Concrete is the most widely used material in construction. It has the characteristics of strong plasticity, good economy, high safety, and good durability. As a kind of structural material, concrete must have sufficient strength to resist various loads. At the same time, due to the brittleness of concrete, compressive strength is the most important mechanical property of concrete. To solve the disadvantages of the low efficiency of the traditional concrete compressive strength prediction methods, this study proposes a firefly algorithm (FA) and random forest (RF) hybrid machine-learning method to predict the compressive strength of concrete. First, a database is built based on the data of published articles. The dataset in the database contains eight input variables  and one output variable (concrete compressive strength). Then, the correlation of the eight input variables was analyzed, and the results showed that there was no high correlation between the input variables; thus, they could be used as input variables to predict the compressive strength of concrete. Next, this study used the FA algorithm to optimize the hyperparameters of RF to obtain better hyperparameters. Finally, we verified that the FA and RF hybrid machine-learning model proposed in this study can predict the compressive strength of concrete with high accuracy by analyzing the R values and RSME values of the training set and test set and comparing the predicted value and actual value of the training set and test machine. Concrete is made up of cementitious material, aggregate, water, admixture, and mineral admixture following a certain proportion by uniform mixing, compaction molding, curing hardening, and becoming a kind of artificial stone ,2,3,4,5.However, in the process of concrete preparation, when cement particles contact with water, the clinker minerals on the surface of cement particles will immediately hydrolyze or hydrate with water to generate new hydration products and release a certain heat, which is called the hydration reaction of concrete ,23. For The heat release rate and size of the hydration heat mainly depend on the mineral composition of cement, cement fineness, admixture, and other factors, among which the mineral composition is the most important factor . The ratAlthough the hydration heat can accelerate the growth of the early strength of concrete, increase the frost resistance of concrete, and has the advantage for concrete construction projects in the winter, the heat in the concrete due to hydration gathered in the interior is not easy to release, which results in a dramatic increase in the temperature inside the concrete, and thus a large temperature difference between the concrete inside and outside, and this causes apparent temperature stress and makes the concrete crack, which greatly affects the strength and other properties of concrete . At the same time, the cement production process will discharge emissions, which has brought a high burden to the environment . To easeResearchers have successfully applied fly ash into concrete after a great deal of research and achieved good results in improving the performance of concrete. Zhu et al. studied the influence of fly ash on the durability of concrete pavement, and the research results showed that the concrete mixed with fly ash could not only reduce the amount of cement but also have a good influence on the durability of concrete ,28. HuanWhen the content of fly ash exceeds 10%, this effect is weakened, and when the expansion agent and fly ash are mixed into concrete at the same time, the original fly ash must be used . Jang etBlast furnace slag is a kind of organic melting mixture discharged from a blast furnace when smelting pig iron, and it is a type of industrial waste residue. In recent years, increasing researchers have paid attention to the improvement of concrete performance by blast furnace slag. Vibha et al. studied the effects of blast furnace slag on the slump, compressive strength, bending strength, and splitting tensile strength of concrete at different displacement levels . Wang etThe results show that air-warming blast furnace slag and crushed limestone both have positive effects on the mechanical properties of concrete, and the influence of air-warming blast furnace slag on the mechanical properties of concrete is better than that of crushed limestone . The comOtherwise, the addition of mineral admixtures will not only not improve the compressive strength of concrete but also negatively affect the properties, such as cohesion, segregation, and condensation time of secreting water. As the quality of fly ash and blast furnace slag is different in different regions, it is of great significance to study the influence of fly ash and blast furnace slag on the compressive strength of concrete. The laboratory test method is the most common method used by researchers to study the compressive strength of concrete. However, the laboratory experiment method has the disadvantages of low efficiency, high cost, and energy consumption. To solve these problems, many researchers have proposed the machine-learning method to predict the compressive strength of concrete. Cui et al. proposed the XGBoost model based on the Boosting Tree algorithm to predict the compressive strength of concrete, and the research results show that the model has high prediction accuracy when the compressive strength is greater than 40 MPa . Al-Shamir et al. proposed a regularized extreme learning machine (RELM) to predict the compressive strength of concrete and used k-fold cross-validation to evaluate the reliability of the established RELM model. The results show that compared with other models, the RELM model can predict the compressive strength of concrete more accurately . The aboAlthough there are many scholars put forward using machine-learning method to predict the compressive strength of concrete, it should be pointed out that most of the prediction models still exist problems, such as low efficiency and bad prediction results ,47,48,49A new regression technique RF algorithm has been used to predict the compressive strength, which is more accurate and computationally efficient than other commonly used prediction tools ,59,60,61In addition, RF can measure the relative importance score of each input variable to quantify the significance level of each influence parameter on the compressive strength of concrete. Therefore, to improve the accuracy and efficiency of the machine-learning model to predict the compressive strength of concrete, a method of predicting concrete compressive strength with the FA and RF hybrid machine-learning model is proposed in this paper.The database is the basis for verifying whether a machine-learning model can accurately predict the compressive strength of concrete. To ensure the sufficient accuracy of the data sets, 225 data sets were collected from the previous literature published by other authors, and a database was established with these data sets . The datA reliable database is a key to verifying the prediction accuracy of concrete compressive strength by the model. To verify the reliability of the database, the author analyzed the data set of the database as shown in To see the data distribution of the nine variables in the database more intuitively, we made the frequency distribution histogram of the nine variables, as shown in The analysis of two or more variables that are correlated is called correlation analysis, which measures the closeness of the relationship between two variables. The correlation coefficient between input variables is high positive or high negative, in other words, the high correlation between input variables will affect the prediction effect of the model. To determine the correlation between input variables, this study conducted correlation analysis on the eight input variables before the model training the result is shown in In this study, a hybrid FA and RF machine-learning model is proposed to predict the compressive strength of concrete, where FA is used to tune the hyperparameters of RF and RF is used to predict the compressive strength of concrete.FA is a meta-heuristic algorithm based on firefly flashing behavior. The main idea of the firefly algorithm is that a firefly with weak light moves to a firefly with strong light to complete a position update. The firefly algorithm has the following three assumptions: (1) fireflies are not differentiated in gender, and fireflies with strong luminescence will attract fireflies with weak luminescence. (2) The attraction between fireflies is proportional to the brightness. (3) The brightest fireflies make random movements. Based on the above three assumptions, the mathematical model of the firefly algorithm is obtained as follows :iI is used to represent the absolute brightness of the ith firefly, and the objective function value of the firefly’s location was expressed by the absolute brightness of the firefly. The absolute brightness iI of the firefly located at First, ith firefly is brighter than the jth firefly, the jth firefly will move toward the ith firefly due to the attraction of the ith firefly. The attraction of the ith firefly to the jth firefly is proportional to its relative brightness. The relative brightness of the ith firefly to the jth firefly is defined as:iI is the brightness of the ith firefly, and γ is the absorption coefficient of light intensity.If the ith firefly to the jth firefly is proportional to the brightness of the ith firefly to the jth firefly, the attraction of the ith firefly to the jth firefly is defined as:β0 is the maximum attraction, ijβ is the attraction of the ith firefly to the jth firefly, ijr is the Cartesian distance of the ith firefly to the jth firefly, and is defined as:Assuming that the attraction of the jth firefly is updated because it is attracted by the ith firefly, and the updated formula is:t is the number of iterations, α is constant, and usually α ∈ . As can be seen from the position update formula, position update mainly depends on the attractiveness, if β0 = 0 in the position update formula, the formula becomes a random walk model. The code of the firefly algorithm can be found in the appendix section. Suppose that the position of the x into RF and find the final output RF algorithm is a typical integrated learning algorithm. RF is based on statistical theory and uses autonomous resampling technology to extract multiple sample sets from training samples. The algorithm constructs several decision tree models by using the extracted sample sets and gathers the decision tree models together to obtain the final result by voting or taking the average. RF is an ensemble classifier constructed by a decision tree