Some reports in the literature show the advantages of fluoride-containing apatite ceramics over hydroxyapatite (HAP), at least in some aspects. While HAP has been used extensively in the treatment of bone defects, fluoridated apatite has hardly been tested in vivo. In order to verify the biological properties of fluoride-doped apatite and to assess its therapeutic potential, we synthesized fluorapatite (FAP) and applied it as a filling in bone defects of experimental animals (rabbits). The treatment effects were evaluated on extracted bones after 3 and 6 months from implantation using peripheral quantitative computed tomography (pQCT), dual-energy X-ray absorptiometry (DXA), radiography (X-ray) and histological staining. The study proved the integration between FAP and the bone tissue, thus indicating its stimulating effect on new bone formation and mineralization. The results achieved after 3 months of treatment were difficult to interpret unequivocally and suggested the transient delay in FAP integration of bone in comparison with HAP. The reasons for this phenomenon are unclear. Most likely, these differences between FAP and HAP resulted mainly from the different porosities, densities and ionic reactivity of the ceramics, which in our opinion affected their solubility, integration and degree of bone tissue resorption. However, it was shown that 6 months after implantation, similar level of bone defect regeneration was achieved for both FAP and HAP. In this article, we present our hypothesis concerning the basis of this phenomenon. The process of bone replacement has been used in surgical practice for many years. Many different materials are used for this purpose, including PMMA-based bone cements. They have been extensively studied in the literature both in vitro ,2,3 and In the literature, there are many studies indicating that the use of fluorapatite in regenerative medicine may be beneficial. Wu et al. revealed that fluoride-doped apatite can increase collagen synthesis . FluoridRecently, we presented the properties and biological potential of a new fluoride-substituted apatite (FAP) dedicated for application in orthopedics and bone tissue engineering . In-deptThe purposes of this study were to evaluate the capability of FAP in bone defect healing, to assess its safety, and to potentially expand the use of fluoride-containing materials in orthopedics and regenerative medicine. Therefore, we conducted an in vivo study in an animal model  where FAP granules were implanted into critical-size bone defects of the tibia to assess new bone formation and the degree of mineralization. Additionally, we applied HAP granules as a reference material to compare the properties and biological potential between less popular fluoride-substituted apatite and widely used non-substituted hydroxyapatite. 2; Acros Organics, Verona, Spain), orthophosphoric acid  and sodium fluoride . The mixture of H3PO4 and NaF with [P]/[F] a molar ratio of 3:1 was added to a 10.8-fold amount of aqueous Ca(OH)2 suspension with continuous stirring at room temperature. The precipitate was allowed to age for 4 days, then washed several times with deionized water and dried at 37 °C. Finally, the FAP precipitate was calcined at 800 °C for 2 h in a muffle furnace. HAP ceramics made using the same method without the use of NaF served as a reference for the FAP material. In this study, we used apatite granules with a diameter of 0.2–0.3 mm. The process of producing FAP and HAP granules and their properties have been described in previous publications [FAP granules were synthesized in a laboratory of the Chair and Department of Biochemistry and Biotechnology , according to the procedure described in the Polish patent no. PL 235803. The following substrates have been used for the synthesis of FAP: calcium hydroxide (Ca(OH)ications ,20. BasiAll research protocols were approved by the Local Ethics Committee (agreement number LKE-70/2016) and the experiment was conducted in accordance with the provisions on animal protection. The implantation procedure was planned and performed according to some current references ,22,23.The in vivo experiment was carried out on a group of male New Zealand white rabbits who entered the study at the age of 6 months and with an average body weight in the range of 2.5–2.8 kg. The 52 animals were placed in the animal facility of the Experimental Medicine Center of the Medical University of Lublin, were bred in optimal environmental conditions appropriate to the species  and fed with complete feeding and constant watering capacity. -Control: Rabbits that have undergone a “sham surgery”, with an empty hole in the bone left to heal (n = 10);-FAP: Rabbits that have implanted FAP granules (n = 18);-HAP: Rabbits that have implanted HAP granules (n = 18).After a one-week adaptation period, rabbits were randomized into 3 groups:Control, FAP and HAP groups were further divided into 2 subgroups according to the time of healing periods, 3 months and 6 months, resulting in the following groups shown in Before surgery, rabbits were subjected to analgosedation via inhalation with 5% isoflurane in 95% oxygen, and then maintained under anesthesia under 3–4% isoflurane in 96–97% oxygen. Rabbits under anesthesia were transferred to the operating table equipped with a heating mat and body temperature monitor. After injecting the first group with anesthesia, animal hair was removed from the operating field using an electric razor, and then the operating field was disinfected with 96% isopropyl alcohol, which is generally used for disinfecting the operating field in humans. The skin and fascia were incised with the help of a scalpel blade no. 15 at a length of 2 cm; hemostasis was performed and the appropriate point for making the hole was located. During the procedure, 9 mm and 4.5 mm wide holes were made in all the animals using a 4.5 mm cortical drill, also used in orthopedics and human traumatology. The holes were made in the proximal end of the tibia on the medial side in the area of the so-called goose foot, the place of attachment of the knee flexors. The implant sites were chosen approximately 1.5 cm below the growth cartilage to avoid damaging it. The holes were similarly made in the area of the left lower limbs and filled with FAP or HAP granules, as shown in After implantation of the ceramics, the fascia of the goose foot area was tightly sutured with a 3–0 absorbable thread to prevent subsequent material migration, and then the skin was sutured with a 3–0 dermal thread. The instruments used for surgical procedures were sterilized in accordance with the rules adopted in the orthopedics of the operating theater. In the Control group, the hole was left to heal itself. Immediately after the surgery, radiographs of the tibiae in the lateral (L) view were performed in all subjects in vivo. After the given period (3 or 6 months), the rabbits were slaughtered, the lower limb bones of the operated area were dissected, and the tibia bones intended for research were cleaned of residual soft tissues. Qualitative and quantitative analyses of the healing process were performed in each group on the bone samples prepared this way.Imaging examinations are methods that allow for the observation of changes in the operated bones in vivo. X-ray is a recognized diagnostic method to assess the process of bone healing or its absence. Comparative analysis of X-ray images obtained on the first day and 3 and 6 months from the fracture provides a qualitative assessment of the healing process. The process of reducing or increasing bone density is directly reflected in the weakening of the X-ray beam, manifested as radiolucency and radioopacity, respectively . MoreoveIt is worth mentioning that the radiological pictures were taken in vivo in the lateral view of all operated bones immediately after the surgery while the anesthesia was still in effect. Based on the