This research used waste ceramic powder (CP) to replace aggregate, fly ash (FA) as filler, and combined them with sulfur to prepare composite cementitious materials. The variations of the mechanical properties with the aggregate proportions  of 65%, 70%, and 75%, and the FA contents (FA mass/aggregate and filler mass) of 0%, 10%, 20%, 30%, 40%, and 50% were studied. The correlation evaluation model of sulfur content, CP content, FA content, and mechanical properties was established using the gray correlation theory, and the comprehensive mechanical property evaluation model was established as the foundation of the entropy method. Finally, the optimum proportion of the solid-waste–sulfur-based cementitious composites was determined. Results showed that, without FA, the CP increased from 65% to 75% and the comprehensive mechanical properties of the specimen increased by 60.53%. After FA was added, the peak point of the comprehensive mechanical properties appeared in group S75F10, which was 0.9210. During the hardening of the cementitious material, sulfur was mainly used as a binder, CP played the role of skeleton and part of the filler, whereas, as a crystal nucleus, the FA promoted the transformation of the sulfur crystals. Both the CP and FA can reduce the porosity of the specimen to a certain extent and have potential defect repair ability, thus densifying the matrix and improving the strength. When the proportion of sulfur: CP: FA is 1:2.7:0.3, the flexural (FS), compressive (CS), and splitting tensile (STS) strengths of the specimen are 14.8, 86.2, and 6.8 MPa, respectively. The flexural (FCR) and tensile (TCR) compression ratios are 0.172 and 0.079, respectively. The annual output of sulfur is roughly 70 million metric tons , which iβ), which has a minimal volume contraction (7%) [Given the thermal expansion and contraction of sulfur, the volume of sulfur reduces during the hardening process of SC. At room temperature, the stable crystal system of sulfur is orthorhombic sulfur (Sα), which has a volume shrinkage rate of 12%. However, the nonuniform shrinkage of sulfur pores and high contraction stress during the hardening process due to the uneven temperature distribution of fresh slurry remarkably reduces the mechanical performance of SC . Currention (7%) . Neverthion (7%) ,12. Addiion (7%) . Waste-cion (7%) . Brito eion (7%)  simply cion (7%)  tested tion (7%)  used wasion (7%)  crushed ion (7%)  used broAn accurate understanding of the relationship between the basic mechanical performance of cementitious composites and the ratio of various materials is the basis for further research. The gray correlation theory  can takeIn summary, the methods to enhance the mechanical characteristics of sulfur cementitious materials mostly focus on a single modification or addition of filler. However, the improvement of the mechanical characteristics of modified sulfur cementitious materials by combining the resource advantages and gain effects of waste ceramics and FA, making waste ceramics into aggregate to completely replace natural river sand, and relying on the synergistic gain effect of CP and FA, should be investigated. The principal purpose of this paper is to offer a neoteric sustainable method for the enhancement of the mechanical characteristics of a sulfur-based cementitious composite by introducing CP to replace natural aggregate completely and sulfur and FA filler for the preparation of WSCC. This study also aims to increase the dosage of CP and FA as much as possible to achieve the best dosage without sacrificing the mechanical strength. Compared with cement-based concrete and traditional SC, the proposed strategy may have numerous advantages, i.e., less carbon dioxide emission, lower life-cycle cost, and excellent mechanical properties. This investigation can supply a theoretical reference for the employment of WSCC in practical projects, and the whole process conforms to the concept of sustainable development.The industrial sulfur, modifier dicyclopentadiene (DCPD), and FA used in the experiment are shown in In the preliminary test, our team found that, when the content of fine aggregate was 60%, the cementing material floated up during the vibration process, leading to the stratification of the specimen. When the content of fine aggregate is 80%, there are many defects in the specimen prepared due to insufficient cementing material which cannot wrap the fine aggregate. In addition, Margareth et al.  found inIn accordance with the Chinese standard , the dimfR is the FS (MPa), fF is the load implemented to the center of the prism when it is broken (N), L is the length between the supporting prism (100 mm), and b is the side length of the square section of the prism (40 mm).Specimens were tested to comply with the FS test method . The tescR is the CS of mortar (MPa), cF is the load implemented to the center of the prism when it is broken (N), and A is the compressive area (mm3).Specimens were subjected to the CS test method . The testsf is the STS (MPa), F is the breaking load (N), and A is the splitting region of the specimen .In accordance with the STS test method , the tesn is total number of stomata cut by the whole conductor.Average chord length of the stomata:2/mm3.Specific surface area:r is the mean pore radius, mm.Mean stomata radius:Air content:3 sample:vn is the number of pores in the 1000 mm3 sample.Number of pores in the 1000 mmThe specimen was cut into 40 mm × 60 mm × 20 mm slices and the surface was ground, polished, blackened, and covered with a coat of zinc oxide. The pore size distribution, specific surface area, gas content, stomata number, and stomata spacing of the specimen were tested using the RapidAir 457. T2 spectrum can reflect the variation of the stomata structure of the porous media. According to the principle of the NMR, the distribution of the NMR T2 spectrum is related to the aperture, and this process can be simplified as [T2 is the free relaxation time of the pore fluid, ms; ρ2 is the transverse surface relaxation strength of T2, μm/ms; S is the stomata surface area, cm2; V is the fluid volume in the pore, cm3.The variation of the NMR ified as ,45:(9)1TT2 relaxation time and aperture [cγ is the radius of the hole; sF is the geometric factor, spherical hole sF = 3, and cylindrical hole sF = 2.For samples that can be equivalent to spherical and cylindrical holes, Equation (9) can be further converted into the relationship between the aperture :(10)1T2=C = ρ2sF, C is the transformation coefficient.Then, Formula (10) can be adjusted as:The specimen was cut into 40 mm × 40 mm × 50 mm specimens, which were immersed with water for 24 h in vacuum saturation equipment. The MesoMR—60 S NMR instrument was used to analyze the aperture composition of the specimen. The magnet in the instrument is a permanent magnet, the magnetic field intensity is 0.50 ± 0.8 T, and the main frequency is 21.3 MHz. T2 and the distribution of T2 can mirror the pore dimension data [It can be seen from Formulas (9)–(11) that the pore radius is proportional to ion data .The core pieces of the specimen were selected after the load experiment, and the specimen was sprayed with gold by using an ion-sputtering instrument, and its microstructure was observed with the Hitachi S-4800 electron microscope . The secondary electron imaging resolution was 1.0 nm at 15 kV and the accelerating voltage was 0.1–30 kV. The effects of the sulfur, CP, and FA in the hardening process of the specimens can be further understood by observing the micromorphology of the samples.The gray relational evaluation is a vital section of the gray gadget theory. This technique locates the numerical relationship among subsystems in the gadget via positive methods. The fundamental thought of the gray relational evaluation is to infer the relationship between unique sequences via the geometric kingdom of the principal sequence curve and the similarity between subsequences . The dipThe entropy weight method is a method to resolve the objective weight of the response . AccordiThe mean values of the FS values for three specimens in each group are shown in In addition, the FS increases initially and then declines with the increasing dosage of the FA. The FS of each group reaches the maximum when the FA content is 10%. Taking the FS of the three groups without FA as the benchmark strength, when the dosage of FA is enhanced from 0% to 50%, the FS values of the S65, S70, and S75 groups change from 12.28% to −12.28%, from 5.34% to −20.61%, and from 5.71% to −14.29%, respectively. Huang et al.  also fouTherefore, the FS of the specimen can be improved by appropriately increasing the amount of aggregate, and the FS increases evidently after adding a proper amount of FA filler. However, the FS of specimens with more than 20% FA content is lower than that without FA. When the amount of aggregate is 75% and the amount of FA is 10%, the FS of the specimen is highest.The CS values of each group of specimens measured by the test are shown in With the enhancement of the dosage of FA, the CS of different series specimens increases initially and then gradually decreases. In specimens with 0% FA, the CS of the S70 specimens is moderately greater than the S75 specimens. Taking S65 specimen increases as an example, when the content of FA in specimens is enhanced from 10% to 50%, the CS decreases from 15.42% to −5.48% compared with that of the specimens without FA. Martinovic et al.  and GwonTherefore, when only CP is taken as aggregate in the WSCC, the CS of the specimen increases until the content of CP reaches 70%. However, if FA is added as the filler, the CS of the specimen can be further improved. The consequence of FA on the CS of WSCC is not remarkable as that on the FS.STS values are shown in When the dosage of FA rises, the STS values of the three groups of specimens with different aggregate ratios increase initially and then decrease. Taking the STS of specimens without FA as the benchmark strength, when the content of FA changes from 10% to 50%, the STS values of the S65, S70, and S75 groups change from 11.63% to −20.93%, from 8.00% to −24.00%, and from 8.00% to −24.00%, respectively. Shin et al. [Therefore, the STS of the specimens can be slightly increased by appropriately increasing the amount of CP. If 10% FA filler is used in conjunction with the aggregate, the STS of the specimens can be remarkably improved. In addition, the adverse consequences of FA on the STS of three groups of specimens with different aggregate ratios do not show a consistent rule. The FA contents of three groups of specimens with STS lower than the initial value were 40%, 20%, and 30%, respectively.The ratio of the FS to the CS of the specimen is the FCR, which can characterize the fracture performance of the specimen. A high FCR indicates improved fracture performance of the specimen. The ratio of STS to CS is the TCR. As one of the indices to measure the mechanical performance of specimens, the TCR can reflect the relative development speed of the two strengths and characterize the brittleness of the matrix material. When the aggregate proportion