model Machine learning has its super-parameters in operation, and these parameters have a great influence on itself. These parameters are often not obtained by training but need to be set before the learning process begins. There are many hyperparameters in the machine-learning model. Before running the machine model, the hyperparameters can be optimized utilizing hyperparameter tuning to improve the performance of the machine-learning model. In this study, the FA model was used to optimize the hyperparameter of the RF model. The relationship between iterations and RSME value is shown in A common test method used to test the accuracy of an algorithm is 10-fold cross-validation. The main idea of this method is to randomly divide the data set into ten parts, and take nine of them and one of them as the test data, in turn, for the experiment. To further obtain the corresponding optimized hyperparameters, 10-fold cross-validation was used for hyperparameter tuning in this study. The results of the 10-fold cross-validation are shown in In the field of machine learning, models need to be evaluated to verify the performance of trained models. Different types of models use different evaluation methods. After the establishment of the machine-learning model for concrete compressive strength prediction, the next important step is to evaluate the prediction effect of the established machine-learning model. In this study, the accuracy of the prediction of concrete compressive strength by the RF model was verified by comparing the predicted value and actual value of concrete compressive strength. To see the fitting effect of predicted value and actual value of training set and test set more intuitively, the scatter diagram of predicted value and actual value of training set and test set is given in However, it should be noted that the minor differences in individual data points do not affect the overall predictive performance of the RF model, that is, the RF model can accurately predict the compressive strength of concrete. The R value of the training set is 0.9747, the RSME value is 3.6037, the R value of the test set is 0.8753, and the RMSE value is 6.6271. Thus, the R value and RMSE value of the training set and the test set have common characteristics—namely, their R value is high, and their RSME value is low. It is proved again that the RF model tuned by FA has a good effect on predicting the compressive strength of concrete, and there is no over-fitting situation.That is to say, cement also has a great influence on the compressive strength of concrete, and the compressive strength of concrete is proportional to the amount of cement. The importance of blast furnace slag, water, superplasticizer, fly ash, coarse aggregate, and fine aggregate to the compressive strength of concrete is 0.8551, 0.7639, 0.5629, 0.4696, 0.1839, decreasing successively. Thus, the importance of these six variables to the compressive strength of concrete decreases successively. From the importance score of variables, it can be seen that the compressive strength of concrete is proportional to the eight variables, that is, the increase in any one of the eight variables will improve the compressive strength of concrete. Since age and cement have a great influence on the compressive strength of concrete, engineers should pay more attention to the age and cement when designing concrete with high compressive strength, and less attention should be paid to the amount of fine aggregate.In this study, a hybrid FA and RF machine-learning model was proposed to predict the compressive strength of concrete. A database of 225 data sets was established based on previously published articles, which was used as the data set for predicting the compressive strength of concrete. The data set took cement, blast furnace slag, fly ash, water, superplasticizer, coarse aggregate, fine aggregate, and age as the input variables. The concrete compressive strength was used as the output variable. The FA algorithm was used to tune the hyperparameters of the RF algorithm, and then the results of the hyperparameter tuning were verified by 10-fold cross-validation. Finally, the accuracy of the model was verified by analyzing the R value and RSME values well as the predicted value and actual value of the training set and the test set. The following conclusions can be drawn from the research process.1.Using FA to tune the hyperparameter of RF, the RSME value decreases greatly at first and then tends to be stable with the increase in iteration number, this proves that FA can achieve better results in adjusting the hyperparameter optimization of the RF model, which is better than the random selection of hyperparameters.2.The RF model tuned by FA can be used to predict the compressive strength of concrete and achieve better results. The R values of the training set and the test set were 0.9747 and 0.8753, respectively, and the RSME values were 3.6037 and 6.6271, respectively—that is, the training set and the test set both had high R values and low RSME values, and the consistency between the predicted value and the actual value of the concrete compressive strength of the training set and the test set was high. The above two conclusions prove that the FA and RF mixed models achieved better results in predicting the compressive strength of concrete.3.The importance scores of age, cement, blast furnace slag, water, superplasticizer, fly ash, coarse aggregate, and fine aggregate to the compressive strength of concrete decreased successively and were all positive. That is, the compressive strength of concrete was proportional to these eight variables, and the importance of these eight variables to the compressive strength of concrete decreased in turn.


With no need for any pre‐irradiation, the as‐fabricated SAOCD/PDMS elastomer could exhibit intense and persistent ML under mechanics stimuli directly, which greatly facilitates its applications in mechanics lighting, displaying, imaging, and visualization. By investigating the matrix effects as well as the thermoluminescence, cathodoluminescence, and triboelectricity properties, the interfacial triboelectrification‐induced electron bombardment processes are demonstrated to be responsible for the self‐charged energy in  SAOCD under mechanics stimuli. Based on the unique self‐charging processes, the SAOCD/PDMS further exhibits mechanics storage and visualized reading activities, which brings novel ideas and approaches to deal with the mechanics‐related problems in the fields of mechanical engineering, bioengineering, and artificial intelligence.Persistent mechanoluminescence (ML) with long lifetime is highly required to break the limits of the transient emitting behavior under mechanics stimuli. However, the existing materials with persistent ML are completely trap‐controlled, and a pre‐irradiation is required, which severely hinders the practical applications. In this work, a novel type of ML, self‐charging persistent ML, is created by compositing the Sr 3Al2O5Cl2:Dy3+ powders into flexible polydimethylsiloxane matrix. In addition to facilitating the applications in mechanics displaying and visualization, the unique self‐charging processes endow the materials with mechanics storage and visualized reading activities, showing broad application prospects in mechanical engineering, bioengineering, and artificial intelligence.Herein, a novel type of mechanoluminescence (ML), self‐charging persistent ML, is reported by compositing the Sr In particular, by using the visible luminescent signals as the medium, ML could enable in situ, remote, distributed and visualized mechanics sensing for complex and irregular interfaces. Therefore, ML is highly promising to develop the next‐generation stress sensing and monitoring technology. Nevertheless, most of the current ML materials intrinsically exhibit instantaneous luminescence with a short lifetime ranging from nanoseconds (ns) to microseconds (ms). Hence, when instantaneous ML is applied for mechanics displaying, imaging and visualization, the emitted ML signals can only be captured by the professional spectrometers, which is evidently inconvenient for the practical applications.Mechanoluminescence (ML) is a phenomenon featuring light‐emitting behaviors when they are subjected to mechanics stimuli, such as fracture, friction, compression, grinding and stretching.1, 2 In previous researches, very limited material systems have been reported to have persistent ML. Smet and co‐workers reported that the BaSi2O2N2:Eu2+ can exhibit blue–green ML which remains visible after removing mechanics for several seconds. Our group further modified the persistent ML of BaSi2O2N2:Eu2+ by introducing Sr2+, and the developed Ba0.5Sr0.5Si2O2N2:Eu2+ exhibited an even higher ML intensity with the persistent time prolonged to tens of seconds. In addition, we also reported another two material systems, i.e., LiGa5O8 and Sr2P2O7:Eu,Y, which showed green and blue persistent ML, respectively. The persistent light‐emitting feature after mechanics stimuli undoubtedly allows the displaying and visualization of mechanics to exist for a while, which is easy to be observed by the naked eyes or the common cameras. Therefore, it shows high convenience and practicability for mechanics visualization‐related applications. However, it should be noted that all of the reported persistent ML is actually established from the trap structure engineering, i.e., the pre‐filled energy in deep traps could be released to the shallow trap under mechanics stimuli, after which the energy in the shallow trap could be spontaneously and continuously transferred to the energy levels of luminescent centers producing the as‐observed persistent ML. Thus, the previous persistent ML always requires pre‐irradiation treatment on the materials to pre‐store energy, which increases the difficulty of the practical applications. As a result, it is highly desirable to develop self‐charging persistent ML that could self‐charge energy in the structure under mechanics stimuli to generate continuous ML with no need for pre‐irradiation.The development of long lifetime ML, i.e., persistent ML, is an effective approach to overcome the drawbacks derived from the instantaneous ML.27 In 3Al2O5Cl2 could exhibit self‐activating ML in the flexible polydimethylsiloxane (PDMS) matrix with the interfacial triboelectrification‐induced electron bombardment processes. Herein, by comprehensively considering the ML self‐activating processes as well as the shallow trap structure with spontaneous transfer activity, we synthesized Sr3Al2O5Cl2:Dy3+ (SAOCD) powders in this work, and investigated their ML performance by compositing with PDMS. It is found that the SAOCD powders could