radiographs, the location and repeatability of the drilled bore, the degree of filling with the bone substitute material in the groups in which it was administered, and the presence of any iatrogenic refractions that may have emerged during the procedure were assessed.Radiologic evaluation of the healing process was documented and performed posthumously in each group . After bone isolation, the radiographs showed all the proximal tibia ends in three projections: posterior anterior (P-A), lateral (L) and oblique (O).The radiographs were taken with a Planmeca Intra X-ray machine ) with a high-frequency generator (66 kHz) via a Toshiba D-0711 SB lamp  (focus 0.7 × 0.7 mm). CCD sensor with dimensions of 24 × 42 × 6 mm, pixel size of 19/38 μm with a closed sensor of 940 kB was used. Anode voltage was in the range from 50 to 70 kV, anode current value was in the range from 2 to 8 mA, and exposure time was from 0.01 to 3.2 s. The electrical exposure conditions repeated for all radiographs were as follows: 60 kV, 5 mA, 0.05 s, and 0.25 mAs.For histological analysis, 2 cm fragments of the proximal part of the tibia were used. The bone material was decalcified in EDTA solution, embedded in a Cryomatrix gel and then frozen in liquid nitrogen. The frozen bone material was cut in cryotome into slices of 10–12 μm. The sections were stained with Harris hematoxylin and eosin . Microscopic images were collected using a Olympus CKX53 light microscope , magnification ×400, and a camera Olympus EP50 .Tissue bone analysis using the DXA method is a recognized procedure and considered to be the “gold standard” in densitometric measurements. This method is widely used in osteoporosis diagnostics, allowing for the determination of the current state of bone mineralization. In our studies, isolated tibia bones were evaluated. The application of this method allowed for the determination of density and mineral content of the examined bones in relation to the osteointegration of bone substitute material. Despite the fact that creating an opening and introducing the evaluated bone substitute material was limited to a specific location and its size was small, it does impact the metabolism of the entire bone. It should be emphasized that in the DXA examination, the bone is treated as a whole, and the measurements performed are two-dimensional (2D). Therefore, the authors considered it appropriate to analyze the damaged area of the bone using peripheral quantitative computed tomography. This method enables the measurement of real volumetric bone mineral density (vBMD) and mineral content (BMC) in a three-dimensional (3D) system. pQCT allowed for an understanding of the intensity of obliteration within the damaged bone area and the incorporation of the bone biomaterial material .In the available literature, a period of 6 months is the most suggested as necessary for proper osteointegration. This applies to both dental implants  and othe2). The DXA test was performed on whole bones isolated from animals using a Norland Excell Plus densitometer  combined with Norland Illuminatus Software Rev. 4.3.1 Small Subject Scan. The scanning parameters included a resolution of 3.0 × 3.0 mm with a scanning speed of 10 mm/s. Calibration of bone mineral density measurements was performed using the hydroxyapatite phantom provided by the manufacturer. The quantitative analysis of DXA was performed in each of the groups after three and six months and in the reference group by analyzing the bone mineral content, BMC (in grams), and bone mineral density, BMD (g/cm3) and total bone mineral content  were assessed. The pQCT study was performed only in the part of the bone subjected to the implantation procedure using the XCT Research SA Plus apparatus  combined with the Stratec v.5.50D software. Initial scanning was performed for the proximal end of the femur in 0.25 mm slices with a table travel of 7–10 mm/s (PITCH). The Region of Interest (ROI) was then selected at the site of the widest section of the bone defect where pQCT quantification was performed. The ROI fragment included the cortical and spongy bone layers and bone substitute material in the research groups. During analysis, the total bone mineral density . One-way ANOVA followed by Tukey’s multiple comparison test was applied to determine statistically significant differences between the tested groups.During the study, all 52 rabbits survived the surgery and the entire period of treatment without any complications. Based on the preliminary radiographs, a similar size of the drilled holes was found. The bone substitutes in each case were applied in a similar volume, which resulted in the complete filling of the bone defect.Radiographic examination of rabbits tibiae during the implantation procedure showed a much higher absorption of X-rays for FAP and HAP bone substitutes than for the surrounding bone. The FAP material showed slightly higher radiopacity at the implantation site in the radiographs than the HAP material. In the Control group, without the addition of the bone material, the defect site appeared as a radiolucency area at the site of bone drilling. Lateral radiographs of rabbit tibiae from FAP, HAP and Control groups on the day of the procedure, and after 3 months and 6 months are presented in On the radiographs taken after three months in the FAP group, a stripe of radiolucency was found in all individuals in the transition zone between the bone graft material and the bone B. After Histological examinations showed that 3 months after the implantation of the FAP and HAP in the part of the proximal tibial metaphysis, the implanted material showed only a slight integration with the bone tissue, and no signs of inflammation were found in the tested preparations. Both in the HAP and FAP groups, it was shown that the material adhered closely to the bone tissue, and numerous osteocytes were present on the edges of the compact and spongy bone A,B.Six months after implantation in the HAP group, further progressive osseointegration with the HAP in the form of a delicate plexus bone layer was found C. In theSubsequently, changes in the microstructure of the bone defect were quantified by measuring bone density and mineral content using peripheral quantitative computed tomography (pQCT) and dual-energy X-ray absorptiometry (DXA). In addition, pQCT bone cross-sections are shown in The mineral content and density of whole bones obtained via DXA showed no statistically significant differences between the study groups. Tibial bone preparations filled with FAP showed a higher mineral content (BMC) compared to the group with HAP granules, 4.388 g and 4.06 g (on the 1st day of the study); 4.134 g and 3.981 g (after three months); and 3.996 g and 3.823 g (after 6 months), respectively; however, these differences were not statistically significant . BMD in Quantitative analysis via pQCT showed statistically significant measurements. In the first day after implantation of ceramic granules, the mean TOT-CNT value for FAP was significantly higher (49.89 mg) than for the HAP group (36.96 mg). After 3 months, TOT-CNT increased in both groups, with a greater increase (in comparison to reference) observed in the HAP group. As a result, the difference in mineral content was not statistically significant between the FAP 3M and HAP 3M groups, while there were statistically significant differences between FAP 3M and Control 3M and between HAP 3M and Control 3M. In sixth month of the experiment, the mineral content in the FAP group increased to 59.9, while in the HAP group, it decreased to 45.1 . The mea3 and 505.4 mg/mm3, respectively. The TOT-DEN values for both materials in the sixth month of the study were similar and amounted to 842.1 mg/mm3 for FAP and 840.1 mg/mm3 for HAP. These values were significantly higher than mineral density in the Control group, which was 579.9 mg/mm3  compared to the group with HAP granules, 658.8 