increases, the FCR of the specimen increases significantly. The FCR of the specimen with 75% CP is 0.032 higher than that with 65% CP. After adding FA, the changing trend of the FCR of the three groups of specimens is slightly different. The FCR values of the S65 and S70 groups first decrease and then increase, whereas the FCR curve of the S75 group shows a “W” shape. However, the three groups of specimens show a common feature, that is, the supplement of FA has no significant positive effect on the FCR. Compared with those of specimens supplemented with FA, the fracture performance of specimens with only CP as aggregate is better.Unlike the curve of the FCR, the curve of the TCR shows another characteristic. When the matrix only has CP, the TCR increases with ceramic powder content. The TCR of the specimen with 75% CP content is 19.35% higher than that of the specimen with 65% CP content. After the addition of FA, when the dosage of FA is 0–10%, the TCR of the S75 group significantly improved, reaching 0.079, whereas those of S65 and S70 groups decreased. When the dosage of FA is 10–40%, the TCR of the S75 group decreases evidently (by 25.32%). The TCR of the S65 group decreases slightly but not significantly (by 5.00%), but that of the S70 group decreases first and then rises again. When the FA level exceeds 40%, the TCR values of the S65 and S70 groups drop again, whereas that of the S75 group rises slightly. When the aggregate is 75% and FA filler is 10%, the brittleness of the specimens is ameliorated best.According to the above tests, the FS, CS, and STS of the WSCC are improved most evidently when the level of FA filler is 10%. Thus, the surface morphology of each group of specimens of 0% and 10% FA is observed and shown in The specimens of the S70 and S75 groups with a high aggregate content are selected for microscopic study. The bright-green area in When increasing the aggregate content from 70% to 75%, the bright-green area in When FA filler is not added, the S75F0 group has a decreased number of 0–100 μm pores, a decreased number of 0–30 μm pores (by 6.42%), evidently an increased number of >100 μm pores, and an increased number of >500 μm pores (by 1490.48%) compared with that of the S70F0 group. When the aggregate has only CP, increasing the amount of CP remarkably increases the pore size of the specimens. After adding 10% FA filler, the proportion of 0–30 μm pores of S70F10 and S75F10 specimens increase, but the proportion of pore > 30 μm decreases remarkably. Gwon et al.  thought Using 10% FA filler can reduce the air content and average chord length of the pores in the S75 group by 62.71% and 63.24%, which are higher than those of the S70 group . Using 10% FA filler can increase the specific surface area in the S75 group by 173.69%, which is higher than that in the S70 group by 23.98%. A high air content of the specimen and long average chord length of pores results in the introduction of increased large-diameter spherical bubbles. The existence of these bubbles enhances the porosity of the SWCC, diminishes the density of the SWCC, and carries off the diminution of the effective carrying capacity section of the specimen. When the specimen is stressed, the stress concentration easily occurs near the pore, which results in reduced mechanical performance. This problem can be effectively avoided by adding FA filler.T2 spectrum is a time constant signifying the recovery process of the transverse component of the nuclear magnetization, also known as the transverse relaxation time, which is caused by the exchange of energy within the nuclear spin system [T2 spectrum can signify the porosity of the specimen, and the peak area can represent the number of pore sizes within the corresponding size range [The n system . The shoze range .T2 spectrum curve of the S70 group. Three peaks correspond to micro-, medium-, and large-radius pores in the specimens. The envelope area of the T2 spectrum curve of S70F10 is smaller than that of S70F0, and the relaxation time of peak 3 of the T2 spectrum curve moves forward. This result indicates that adding 10% FA filler can efficaciously lessen the number and volume of pores, and the improvement effect for macropores is significant. T2 spectrum of the S75 group, and the spectral line of S75F0 has only two peak points. The envelope area of peak 5 is large, which indicates that only increasing the CP content without adding FA filler increases the medium and large pores in the specimens. S75F10 is observed with three peaks, and the medium and large pores are remarkably reduced.The existence of pores leads to the stress concentration of the specimen when it is stressed, and if the number of pores is extremely large, the bearing capacity of the specimen is affected. However, 10% FA filler, which fills the natural defects of sulfur and improves the grading of CP, can well alleviate this problem, thus reducing the pore defects caused by an insufficient sulfur dosage. On the basis that the mechanical properties of the specimen have been improved by a high content of CP, the compactness of the specimen is further strengthened to improve the bearing capacity. Gwon et al.  also estβ) and polymeric sulfur (S∞), in which Sa and Sβ are composed of sulfur eight rings (S8), while S∞ is a long chain structure with 106 atoms. Sγ is the state of sulfur at the temperature of 159 °C, and all sulfur is composed of S8 at this time. When the temperature is higher than 159 °C, the sulfur is in the Sμ state, and the sulfur is in the mixed state of S8 and S∞ molecules.At room temperature, the crystal stable form of sulfur is orthorhombic (Sa), and other allotropes include monoclinic sulfur (Sβ) in the hardened slurry of sulfur-based materials is composed of plate-like single crystals, and a small part of the modified sulfur is polymerized into a chain structure. Juhyuk et al. [8 ring of the liquid sulfur and polymerizing it to form a long chain structure, and the sulfur with the long chain polymer structure has better durability. Nevertheless, some defects can be clearly seen in the matrix with a high ceramic aggregate content, and the surface also presents a honeycomb flocculent structure, which indicates that the bonding effect between the aggregate and matrix is not ideal.S75F0 and S75F10 are selected for microscopic observation . As can k et al.  thinks tThe spherical particles of the FA coated with sulfur can be observed in The cooling crystallization mechanism and microscopic morphology of sulfur shows that the FA is physically bonded with the sulfur; that is, the FA particles are enfolded and constant through the liquid sulfur. Nonhydrated FA granules may also have the function of crystal kernels during sulfur crystallization . In the Given that the dosage of sulfur, CP, and FA affect the mechanical properties of the specimens, instituting a model to evaluate the correlation between the influencing factors and mechanical properties is indispensable. The FS, CS, STS, FCR, and TCR of the specimens are different under different proportions of CP and FA. Therefore, the gray correlation technique is chosen to determine the relationship of the dosages of sulfur, CP, and FA with FS, CS, STS, FCR, and TCR. The contents of sulfur, CP, and FA are chosen as evaluation columns, and the FS, CS, STS, FCR, and TCR are chosen as reference columns. The technique of deciding the gray correlation model between three influencing elements and five mechanical overall performance indices is as follows:The initial matrix is constructed as follows:X1, X2, …, nX), m = 18 and n = 3. In the matrix of , m = 18 and n = 5.In the matrix of  is calculated as follows:The correlation coefficient of the gray entropy (ξ is the resolution coefficient and 0.5 in this paper.G) is calculated using the following equation:The gray correlation degree (The average processing results of Formulas (14) and (15) are displayed in The CP content has a high correlation with the four indices of the specimen . The correlation degree between sulfur dosage and CS is also significant, reaching 0.8121, and the correlation degrees between the sulfur dosage and FS, STS, FCR, and TCR are slightly lower than CP but is maintained between 0.75 and 0.80. The correlation degree between the FA content and five mechanical performance indices is maintained at about 0.50. The dosages of CP and sulfur are considered to play an important role in the FS, CS, STS, FCR, and the TCR of specimens, and FA also has a certain gain effect. CP plays the role of the skeleton, sulfur plays a role in bonding and lubrication, and FA plays the role of filling, and the three components influence one another. However, the optimum mixture ratio needs to be further discussed.it is the weight of the target and iS is a standardized target.The comparison of the test results of the mechanical properties of each group of specimens shows that the FS, CS, STS, and TCR of the S75F10 group are the best, but the FCR is not the best. Therefore, the ratio of sulfur, CP, and FA in the S75F10 group of specimens cannot be considered to produce the best comprehensive mechanical properties. The gray entropy principle is picked out to give weight to the five mechanical properties indices of the specimens for the determination of the comprehensive mechanical properties and omnifaceted evaluation of the mechanical properties of each group of specimens. Then, in accordance with the order of the results of the comprehensive mechanical properties, the optimum mixture ratio is selected. The evaluation system of the comprehensive mechanical performance index is expressed as follows:Y1, Y2, …, nY), where m = 18 and n = 5.The FS, CS, STS, FCR, and TCR of the specimen are arranged in turn as the original data matrix, and the initial sequence matrix is still the matrix in Formula (13):  is calculated in accordance with Formula (18). Then, a weight is given to each mechanical performance index, and the process is as follows.The difference matrix (P) is determined as follows:The proportion of each index (e) is determined as follows:Entropy (W) of every target is computed as follows:The weight (The comprehensive mechanical properties of each group of specimens are determined as follows:In summary, the optimum dosage of FA filler is 10% for the WSCC with waste CP as aggregate. In this experiment, the comprehensive mechanical properties of the S75F10 group are the best. The optimum mixture ratio of sulfur: CP: FA is 1:2.7:0.3. When the proportion of sulfur: CP: FA is 1:2.7:0.3, the FS, CS, and STS of the specimen are 14.8, 86.2, and 6.8 MPa, respectively. At this point, the synergistic effect of sulfur–CP–FA has reached an ideal state, and the mechanical bite force between particles is largest. The freshly mixed slurry in the construction process is easy to pour and vibrate, minimal defects in the specimen are observed after cooling and molding, and the mechanical traits of the specimen can be remarkably enhanced to meet the actual engineering needs.When the dosage of the aggregate is 75% and the dosage of FA filler is 10%, the FS, CS, and STS of the WSCC increase most evidently. Increasing