exhibit intense and self‐activating ML in PDMS under mechanics stimuli with no need for any pre‐irradiation. The most attractive feature is that the self‐activating ML of SAOCD/PDMS could last for a certain period, suggesting that we have successfully achieved the self‐charging persistent ML behaviors. In addition to facilitating the practical applications in mechanics displaying and visualization by the development of self‐charging persistent ML, the unique self‐charging processes further endow the SAOCD/PDMS composites with mechanics storage and visualized reading activities, which shows broad application prospects in the fields of mechanical engineering, bioengineering and artificial intelligence.The self‐charging persistent ML should be established on the self‐activating ML processes, in which the ML could be directly produced by the mechanics stimuli with no need for any other assistance or any pre‐stored energy. By introducing appropriate shallow tarp level and further connecting it to the ML self‐activating processes, it is feasible to realize the as‐expected self‐charging persistent ML. Very recently, we reported that the rare earth‐doped Srrocesses.32 Her22.13Al2O5Cl2 is illustrated in Figure 3Al2O5Cl2 belongs to the orthorhombic space group 12121P2, in which Al3+ and Sr2+ ions exist in the forms of [AlO4] tetrahedra and [SrO5Cl4] polyhedra, respectively. Considering the ionic radii of Sr2+ , Al3+ (RCN = 4 = 0.39 Å) and Dy3+ (RCN = 9 = 1.083 Å), the dopant of Dy3+ should substitute the ninefold coordination Sr2+ site in Sr3Al2O5Cl2 to form a solid solution, instead of the fourfold coordination Al3+ site. Figure 3+ doping contents. It is found that the patterns are narrow and strong, suggesting that the samples have high crystallinity. Meanwhile, all the diffraction peaks match well with the standard inorganic crystal structure database PDF no. 97‐006‐8365 (ICSD file no. 68365), indicating that the single phase has been obtained for all samples and no any impurity phase is formed after doping with Dy3+ ions.The crystal structure of Sr6H15/2→4K13/2, 6H15/2→4K15/2, and 6H15/2→6P7/2, 4M15/2 transitions of Dy3+, respectively. The peaks at 269 and 343 nm could be originated from the oxygen vacancy defects, which could be further confirmed by the atmosphere experiment  image was measured to reveal the morphology and microstructure of SAOCD, as shown in Figure ectively.36 The2.2Figure 3+ ions under the stretching mode . The samples all show light‐yellow ML composed of three main emission peaks at 490, 580, 674 nm, corresponding to the characteristic Dy3+ transitions of 4F9/2→6H15/2, 4F9/2→6H13/2, 4F9/2→6H11/2, respectively. No emissions from 400 to 450 nm can be found in the ML spectra, suggesting that the intrinsic oxygen vacancies are not involved in the ML processes. With the increase of Dy3+ content, the ML intensity of SAOCD/PDMS composite elastomers increases first and then decreases due to the concentration quenching, and the optimum doping content of Dy3+ is obtained as 0.04. The ML intensity also exhibits a direct responsiveness to the applied stress/strain. As shown in Figure  showing broad applications in the fields of structural health monitoring, bio‐mechanics monitoring and artificial intelligence.To facilitate the ML investigation, the SAOCD powders were composited with PDMS because of its efficient stress transfer ability and transparent characteristic. The fabrication processes are illustrated in ectively.36 No  To further confirm this viewpoint, the ML performance for the SAOCD/PDMS with various contents of traps was investigated. The samples were filled with energy by an ultraviolet (UV) lamp first, and then pre‐heat‐treated at various temperature for 10 min. In this case, the contents of the trapped carriers are gradually decreased with the increase of the pre‐treated temperature. When the pre‐treated temperature reaches 623 K, most of the carriers can be cleared as shown in Figure It should be noted that the ML of the as‐fabricated SAOCD/PDMS elastomer can be directly generated with no need for any pre‐irradiation. This suggests that the ML of SAOCD/PDMS should be independent from the intrinsic traps, which is different from most of the previous researches.41 To 2.3Figure 3+ contents after stretching stimulus . It is found that the persistent ML of SAOCD/PDMS is highly dependent on the doping content of Dy3+, and the sample with 0.04 Dy3+ doping exhibits the highest initial intensity and the longest afterglow time. Previously, researchers can only achieve the persistent ML via the trap engineering in the trap‐controlled ML systems. Namely, the persistent ML can only be obtained by the energy releasing from the deep traps to the shallow ones driven by mechanics stimuli, e.g., Ba0.5Sr0.5Si2O2N2:Eu2+, LiGa5O8 and Sr2P2O7:Eu,Y. However, such kind of persistent ML requires pre‐irradiation to fill energy in traps, which is an irreversible process resulting in unrecoverable persistent ML. For the persistent ML in this work, it requires no any pre‐irradiation. Even though the trapped carriers are fully cleared, the SAOCD/PDMS can still exhibit intense ML and afterglow. It suggests that the as‐obtained persistent ML of SAOCD/PDMS should be the self‐charging one under mechanics stimuli, which is different from the previous reports and shows higher application values.In addition to the ML under mechanics, the SAOCD/PDMS composite elastomer can also exhibit ML afterglow (persistent ML) after the mechanics stimuli, i.e., the ML after removing mechanics could last for ≈15 s observed by naked eyes in dark environment.  systems.31 Nam2.4 However, the as‐observed ML of SAOCD/PDMS in this work is independent from the pre‐stored energy in traps as discussed in Figures Figure 3+ could produce a certain localized piezoelectricity in the structure. Therefore, the conventional trap‐ or piezoelectricity‐involved mechanisms cannot be employed to explain the ML in this work. Recently, a novel physical model in terms of the interfacial triboelectrification‐induced electron bombardment was proposed by our group to explain the unusual self‐activating ML. This model should be established on the following four aspects: i) the ML is non‐piezoelectricity‐related; ii) the ML is independent of traps; iii) the material can exhibit ML only when it is composited with the matrices that can accept electrons under triboelectrification; iv) the ML powders have radiative pathways under the bombardment of high energy (HE) electrons. For the ML of SAOCD, it is non‐piezoelectricity‐related  by the SAOCD/PDMS. As shown in Figure To further understand the persistent ML performance, thermoluminescence (TL) spectra of SAOCD/PDMS before and after stretching stimulus were measured. As shown in Figure 2.5 These unique physical processes of the persistent ML of SAOCD/PDMS inspire us an effective strategy to achieve the mechanics storage and visualized reading. As illustrated in Figure During the physical processes of the self‐charging persistent ML Figure , the app46 The1 in Figure 2 in Figure 3 in Figure To visually present the mechanics storage and reading activities of SAOCD/PDMS, we take the optical photos for each step as shown in Figure 33+‐doped Sr3Al2O5Cl2 powders were synthesized, and their ML properties were investigated by compositing with PDMS. Different from the conventional ML materials, the Sr3Al2O5Cl2:Dy3+/PDMS composites exhibited intense and self‐activating ML with no need for any pre‐irradiation. The self‐activated energy by mechanics during ML could be further transferred to the intrinsic traps, and therefore the attractive ML performance in terms of self‐charging persistent ML was created. In addition to facilitating the practical applications in mechanics displaying and visualization, the unique self‐charging processes further endowed the SAOCD/PDMS composites with mechanics storage and visualized reading activities, showing broad application prospects in the fields of mechanical engineering, bioengineering, and artificial intelligence.In summary, the Dy43‐xAl2O5Cl2:xDy  powders were synthesized by a high‐temperature solid‐state method. First, stoichiometric amounts of SrCl2.6H2O (AR), SrCO3 (AR), Al2O3 (AR), and Dy2O3 (99.99%) raw materials were weighed and thoroughly ground in an agate mortar. Then, the mixture was pre‐sintered at 800 °C for 2 h under air in a muffle furnace, and sintered at 1200 °C for 4 h under the atmosphere of 90% N2 and 10% H2 in a tube furnace. After cooling to room temperature, the SAOCD powders were obtained.A series of SrTo quantitatively analyze the ML properties, SAOCD powders were embedded into transparent PDMS  with a powder‐to‐polymer mass ratio of 1:1. First, PDMS base resin (2 g) and curing agent (0.2 g) with a mass ratio of 10:1 were mixed in a petri dish (diameter: 30 mm). Then, 2 g of SAOCD powders were dispersed into the above PDMS precursor by mechanical stirring for 10 min to form a homogeneous paste. After that, the mixture was poured into a dumbbell‐shaped mold  and removed the gas under negative pressure  for 10 min. After curing at 80 °C for 30 min, standard test samples of SAOCD/PDMS composite elastomers were obtained.The preparation processes of SAOCD/PU, SAOCD/SG and SAOCD/ER were similar to the fabrication of SAOCD/PDMS, and the curing conditions were adjusted to 60 °C for 120 min. The ratio of base resin: curing agent: SAOCD for SAOCD/PU, SAOCD/SG and SAOCD/ER were 1:1:2, 1:1:2, and 3:1:1, respectively.α radiation (λ = 1.54178 Å). The morphology and element distribution of the samples were obtained by SEM (FEI Quanta 650 FEG) with energy dispersive X‐ray spectroscope fittings (EDAX ELEMENT). The TL curves were measured using a microcomputer thermoluminescence spectrometer  at a heating rate of 1 Κ s−1. ML signals were collected in situ from a homemade tensile testing machine using a high‐throughput optical fiber. The ML spectra were recorded by a fluorescence spectrophotometer  equipped with a CCD camera . The stress‐strain curve of SAOCD/PDMS elastomer was applied by a universal testing machine (Shimadzu AGS‐X‐500 N). The triboelectric potential was collected by using the electrostatic measuring probe  Co., Ltd.) at a distance of 10 mm. The CL spectrum of SAOCD was detected on the modified Mp‐Micro‐S instrument attached to the SEM. High‐temperature environments were provided by the heating table (JF‐956A). All optical photos were taken by a digital camera (Canon EOS 77D).Powder XRD patterns of the as‐synthesized SAOCD were carried out on an XRD‐6100 (Shimadzu. Japan) X‐ray diffractometer with CuKThe horizontal comparison of the ML properties in Figures The authors declare no conflict of interest.Supporting InformationClick here for additional data file.