mg/mm9 mg/mm3 .Both the bone graft materials (FAP and HAP) appeared on the radiographs as areas of radiopaque with a much higher degree of radiation absorption than the surrounding bone tissue. The qualitative assessment of the radiographs showed a difference in radiopaque between FAP and HAP, with a higher degree of radiation absorption in the FAP group which results from the higher density of the FAP granules, as presented in In general, the FAP material integrated well with the bone tissue. After 3 months, an interesting phenomenon was observed at the bone-implant interface B. StripeSome periosteal reactions observed on the border between the bone graft material and the normal bone in the HAP 3M group indicate good integration of HAP with tissue in vivo. This observation is consistent with other studies indicating good bioactivity and high biocompatibility of HAP ,33,34. IAccording to DXA, the biggest difference in BMC was between the FAP Ref and HAP Ref groups. Considering the same size of bone defects in both groups and the same volume of implanted material, this difference is probably due to the density of these granules, as shown in Contrary to DXA, pQCT results showed statistically significant differences between some tested groups. BMC in the FAP group continued to increase over time, while in the HAP group, it reached its highest level after 3 months, and after 6 months, there was a slight decrease. A continuous increase in BMC in the FAP group may indicate a natural increase in bone mineralization during the repair processes in the absence of significant resorption of bone substitute material. The decrease in BMC in the HAP group in the sixth month of observation, after its initial increase in the third month of measurement, most likely indicates partial resorption of the bone graft material . Our quaIn further scientific work, we plan to focus on developing and testing the biological potential of composite materials containing FAP. Numerous reports indicate the advantages of adding a polymer components to various granules, powders or nanomaterials ,45,46,47The purpose of this paper was to verify the advantage of FAP over HAP in bone tissue regeneration in vivo, based on the literature and our previous in vitro studies. However, the results obtained in the animal study did not conclusively support this hypothesis, as similar bone regeneration effects were obtained for both tested ceramic materials after 6 months of treatment. These observations can be a starting point for further works related to the optimization of FAP properties or the development of a new composite material containing FAP in order to stimulate the bone tissue regeneration process.Borkowski: L.; Belcarz, A.; Przekora, A.; Ginalska, G. Production Method for Biocompatible Implant Material. Polish Patent no. 235803, 6 October 2020.


Al/Fe bimetals prepared by a compound casting method, combining the excellent properties of both the Al alloy and the ductile cast iron, exhibit great potential for application in achieving engine weight reduction. However, the problem of insufficient interfacial bonding ability because of the difference in thermophysical properties of Al and Fe is particularly prominent. Therefore, in this work, the electrodeposited Cu coating on the surface of the Fe matrix was used as the interlayer of Al/Fe bimetal fabricated by coupling hot-dipping with compound casting to solve the above problem. The effect of Cu interlayer thickness on the interfacial microstructure and shear strength of bimetal was investigated. The experimental results showed that the shear strength up to 77.65 MPa in regard to Al/Fe bimetal with a 5 μm Cu interlayer was obtained. No Cu element was detected at the interface of bimetal regardless of the thickness of the Cu interlayer. The diffusion behavior of the Cu atom at the interface and the influence of the Cu layer at the atomic scale on diffusion reaction and the Al/Fe interface were further revealed by combining first-principle and molecular dynamics calculations. The simulation results revealed that the Cu layer gradually dissolved into an Al alloy at 750 °C, thereby promoting the diffusion reaction of the Al/Fe interface. Meanwhile, the protective role of the Cu layer against oxidation on the surface of the Fe matrix was confirmed. As a result, the interfacial bonding performance was enhanced when the Cu interlayer was introduced. The bimetal composites formed by the combination of two metals through a specific process technology can give full play to the advantages of both metal materials, thus effectively improving the overall performance ,2. Al/FeA review of the available literature reveals that a coating present on the surface of the iron matrix by surface treatment as the interlayer could improve the wettability of the Al alloy melt on the solid Fe surface ,9,10. AtAlthough preliminary studies have been conducted on the preparation of electrodeposited Cu coating as an interlayer in bimetals, there is still a lack of research reports on the effect of Cu interlayer thickness on the interfacial microstructure and properties of the bimetal. Therefore, in this work, the mechanism of the Cu interlayer in the bimetal forming process and the law of its thickness on the microstructure and properties will be revealed through a combination of experiments and simulations.In this work, ductile cast iron was selected as the solid matrix material, and Al-Si alloy was used as the raw material of the liquid Al alloy melt during hot-dipping and casting. Prior to compound casting, the ductile cast iron matrix was machined into tubular substrates with an outer diameter of 41 mm, inner diameter of 36 mm, and height of 65 mm. Then, Cu coating was deposited on the surface of substrates by electro-brush plating equipment. The specific process was conducted in the following steps. The substrate was first subjected to electrical cleaning and then activation treatment, followed by electro-brush plating. Finally, the substrate was cleaned with alcohol and dried in cold air. Among them, it is critical to rinse the substrate with deionized water after finishing each step. The velocity of electro-brush plating was about 400 r/min. As the thickness of Cu coating depends on the deposition time, therefore, the deposition times in this work were 5 min, 10 min and 15 min. Subsequently, the thickness of Cu coating at different times was measured by the thickness tester, and the average of the four measurements was taken as the final value, as shown in During compound casting, the substrates with Cu coating were first preheated to 250 °C for 5 min, followed by hot-dipping in the Al-Si alloy melt at 750 °C for 1 min. After that, the substrates were rapidly placed into a metal mold that was subjected to preheating to 300 °C. Then, the Al-Si alloy melt at 710 °C was poured into the mold around the substrate immediately. When the mold cooled to room temperature, Al/Fe bimetal with Cu interlayer was obtained. Meanwhile, Al/Fe bimetal without Cu interlayer, i.e., the as-casted bimetal, was also prepared for comparative investigation. For convenience, the as-casted bimetal and the bimetal with different thickness Cu interlayer  are represented by Cu-1, Cu-2, Cu-3 and Cu-4, respectively.The interfacial microstructure of Al/Fe bimetal with and without Cu interlayer was characterized by scanning electron microscopy (SEM) equipped with energy-dispersive X-ray spectroscopy (EDS). Push-out tests were detected using a universal testing machine to evaluate the interfacial bonding property of bimetal under the displacement rate of 1 mm/min; the detail of the test specimens has been reported in the previous literature . The fra−5 eV/atom, and the structures relaxed until the forces acting on the atoms were less than 0.03 eV/Å. For the pseudo-potential, the electronic configurations were [Al]3s23p1 [Fe]3p63d64s2 and [Cu]3p63d94s2, respectively.The