the proportion of aggregate can successfully ameliorate the mechanical traits of the specimens but adding FA filler to the matrix with high-content aggregate is better. Reducing the proportion of aggregate can reduce the pore defects of specimens but using the appropriate quantity of FA filler is more effective than simply reducing the proportion of aggregate. Therefore, when improving the mechanical properties of sulfur cementitious materials, adding the appropriate amount of FA filler based on the CP aggregate matrix instead of blindly reducing the amount of aggregate is suggested.The supplement of the appropriate amount of FA filler can improve the gradation of aggregate and the compactness of the matrix and effectively remove air bubbles in the casting process, thus reducing the porosity of the specimen and enhancing its strength. FA particles play the position of crystal nuclei during the cooling and crystallization of sulfur. In the cooling and molding of specimens, FA particles, as the kernel of sulfur crystal development, can boost the sulfur crystal switch. Liquid sulfur accumulates, seriously changes close to the area of the FA particles, develops and extends around the particles, and subsequently bonds into a uniform matrix. Ceramic aggregate and fly ash filler can be used as weak interface transition zone of the WSCC, and sulfur can bond ceramic aggregate and fly ash filler to form a uniform and firm structure under an ideal covering condition.The dosage of sulfur and CP is closely related to the FS, CS, STS, FCR, and TCR of the specimen. The dosage of FA filler also has a certain degree of influence. When the mass ratio of sulfur: CP: FA is 1:2.7:0.3, the comprehensive mechanical properties of the WSCC is best. At this point, sulfur, CP, and FA can achieve the ideal bonding state. Sulfur can wrap all CP and FA particles, the mechanical engagement between particles is best, and the freshly mixed slurry in the construction process is easy to pour and vibrate. After the specimen is cooled and formed, minimal natural defects and bonding cracks are observed, and the mechanical properties of the specimen can be remarkably improved. The FS, CS, and STS of the specimen are 14.8, 86.2, and 6.8 MPa, respectively. The FCR and TCR are 0.172 and 0.079, respectively.In this study, on the basis of modified sulfur, WSCC is prepared using waste CP as aggregate and adding FA filler. We investigate the effect of the content of CP and FA on the mechanical traits of the specimens and discuss its microstructure and strength formation mechanism. In addition, on the basis of the gray theory, two research models are established, and the influences of sulfur, CP, and FA on the mechanical properties are analyzed. The mixture ratio of the WSCC has also been scientifically evaluated. The principal discovery of this research is as follows.


There were no statistical differences in new pressure ulcers or the cumulative incidence of both adverse events. Mean bell calls for each patient were 15.4 ± 24.1 in the intervention group and 13.7 ± 20.5 in the control group (p = 0.38). Additionally, patient satisfaction in the intervention group was almost at the maximum level. Our study supports the usefulness of Intentional Rounding in a complex and vulnerable population such as that hospitalised in internal medicine units.The aim of the study was to explore the effects of Intentional Rounding, a regular-based proactive patient monitoring, on falls and pressure ulcers in internal medicine units. This is a cluster-randomised controlled study, where units were assigned (1:1) to Intentional Rounding (intervention group) or Standard of Care (control group). The primary outcome was the cumulative incidence of falls and new pressure ulcers. These events were considered separately as secondary endpoints, together with the number of bell calls and the evaluation of patient satisfaction. Primary analyses were carried out on the modified intention-to-treat population . Recruitment occurred between October 2019 and March 2020, at which time the study was prematurely closed due to the COVID-19 pandemic. Enrolment totalled 1822 patients at 26 sites; 779 patients were included in the modified intention-to-treat analysis. The intervention group had a lower risk of falls (adjusted incidence rate ratio 0.14; 95% confidence interval, 0.02–0.78;  In recent years, the healthcare setting has become very dynamic, and it requires healthcare professionals to explore new strategies to provide high-quality, evidence-based care that focuses on patient needs, patient satisfaction, and time-cost efficiency ,2.Patients hospitalised for acute diseases or exacerbation of chronic diseases often require intensive treatment and complex nursing interventions. Depending on the level of severity of the disease, the requests made to health professionals from patients can vary; often, the response to non-urgent requests , which mThe 2013 Francis report highlighted how fundamentals of care have been disregarded in recent years, and how failures in this area are reflected in the dignity of inpatients and the quality of care provided, resulting in negative clinical outcomes  ,6. In reThis study was conducted within the fundamentals of care framework , where tDespite this, the literature reports that IR is not free of barriers and criticisms, and is related to an increased workload; moreover, some nurses report that it can limit the nurse’s decisional and critical capacity by making the work routine ,3.The proactive method IR has been the subject of interest for the past decade, particularly in the United States, as the country of origin of this method, and more generally in the English-speaking world . NeverthThe FADOI-INTENTO is a cluster-randomised, controlled study  promoted by the Italian Scientific Society of Internal Medicine, FADOI , in collaboration with the National Association of Nurses of Medicine, ANìMO .The study sites were selected to be representative of internal medicine wards in Italy in terms of geographical distribution, hospital size, and level of care intensity. All patients aged 18 or above and consecutively admitted to the participating internal medicine wards were eligible for the study. No specific exclusion criteria were applied except refusal of consent. All enrolled patients were appropriately informed about the study procedures and aims and were requested to sign a written consent.Twenty-eight hospital wards were selected by the scientific societies FADOI and ANIMO in order to be representative of the geographical distribution and level of care intensity of internal medicine units in Italy. These wards were randomly assigned (1:1 ratio) to the intervention or Intentional Rounding (IR) (n = 14) or Standard of Care (Soc) arm (n = 14) using a predefined list and the order of selection of the centres for the study.Due to issues raised by local authorities , two sites allocated to the SoC arm were unable to participate. Patients were therefore enrolled in 14 and 12 sites in the IR and SoC group, respectively. Blinding was not applicable in this study.Participants were recruited from October 2019 to March 2020.The IR study was delivered in 2 phases: preliminary and active phase. In the preliminary phase, the intervention sites received specific training to familiarise themselves with the study procedures and how to complete the IR log. The IR log collected data assessed along the IR  . The traThe primary outcome of the study was the cumulative incidence of falls, defined as “an unexpected event in which the participants come to rest on the ground, floor or lower level” , and newThe estimates for the calculation of the sample size were made on the basis of a pilot study performed at the coordinating centre. With a two-tailed test  on the null hypothesis H0: incidence rate ratio (IRR) = 1 compared to the alternative hypothesis Ha: IRR ≠ 1, it was calculated that samples of 485 subjects in the IR group and 485 subjects in the SoC group allowed a power of 80% to detect an IRR of 0.5 , assuming an incidence rate in the IR group equal to 20 events per 1000 person-days, an average exposure time in both groups of 5 days, the dispersion parameter of the statistical model used  being equal to 1.0 (conservative estimate), and the level of significance  being 0.05.Primary analyses were carried out on the modified intention-to-treat (mITT) population, which included the set of patients who had a hospitalisation of at least 10 days. Baseline descriptive statistics of patients according to the intervention and control group are reported. Continuous data are summarised as mean  and categorical data are reported as absolute frequencies and percentages. Wilcoxon-type tests were performed for continuous variables and the Pearson chi-square test, or Fisher’s exact test, whichever was appropriate, was performed for categorical ones. The IRRs for the clinical trial endpoints were computed considering, for the person-time calculation, the in-hospital length of stay. The model-adjusted IRRs were also estimated together with the 95% confidence interval. A negative binomial linear mixed model (LMM) was computed considering an offset term on the logarithm of person-time  and a random intercept term accounting for the within-centre correlation. Computations were performed using R 3.6.2 language programming with lme4 packages.In the active phase, in both the intervention and control sites, the following core information was collected for each patient at specified time-points: occurrence of falls and pressure ulcers and number of bell calls, twice a week and at discharge; patient satisfaction, only at discharge. Information on patient satisfaction was collected from patients who were able to answer two questions concerning the quality of nursing care and on the overall hospital stay. For each of these two questions, there was a score ranging from 1 (bad) to 7 (excellent). At the end of the project, the nurses involved in the project would be given a questionnaire for the evaluation of critical thinking. Other details on the characteristics of patients were collected at the time of admission to hospital including: age, sex, origin (home or other), presence of caregiver, chronic or acute active diseases, Barthel Index score , historyFrom October 2019 to March 2020, a total of 1822 patients were enrolled at 26 study sites; 779 patients were included in the mITT analysis .Enrolment for the study ended concurrently with the development of the COVID-19 pandemic. This decision was made by the Steering Committee in consideration of the transformation of some wards participating in the study into units for patients with COVID-19; the continuation of the study would have resulted in the enrolment of patients with very different characteristics compared to those that had occurred during the study. The pandemic also prevented us from carrying out the nurse critical thinking evaluation since we believed that the concomitant and very complex professional condition would have affected the reliability of the results of the survey in an unacceptable way.p = 0.08). Patients