In this study, aiming at the application of circular CFHST members using Q690 steel (yf ≥ 690 MPa), a total of 15 CFHST beams were examined using a three-point loading test to investigate the failure mode, bearing capacity and plasticity evolution. Subsequently, finite element models (FEMs) were established to analyze the full-range curves, composite effect, failure mechanism and influences of key parameters including material strengths, D/t ratios, and shear-span ratios. A simplified calculation method for bearing capacity was finally proposed and verified. The results indicate that the full-range performance of tested CFHST members with out-of-code D/t ratios have ductile behavior, though they fail through the mode of steel fracture and concrete cracks in the tension zone as well as through local buckling in the compression zone; out-of-code CFHST members  can perform reasonable composite behavior because of contact pressure larger than 2.5 MPa, where a thin-walled steel tube experiences an arch failure mechanism similar to core concrete at a trussed angle of 45°; the simplified bearing capacity model achieves a mean value of 0.97, and can be accepted as a primary tool to perform structural design and performance evaluation.Using high-strength steel (yield strength  In ren weight ,4. Howevn weight ,6. For ea/D) ratios and depth-to-width (D/B) ratios on the flexural performance, and calibrated the accuracy of the existing design method on rectangular steel-reinforced CFST members stipulated in Eurocode 4 (EC4) using experimental results. Shi et al. [yf up to 780 MPa) and ultra-high-strength concrete (compressive cylinder strength up to 180 MPa), and proposed a design recommendation by modifying the EC4 design method to predict the flexural capacity. Hanifehzadeh et al. [Many scholars have conducted studies on the flexural performance of CFST members ,10,11,12i et al.  reportedi et al.  providedi et al.  establisi et al.  revealedi et al.  investigh et al.  studied h et al.  proposedD/t) ratios specified by EC4, GB 50936-2014 and AISC 360-16 are, respectively, the 90∙235yf, 177∙235yf and 0.31∙sE/yf [D/t ratios is still limited. Therefore, it is necessary to investigate the flexural performance of CFHST members with out-of-code D/t ratios to promote its potential application.The abovementioned studies provide significant contributions to composite mechanisms and bearing capacity under flexural loading; however, those current design methods still carry an obvious deviation on accurately predicting maximum flexural capacity for CFSTs. For CFHST members, the proposed calculation methods might not be conducive to ductility evaluation and the rational use of bearing capacity. Moreover, the limitations on diameter-to-thickness  were established to analyze the full range of behavior, confinement effect, failure mechanism, and influences of various parameters . Finally, a calculation method on flexural bearing capacity was proposed and verified.In this study, a total of 15 CFHST specimens with out-of-code D/t ratio on flexural performance. Generally, D/t ratios are not allowed to be greater than 28.5, 56.13, and 84 according to the limitation of EC4, GB 50936-2014, and AISC 360-16, respectively; however, in this study, five groups of tested specimens were, respectively, designed with out-of-code D/t ratios, including 120, 140, 160, 180, and 200, by maintaining a constant wall thickness of 2 mm. These specimens had a constant span length of 1800 mm, and both ends were supported by a hinge boundary. The regular hexadecagon cross-section was used to closely approximate the circular section due to convenient manufacture. All CFHST members were designed with the combination of HS steel Q690 and concrete C50/60 [A total of 15 CFHST beams, described in e C50/60 . The conThe mechanical property test of HS Q690 steel was conducted using a tensile testing machine, where the size and loading device were illustrated in yf) and tensile strength (uf) of steel coupons were 741 MPa and 795 MPa, respectively. The elasticity modulus (E) and Poisson’s ratio were, respectively, 201.5 GPa and 0.24. During the concrete casting, concrete test cubes (150 × 150 × 150 mm) and prisms (150 × 150 × 300 mm) were reserved and cured under the same conditions as the tested CFHST members. The average measured compressive strengths of the cubic specimen (cuf) was 51.2 MPa, and the elastic modulus of the concrete prism was 31,833 MPa by multiple loading stages according to the method in GB/T 50081-2002 [The test was loaded using a displacement controlling mode, and the measured curve of tensile stress versus strain is shown in 081-2002 . The maxcuP, where cuP was the predicted target load calculated by numerical models. After reaching 0.6 cuP, the vertical load was controlled by a displacement loading mode with a continuous speed of 0.2 mm/min. The test was terminated when local buckling and fracture damage to the steel tube, or concrete crushing, obviously occurred.Considering that the load of the transmission pole tower is only the upper wire and its own weight, the axial compression ratio is relatively small, and the small vertical load has little influence on the maximum bending capacity. Therefore, only the influence of flexural stress on the transmission pole is considered in the test. According to standard GB 4623-2006 for transmission poles, a three-point loading experiment was adopted to examine the flexural performance of CFHST members . Figure The typical failure modes of an out-of-code CFHST member are depicted in D/t ratios (Group C240) reach a further failure displacement, which can be ascribed to the higher confinement coefficient ξ = yAsf/(ckAcf), where cA and sA, respectively, indicate the cross-sectional areas of core concrete and steel tube, and ckf is the concrete prism strength. To obtain the moment (M)–curvature (ϕ) relationship of CFHST beams, Equations (1) and (2) were used to derive average curves:ε1 and ε2 are, respectively, the longitudinal strain at various heights h1 and h2 of mid-span cross-section, and V is the vertical load.D/t ratio increases, the flexural capacity of specimens is, respectively, enhanced by 33.56%, 65.07%, 112.33%, and 194.52%. When the shear-span ratio of specimens is greater than 2, the bending moment plays a dominant role in the failure of the specimens, while the shear force has little effect [e effect . TherefoM) versus strain (ε) curves for all specimens at the mid-span section. The red dashed line represents the position where the longitudinal strain is equal to 3000 με. It can be concluded that, for the longitudinal strain in the tension zone, it increases faster than in compressive zone, and the longitudinal tensile strain tends first to achieve yield strain compared to compressive strain. Moreover, the longitudinal tensile strain displays a higher anti-deformation capacity, up to 20,000 με , reflecting the sufficient plasticity development, although the HS thin-walled steel tubes finally fracture.εL) distribution along the loading process, the strain distributions in the mid-span section were extracted along the section height (D). To investigate the longitudinal strain  of the tested specimens were established in ABAQUS software, where the element types of the steel tube and core concrete were, respectively, S4R and C3D8R, as shown in The established FEMs for CFHST members were validated in terms of failure mode and full-range curves of load versus displacement compared to the test results. As for the full-range test curves, as shown in D), thickness (t), span length (L) and compressive cylinder strength of concrete (cf) are, respectively, 240 mm, 2 mm, 1800 mm and 30 MPa. Additionally, Q741 shows that the yield strength (yf) of a steel tube is 741 MPa, therefore forming the notation C240-2-30-1800-Q741. As displayed in One typical CFHST specimen was used for the explanation of full-range bending behavior and composite mechanism, where the diameter Stage 1: Elastic stage (Points O–A). In this stage, the CFHST member retains elastic behavior. The load–displacement curve shows a linear growth relationship, and the HS steel tube and core concrete withstand, respectively, 69% and 31% of the specimen flexural capacity at Point A a. In Fig(2)yf, and the stress of the core concrete is higher than its cylinder strength cf due to the confinement effect provided by steel tube.Stage 2: Yield stage (Points A–B). The load–displacement curve enters the yield stage, and the loading-carrying proportions of the HS steel tube and core concrete are, respectively, 72% and 28% at Point B. The local buckling of the steel tube in the compressive zone causes the contact pressure to increase slowly at Point 1, and the contact pressures at Points 2 and 3 gradually increase due to the significant expansion deformation of the confined concrete. At the same time, an obvious stress-redistribution phenomenon exists in the compression zone, and the neutral axis increasingly moves upward, owing to the concrete failure in tensile zone, as shown in (3)Stage 3: Hardening stage (Points B–C). The plastic deformation occupies a major part, and the contribution of the steel tube to the flexural capacity generally retains a higher percentage, for which the vertical bearing capacity proportions of the HS steel tube and core concrete are, respectively, 66% and 34% at Point C. A large value of 5.89 MPa can be reached for contact pressure at Point 3 compared to the lower value at Point 2, reflecting a compact interaction between the steel tube and concrete. Although the core concrete suffers from severe damage during this period, the damaged concrete can still effectively resist the ovalization and buckling of the steel tube.In this section, the load-transfer mechanism of the CFHST beam is investigated corresponding to the typical specimen in From D/t ratio, concrete strength and shear-span ratio. To examine the influence of various parameters on the mechanical properties of the CFHST beam, a parametric study was therefore conducted. D/t ratios from 60 to 240 were investigated by keeping the diameter constant. Compared with the maximum D/t ratio (D/t = 240), the vertical capacity of 60~120 is increased by 79%, 157%, and 235%, and the stiffness is increased by 103%, 158%, and 213%, respectively. This can be ascribed to a stronger confinement effect induced by increased wall thickness, therefore making an obvious enhancement to the interface contact pressure. Given the existing study, the interaction pressure of CFST members within D/t = 47~75 usually focuses on the scope of 2~5 MPa [D/t ratios  can perform reasonable composite behavior due to the acceptable contact pressure larger than 2.5 MPa. Using HS steel can provide a higher confinement effect to the core concrete for the purpose of reduced material consumption.By increasing the steel yield strength from 550 to 741 MPa, the bearing capacity compared to the benchmark specimen C240-2-30-1800-Q550 can be, respectively, enhanced by 7%, 12%, 16% and 20%, as shown in  2~5 MPa ,37; therAs shown in To study the influence of shear-span ratio on the flexural capacity of a CFHST member, various shear-span distances ranging from ~900 to ~2100 mm were examined. As depicted in (1)The cross-section remains plane after deformation;(2)The concrete in the tension zone is neglected for calculating the flexural capacity;(3)The steel tube in the compression zone enters the yielding stage.A simplified plastic calculation method was used to determine maximum flexural capacity. Corresponding to the numerical and test analysis, the CFHST beam is considered to reach the ultimate state as the height of the neutral axis is distributed at the center line of the core concrete, as shown in cN is the capacity contribution of the core concrete; scN and stN are, respectively, the capacity contributions to compression and tension of HS steel tube; cA, scA, and stA are, respectively, the compression area of concrete, the compression area and tension area of steel tube; and Therefore, according to the mechanical equilibrium, the following equation can be obtained.The compressive strength of the core concrete can be used by Sakino .