first-principle calculations were performed by the CASTEP package ,17, whicz-direction). The schematic diagram of the Al-Cu-Fe interdiffusion model is illustrated in All of the MD simulations in the present work were conducted with the program Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) developed by Sandia National Labs . The modFrom 2Fe3Si3 phase with a white particle shape. In addition, according to 3Fe, Al5Fe2 and Al2Fe3Si3 phase, while the region adjacent to the Al alloy side is dominated by Al8Fe2Si phase. This is consistent with what is mentioned in the existing literature [In order to identify the effect of the Cu interlayer on the interfacial phase composition of Al/Fe bimetals, the composition of the different regions of the interface was examined, and the results are summarized in terature ,22,23,25The above experimental data reflect that the Cu interlayer is highly susceptible to complete dissolution during the hot-dipping and casting process; therefore, it is necessary to investigate the diffusion behavior of the Cu atom at the interface. Combining first-principles and molecular dynamics calculations, the influence of the Cu layer at the atomic scale on diffusion reaction and the Al/Fe interface is further revealed. This work focuses on the Al(100)/Cu(001)/Fe(001) interface selected based on the mismatch theory. The atomic structure of the Al/Cu/Fe interface is optimized using first-principles calculations, and the surface model of the interface tends to converge with the relaxation of atomic positions for a 7-layered Cu structure. Subsequently, molecular dynamics simulations of interfacial diffusion are performed on the Al/Fe bimetallic model with a 7-layered Cu structure, as depicted in In this work, the electrodeposited Cu coating was used as the interlayer of Al/Fe bimetal prepared by compound casting to improve the interfacial bonding strength. The experimental data revealed that when the thickness was 4.7–26.7 μm, the Cu interlayer was completely dissolved during the fabrication of Al/Fe bimetal. The simulation result also confirmed that the Cu layer gradually dissolved into Al alloy at high temperature, and when the Cu layer completely dissolved, the interface diffusion reaction between Al and Fe atoms occurred. The reaction layer width was increased after introducing the Cu interlayer, but the morphology of the reaction layer near the Al alloy side gradually became smooth from a rough boundary as the thickness of the Cu interlayer increased. The phase composition of the reaction layer was not significantly affected due to the dissolution of the Cu interlayer. Nevertheless, the shear strength of Al/Fe bimetal with a 5 μm Cu interlayer was about 1.5 times higher than that of as-casted bimetal. This was mainly attributed to the barrier of the Cu interlayer to the oxide film on the surface of the Fe matrix, the dissolution of the Cu interlayer contributing to the adequate interfacial reactive layer, as well as the special structure of the reaction layer adjacent to Al alloy side increasing the contact area.


The subject matter of the reported work refers to studying the interactions followed by the excited-state generation, which are chemical models of oxidative processes leading to a weak light emission emerging from living cells, and to explore the possibilities of using them as tools for evaluating the activity of oxygen-metabolism modulators, most prominently, natural bioantioxidants of biomedical value in particular. Methodologically, major attention is paid to analyzing the shapes of the time profiles of the light emission derived from a model sensory system in the presence of lipid samples of vegetable and animal (fish) origin rich in bioantioxidants. As a result, a modified reaction mechanism involving 12 elementary steps is proposed to rationalize the light-emission kinetics in the presence of natural bioantioxidants. We conclude that free radicals formed from bioantioxidants and their dimerization products contribute significantly to the general antiradical activity of lipid samples, which should be taken into account in developing efficient bioantioxidant assays for biomedical applications and while establishing the mechanisms of bioantioxidant effects on metabolic processes in vivo. It has long been known that numerous life forms produce light ranging from the ultra-weak spontaneous glow of cells and tissues to the bright bioluminescence of fireflies and a variety of marine organisms ,2,3,4,5.Bioantioxidant ingredients of food, medicines and other products are most frequently considered in terms of the protective role they play in living organisms that consume these constituents. However, it is noteworthy that overloading with exogenous antioxidants , the disproportionation reaction of which (reaction (1), The use of such a model chemiluminescence process consists of measuring the intensity of the light emission  as the function of [AOH].As the pertinent alternative to such an approach, bioantioxidant assay utilizing luminol chemiluminescence is noteworthy .J) in the case of the reaction mechanism exhibited in k3 is then estimated based on its proportionality to the maximal slope, (dJ/dt)max, at the inflection point on the chemiluminescence-intensity time profile, J(t), which should remain constant at different antioxidant concentrations [The ability of chain-breaking bioantioxidants to inhibit oxidation processes is governed by their propensity to interact with peroxide radicals ROO˙ according to reaction (3), the rate constants of which are the characteristics of the antiradical activity of bioantioxidants ,9. Typictrations ,9.However, the question arises, how would the light-emission kinetics differ from the ideal case  if by-prJ/dt)max, at the inflection point on the chemiluminescence time profile, J(t), as the initial concentration of an antioxidant increases (Chemiluminescence kinetic curves measured in the presence of lipids are exhibited in ncreases .J/dt)max, at the inflection point on the chemiluminescence-intensity time profile should remain constant at different antioxidant concentrations [k1 = 1 × 107, k2 = 1.7, k3 = 3.6 × 106, k4 = 1 × 108, k5 = 1 × 103 M−1s−1. These values have been chosen in accordance with the rate constants of similar reactions available in the literature [J/dt)max value, which is inconsistent with the experimental finding. Indeed, a clear decrease in the slope, (dJ/dt)max, of the kinetic curves, J(t), was observed with the increase in the initial concentration of bioantioxidants . k7. For the rate constants of the other elementary reactions  with the rate constant eactions  added toeactions , the folure data ,23,24,25k3 value), effectively competing with the ROO˙ disproportionation (leading to light emission), the overall chemiluminescence kinetics is rather sensitive to the reaction with AAOH. Thus, the increase of k7 in the range of 104 to 105 M−1s−1 reduces the maximum slope, (dJ/dt)max, of the kinetic curves, J(t), and leads to the appearance of a relatively gently sloping area on the chemiluminescence time profiles at the end of the induction period max, of the curves of type 6 is less than that of the curves of type 1, which corresponds to the difference in the rate constants k7 and k3, indicating that the end of the induction period on curves of 6 type corresponds to the predominant consumption of the AAOH product with lower antiradical activity (rate constant k7) compared to the activity of the original antioxidant AOH (rate constant k3).The correspondence between the experimental and the computed chemiluminescence kinetic curves confirms the adequacy of the model kinetic pattern obtained on the basis of the extended mechanism involving 12 elementary reactions . A furthn period . At the −5 M) but at different values of the rate constant of reaction (6): k6 = 103 M−1s−1 (A) and k6 = 104 M−1s−1(B). The mechanistic and