in the IR arm were significantly older (p < 0.0001), were more frequently affected with respiratory diseases (p = 0.001), had worse functional ability (Barthel Index) (p = 0.001), and had a higher risk of falls according to the Morse Scale (p < 0.0001) and history of falls (p = 0.01). On the other hand, patients in the SoC group were more frequently affected with endocrine or metabolic diseases (p = 0.002). The characteristics of patients observed in the overall study population are reported in the The demographic and clinical characteristics of the mITT population are reported in p = 0.26) (p = 0.73). In total, 4 and 19 episodes of falls occurred in patients in the groups IR and SoC, respectively . The numbers of new pressure ulcers reported were 24 for IR and 23 for SoC .The primary outcome of cumulative incidence of falls and new pressure ulcers accounted for 28 events in the IR group and 42 events in the SoC group , 0.15 to 1.67;  = 0.26) . PatientCumulative numbers of events  during hospital stays are provided in Data on occurrence of falls and pressure ulcers in the overall study population are reported in the p = 0.38). The patient satisfaction questionnaire presented an average score of 13.25 ± 1.72 for IR and 12.17 ± 1.87 for SoC (p = 0.87).The mean number (SD) of bell calls for each patient was 15.4 ± 24.1 in the IR group and 13.7 ± 20.5 in the SoC group ; the effect was mostly related to a relevant and statistically significant difference of incidence of falls .Patient safety is a major objective for the implementation of a nursing care pattern, and the occurrence of falls has been investigated in a number of studies assessing the effectiveness of IR ,27,28,29Pressure ulcers are one of the most reported nursing-sensitive patient outcomes, with rates ranging from 5% to 32% of patients, and an estimated mean prevalence of 21% in acute settings . ThroughAlthough less clinically relevant than new pressure ulcers or falls, the phenomenon of calling the staff is one of the most investigated outcomes related to IR. The potential opportunity offered by IR is to anticipate the needs of the person and therefore achieve a greater satisfaction with the assistance received ; this caThe perceived satisfaction with the nursing care received is an additional point to consider while implementing a new method aimed at improving the quality of care. In the specific case of IR, this pattern of care could lead to an increase in satisfaction since patients perceive that the nurse is really interested in their care needs, both physical and emotional, thus feeling more peaceful and secure ,34. On tThe introduction of IR has brought with it doubts and perplexities that have been discussed in the scientific literature ,3, such Our results suggest that IR can be implemented in clinical practice. Based on our experience, to overcome barriers and for the successful implementation of IR, the leadership and the education play a key role ,10,36; iThe study has some points worth discussing and that can be considered possible limitations. First is the choice of the composite outcome. The literature indicates three recommendations for the ideal use of composite endpoints: the outcomes must be of similar importance for the patient, be of similar frequency, and have the same degree of sensitivity to the intervention . In our In conclusion, our study provides new data to support the usefulness of IR in addressing fundamentals of care, in particular in a complex and vulnerable population such as that hospitalised in internal medicine wards. The significant effect of reducing falls among patients assisted with IR represents an important clinical element in favour of patient safety and the adoption of this method. Future studies should further strengthen the evidence in this direction and address the open issues related to the implementation of IR, such as the profile of the patient who can benefit most from this method, as well as the workload associated with IR and its impact on the recovery of physical activities, self-government, and the critical thinking and decision-making ability of nurses.


A full PDMS micro-droplet chip for 3D cell culture was prepared by using SLA light-curing 3D printing technology. This technology can quickly customize various chips required for experiments, saving time and capital costs for experiments. Moreover, an injection molding method was used to prepare the full PDMS chip, and the convex mold was prepared by light-curing 3D printing technology. Compared with the traditional preparation process of micro-droplet chips, the use of 3D printing technology to prepare micro-droplet chips can save manufacturing and time costs. The different ratios of PDMS substrate and cover sheet and the material for making the convex mold can improve the bonding strength and power of the micro-droplet chip. Use the prepared micro-droplet chip to carry out micro-droplet forming and manipulation experiments. Aimed to the performance of the full PDMS micro-droplet chip in biological culture was verified by using a solution such as chondrocyte suspension, and the control of the micro-droplet was achieved by controlling the flow rate of the dispersed phase and continuous phase. Experimental verification shows that the designed chip can meet the requirements of experiments, and it can be observed that the micro-droplets of sodium alginate and the calcium chloride solution are cross-linked into microspheres with three-dimensional (3D) structures. These microspheres are fixed on a biological scaffold made of calcium silicate and polyvinyl alcohol. Subsequently, the state of the cells after different time cultures was observed, and it was observed that the chondrocytes grew well in the microsphere droplets. The proposed method has fine control over the microenvironment and accurate droplet size manipulation provided by fluid flow compared to existing studies. Microfluidic cell culture integrates knowledge from biology, biochemistry, engineering, and physics to develop devices and techniques for culturing, maintaining, analyzing, and experimenting with cells at the micro-scale. A key component of a microfluidic cell culture chip is being able to mimic the cell microenvironment which includes soluble factors that regulate cell structure, function, behavior, and growth. For example: co-cultivation and interaction between cells, construction and simulation of in vitro cell microenvironment, single-cell manipulation, bacterial culture and analysis, and chip organs, etc. ,2,3. MicTo sum up the multiple defects of 2D cell culture, the microenvironment of the cells in these defects is quite different from the real cell growth environment in vivo, so two-dimensional cell culture cannot truly and accurately reflect the true reaction of the cells in the body and will result in experimental deviations, so that the reliability and authenticity of the experimental results cannot meet the predetermined requirements. Three-dimensional (3D) cell culture just solves the problem of authenticity simulated in 2D cell culture and can reflect the normal anatomical and physiological characteristics of cells. The most common way to establish a three-dimensional cell culture environment on a microfluidic chip is to grow cells in a variety of natural or synthetic materials that mimic the extracellular matrix, such as Matrigel , collageIn summary of the various shortcomings and shortcomings of two-dimensional (2D) cell culture, this article is based on droplet microfluidics to study the rapid customization method and manipulation mechanism of micro-droplet chips for three-dimensional (3D) cell culture . BecauseMicrochannels are fabricated by casting the mixture of polydimethylsiloxane (PDMS) elastomer and a curing agent  against a 3D-printed mold. The mold was fabricated with a photocurable resin , using a commercial stereolithography machine.The preparation process of the micro-droplet chip is shown in (1)Modeling of chip convex moldUsing additive manufacturing, the positive mold required to prepare the full PDMS micro-droplet chip is printed out. The manufacturing steps are as follows:Design the flow channel structure of the micro-droplet chip and save it in STL format .(2)Parameters setting and printingThe principle of 45° angle;The principle of least support;The principle of single-angle start. Combining the above three principles, taking into account the subsequent requirements of the chip microchannel pouring Bonding re-quires surface roughness and transparency. It is not advisable to add too many sup-ports to the chip support plane. Therefore, we choose a cylindrical support with a den-sity of 100% and a printing inclination of 60° for chip printing .Formlabs company provides a dedicated data processing software environment. The software provides a simple function of automatically generating support and layout, and also provides the function of customizing the support and layout. When making a model layout and adding support, the following requirements need to be met: (3)Post-printing processingTake off the forming platform, insert it into the bracket, and then use a special shovel to remove the formed die model of the chip. Place the formed chip convex mold model in the cleaning box containing isopropanol solution on the left and soak for 10 min and shake it from time to time to clean the residual resin on the surface of the model, and then place it on the right and clean with 98% ethanol solution. Rinse in the box for 5–10 min to remove the isopropanol liquid on the chip. Place the model in a dust-free environment for 5~10 min to completely volatilize the ethanol on the surface of the chip, and also make the surface of the chip not fully cured for secondary curing.After drying, use a special tool to remove the model. Use 2500 mesh sandpaper to polish the surface with support residues to obtain the preliminary finished product of the chip.(4)Finished product on the surface of the substrate convex mold.Use a microscope to observe the surface of the printed substrate convex mold, as shown in (1)Preparation of the moldSubstrate mold production: use cardboard to make a rectangular paper cofferdam with a length and width slightly larger than the length and width of the substrate convex mold by 3 mm, and then place the substrate convex mold in the cofferdam to form a PDMS replication mold. The cover slip mold uses a Petri dish with a diameter of 75 mm as the mold.(2)The ratio and mixing of PDMS and curing agentIn order to improve the chip packaging strength, it can be achieved by changing the ratio of the matrix/curing agent in the PDMS cover sheet and the substrate. The main reason is: when the ratio of the matrix/curing agent in the PDMS cover sheet and the substrate is different, the adhesion interface layer produces molecular diffusion, thus forming a strong adhesion transition layer. Therefore, in this paper, the substrate is prepared according to the ratio of PDMS and curing agent of 10:1, and the cover sheet is prepared according to the ratio of PDMS and curing agent of 15:1. (3)Degassing to remove bubblesThe prepared substrate PDMS and cover sheet PDMS were placed in a transparent vacuum chamber for 30 min. The pressure in the vacuum chamber was maintained at −1 bar through a vacuum pump. As shown in (4)Pouring PDMS on the moldSpray an appropriate amount of release agent on the substrate mold and cover sheet mold in advance to separate the molded PDMS substrate and cover sheet; then, respectively, the substrate PDMS and cover sheet PDMS close to the edge of the mold and slowly pour into the mold, avoid new bubbles during the pouring process.