(14)σccuM is the total flexural capacity of CFHST members; ucM is the flexural capacity of steel tube and concrete in compression zone; stM is the bearing capacity of the steel tube in the tension zone; scM and cM are the flexural contributions of the steel tube and concrete in compression zone, respectively; y is the distance away from the neutral axis; R0 is the radius of core concrete; and t is the thickness of steel tube.Then, the flexural bearing capacity can be obtained by superposing the moment of tensile stress and compressive stress:To verify the accuracy of the proposed calculation method, the results of calculation method and related literature  results are listed in Meanwhile, the simplified method in this paper achieves a reasonable accuracy in terms of the mean value (MV) of 0.97 compared to the corresponding MVs of 0.93, 0.68 and 1.12 of existing design codes. The differences in predicting ultimate bearing capacity may be ascribed to the different definitions in the ultimate limit state. Generally, the simplified method proposed in this paper can be accepted to perform structural design and performance evaluation, and pursuing a more accurate strength model is also the continued aim.D/t ratios.The tested CFHST members fail in a mode of steel fracture and concrete cracks in the tension zone, as well as local buckling in the compression zone, to form a plastic hinge with ductile behavior. Due to the higher confinement effect of HS steel, the strain distribution along the section height approximately adopts a linear trend, revealing that the plane cross-section assumption is still justified for CFHST members with out-of-code The FE model was developed and verified for the analysis of full-range composite behavior; meanwhile, the load–displacement curves can be divided into three various working stages. The HS thin-walled steel tube experiences an arch mechanism similar to the core concrete, where the maximum tensile stress approximately transmits in an angle of 45° and vice versa.D/t ratio and shear-span ratio) on the full-range load–displacement curves and interaction behavior, in which the CFHST members with out-of-code D/t ratios  can perform with reasonable composite behavior due to an acceptable contact pressure larger than 2.5 MPa.A detailed parametric study was conducted to examine the influences of key parameters (e.g., the material strength, A simplified theoretical model for calculating flexural capacity was derived and established by achieving a MV of 0.97 and a COV of 0.14 compared to the prediction results of existing design codes. Meanwhile, the method specified in AISC 360-16 performs a more conservative prediction trend compared to the counterparts in the codes of GB 50936-2014 and Eurocode 4. Therefore, the simplified method in this paper can be accepted as a primary tool to conduct structural design and performance evaluation.This paper systematically investigated the flexural behavior of out-of-code CFHST members. Based on the test, FE and theoretical analysis, some valuable conclusions can be drawn within the scope of current research:In this study, the influence of shear force and shear-span ratio could not be completely excluded in the test. Although the bending moment plays a leading role in the bearing capacity of specimens with a large shear-span ratio and the shear force has little influence on the bearing capacity, the influence of shear force on the flexural bearing capacity could not be completely excluded. In future research, a four-point bending test should be considered, and the diameter–thickness ratio and concrete strength should be studied while keeping the diameters of specimens unchanged.


Background: Studies of antibiotic prescribing choice and duration have typically excluded women with recurrent UTI (rUTI), yet the Infectious Disease Society of America (IDSA) UTI treatment guidelines are applicable to recurrent and sporadic cystitis. We sought to better understand prescribing practices among uncomplicated rUTI patients in terms of choice of drug, duration of therapy, and the risk factors for receiving guideline-discordant therapy. Methods: We performed a retrospective database study by extracting electronic health record data from adults seen at academic primary care, internal medicine, or urology practices between November 2016 and December 2018. Inclusion criteria included having ≥2 or ≥3 International Classification of Diseases Tenth Edition (ICD-10) cystitis codes recorded within a 6- or 12-month period, respectively. We excluded patients with ICD-10 codes indicating any structural or functional genitourinary comorbidities, interstitial cystitis, vaginosis, compromised immune systems, or pregnancy in the prior year. Patients were also excluded if they had signs or symptoms of pyelonephritis at presentation. Results: Overall, 232 patients presented for 597 outpatient visits. Most were married (52.2%), non-Hispanic white (62.9%), and female (92.2%), with a median age of 58 years . Only 21% of visits with an antibiotic prescribed for treatment consisted of a first-line therapy agent prescribed for the recommended duration. In terms of antibiotic choice, these agents were prescribed in 58.4% of scenarios, which primarily included nitrofurantoin (37.8%) and trimethoprim-sulfamethoxazole (TMP-SMX) (20.3%). Guideline-discordant choices of fluoroquinolones (28.8%), and β-lactams (11.2%) were the second and third most commonly prescribed drug categories, respectively. Multinomial logistic regression identified age  or having a telephone visit  as independent risk factors for receiving a β-lactam. The duration exceeded the 3-day guideline recommendation in 87.6% of fluoroquinolones and 73% of TMP-SMX (73%) prescriptions, and 61% of nitrofurantoin prescriptions exceeded the recommended 5-day duration. Multiple logistic regression analysis revealed that seeking care at a urology clinic  served as an independent factor for therapy duration exceeding guideline recommendations. Conclusions: This retrospective study revealed shortcomings in prescribing practices in the type and duration of therapy for rUTI. rUTI as well as sporadic UTI are important targets for outpatient antibiotic stewardship interventions.Funding: This investigator-initiated research study was funded by Rebiotix Inc, a Ferring Company.Disclosures: None


To process and evaluate the data from broiler fattening and slaughtering, we investigated the production data of 107 straight run flocks of the commercial meat-type breed Ross 308 . All flocks were raised and slaughtered in Germany and the average slaughter age was 37 days. The health outcomes of interest were mortality, average weight, and the slaughter results. First-week mortality, cumulative mortality, stocking density, flock size, season, production week of the parental flock, farm, antibiotic treatment, and the interaction between antibiotic treatment and season were considered as possible influencing factors. The average first-week mortality (FWM) and cumulative mortality percentages were 0.66 and 2.74%, respectively. First-week mortality was influenced by flock size, production week of the parental flock, and the interaction between antibiotic treatment and season, whereas cumulative mortality was influenced by antibiotic treatment, farm, and first-week mortality. The average weight (mean 2.30 kg) was influenced by season, stocking density, flock size, farm, and the interaction between antibiotic treatment and season. The condemnation rate was on average 1.48%, with the most common causes being deep dermatitis (mean 0.63%), ascites (mean 0.53%), and not suitable for production/general disease (mean 0.25%). Several factors influenced the causes of condemnation, with season being the most predominant one, followed by the interaction between antibiotic treatment and season, the antibiotic treatment alone, and stocking density. Although vegetarian nutrition is becoming more popular these days, broiler meat is still favored because it is low in fat, easy to prepare, and affordable. The German meat industry produced 623,165,170 broilers in 2020, corresponding to a weight of 1,066,528,075 tons , 9,700 , 10,100 , 29,200 , 41,500 (barn 1–4 and 6 of farm 2), 19,300  with an average 27,000 birds per flock. All barns were equipped with round feeders and feed was supplied 3 per housed animal and hour and was adapted to the size of the birds and their necessity by a temperature and humidity control system.To keep the temperature in the desired range, all barns were equipped with spray cooling systems and a gas heating system. Before housing, the barns were heated up to an air temperature of 33°C. All barns were closed barns with a forced ventilation system. The ventilation capacity ranged between 6.7 to 14.5 mvia drinking water at day 16 on the farm.Both farms received their chicks from the same hatchery and the proximity from hatchery to farm was similar (287 km for farm 1 and 276 km for farm 2). Both farms used the same vaccination program: vaccination program against Infectious Bronchitis Virus (IBV) where a primer  and booster (full doses) were applied at the hatchery and at day 10 on the farm, Newcastle