mineral-oil emulsion metalworking fluids (MWFs) in finish turning an Inconel 718 alloy bar with a high hardness (HB 397–418). In this study, a coolant with a lean concentrate diluted at 6.5% to create an emulsion with stabilised water hardness was used to prepare each MWF. The finish-turning method used a small tool nose radius (0.4 mm) and small depth of cut (0.25 mm) to turn down 52.5-mm diameter bars in multiple passes to reach a maximum tool flank wear of 200 µm. In each MWF turning test, the tool flank wear, cutting forces, and surface roughness were measured against cut time. Chips from each MWF turning test were also collected at the same cut time instances. The surface and subsurface integrity on a workpiece obtained from each MWF turning test were compared by using a new unworn tool. Overall, for the machining parameters studied, the findings suggest the bio-esters were capable of equivalent machining performance as the mineral-oil emulsions, apart from one bio-ester that displayed improved surface roughness. Common to all MWF turning tests was a change in the chip form at low flank wear, which is discussed. Further findings discussed include the sensitivity of the concentration of the MWF diluted in the emulsion and the effect of the workpiece hardness within the batch used, with useful recommendations to improve the finish-turning method for the assessment of MWFs. Full article

To measure vibration signals, a low-frequency fiber Bragg grating (FBG) acceleration sensor featuring a flexible hinge with a spring support and symmetric compensation structure has been designed. Based on the mechanical model of the sensor’s structure, the expressions for sensitivity and resonant frequency of the sensor are derived. The structural parameters of the sensor are optimized, and a simulation analysis is conducted using ANSYS 19.2 software. According to the results of simulation analysis and size optimization, the sensor prototype is constructed. Subsequently, its amplitude-frequency response, sensitivity, and temperature characteristics are investigated through vibration experiments. The experimental results show that the resonant frequency of the sensor is 73 Hz, the operating frequency range is 0~60 Hz, and the sensitivity measures 24.24 pm/g. This design meets the requirements for measuring vibration signals at low frequencies. Full article

To explore and compare the failure modes, deformation behaviors, and load-bearing capacities of single-edge notched (SEN) beams strengthened with carbon fiber-reinforced polymer (CFRP) and steel bars, static and dynamic three-point bending tests on both types of concrete beams have been carried out in this study. During the static tests, the electro-hydraulic servo machine served as a loading device to apply pressure to CFRP beams and reinforced concrete (RC) beams. During the impact experiments, different impact velocities were imparted by adjusting the drop hammer’s height. Thus, information regarding crack propagation, energy absorption, and deformation was obtained. The results from the static tests showed that the RC beams predominantly experienced shear failure. In contrast, the CFRP beams primarily exhibited bending–shear failure, attributed to the relatively weaker bond strength between the bars and the concrete. Impact tests were conducted at three different velocities in this study. As the impact velocity increased, both types of concrete beams transitioned from bending failure to bending–shear failure. At the lowest velocity, the difference in energy absorption between beams reinforced with different materials was insignificant during the bending process. However, at the highest velocity, CFRP beams absorbed less energy than RC beams. The study of structures’ impact failure modes and their mechanical characteristics offers valuable references for the anti-collision design and protection of structures. Full article

This paper tests the hypothesis that action-based fiscal consolidations have a negative effect on GDP growth. Using the IMF’s dataset on action-based fiscal consolidations, instrumental variables’ regressions show that action-based fiscal consolidations have a significant positive effect on GDP growth. The instrumental variables’ regressions also show that action-based fiscal consolidations significantly increase investment and productivity. The findings presented in this paper thus strongly reject the hypothesis that action-based fiscal consolidations reduce growth. The paper argues that least squares estimates presented in previous literature suffer from negative reverse causality bias: GDP growth has a significant positive effect on both the likelihood and the magnitude of action-based fiscal consolidations. To uncover causal effects of action-based fiscal consolidations, researchers need to use an instrumental variables approach. Full article