(5)PDMS cutting and punching.Cut the two strips of PDMS into a 60 mm × 40 mm rectangle, and then punch holes in the corresponding position of the cover sheet PDMS with a diameter of 1.5 mm, as shown in (6)PDMS baking and stripping moldPut the prepared PDMS in a constant-temperature drying oven for 40 min. The temperature of the drying oven is constant. The removed substrate PDMS and cover piece PDMS are air-cooled to room temperature. And then the two pieces of PDMS are slowly peeled out of the mold. When the temperature in the drying box is set to 80 °C, the effect of PDMS is shown in The surface-forming effect of the runner is better without too obvious defects; but there are obvious cracks on the surface of the chip in contact with the mold. As shown in After several adjustments, it is found that the PDMS substrate has no previous cracks at 75 °C, as shown in (7)Bonding of PDMS chipThe bonding method of the PDMS chip can be roughly divided into the natural sealing method  or the sThe mixture of pure water and sodium alginate solution is used as fluid flow 1 of laminar two-phase flow and level set coupling, and mineral oil is used as fluid flow 2 of laminar two-phase flow and level set coupling. The basic parameters of the two fluids are shown in According to the three sets of data of the disperse phase flow rate X1 as 100 μL/h, 150 μL/h, 200 μL/h, set the continuous phase flow rate X2 with the difference of 10 arithmetic sequence to increase slowly, and observe the drop size situation, the experimental results are shown in The measured data shows that when the flow rate of the dispersed phase remains unchanged, as the flow rate of the continuous phase gradually increases, the droplets formed gradually decrease, as shown in There are many ways to establish a geometric model in COMSOL Multiphysics software. The first is to establish the geometric model of the flow channel structure in the built-in drawing module of COMSOL Multiphysics software, but this method is difficult for drawing complex shapes; the second is to draw the geometric model in AutoCAD and other drawing software and import it. The total length of the channel structure of the micro-droplet chip is 20.51 mm and the total width is 9.82 mm.According to the continuous phase X2 flow rate of 100 μL/h, 150 μL/h, and 200 μL/h three sets of data, set the dispersed phase flow rate X1 to slowly increase the arithmetic sequence with a difference of 10 for introduction, and observe the droplet size change In this case, the experimental results are shown in Based on comparing the data and relation from droplet size and the phase transition in The sodium alginate micro-droplets and 3% calcium chloride solution were subjected to an ion cross-linking reaction. The core of the cross-linking reaction is that the calcium ions in the calcium chloride solution replace the sodium ions on the sodium alginate G unit to form an “egg-box” structure. This structure can greatly improve the mechanical strength of the gel, so that the gel meets the requirements of mechanical properties. When the micro-droplet undergoes a cross-linking reaction, the micro-droplet becomes a micro-spherical droplet with a 3D structure. At this time, the droplet has certain mechanical properties and mechanical properties. The micro-droplets after cross-linking are shown in Calcium silicate powder and polyvinyl alcohol (PVA) solution are mixed to prepare a printing material, and the three-dimensional scaffold structure is printed out by a 3D-bioplotter printer and sintered to obtain a biological scaffold for supporting microspheres, as shown in After the cells were cultured for 0 h, 24 h, and 48 h, the Petri dish containing the microsphere droplets with 3D morphology was taken out of the incubator. Place the Petri dish under the YDF-880 fluorescence microscope for microscopic observation, and take pictures of the cell culture through the image acquisition function of the microscope. The culture of chondrocytes on the chip is shown in Microfluidic chips are now widely used in many fields such as gene mutation detection, genotyping, DNA sequencing, cell culture, cell sorting, and cell state research. These works mainly focused on the design and rapid customization of micro-droplet chips for three-dimensional (3D) cell culture, and apply SLA light-curing 3D printing technology to the preparation process of micro-droplet chips, making the preparation of micro-droplet chips faster and more convenient and more economical. The performance of the full PDMS micro-droplet chip in biological culture was verified by using a solution such as chondrocyte suspension, and the control of the micro-droplet was achieved by controlling the flow rate of the dispersed phase and continuous phase. Experimental verification shows that the designed chip can meet the requirements of the experiments, and it can be observed that the micro-droplets of sodium alginate and the calcium chloride solution are cross-linked into microspheres with three-dimensional (3D) structures. These microspheres are fixed on a biological scaffold made of calcium silicate and polyvinyl alcohol. Subsequently, the state of the cells after 0 h, 24 h, and 48 h culture was observed, and it was observed that the chondrocytes grew well in the microsphere droplets. All the results presented in this work verified that the chip design and manufacturing process used are feasible. It shows prosperous applications in the field of life science due to its nontoxicity and biocompatibility.This microfluidic chip is easy to manipulate and quantify for customizing. The proposed method has fine control over the microenvironment and accurate droplet size manipulation provided by fluid flow compared to existing studies.


Aphids are one of the main pests of cotton and have been an important disaster limiting cotton yield. It is important to use satellite multispectral data to monitor the severity of cotton aphids in a timely and accurate manner on regional scale. Based on the combination of derivative of ratio spectra (DRS) and random forest (RF) algorithm, this study researched the quantitative monitoring model of cotton aphid severity based on Sentinel-2 data. First, the cotton area was extracted by using a supervised classification algorithm and the vegetation index threshold method. Then, the DRS algorithm was used to analyze the spectral characteristics of cotton aphids from three scales, and the Pearson correlation analysis algorithm was used to extract the bands significantly related to aphid infestation. Finally, the RF model was trained by ground sampling points and its accuracy was evaluated. The optimal model results were selected by the cross-validation method, and the accuracy was compared with the four classical classification algorithms. The results showed that (1) the canopy spectral reflectance curves at different grades of cotton aphid infestation were significantly different, with a significant positive correlation between cotton aphid grade and spectral reflectance in the visible band range and a negative correlation in the near-infrared band range; (2) The DRS algorithm could effectively remove the interference of the background endmember of satellite multispectral image pixels and enhance the aphid spectral features. The analysis results from three different scales and the evaluation results demonstrate the effectiveness of the algorithm in processing satellite multispectral data; (3) After the DRS processing, Sentinel-2 multispectral images could effectively classify the severity of cotton aphid infestation by the RF model with an overall classification accuracy of 80% and a kappa coefficient of 0.73. Compared with the results of four classical classification algorithms, the proposed algorithm has the best accuracy, which proves the superiority of RF. Based on satellite multispectral data, the DRS and RF can be combined to monitor the severity of cotton aphids on a regional scale, and the accuracy can meet the actual need. It has the characteristics of large-scale outbreaks and is widely distributed in major cotton regions all over the world  Based on the multitemporal Sentinel-2 satellite data, the cotton area in the study area was extracted by using the supervised classification algorithm and vegetation index (VI) threshold method to remove unnecessary disturbing factors for the classification of aphid infestation severity; (2) The DRS algorithm was used to process and analyze the ground hyperspectral data, ground hyperspectral resampling data and Sentinel-2 multispectral image sampling point data. The sensitive bands associated with aphid infestation were extracted by Pearson correlation analysis, and the effectiveness of the DRS algorithm was verified; (3) The RF algorithm was trained and accuracy validated by multispectral image sample data for Sentinel-2 image classification and compared with four classification algorithms, spectral angle matching (SAM) , support22.1Xinjiang has very superior climate resources for agricultural production, and is especially suitable for cotton cultivation. Xinjiang is currently the main cotton growing area in China, accounting for 78.9% of the total cotton growing area and 87.3% of the total cotton production in the country in 2020. Due to the long growth period of cotton, the pest infestation effect is very obvious, resulting in many yield losses. There are four main species of cotton pests in Xinjiang, namely cotton aphid, cotton bollworm, cotton red spider and cotton plant bug , see 2.2.22, and the five-point sampling method was used to collect spectral data five times. Each measurement generated 10 spectral data, that is, the collection of ground spectral data of one sample point was completed. The collection of cotton canopy spectral data of 60 sampling points was completed according to this standard.The experimental period was the boll stage of cotton, when the cotton field was basically closed, which was conducive to the acquisition of cotton spectral information. The Field Spec Handheld portable non-imaging spectrometer was used to collect hyperspectral data of the cotton canopy. The wavelength range of the spectrometer is 325 nm-1075 nm and the spectral resolution is 1.4 nm. The spectral acquisition was carried out in sunny, windless, cloudless and well-lit weather. The acquisition time was between 10:00-16:00 Beijing time. The range of each sampling point was 4 mThe abnormal spectrum was removed from the cotton canopy hyperspectral data collected at each sampling point, and the average hyperspectral data of each sampling point were obtained. All