kinetic implications of these computational results will be accordingly addressed in the Discussion section.Reaction (6) of free radicals AO˙ formed from antioxidant molecules is the key to the formation of the active AAOH species capable of interacting with peroxide radicals, ROO˙, according to reaction (7) and thus affecting the kinetics of the free-radical oxidation process and the character of the chemiluminescence emission. This reaction competes with reaction (5), the products of which are non-reactive. J/dt)max) of the intensity curve, J(t), with the increase in the initial concentration of the reaction inhibitor and the presence of the gently sloping area on emission-intensity time profiles. The efficiency and the nature of the inhibitory activity largely depend both on the possibility of the formation of antioxidant products in reaction (6) (k7 of reaction (7). The extended reaction mechanism   and on techanism  involvesk7) reveals that the effect of reaction (6) on the chemiluminescence emission is ambiguous. Thus, we have noticed that at small k7 values  is insufficiently active due to low k7. Conversely, at high values of k7 = 105 to 106 M−1s−1, a comparison of the “equikinetic” light-intensity curves , the contribution of reactions (7) and (8)  increases, which leads to the inhibition of the chain oxidation process.The intricacies of the chemiluminescence kinetics derived from newly considered elementary reaction steps are particularly noteworthy. First of all, a comparison of the “equikinetic” chemiluminescence time profiles  subject to oxidation initiated by free radicals derived from 2,2′-azobisisobutyronitrile (AIBN) upon its thermal decomposition ,9,23. AsEleginus gracilis) with a binary solvent mixture according to the standard methodology [Research samples of the sunflower oil have been generously donated by Professor Vessela Kancheva . Fish-derived lipids were extracted from the muscle tissue of saffron cod max, of the chemiluminescence kinetic curve, J(t), decreases with the increase in the initial concentration of the lipid-born bioantioxidant analyte, and (ii) the gently sloping area of the light-emission kinetics is observed at the end of the induction period of the oxidation process.The present study reveals the new characteristic features of the light-intensity time profiles upon the addition of natural lipid samples into the chemiluminescence sensory system based on the free-radical chain oxidation of a model hydrocarbon substrate: (i) the maximal slope, (dA reaction mechanism of 12 elementary steps is proposed, which accounts for the observed chemiluminescence kinetics in the presence of lipid-born antioxidants.Free radicals formed from bioantioxidants and their dimerization products contribute significantly to the general antiradical efficiency of lipid samples, which should be taken into account in developing the efficient bioantioxidant assays for biomedical applications and in considering the mechanisms of altering the natural metabolic equilibrium upon consumption of exogenous bioantioxidants.Clearly, challenges in chemiluminescence studies of biological samples with antioxidant activity are not limited to the kinetic intricacies considered herein. First of all, for further development of effective and reliable chemiluminescence bioantioxidant assays, the follow-up analysis of the ways and conditions of possible conversion of antioxidant properties into prooxidant ones needs to be carried out. To address this problem, further elaboration of experimental approaches, most prominently for studying the kinetics and stoichiometry of the bioantioxidants’ action as a function of their concentration, is required along with the subsequent development of the computer mathematical modeling of oxidative processes in the presence of bioantioxidants.


The accurate extraction of navigation paths is crucial for the automated navigation of agricultural robots. Navigation line extraction in complex environments such as Panax notoginseng shade house can be challenging due to factors including similar colors between the fork rows and soil, and the shadows cast by shade nets.In this paper, we propose a new method for navigation line extraction based on deep learning and least squares (DL-LS) algorithms. We improve the YOLOv5s algorithm by introducing MobileNetv3 and ECANet. The trained model detects the seven-fork roots in the effective area between rows and uses the root point substitution method to determine the coordinates of the localization base points of the seven-fork root points. The seven-fork column lines on both sides of the plant monopoly are fitted using the least squares method.The experimental results indicate that Im-YOLOv5s achieves higher detection performance than other detection models. Through these improvements, Im-YOLOv5s achieves a mAP (mean Average Precision) of 94.9%. Compared to YOLOv5s, Im-YOLOv5s improves the average accuracy and frame rate by 1.9% and 27.7%, respectively, and the weight size is reduced by 47.9%. The results also reveal the ability of DL-LS to accurately extract seven-fork row lines, with a maximum deviation of the navigation baseline row direction of 1.64°, meeting the requirements of robot navigation line extraction.The results shows that compared to existing models, this model is more effective in detecting the seven-fork roots in images, and the computational complexity of the model is smaller. Our proposed method provides a basis for the intelligent mechanization of Panax notoginseng planting. However, the production process still relies on outdated technology, and there is a need for efficient and intelligent production methods to improve productivity. One potential solution is the use of mechanized and intelligent agricultural equipment such as robots, which can replace manual labor and increase the scale of cultivation . In the Automated navigation techniques used for unstructured environments, such as large fields and orchards, mainly include satellite positioning navigation, Light Detection and Ranging (LiDAR) navigation, and visual navigation . HoweverThe ability of traditional image processing methods to distinguish between scenes with similar backgrounds and targets is reduced due to their susceptible to light, canopy cover, and weeds. However, deep learning methods can extract features beyond our understanding for object detection. In recent years, the development of artificial intelligence and computer hardware has facilitated the deployment of deep learning models on embedded devices . MoreoveTherefore, in this paper, based on the environment inside Panax pseudoginseng shade house, we address the bottlenecks associated with robot navigation line extraction algorithms between the rows of the shade house in the complex farmland environment, including poor effects and adaptability. In particular, we propose a method that combines deep learning and least squares (DL-LS) algorithms to obtain the inter-row navigation lines in Panax pseudoginseng shade house. In order to improve the detection accuracy and speed, we take the position of the root point of seven branches as the main navigation information, and propose a lightweight network model with improved YOLOv5s architecture to identify the roots to accurately identify navigation lines in the complex shade house environment. (1) Based on YOLOv5’s target detection model, we weaken the backbone network by replacing the original backbone with MobileNetv3, and introduce the ECANetention mechanism module to pay more attention to the seven-branch root characteristics.(2) Verifying the effectiveness of the improved YOLOv5s by an ablation study and comparing it with other mainstream single-stage target detection models.