Disease Virus (NDV) and Infectious Bursal Disease  were applied 2, with a minimum of 30.08 and a maximum of 39.43 kg/m2. For further analysis, the flock size was categorized into small , medium , and large . Regarding the genotype, only Ross 308  broilers were included in this study. All flocks were of straight run. Only birds from the final depopulation were included in the study, and the average duration of the fattening period was 37 days (minimum 35 days and maximum 40 days).The first chicks were housed in January 2019 and the last in June 2020, and 107 fattening periods were considered in the study. The following number of fattening periods were included for each barn: barn 1, farm 1: 8; barn 2 farm 1: 8, barn 3, farm 1: 8; barn 4 farm 1: 8, barn 5, farm 1: 9; barn 1 farm 2: 11, barn 2, farm 2: 11; barn 3 farm 2: 11, barn 4 farm 2: 11; barn 5 farm 2: 11; barn 6 farm 2: 11. The mean stocking density was 33.86 kg/mThe catching time was evaluated and was divided into day (>4 am until < 9 pm) and night (≥9 pm until ≤ 4 am). In total, 82 flocks were caught at night time and 25 flocks were caught during the day. All birds were brought to the same processing plant with a transport distance from farm 1 of 229 km and 242 km from farm 2. Slaughtering took place from February 2019 to July 2020, using a controlled atmosphere stunning as the stunning method. The meat inspection was done by official authorities and the staff of the processing plant, according to Commission Implementing Regulation (EU) 2019/627 .To analyze the influence of the seasons, the following seasons were used: winter , spring , summer , and fall . The production week of the parental flock was also included in the study and varied from 3 to 38 weeks.The information and data used in this study were obtained from the following four sources: (i) farm record: date of housing, number of chicks per flock (flock size), mortality , litter material, catching time; (ii) delivery note: production week of the parental flock, genotype; (iii) delivery and application documents from the veterinarian: antibiotic treatment ; (iv) slaughter records: date of slaughter, average weight, number of birds processed, condemnation rate, dead-on-arrival (DOA) rate, and causes of condemnation. The latter included deep dermatitis, ascites, not suitable for production/general disease, hepatic changes, polyserositis, underdevelopment/emaciation, other pathologic findings/hematoma/injuries, and changes in color/odor/texture. Before the start of each antibiotic treatment, a clinical examination of the flock was performed by a veterinarian. The clinical diagnoses were used, together with pathological findings of dead or culled birds, a microbiological examination and antibiogram were carried out to find the most suitable antibiotic. All microbiological examinations and antibiograms were performed at the laboratory of the veterinarian in charge and the data sets were provided by the farmer.All information about the broilers, considering the whole fattening period and the details about the slaughtering of the flocks, was provided by the farmer and handed in on paper. The data were collected and transformed into an Excel table and then transferred to IBM SPSS Statistics software, version 27 . Data inputs were validated and descriptive statistics were obtained to validate the information, followed by a calculation of the means, the minimum and maximum values, and the standard deviation. Histograms on all relevant farm-level and slaughter variables were conducted and checked visually for potential errors, extreme values, and normal distribution.p-value ( ≤ 0.05) were included in the model. This led to eight independent variables plus the interaction between season and antibiotic treatment as a random effect , production week of the parental flock (p = 0.044), and the interaction between antibiotic treatment and season (p = 0.004). Smaller flock sizes and parental flocks in an earlier production week led to a lower FWM. In addition, the FWM was higher in flocks without reported antibiotic treatment (0.67%) than in flocks reported to have been treated with antibiotics (0.64%).The descriptive results for FWM, cumulative mortality, and average weight are presented in p = 0.026; p = 0.003), farm (p = 0.008), and antibiotic treatment (p = 0.026) on cumulative mortality  and the lowest in fall (2.20%), but seasonal variations observed did not differ and were thus excluded from the final model. Flocks that had been treated with antibiotics had higher cumulative mortality (3.28%) than flocks that had not been treated (2.52%) . Stocking density (p < 0.001), farm (p = 0.003), and flock size (p = 0.002) also had an effect on the average weight , the production week of the parental flock (p = 0.008), and the use of antibiotics , flock size (p = 0.046), the use of antibiotics (p = 0.018), and the interaction between antibiotic treatment and season . Deep dermatitis was the most common cause of condemnation during slaughter in our study and was influenced by the season (p = 0.021) and the production week of the parental flock , the flock size (p = 0.002), antibiotic treatment (p < 0.001), and the interaction between antibiotic treatment and season . The pathological findings were that not suitable for production/general disease (p < 0.001) and hepatic changes (p = 0.001) were both influenced by the stocking density, and another finding was that not suitable for production/general disease was additionally influenced by the season (p = 0.044). Although polyserositis was only recorded in 0.09% of the condemned carcasses (p < 0.001), antibiotic treatment (p < 0.001), and the interaction between antibiotic treatment and season  and by stocking density (p < 0.001), whereas other pathologic findings/hematoma/injuries were influenced by season (p = 0.014), cumulative mortality (p = 0.015), production week of the parental flock (p < 0.001), and the interaction between antibiotic treatment and season , stocking density (p = 0.048), flock size (p = 0.013), antibiotic treatment (p = 0.022), and the interaction between antibiotic treatment and season  and ascites (mean 0.53%) being the major causes of condemnation . The conarcasses , the muln = 18), whereas fewer flocks received antibiotic treatment in winter (n = 8), summer (n = 3), and fall (n = 1). Eight flocks were treated two times within the fattening period , and two flocks were treated three times (both in spring). The other 20 flocks were treated one time with antibiotics during the fattening period.Regarding the antibiotic treatment, 30 of the 107 flocks were reported to have been treated with antibiotics during the fattening period, whereas 77 had not been treated . Of the n = 107 flock cycles) was influenced by flock size, production week of parental flock, and the interaction between antibiotic treatment and season. The interaction between antibiotic treatment and season described whether antibiotics were used in the flock during the fattening period and the differences between the number of treatments per season and its effect on the FWM. Previous studies reported higher percentages of 0.94, 1.03, 1.10, and 1.82% than we observed  and was influenced by the FWM, the use of antibiotics during fattening, and the farm.The average cumulative mortality in our study was 2.74%  and was influenced by stocking density, flock size, farm, season, and the interaction between antibiotic treatment and season. With an increase in the stocking density, the average weight increased as well, which is contrary to the results of Dozier et al. , with a minimum of 0.12% and a maximum of 4.63%. Of the variables we analyzed, the season, the production week of the parental flock, and the use of antibiotics significantly influenced the condemnation percentage. The average condemnation percentage of our study is higher than those reported by van Limbergen et al. ,n et al.  (1.10%),n et al.  (0.88%).n et al.   and was influenced by flock size, FWM, the use of antibiotics, and the interaction between antibiotic treatment and season. The mean DOA percentages reported in the literature vary greatly and range from 0.07%  in our study and was influenced by the season and the production week of the parental flock. Dermatitis usually starts with an initial skin lesion and is followed by a secondary bacterial infection . Ascites, the abdominal accumulation of fluid . Season was the only factor which influenced all of those dependent variables, except hepatic changes, which were only influenced by stocking density. These findings emphasize the need for maintaining good housing conditions during each season to keep the broilers in a healthy condition and thus maintain low mortality percentages. A high stocking density can be a reason for high levels of the various causes of condemnation because more birds per square meter can lead to an increase in infection pressure, stress level, and injury risk.All broilers assessed in our study had been slaughtered at the same processing plant. Thus, the potential variance due to different assessment schemes that could lead to differences in the evaluation and documentation of slaughter results could be considered as low. Nevertheless, differences have been seen between the people who assess the birds during meat inspection , and alsE. coli infection in broiler chicks. Antibiotic treatment was used when the mortality in a flock had increased significantly or an illness was diagnosed in the chicks. These results are in line with other publications considering antibiotic treatments of broilers , enteritis (E), arthritis, and broilers . Other abroilers , and thebroilers . Two of An interaction between the antibiotic treatment and the season was visible for the FWM within the multivariate model, with differences between the season in which the treatment was done and also the number of treatments per flock. Most of the flocks that received antibiotics were treated during spring (18 of 30 flocks). Furthermore, only in spring two of the flocks were treated three times. An effect of the interaction between antibiotic treatment and season was observed on the average weight of the broilers, but for antibiotic treatment alone no effect was proven. The interaction between antibiotic treatment and season describes the seasonal differences between the flocks which had been treated and those which were not treated. Flocks without antibiotic treatment had a higher average weight, which could be linked to the better health status and a better appetite of the flocks, resulting in a better feed intake. After having discussed our results with the farm management of the two farms of our study, we were