the obtained hyperspectral data were classified according to different aphid infestation grades, and then the average value was calculated. Finally, the average spectrum of aphid infestation at different grades of cotton was obtained, as shown in In this study, the Sentinel-2B spectral response function was used to resample the ASD hyperspectral data to obtain the Sentinel-2B simulated spectrum of the ground sampling point. The resampling formula is:r_λn and are the band range corresponding to the ith band of the broadband sensor; and f(r) is the spectral response function corresponding to the broadband sensor (Sentinel-2B in this study).where R is the reflectivity of a channel of the simulated wideband sensor; r is the relative reflection value of the wavelength of the narrow band sensor; The specific operation method was to establish the average spectral data of each sampling point as a spectral library file in ENVI, and then resample the spectral library using the Sentinel-2B spectral response function of ENVI software to convert the narrow band spectrum into a wide band spectrum. The spectrum after resampling is shown in 2.2.3https://scihub.copernicus.eu/), including two satellites A and B, which can cover 13 spectral bands, from visible near-infrared to short wave infrared, with different spatial resolutions. The two satellites complement each other, and the revisit period is 5 days. Sentinel-2 is the only data with three bands in the red edge range, which is very effective for monitoring vegetation health information. The images used in this paper are Sentinel-2B L1C data. The specific parameters are shown in Sentinel-2 satellite data are from the ESA’s official website , ten bands of B1, B2, B3, B4, B5, B6, B7, B8, B8A and B9 were selected for the satellite band, and the spectral range was 442.3 nm-943.2 nm.According to the spectral acquisition time of the cotton ground canopy, the Sentinel-2B image data of two scenes on June 3 and July 13 were selected. Among them, the satellite image on June 3 is the auxiliary data. The cotton planting area was extracted from the multitemporal satellite data, and the satellite image on July 13 is the corresponding time data collected by the ground spectrum for processing and analysis.2.32.3.1To more accurately study the spectral feature extraction algorithm of different grades of cotton aphid infestation and avoid the interference of other ground objects, it is necessary to extract the cotton planting area in the study area. First, vegetated and non-vegetated areas need to be separated, according to the feature types on the satellite images of the study area, five ground types, including vegetation, buildings, roads, bare lands and clouds, were selected as supervised classification samples. Then, the SVM classification algorithm was used to classify the Sentinel-2 images in the study area on July 13. According to the classification results, vegetation areas were extracted and made into masks. As the main vegetation in the Korla region includes cotton and fragrant pear trees, according to the difference of NDVI values of cotton and fragrant pear, the Sentinel-2 image on June 3 was used to extract the fragrant pear planting area by using the VI threshold method  to make a mask. The cotton planting area mask in the study area was obtained by subtracting the fragrant pear mask extracted on June 3 from the vegetation area mask extracted on July 13. Finally, the mask was used to subset the Sentinel-2 image on July 13 to obtain the cotton planting area in the study area. The main process is shown in 2.3.2The DRS algorithm is a special spectral processing method based on the linear mixing model. The purpose of using the algorithm is to eliminate the influence of other features in multiple features to obtain the correspondence between the mixed spectra of the target feature and multiple features and finally extract the band that is sensitive to the spectral information of the target feature. First, the ratio of two continuous spectra is calculated band by band, and then the ratio spectrum is differentiated to obtain the DRS curve . AssuminjF is the proportion of each endmember in the mixed pixel. Under the premise of neglecting the error term, assuming that there are only two substances in the mixed pixel, the linear spectral mixing model can be simplified into formula (3).where i=1, 2, 3, …, m is the spectral band, j=1, 2, 3, …, n is the endmember component, and Both sides of formula (3) are divided by the spectrum of the second component at the same time, which becomes formula (4).Derive from both sides of formula (4) to obtain formula (5).2F, that is, the spectrum after derivation is only linearly related to the abundance of the first component, but not to the abundance of the material component as a divisor.It can be seen from formula (5) that the derivative spectrum is already independent of the content of the second component In this study, each pixel in the Sentinel-2 satellite multispectral image can be considered a mixed pixel of background plant and pest-stressed plant canopy spectra. Among them, the background plants are relatively healthy cotton plants that are not affected by pests, and aphid infestation is the main stress. To remove the interference of the background healthy plant information, the healthy cotton spectrum was selected as the background endmember, and the Sentinel-2 imaging spectral data were subjected to DRS processing pixel by pixel with it as the denominator, so as to obtain the spectral features that only reflect the stress degree of the cotton aphid, and then the effective band that can reflect the cotton aphid infestation was extracted.2.3.3RF is an integrated machine learning algorithm based on multiple decision trees proposed by Leo Breiman , which i(1) Suppose that the original sample set has N training samples, each sample has M features, and in the process of model training, n (n<N) sample subsets are extracted from the training samples with replacement through the bootstrap method.(2) The decision tree model is constructed by using N training samples extracted each time and randomly selecting m (m<M) features at each node. The information of each feature is used to calculate and determine the growth direction of the decision tree at the split node.(3) After K rounds of training, the results of each decision tree form a base evaluator sequence and then use a simple voting method to determine the results of the integrated evaluator.H(x) represents the final classification result of the model; I(.) is a property function; ih is a single decision tree classifier ; and Y is the output target variable (target variable). The upper bound of the generalization error is:where where PE* is the model generalization error; 2.3.4In this study, the cotton planting area was extracted based on the SVM supervised classification and the VI threshold method through multitemporal Sentinel-2 data. Then, the DRS was processed on the cotton aphid spectrum at three scales, and the differences in spectral characteristics were analyzed and compared, which proved the effectiveness of the proposed algorithm. The Pearson correlation analysis algorithm was used to extract the bands significantly related to aphid infestation. Finally, combined with the RF classification algorithm, the multispectral image data samples after DRS processing were divided into training samples and test samples according to the ratio of 2:1 for model training. According to the model result, the Sentinel-2 image was classified into aphid severity grades, and the classification accuracy was calculated. To prove the superiority of this algorithm, we compared it with four commonly used classification algorithms. The confusion matrix algorithm was used as the evaluation standard of the stability and prediction ability of the constructed model, and the effect of the DRS algorithm was evaluated. The main process of this study is shown in The confusion matrix, also known as the error matrix, is a standard format for accuracy evaluation in the form of a matrix with n rows and n columns. The specific evaluation indexes include four kinds: overall accuracy (OA), producer’s accuracy (PA), user’s accuracy (UA) and kappa coefficient, which reflect the accuracy of image classification from different aspects .ii represents the number of samples correctly classified, and nij represents that they belong to class j and are wrongly classified into class i, the evaluation index formula is as follows:Assuming that n represents the total number of samples in the classification accuracy evaluation, K represents the total number of classification categories in the classification accuracy evaluation, n33.1Using Sentinel-2 images of the study area, the cotton planting areas extracted by a combination of SVM supervised classification algorithm as well as VI thresholding method are shown in 3.23.2.1According to formula (4) in subsection 2.3.2, the ground ASD hyperspectral cotton canopy aphid infestation spectra of different grades in The spectra in 3.2.2Through formula (4), the spectral curves of cotton aphid infestation at different grades after ASD hyperspectral resampling were processed by the DRS algorithm. Similarly, using the healthy cotton plant spectra as the divisor and the aphid infestation stress spectra as the divisor , the Yueqi Young Scholar of China University of Mining and Technology (Beijing) (Grant No.2020QN07), the Geological Research Project of the Hebei Bureau of Geology and Mineral Resources (Grant No.454-0601-YBN-DONH), and the State Key Laboratory of Coal Resources and Safe Mining Open Research Project [Grant No.SKLCRSM20KFA09], the National Natural Science Foundation of China (41701488).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.


Academia Brasileira de Neurologia) was founded on May 5, 1962 in the city of Rio de Janeiro, under the leadership of Professors Deolindo Augusto de Nunes Couto and Adherbal Tolosa, who were disciples of Professors Antonio Austregésilo (founder of the first school of Neurology in Brazil and first professor of Neurology at the Faculty of Medicine of Rio de Janeiro in 1912) and Enjolras Vampré (founder of the São Paulo School of Neurology in 1925 and first professor of Neurology at the University of São Paulo), respectively.The Brazilian Academy of Neurology (ABN –At this time, the ABN symbol was created , which The first formal scientific meeting of ABN was held in the city of Curitiba, Paraná, in 1963, from June 30 to July 5, at the rectory of the Federal University of Paraná.In the same year as its foundation, ABN joined the World Federation of Neurology, and the first exam to obtain the title of specialist in Neurology took place in 1972.The ANP will complete 80 years of uninterrupted publication in 2023, since its creation, in 1943, by a group of professors from the University of São Paulo, under the initial coordination of Professor Oswaldo Lange and Professor Antonio Spina-França.Thus, in its 60 years of existence, ABN has achieved its primary objective, which is to promote the scientific development of Brazilian Neurology.