(3) We use the improved YOLOv5s model to locate the small area of the seven-fork root within the region of interest (ROI) in the video and extract the coordinates of the midpoint of the lower bottom frame line rather than using the root point. We then combine the least squares method to fit the tree line on both sides and use the angle tangent formula to extract the traverse navigation line for the robot.(4) Establishing a new dataset of shade house environments, and the proposed method was tested and analyzed using a built data acquisition robot.The remaining part of this paper is organized as follows. The second section discusses the navigation line extraction method, the improved YOLOv5s, and the evaluation metrics. The third section presents the robot platform and the experimental results, the fourth section shows the discussion, and the fifth section summarizes the conclusions.22.12.2Traditional Panax notoginseng shade house are typically constructed using seven-fork structures with diameters ranging from φ5 to φ8 cm. They are generally planted based on a grid of 2.4 m × 2.0 m (length × width) dimensions, with a 1.8 m scaffold height and a shade net covering the top layer to provide uniform light transmission. The test pictures were taken on November 9, 2022, in a Panax notoginseng shade net plantation in Shilin Yi Autonomous County, Kunming City, Yunnan Province, China. The plantation included a seedling plot, a plot to be sown, and a shade house planting site just after harvest. For the image acquisition, a COMS camera was mounted horizontally on a robotic platform 1.4 m above the ground and placed in the row center. We collected a total of 412 images from three scenes under different angles and lighting conditions: the Panax notoginseng sowing field; the Panax notoginseng harvesting field; and the Panax notoginseng seedling field. 2.3To improve the robustness of the model and suppress overfitting, we added random perturbations such as saturation, flipping, and luminance during the training process. This expanded the amount of available information and enhanced the richness of the experimental data. As a result, the 412 images were expanded to 936 images and divided into training and validation sets with a ratio of 8:2. Moreover, we used 180 images captured by an external computer camera as the test set to evaluate the performance of the model during the training process. The test set was not involved in the actual training. In each example image, the roots of the seven-forks were marked by rectangular boxes and LabelImg installed on Anaconda was used for the image labeling. To ensure labeling efficiency and accuracy, we only labeled two rows of hepta-roots within 12 m of the capture point. Each side of the tree rows contained 3–5 labeled hepta-roots. A total of 936 images were labeled, resulting in 7,288 labeled hepta-roots, which were saved as label files in XML format. This labeling process was based on a robot walking speed of 0.5–1 m/s.2.4The YOLOv5s model is a lightweight version of You Ony Look Once (YOLO) algorithm with fewer layers, allowing for a faster detection. Therefore, the aim of this paper is to apply the improved model to the detection of seven-fork roots based on the YOLOv5s model. The Im-YOLOv5s is improved by reducing its backbone network using MobileNetv3 and introducing the ECANet attention mechanism module to enhance the extraction of useful information and compress useless information. This enhances the recognition accuracy and robustness of the model. With these improvements, the model can efficiently, accurately, and quickly obtain the root information of the seven-fork in the shadow trellis while reducing the weight size, which is convenient for use in embedded devices.2.4.1The YOLOv5 target detection model is known for its faster detection speed and smaller model size with guaranteed accuracy, making it an ideal choice for efficiently detecting the seven-fork roots in this study. The YOLOv5 model is divided into four variants: YOLOv5s; YOLOv5l; YOLOv5m; and YOLOv5x . YOLOv5s2.4.2A large number of convolutional layers increases a model’s memory footprint. This is not conducive to deploying the model on embedded devices. Compared to heavyweight networks, lightweight networks have fewer parameters, require less computation, and have a shorter inference time. Lightweight networks are thus more suitable for scenarios with limited storage space and power consumption, such as embedded terminals, robots, and other small systems. MobileNetv3  is the t2.4.3The channel attention mechanism has the potential to greatly improve the performance of deep convolutional neural networks (CNNs). However, while SE downscaling can reduce model complexity, it destroys the direct correspondence between channels and their weights. To overcome the trade-off between performance and complexity, and to improve the accuracy and efficiency of the algorithm for seven-fork root detection in a three-seven shade house environment, we introduce an efficient channel attention (ECA) module  into theIn this study, we used MobileNetV3 as the backbone model and combined YOLOv5s with the ECANet and CBAM modules to perform seven-fork root detection experiments. 2.4.4The Complete Intersection over Union (CIoU) accounts for the overlapping area, height, and centroid distance of the target and prediction boxes, which addresses the shortcomings of the Generalized Intersection over Union (GIoU) loss function. This results in a more stable regression equation for the target box, with a faster convergence speed and higher convergence accuracy. Therefore, we used the CIOU_Loss function rather than the GIOU_Loss function for the bounding box loss in Im-YOLOv5. To calculate the loss of class probability and the target score, we employed the binary cross-entropy and logit loss functions , respectwhere A is the prediction box; B is the ground truth box; C is the smallest box that completely encloses A and B; 2.4.5In this paper, we employed five metrics, namely precision (P), recall (R), mean average precision (mAP), model size, and detection speed, to evaluate the seven-fork root detection model. A true positive case indicates that the intersection over union (IoU) is greater than or equal to 0.5; a false positive case indicates that the IoU is less than 0.5; and a false negative case indicates that the IoU is equal to 0 . P, R, Fwhere TP, FP, and FN are the number of true positives, false positives, and false negatives respectively; and M is the number of detection categories.Furthermore, we employed frames per second (FPS) to evaluate the detection speed of different models. A higher value of FPS indicates a better real-time performance of the model. We also used giga floating point operations per Second (GFLOPs) as an evaluation indicator to measure the computational power of the model, with higher values denoting a higher demand on the machine’s computing power.2.5® W-214 CPU; and an NVIDIA RTX 2080Ti GPU with 11 GB of video memory. The workstation operated on Windows 11 (64-bit), and the training was conducted using Python 3.9 with the deep learning platform CUDA 11.6 and the Pytorch framework.The models were trained on a desktop workstation with the following specifications: 64 GB of memory; an Intel XeonThe quality of the training model is significantly influenced by the difference in training parameters, and hyperparameters such as the learning rate, batch size, and number of iterations must be set manually during the training process. Among them, the learning rate is crucial in deep learning optimizers as it determines the speed at which weights are updated. If the learning rate is too high, the training results will exceed the optimal value, while if it is too low, the model will converge too slowly. The batch size depends on the size of the computer memory, with larger batches providing better model training results. The number of iterations determines the number of training rounds, with more iterations taking longer to complete. The iteration typically ends when the loss value has fully converged. After