informed that the farm has noticed an increase in the flocks which needed to be treated within the first week. Therefore, it can be assumed, that our data collection was carried out during the period when the problems in the broiler fattening started and are less due to the time of the year.The use of antibiotics during fattening also influenced the DOA percentage in our study. The mean DOA percentage in flocks without antibiotic treatment was 0.15%, whereas that in flocks that had been treated was 0.21%. The birds that had been treated were probably less resistant to stress during the transport, owing to their poorer state of health which made the previous treatment necessary.E. coli infections, the main bacterial agent for antibiotic treatment in our study  both were influenced by the season. Deep dermatitis was additionally influenced by the production week of the parental flock, whereas ascites was additionally influenced by the flock size, the use of antibiotics, the interaction between antibiotic treatment and season, and also by the average weight. Season, followed by the interaction between the use of antibiotics and season and stocking density were the independent variables, which mainly influenced the condemnation causes in our study. Although the rearing conditions are supposed to be consistent in each barn and flock throughout the whole year, there seem to be differences regarding the seasons which result in those outcomes. The stocking density could be an influencing factor because, with its increase, the infection pressure can increase similarly. The influence of antibiotic treatment alone or its interaction with the season has been observed several times in our study. This influence should be reduced by keeping excellent rearing conditions and feed and water of good quality to meet the national standards. Nevertheless, antibiotic treatment, if necessary, should be done as early as possible because infections in the flocks can increase the condemnation percentage, can lead to financial losses, and are of concern from an animal welfare perspective.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.Ethical review and approval was not required for the animal study because the study exclusively included data generated after slaughter without any procedure or intervention on living animals. The data used is also generated within normal husbandry conditions in livestock.LD collected most data and transferred them to an Excel table. AJ checked the data and supplemented and completed them, conducted the statistical analysis, and prepared the first draft of the manuscript. HL commented on the previous versions of the manuscript. All authors approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Auk) and pore structure of concrete under uniaxial compression and carbonation were measured by the Autoclam method and mercury intrusion porosimetry (MIP). The Autoclam test results showed that the concrete Auk changed in a concave parabolic manner with the compressive stress level, and the inflection point of the stress level was 45%. The MIP results showed that the characteristic pore structural parameters  first decreased and then increased with the stress level change. The change in concrete microstructure was a result of the combined effect of pore filling, decalcification, and densification, as well as the split effect. The key pore structural parameters affecting Auk were confirmed using gray relational analysis (GRA). The top three parameters with the highest correlation with the carbonated concrete Auk were porosity , median pore diameter by volume (iγ = 0.763), and proportion of transition pore volume (iγ = 0.827). Furthermore, the regression analysis showed a good linear relation between Auk and the important pore structural parameters.Concrete structures have to withstand the combined effects of external load and environmental factors. Therefore, it is meaningful to study the durability of concrete under compression and carbonation. The air permeability coefficient ( The main reason for focusing on this topic is that concrete carbonation reduces the pH of the pore solution and then destroys the passivation film protecting the reinforcement in the concrete structure. Furthermore, carbonation causes serious damage to concrete structures because the CO2 concentration in the air has increased considerably in recent years. Therefore, it can be estimated that damage to concrete structures due to CO2 attacks will become more serious.Carbonation, a chemical reaction between the CO2 concentration [2 diffusion rate and deeper carbonation depth under high stress. As shown in Many factors affect the concrete carbonation: water–cement ratio ,2, supplntration ,10,11, rntration ,12,13,14ntration ,23,24,25ntration  and Tangntration  reportedntration  found thntration  and Zengntration  investigntration , Lei et ntration , and Wanntration  presenteThe porosity, interconnectivity of pores, and microcracks of concrete are the most important microstructure parameters that critically influence gas transport ,32,33,34The gas permeability coefficient is evaluated for concrete carbonation damage, and some studies were based on experiments using concrete specimens in a load-free state. Dhir et al.  and TorrFurthermore, some scholars studied gas permeability under stress. Yang et al.  studied Even though concrete is subjected to the synergetic action of stress and environmental actions, it is not easy to achieve axial compression and carbonation on specimens simultaneously in labs. Fortunately, RILEM TC 246-TDC ,42 provicD), air permeability coefficient (Auk), and characteristic pore structural parameters were tested. The gray relational analysis (GRA) method was used to analyze the relation between Auk and the pore structure of concrete under C–C, and, from this, a model between Auk and the key pore structural parameters was developed. This research will be helpful for improving the understanding of concrete deterioration under C–C.In this paper, a systematic analysis was performed to investigate the simultaneous influence of carbonation and compression (C–C) stress on air permeability and pore structure of concrete, during which time the carbonation depth  was used, and its chemical and physical properties are shown in The concrete mix proportion is shown in Prism specimens with dimensions of 100 × 100 × 300 mm were prepared for the test. The compression test rigs used in the experiment, as shown in The gas permeability coefficient of concrete was tested using the Autoclam test system ,44,45, a2) of concrete was calculated according to Equation (1).The bonded bottom ring (②) was fixed to the exposed surface of the concrete specimen (④) using a thermosetting adhesive; then air pressure of 0.5 bar was applied to the test chamber (③) using a syringe. The air in the chamber gradually penetrated into the concrete, and the display (①) showed the attenuation of test-chamber pressure in real time. Each test took 15 min, and the system recorded the air pressure every minute. The natural logarithms of the air pressure were plotted against time to calculate the air permeability index (API). The slope of the last 10 data points was reported as the API (Ln(bar)/min). The air permeability coefficient of concrete (mAd), median pore diameter by area (M-Ad), median pore diameter by volume (M-Vd), and pore volume distribution (PVD)—were measured by mercury intrusion porosimetry (MIP) through tracking pressure and the intrusion volume of mercury using the AutoPore IV 9510 . The parameters had a maximum intrusion pressure of 33,000 psi, meaning that the mercury could intrude into the pore diameter between 0.006 μm and 1000 μm.The pore structural parameters—porosity, average pore diameter (The test procedure is shown in All the concrete specimens were demolded for 1 day and placed in a standard curing room at 20 ± 2 °C and 95% relative humidity (RH) for 25 days. Then, all specimens were put into an electric drying oven at 60 °C for 2 days to evaporate excess water and balance the relative humidity within the specimens. Finally, they were taken out and cooled down to room temperature (20 °C) before the subsequent tests were carried out. The experiments were carried out according to Chinese standard GB/T 50082-2009.To meet the needs of practical engineering, this study chose a wider range of stress levels: SL0, SL0.15, SL0.30, SL0.45, SL0.60, and SL 0.75. Six groups of concrete specimens  were tested in the following steps:1. To prevent carbonation damage that may cause eccentric compression, the concrete specimens were sealed with aluminum foil, leaving two opposite sides for carbonation.cf in 2. The wrapped specimens were properly placed on the test rig as shown in 2 concentration of for 28 days of accelerated carbonation.3. The loaded specimen and the test rig were put into a carbonation chamber at 20 ± 3 °C, 65 ± 5% relative humidity, and 20 ± 3% COAuk of carbonated concrete was measured according to the test method in 4. After the 28 days of accelerated carbonation and compression, the Auk measurement. Then, the carbonation depth and pore structure of the carbonated concrete were measured on the unloaded specimens.5. The specimen was unloaded after ①CD)Carbonation depth . The average of these values was taken as the carbonation depth of the specimen at the corresponding stress level. The ②Pore structural parametersAd, M-Ad, and M-Vd) and the PVD of the carbonated concrete were measured using the MIP method in The carbonated concrete specimen (three specimens for each group) was broken into smaller pieces, and then 3–5 mm particles were selected from the cement mortar fragment in the fully carbonated zone. Next, the samples were immersed in alcohol to terminate cement hydration for 2 days. Then, the samples were dried at 60 °C in an oven for 2 days to remove alcohol and evaporate water. Finally, the porosity (The reference concrete (RC) specimen (three specimens per group) was tested in the following steps:1. The specimens were stored in the dry air chamber at 20 ± 3 °C and 65 ± 5% relative humidity for 28 days. This operation aimed to keep the RC specimen at the same relative humidity as the groups undergoing accelerated carbonation in Auk and pore structure parameters of the RC specimen were tested at the same age as SL0. The test methods are described in 2. The Auk of concrete under C–C is shown in Auk of the RC specimen (without carbonation and compression) is plotted in The Auk of RC (15.79 × 10−17 m2), the Auk of SL0 (with carbonation only) increased by 50.28%. Meanwhile, the Auk of SL0.15, SL0.30, SL0.45, SL0.60, and SL0.75 (with the combination of compression and