Following the publication of this article , similarSimilarities included the following figures, which appear to fully or partially overlap, despite being published in different articles and representing different conditions:inhibitor panel in Fig 3E of  and miR-pCDNA-PAQR3 scamble panel in Fig 5E of  and the PAQR3 panel in Fig 4D of , L1CAM pLanes 1–2 of the GAPDH panel in Fig 4D of .PLOS ONE did not receive responses to the queries regarding these concerns by the end of the original deadline and extension.Although the corresponding author initially replied to acknowledge receipt of our message, PLOS ONE Editors retract this article [The unresolved concerns call into question the validity and provenance of the reported results, and the adherence of this article to the PLOS Authorship policy. Therefore, the  article .All authors did not comment on the retraction decision, did not respond directly or could not be reached.


Knowing the personality and autonomy factors of bodybuilders is a necessity in order to improve sports training, which would lead to the development of mental skills specific to competitive bodybuilding. The purpose of the study was to identify perception differences in personality and autonomy factors for three age categories of competitive bodybuilders in order to optimize the sports training process. The secondary purpose of the study was to identify perception differences in the characteristics of personality and autonomy in relation to the increase in the sporting age category of the competitive bodybuilders. The research sample included 30 competitive bodybuilders aged between 18 and 53 years, of which 21 were male and 9 were female, who were divided into three groups according to the sporting age category: G1—junior (18–23 years old), 10 athletes (33.3%); G2—senior , 12 athletes (40%); G3—masters , 8 athletes (26.7%). In the precompetitive stage, three standardized questionnaires were applied to the study participants, namely, two personality questionnaires (CP5F and ZKPQ) and a personal autonomy questionnaire (PAQ), which provided us with useful information for understanding the psychological profile of bodybuilding athletes. The results of the study were statistically significant, with Cronbach’s Alpha coefficient indicating high internal consistency of the three questionnaires for all three sporting age groups, with higher values than the selected reference threshold of 0.700. According to the results of our study, the following personality and autonomy factors recorded higher and higher scores in direct relation with the increase in sporting age: extraversion, agreeableness, conscientiousness, emotional stability, autonomy, impulsive sensation seeking, value autonomy, behavioral autonomy, and cognitive autonomy. The personality and autonomy factors of which the scores did not increase directly proportionally to the sporting age category were sociability, activity, aggression–hostility, neuroticism–anxiety, and emotional autonomy. Competitive bodybuilders perceive the factors of personality and autonomy differently in relation to particularities of age and sports experience, and knowledge of these changes can contribute to the improvement of the sports training process Competitive bodybuilding aims to improve the esthetic and physical condition of the body through the symmetrical and harmonious development of muscle mass. The training process of bodybuilders includes specific exercises that use weights and specialized equipment. Athletic performance is influenced by age characteristics, anthropometric features, and the level of sports training ,2. CompeThe identification and impact of personality factors in elite bodybuilders is a topic of great interest for sports psychologists, coaches, and athletes to understand both the complex process of achieving success in sport and the sporting life motivations ,22,23,24Studies have highlighted that by carrying out a long formative process, such as sports training, it is possible to optimize characteristic psycho-neurological manifestations, behavior, temperament, and even personality as elements of the human genotype ,37,38. TThe specifics and characteristics of the practiced sport condition the staged and complex selection process regarding anthropometric parameters, physical and technical abilities, certain characteristics of personality, and autonomy in order to select subjects with the best sporting potential ,54,55,56Much research has focused on psychological training in competitive sport ,62, but The purpose of the study was to identify perception differences in personality and autonomy factors for three age categories of competitive bodybuilders in order to optimize the sports training process. The secondary purpose of the study was to identify perception differences in the characteristics of personality and autonomy in relation to the increase in sporting age category of competitive bodybuilders. The main hypothesis of the study started from the assumption that the characteristics of personality and autonomy are perceived differently by competitive bodybuilders in relation to the sports category of age and sports experience with an impact on the improvement of the training process. The knowledge by sports psychologists and coaches of the perception of personality and autonomy factors by competitive bodybuilders will facilitate the scientific management of training by understanding the psychological and behavioral aspects of athletes.The study was conducted from 18 August to 8 September 2021, in the precompetitive period of the National Bodybuilding and Fitness Championship organized between 9 and 11 September in Sibiu. The questionnaires were selected at the recommendation of sports psychologists, who argued that developing a complex psychological profile of the competitive bodybuilders should also incorporate the personality and autonomy dimensions. Studies have confirmed the multidimensional approach to the personality of elite athletes, recommending the parallel analysis of the three questionnaires selected for this research ,69,70,71The questionnaires were applied by sports psychologists and the authors of the study. Bodybuilders were contacted directly or by phone in order to agree to participate in the study. Through a video meeting on Google Meet, the bodybuilders were informed about the content, structure of the questionnaire, and the method of completing and evaluating the items. The questionnaires were edited online in Google Form and were competed online by the athletes in the presence of the authors using laptops/tablets. After completing the questionnaires, the results were centralized for statistical processing.G1—juniors aged 18–23, consisting of 10 athletes (33.3%): 4 female and 6 male; average years of competitive experience: female 3 years, male 5 years;G2—seniors aged 24–35 for female and 24–40 for male, consisting of 12 athletes (40%); 4 female and 8 male; average years of competitive experience: female 7 years, male 11 years;G3—masters aged over 35 for female and 40 for male, consisting of 8 athletes (26.7%); 3 female and 5 male; average of years competitive experience: female 16 years, male 21 years.The ascertaining study involved 30 competitive bodybuilders, of which 21 were male (70%) and 9 were female (30%). The 30 participants represented 95% of the established competitive bodybuilders in Romanian. All athletes included in the study are active, have relevant sports records, are qualified, and participate in national and international bodybuilding competitions. The sample was divided into three sporting age categories in compliance with the provisions of international bodybuilding regulations as follows: Inclusion criteria: active athletes qualified for the National Bodybuilding and Fitness Championship organized between 9 and 11 September 2021 in Sibiu, participants in bodybuilding competitions in the last 6 months, optimal health status, sports records as at least national champions, full completion of the questionnaires. Exclusion criteria: training discontinuity in the last 6 months due to illness or injury, non-qualification or non-participation in competitions in the last 6 months, returning incomplete questionnaires. The optimal state of health aims at the acceptance of the sports doctor for participation in trainings and competitions. The athletes were asked about the periodic medical visa and about injuries, illnesses, and treatments in the last 6 months. In the study were included only athletes with up-to-date medical visas and with the status of clinically healthy, as approved by the sports doctor. This aspect was relevant for the study, because a poor state of health determines the interruption of the preparation process and participation in competitions, and this situation can influence the mental state of bodybuilders and implicitly their perception of the factors analyzed in this study. Participation in the test was voluntary and based on the informed consent of each athlete. The study complies with the principles of the Declaration of Helsinki and was approved by the Ethics Board of the National University of Physical Education and Sport in Bucharest, Romania, no. 2089/01.10.2020.Two personality questionnaires were used in the study, which complement each other and integrate different and relevant characteristics for the investigated athletes, but also a personal autonomy questionnaire that provided important information for understanding the psychological profile of bodybuilding athletes. We mention that the questionnaires applied in this study were validated for the Romanian language ,72,73,74Five-Factor Personality Questionnaire (CP5F)—assesses extraversion, agreeableness, conscientiousness, emotional stability, and autonomy, being validated for the Romanian language ,69,70,71Zuckerman–Kuhlman Personality Questionnaire (ZKPQ)—investigates the five factors of the Alternative Five-Factor Model (AFFM). The questionnaire was structured into the five subscales , which were rated on the Likert scale as follows: 1 point—suits me very little, 2 points—suits me less, 3 points—suits me about half, 4 points—suits me much, 5 points—suits me very much ,71,72,73Personal Autonomy Questionnaire (PAQ)—assesses a person’s ability to control their own life and the feeling that there is a possibility to exercise this control ,74. The Description of the study questionnaires:T-scores were used to interpret the results obtained by the study participants (taking into account their gender and age) on the personality test scales. Standardized gender and age-group samples are valid for individuals included in the nonclinical population and allow the conversion of raw scale scores into T-scores. A T-score is low if it is less than 40 and high if it is above 60. Average T-scores are in the range of 40 to 60 . The queIndividual results, more specifically the responses to all items of the three personality questionnaires administered to each athlete, were entered into the CAS++ (Cognitrom Assessment System) application ; the sysp < 0.05.The results of the study were statistically