several parameter adjustments, the parameters in the model were set according to the values provided in 2.6The selection and extraction of navigation features are crucial for inter-row navigation in shade house. In this paper, we defined the root point as the midpoint of the dividing line between the seven-fork point and the ground. The root point of the fork is used as the base point for row positioning in the construction of Panax notoginseng shade house. Therefore, the root point of the fork is considered the optimal inter-row navigation feature. However, since the target color of the Panax notoginseng shade house environment is similar to the background color, it is both challenging and time-consuming to filter out other interferences using image processing methods. To address this issue, rather than using navigation base points, we proposed a heptagram-based generation method. We trained a deep learning-based seven-fork root model and used the trained detection model to generate the minimum rectangular detection frame outside the bottom of the seven-fork. The midpoint of the bottom edge of the detection frame was observed to correspond well with its root point.2.7Once the root points of the bottom of the seven-fork were obtained, we fitted the crop rows using the seven-fork root points of the Panax notoginseng shade house. We employed the least squares method to fit the coordinates of these root points using equations (11)–(13):where 1 and L2. If for example, the absolute value of 1 and vice versa for L2. In order to obtain two lines from the detected coordinates of the root points, we separated the points using a positive threshold and a reference point. We set a positive threshold m and 1m is equal to the tangent angle between m and 2m:Once the expressions of the line parameters on both sides were determined, we used the angular bisector of the left and right seven-forked row lines as the robot navigation baseline. The principle of tangency between two lines was then adopted to obtain the robot navigation parameters via equation (14). More specifically, we calculated the robot navigation line slope m based on the relationship that the tangent angle between m is the slope of the robot’s navigation center line; 1m is the slope of the left seven-branch line; and 2m is the slope of the right seven-branch line.where 3The focus of this study is the acquisition of navigation information in the Panax notoginseng shade. The obtained navigation information can be used in later path planning stages of the robot to facilitate autonomous driving. It can also be used as a basis for adjusting the driving state of the robot.3.1Due to the complex environment in the Panax notoginseng shade house, its small plots, large slopes and high soil moisture, a triangular crawler chassis with an upland gap was used as the walking platform in this experiment. As shown in We developed a LABVIEW program to control the robot platform using the ARM embedded software architecture of the STM32. This facilitated data monitoring. improved development efficiency, and reduced costs. 3.2We compared our improved target detection model with three of the most advanced, fastest detecting, and widely used models. mAP@0.5 was employed to plot the line graphs. 3.2.1To evaluate the performance of the detection models proposed in this paper, we trained the Im-YOLOv5, YOLOv3, YOLOv5s, and YOLOv7 algorithms under the same conditions and evaluated their performance on a test set. 3.2.2The improved Im-YOLOv5 model reduces the number of parameters by replacing the MobileNetv3 network with the ECA attention mechanism module. This allows the model to focus more on the target for feature extraction and less on the roots of the seven-forks that are further away and beyond the sides. To evaluate the detection performance of the Im-YOLOv5s model in this study, we verified the trained model using 180 test set images and 3 test videos for detection accuracy and speed. The Im-YOLOv5s detection model achieved a 47.9% reduction in weight size, from 14.4 MB to 7.5 MB (3.2.3We utilized the Im-YOLOv5s model for target detection recognition in the test set and compared the experimental results of three scenes of the sowing, seedling, and harvested fields with high and low light intensity conditions. The results reveal a higher recognition accuracy for the sowing and seedling fields with a relatively clean background, reaching 95.7% and 95.2%, respectively (3.3After identifying and framing the root of the seven-fork using deep learning, the coordinate values of the corner points of the rectangular bounding box were extracted. This included the coordinates of the upper left 3.4We experimentally verified the practical feasibility of the proposed inter-row navigation information acquisition method by selecting several pictures from the dataset collected by the external camera connected to the PC for testing. The images contained three scenes: sowing field, seedling field and harvesting field. The effect of the navigation line extraction for different scenes is shown in 4The success of target detection algorithms heavily depends on the extraction of navigation lines using deep learning methods. In this paper, we compared the proposed Im-YOLOv5s algorithm with existing detection methods for similar targets. Although the proposed method in this study can accurately extract the centerline of seven-fork rows in Panax notoginseng shade house, we came across several limitations. While the improved deep learning model enhances detection accuracy and speed, the field of view range and camera jitter can affect the detection accuracy rate of the seven-fork roots, which, in turn, affects the fitting error of the navigation line. For the complex and variable inter-row environment, relying solely on visual sensing to obtain navigation feature information may pose significant risks to the actual safety of robot operation. In future work, we plan to transfer the deep learning model and seven-fork row centerline extraction algorithm to a mobile robot platform and combine them with multi-sensor fusion technology to achieve automatic navigation in the semi-structured environment of Panax notoginseng shade trellis.5In this paper, we proposed a navigation line extraction method based on Im-YOLOv5s. By replacing the original backbone with a lightweight network architecture, MobileNetv3, and introducing the ECANet attention mechanism module, we improved the model’s recognition accuracy and robustness while reducing its weight size by 47.9%, increasing the frame rate by 27.7%, and improving the average accuracy by 1.9%. The algorithm efficiently and accurately extracted information on the seven-fork roots in the shade trellis with an average detection accuracy of 94.9%, and was resilient to light and shadow disturbances. We located the coordinates of the root point according to the bottom edge midpoint of the outer rectangular box of the detected seven-fork roots and used the least squares method to fit the navigation reference line on both sides. The maximum deviation of the row direction was 1.64°, which met the criteria for navigation line extraction. We then used the detected bilateral column line as the navigation reference line and extracted the middle navigation line using the angle tangent formula to determine the robot’s forward direction. The proposed method provides a technical reference for inter-row path planning.The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.YT designed the lightweight model and trained the model, YT and PL collected the images of Panax notoginseng shade house, JJ guided the experiment, YT designed hardware and software for the robotics platform and wrote the original draft, CLW, WS, QHL, JJ and YW reviewed and edited the paper. 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 authors contributed to the article and approved the submitted version.