carbonation) increased by 40%, 28%, 17%, 54%, and 82%, respectively. The increased tendencies of the Auk illustrate that carbonation and the combination of carbonation and compression both worsened gas permeability resistance.Compared with the Auk of concrete under C–C initially decreased with the stress level, but then began to increase rapidly after the compressive stress level exceeded 0.45. This result was consistent with the reports from Tang et al. [Auk of concrete had a minimum value at the 0.45 stress level. We noticed that the minimum concrete carbonation depth was at the stress ratio of 0.45  M-Ad, and median pore diameter (volume) M-Vd—are listed in MIP was used to measure the pore microstructure at four stress levels. The characteristic parameters of pore structure under carbonation and compression—porosity, average pore diameter Ad, M-Ad, and M-Vd of concrete SL0 increased by 6% (2 concentration (20%) than in our carbonation test. The carbonation of C–S–H at a higher CO2 concentration increased porosity and pore diameters [From ed by 6% a, 35% , 11.04% (SL0.45), and −11.69% (SL0.75) compared to that of SL0, as shown in Ad, M-Ad, and M-Vd with stress levels all showed an increasing trend after a short reduction. When the stress level was less than 0.45, the Ad, M-Ad, and M-Vd decreased with the stress level, suggesting that the concrete matrix became more and more compact with the increase in stress. The decreased tendency of Ad, M-Ad, and M-Vd at lower stress levels indicated that the concrete pores may be greatly compressed under a small external compressive load. Thus, the compression of gradually compacting concrete and reduction in the transition of harmful ions is defined as “the densification effect”. As presented in Ad, M-Ad, and M-Vd increased with the stress level. These results implied that compression and a stress level > 0.45 worsened the microstructure of concrete and damaged pore walls. We defined this worsening effect as “the split effect”.When the stress level exceeded 0.45, the λ of gas ) and the pore size. The diffusion of gas in concrete can be divided into three different types:Concrete is a porous, nonhomogeneous material; hence, its internal pore distribution is tortuous and complicated. According to Houst and Wittmann , the difλ.(1) Fick diffusion or normal molecular diffusion frequently occurs in pores with a diameter larger than 10λ.(2) Knudsen diffusion refers to the phenomenon of gas molecules bouncing back from the pore’s wall when the size of the gas molecule is close to that of the pore size. The collision between the molecules can then be ignored . Knudsenλ and 10λ.(3) Transition diffusion, unlike Fick and Knudsen diffusion, usually occurs in pores with a diameter between According to Peter et al.  and MuntAuk of concrete, and the temperature and relative humidity for carbonation were 20 ± 3 °C and 65 ± 5%, respectively. The mean free path of air 23), −10 m), and In this paper, we used air as a transmission medium to measure the tion (2) .(2)λ=RgThe saturated pore diameter was calculated as 10 nm according to Equation (3) ,54.(3)dWe divided the tested concrete pores into four levels according to pore diameter on the basis of these two calculations. Fick pores had a diameter larger than 690 mm, while the transition pores had a diameter between 690 and 69 nm. Knudsen pores had a diameter between 69 and 10 nm, while the saturated pores had a diameter between 69 and 10 nm.The PVD of concrete under C–C according to these four pore ranges is illustrated in K) of SL0 was smaller than that of the RC, and the proportion of transition pores (PROPT) of SL0 was larger than that of the RC.The mixing proportions of the RC and SL0 were the same. However, after 28 days of carbonation, the proportion of Knudsen pores  and Fick pores (PROPF) of SL0 barely changed compared to RC, indicating that the carbonation reaction did not affect the smaller (<10 nm) or larger pores (>690 nm). Compared with concrete SL0, S and PROPF of concrete under C–C were almost unchanged as stress levels increased. The maximum variation values were 0.89% and −1.26% for PROPS and PROPF, respectively. Therefore, we focused on the PROPT and PROPK of concrete under the carbonation and compression.It was noticed that the proportion of the saturated , calcium silicate hydrates (C–S–H), and ettringite.CH and C–S–H are the most abundant cement hydration products and the earliest to react with carbon dioxide. The neutralization reactions of CH and C–S–H and the solid-phase volume changes are shown in Equations (4) and (5) .(4)Ca(O3). The volume of CaCO3 produced by the carbonation reaction of CH and C–S–H increases by 12% [Equations (4) and (5) indicate that the carbonation reactions cause the precipitation of calcium carbonate ), with the ultimate products being CaCO3(s) and SiO2 gel (Equation (7)) [2 concentration and smaller Ca/Si ratio, showing a maximum at high-to-moderate relative humidity [In addition, the C–S–H reacts with COion (7)) . With inion (7)) ,47,55,56humidity .(6)2Ca9TPROP of concrete SL0 compared to RC  effect; conversely, when the concrete was subjected to a stress level larger than 0.45, it experienced the negative compression (split) effect.According to the above analysis, the main effects to the concrete microstructure under carbonation and compression are shown in The pore-filling effect clogs the pores and improves the permeability resistance of carbonated concrete . NeverthAuk, cD, porosity, Ad, M-Ad, and M-Vd of concrete SL0.45 were smaller than those of SL0, indicating that the cement matrix of SL0.45 became denser than the sample of SL0, implying that, in the densification, the pore-filling effects prevailed over the dual effects of densification decalcification.When the concrete was subjected to compression, the air permeability decreased and then increased with the stress levels see ; the kAuThe microstructure of concrete become looser and more porous, and many cracks appeared when the stress levels increased from 0.45 to 0.75. The higher external loads dominated the split of the pore walls inside the concrete, accelerating pore microstructure deterioration. Moreover, decalcification of C–S–H could further promote the destruction of the pore structure. The carbonation products filling the pores could not compensate for the shortcomings of the higher stress levels or the decalcification of C–S–H to generate microcracks that led to structure destruction. The dual effects of the split and decalcification effects prevailed over the split and pore-filling effects.That is to say, when concrete was under the compression and carbonation, the degradation was dominated by the applied stress level. When it was below 0.45, the pores were compressed by the external compressive load and became filled with carbonation products, which made the concrete matrix denser and improved air permeability resistance. On the other hand, when stress levels went beyond 0.45, the pores were further compressed. Meanwhile, the decalcification of C–S–H in the pore walls prevailed over the filling effect of carbonation products, pore wall damage, and the decreasing air permeability resistance.Auk to illustrate the changes induced by the carbonation and compression on the air permeability coefficient.Gray relational analysis (GRA) is a measurement method in gray system theory that analyzes uncertain relations between one main factor and others in a given system . We usedAuk under C–C as the original reference sequence, represented by X(l). The eight specific pore structural parameters  were used as comparison sequences, represented by iY(l). Data preprocessing was required since the range and unit in one data sequence may differ from those in others. The sequences were normalized on the basis of RC as follows:l = 1, 2, …, m, m is the number of experimental data items (m = 5); i = 1, 2, …, n, and n is the number of parameters (n = 8).We took the i-th performance characteristics in the l-th experiment is expressed as follows [After data preprocessing, the gray relational coefficient  follows ,62,63: reached 0.992, indicating a good linear relationship between the Auk and the three pore structure parameters.The relationship between the air permeability coefficient and the top three important pore structure parameters was established by regression analysis using Statistical Product and Service Solutions (SPSS) software , as showAuk reflected the current state of the permeability resistance of concrete under C–C, and the Auk could be used to predict the service life of concrete subject to carbonation and compression on the basis of existing models [The results demonstrated that the relationship between the air permeability coefficient and pore structural parameters of concrete subjected to C–C was linear. The g models .Auk was investigated. The following conclusions were drawn:This paper studied the deterioration of pore structure and air permeability of concrete under C–C. In addition, the correlation between pore structural parameters and Auk and the CD of concrete responded to stress levels showing concave parabolic trends. The minimum Auk and CD were obtained at the stress level of 0.45. The concrete deterioration deepened as the stress level exceeded 0.45. (1) The (2) When the applied stress levels of concrete were below 0.45, the dual effects of the densification by lower compression and the carbonation product filling of the pores were dominant under carbonation, promoting a compact concrete matrix. However, when the applied stress levels of concrete exceeded 0.45, the beneficial effect of pore filling was weakened, and the dual split effect of higher compression and decalcification of C–S–H accelerated structural deterioration.Auk were porosity, the proportion of the transition pore volume (PROPT), and the median pore diameter by volume (M-Vd). These three parameters played an important role in the air permeability under C–C. Meanwhile, regression analysis showed a good linear relationship between air permeability and these pore structure parameters.(3) The GRA results showed that the top three parameters with the highest correlation to the carbonated concrete This work was a pilot study on the air permeability of concrete under carbonation and compression. The test of the air permeability coefficient and pore structural parameters was based on OPC concrete. However, supplementary cementitious materials (SCMs) are increasingly used in concrete, and their presence influences the hydrates formed in cementitious systems. Thus, more work is needed to understand the evolution of air permeability and its relationship with the pore structure in concrete under C–C.