processed using SPSS 2022 software. To highlight the correlations between the results, the following statistical parameters were used: mean (X), standard deviation (SD), Student test (t), and the two-level (lower/upper) confidence interval (95% CI). Principal component analysis (PCA) was calculated for Bartlett’s Test of Sphericity (Chi-square) and the Kaiser–Meyer–Olkin (KMO) Test. For the reliability or internal consistency of the questionnaires, Cronbach’s Alpha index was calculated, and the lower bound was 0.70 for all measures. The mean difference between the three independent age groups was analyzed using analysis of variance (ANOVA). The value of the statistical reference significance was The relevant results obtained by the three sporting age categories of competitive bodybuilders were structured and presented according to the three questionnaires and the study objectives.2 (15) = 37.373, p < 0.001; for G2, χ2 (15) = 60.117, p < 0.000; for G3, χ2 (15) = 33.439, p < 0.004. According to Analysis of the mean scores for CP5F  highlighp < 0.05 for the three sporting age categories. The highest arithmetic means were recorded by G1 for the Agreeableness subscale with 48 points, by G2 for the Autonomy subscale with 54.230 points, and by G3 also for the Autonomy subscale with 57.625 points. The lowest arithmetic means were recorded by G1 for the Extraversion subscale with cu 44.692 points, by G2 for the Agreeableness subscale with 48 points, and by G3 also for the Agreeableness subscale with 54.125 points. Analyzing the results in The arithmetic means recorded for the CP5F subscales  showed t2 (10) = 30.988, p < 0.003; for G2, χ2 (10) = 37.364, p < 0.000; for G3, χ2 (10) = 38.607, p < 0.002. According to Bartlett’s Test of Sphericity values indicate a sufficiently high correlation for PCA between the Personal Autonomy Questionnaire (PAQ) subscales as follows: for G1, χThe total score of the Personal Autonomy Questionnaire (PAQ) reflected that all three sporting age groups fell within the average range (40–60 points) of T-score interpretation. Mean score differences between the three samples were 0.400 points for G1–G2; −1.201 points for G1–G3; and −1.601 points for G2–G3 .p < 0.05 for the three age groups; at the same time, all these values fell within the lower and upper bounds of the 95% CI.The Zuckerman–Kuhlman Personality Questionnaire (ZKPQ) is a complex tool that consists of five subscales measuring the basic factors of personality, which can be used to optimize the behavior of elite athletes. Analyzing the results of each sporting age category , it was A comparative analysis of the results shown in It should be noted that for the Sociability and Activity subscales, the highest mean scores were recorded by G3 and the lowest mean scores by G2; for the Impulsive sensation seeking subscale, the highest mean score was recorded by G3 and the lowest mean score by G1; for the Neuroticism–Anxiety and Aggression–Hostility subscales, the highest mean scores were achieved by G2 and the lowest mean scores by G3 .2 (10) = 6.266, p < 0.000; for G2, χ2 (10) = 75.659, p < 0.000; for G3, χ2 (10) = 66.067, p < 0.004.Cronbach’s Alpha scores  revealedThe T-score of the Personal Autonomy Questionnaire (PAQ) showed that all three sporting age groups fell within the average range (40–60 points) of T-score interpretation. The lowest personal autonomy (PA) was recorded by G1: 18–23 years of age, with a total mean score of 48.777 points, and the highest PA was recorded by G3: Over 35F/40M years of age, with a total mean score of 56.781 points, which also reflects the level of sports experience. Mean differences between the T-scores of the three samples were as follows: 5.972 points between G2 and G1, 8.004 points between G3 and G1, and 2.032 points between G3 and G2, which indicated that an increase in sporting age category leads to an increase in the level of personal autonomy.p < 0.05 and fell within the lower and upper bounds of the 95% CI. As regards the Personal Autonomy Questionnaire (PAQ), G1 (18–23 years of age) recorded the highest arithmetic mean for the Value autonomy subscale with 52 points and the lowest mean score for the Cognitive autonomy subscale with 45.222 points; G2 (24–35F/40M years of age) recorded the highest arithmetic mean for the Behavioral autonomy subscale with 55.769 points and the lowest mean score for the Emotional autonomy subscale with 52.692 points; G3 (Over 35F/40M years of age) achieved the highest score for the Behavioral autonomy subscale with 60.500 points, while the Emotional autonomy subscale, with 50.500 points, was less relevant for the study athletes. Overall, the subscale that recorded the highest total mean score (T-score) was the Behavioral autonomy subscale with 60.500 points for G3, and the lowest T-score was recorded by G1 for the Cognitive autonomy subscale with 45.222 points.According to Mean score differences for each subscale of the Personal Autonomy Questionnaire (PAQ) revealed that the largest differences were recorded between G1 and G3 for the Value autonomy, Behavioral autonomy, and Cognitive autonomy subscales, and the smallest difference, −1.723 points, was recorded also between G1 and G3 for the Emotional autonomy subscale. The mean differences between G1 and G2 and G2 and G3 highlighted that the largest differences were recorded for the Cognitive autonomy and Behavioral autonomy subscales, and the smallest differences for the Value autonomy subscale. Analyzing the dynamics of these differences in relation to the increasing age of inclusion into the sports category, it was found  that as the individual grew older, there was an increase in value autonomy, behavioral autonomy, cognitive autonomy, and emotional autonomy, and the dynamics of these results reflected that the largest differences were between G1 and G3, but the differences between G1 and G2 were also larger than those between G2 and G3 for all subscales .The ANOVA data  facilitaThe present study aimed at identifying the differences in personality and autonomy factors in order to identify the differences in perception for three sporting age categories of bodybuilding athletes. We believe that the results obtained and analyzed in this study will contribute to a better understanding and the expansion of knowledge about the possibilities of developing personality traits in relation to the sport practiced and the bodybuilding-specific differences by sporting age category. The main results of the study fall within the research directions specific to sports psychology, pointing out particular psychological aspects typical to competitive bodybuilders. Psychological profiles can be developed by highlighting the dynamics of perceived personality factors according to the three sporting age categories, which are regulated for international competitions as follows: junior: 18–23 years old; senior: 25–35 years old for female and 25–40 years old for male; masters: over 35 years old for female and 40 for male. The results of our study emphasize numerous differences between the three age categories of competitive bodybuilders, and we believe that these differences arise from athletic experience, competitive experience, and psychological and behavioral maturation in relation to the specifics of the sport practiced.The concerns of experts in sports psychology and specialists in competitive sports have focused on how personality factors determine and influence the optimization of sports performance ,76,77,78Extraversion was another personality factor studied by sports psychologists, who emphasized that bodybuilding and fitness athletes with high levels of extraversion were more susceptible to exercise addiction ,90. The Several studies have examined the relationship between personality and competitive anxiety, concluding that the type of sport and the gender of athletes are determining factors for the level of sports anxiety ,96,97. OThe strengths of the study are as follows: identification of the differences between the three sporting age samples of competitive bodybuilders included in the study; the inclusion in the study of all successful competitive athletes at the 2021 Romanian national championships; and the complex analysis of ten personality factors and four personal autonomy factors. Limitations of the study include the relatively low number of elite bodybuilding athletes in our country; unequal gender distribution of athletes into the three study groups; and the inclusion in the current study only of competitive bodybuilders who obtained the title of national champion and participated with good results in international competitions at the Balkan, European, and world levels.The results of the study confirm the main hypothesis, which is that there are significant differences in the perception of the factors of personality and autonomy of competitive bodybuilders in relation to the sports age category and sports experience. According to these results, the following personality factors recorded higher and higher scores in direct relation with the increase in sporting age: extraversion, agreeableness, conscientiousness, emotional stability, autonomy, and impulsive sensation seeking. Personality factors such as sociability and activity recorded higher values in the junior and masters groups compared to the senior group. The aggression–hostility and neuroticism–anxiety personality factors had also lower scores in the junior and masters groups compared to the senior group. Analyzing the results of the Personal Autonomy Questionnaire (PAQ), it was seen that the value autonomy, behavioral autonomy, and cognitive autonomy factors increased with the increase in sporting age category, while the emotional autonomy factor recorded the lowest scores in the junior and masters groups and the highest score in the senior group. Achieving performance in bodybuilding depends on the level of development and manifestation of personality and autonomy factors, and their dynamics are influenced by age characteristics, athletic experience, and the type of sport practiced. The scientific management of sports training requires from the staff the knowledge of athletes in their complexity, and the factors of personality and autonomy are important in understanding the personality and behaviors of athletes. The identification of the differences in the perception of competitive bodybuilders depending on the age category and sports experience contributes to the identification by sports psychologists and coaches of the most effective strategies for approaching the psychological counseling process. The identification of the common aspects and the differences of perception of the factors of personality and autonomy are current concerns of the specialists and researchers in the field of sports psychology, and the expansion of the knowledge of these aspects depending on the training and competition characteristics of the sport, the sports experience, the category of sports age, such as the breakdown of specialists from the technical staff, etc., can contribute to the optimization of the sports training process.