To analyze the influence path of the interaction between the unit environment, achievement transformation willingness, and achievement transformation cognition on achievement transformation output to provide a basis for optimizing the achievement transformation environment of medical and health institutions and improving the efficiency of scientific and technological achievements transformation.Through the questionnaire survey, 292 data points were obtained. SPSS20.0 was used to conduct cross-table chi-square analysis and binary logistic regression analysis on the willingness, cognition, and output of scientific and technological achievements transformation. The process 14.0 plug-in is used to analyze the mediating effect of transformation cognition and the moderating effect of the unit environment.Achievement transformation willingness has a significant positive impact on achievement transformation cognition and achievement transformation output. Achievement transformation cognition has a positive impact on achievement transformation output, and the mediating effect of transformation cognition is significant and partial. The unit environment has a negative moderating effect on the influence of achievement transformation willingness on achievement transformation cognition, and a positive moderating effect on the influence of achievement transformation willingness on achievement transformation output.Personal factors and unit achievement transformation environment have an obvious influence on the willingness and cognition of achievement transformation. It is necessary to optimize the environment of unit scientific and technological achievements transformation, improve the policy system of benefiting from the achievements of scientific and technological achievements transformation of medical and health personnel, implement the disposal right, income right and distribution right of scientific and technological achievements transformation of medical and health institutions, and stimulate the enthusiasm of scientific and technological achievements transformation of medical and health personnel. Scientific and technological innovation is the core driving force for high-quality development. As an important carrier of scientific and technological innovation, medical and health institutions have outstanding characteristics of being talent-intensive, knowledge-intensive, and innovation-intensive . In 2018Theoretical model diagram . TransfoHypothesis 1(H1): Achievement transformation willingness has a positive and significant impact on achievement transformation output.Hypothesis 2(H2): Achievement transformation cognition has a positive and significant impact on achievement transformation output.Hypothesis 3(H3): Achievement transformation willingness has a positive and significant impact on achievement transformation cognition. The influence of achievement transformation willingness on achievement transformation cognition is regulated by the unit environment.Hypothesis 4(H4): The unit environment has a moderating effect on the influence of achievement transformation willingness on achievement transformation cognition. The influence of achievement transformation willingness on achievement transformation output is regulated by the unit environment.Hypothesis 5(H5): The unit environment has a moderating effect on the influence of achievement transformation willingness on achievement transformation output. achievement transformation cognition mediates achievement transformation willingness.Hypothesis 6(H6): achievement transformation cognition mediates achievement transformation willingness and achievement transformation output.An online questionnaire survey was conducted through the healthcare staff attending the course and 292 questionnaires were collected. The questionnaire includes: province, level of unit, type of unit, gender, age, title, years of working experience, education, type of title, environment of the unit, willingness cognition, and output of achievement transformation. Among them, 291 were from Zhejiang Province and 1 from Heilongjiang Province. Some options were deleted because they were missing, and 291 valid samples were retained. There were 97 males (33.3%) and 194 females (66.7%). There were 21 people aged 20–29 (7.2%), 149 people aged 30–39 (51.2%), 97 people aged 40–49 (33.3%), and 24 people aged 50–59 (8.2%). There were 6 people with ungraded titles (2.1%), 28 people with primary titles (9.6%), 127 people with intermediate titles (43.6%), 97 people with deputy senior titles (33.3%), and 33 people with senior titles (11.3%). There were 16 doctors (5.5%), 117 masters (40.2%), 155 undergraduates (53.3%), and 3 junior college and below (1%). There were 19 medical and health personnel at the provincial level (6.5%), 168 at the municipal level (57.7%), and 104 at the county level (35.7%). There were 280 people from medical and health institutions (96.2%), 3 people from scientific research institutes (1%), 1 person from higher medical colleges (0.3%), 3 people from disease control and prevention (1%), and 4 others (1.4%). Among the types of professional titles,12 were researchers (4.1%), 213 were medical technicians (73.2%), 18 were management technicians (6.2%), and 48 were others (16.5%). On the whole, the survey samples are mainly female, concentrated in the age group of 30–49 years old, with bachelor degree or above, intermediate title or above, medical technology, medical and health institutions, in line with the distribution law of general medical and health personnel.SPSS20.0 and the Process are used to verify and process the model. Descriptive statistical analysis, cross-table chi-square analysis, binary logistic regression analysis, and mediating and moderating effects were performed. P < 0.05 indicated that the difference was statistically significant.Excel is used to process, summarize, and clean the data, and In the unit environment, achievement transformation cognition, and achievement transformation output demographic chi-square analysis , it can The chi-square analysis of the willingness and cognition of achievements transformation  shows thAnalysis of the intermediary effect of achievement transformation cognition The highest-order unconditional moderating effect test , in whicThe adjustment effect of the unit environment on achievement transformation willingness on achievement transformation output . AchieveAccording to the numerical table of the unit environment adjustment effect , under aMen are more willing to transform their achievements in terms of gender, which is consistent with the existing research . The wilAchievement transformation willingness has a positive and significant impact on achievement transformation cognition and achievement transformation output. achievement transformation cognition has a positive and significant impact on achievement transformation output. achievement transformation cognition has a significant mediating effect on achievement transformation willingness and achievement transformation. This shows that in the chain of scientific and technological achievements transformation, the willingness to transform achievements is the starting point of achievement transformation, and the willingness to transform achievements further deepens the understanding of achievement transformation and brings about the output of achievements. At the same time, achievement transformation willingness can directly affect achievement transformation output; that is, the intensity of achievement transformation willingness is one of the factors affecting achievement transformation output. Achievement transformation willingness and cognition are important factors influencing outcome outputs, which is consistent with existing research and clarifies the pathways of outcome output impacts.The regulatory role of the unit environment is manifested in two main aspects. First, the unit achievement transformation environment regulates the impact of the willingness to transform achievements on achievement transformation cognition, that is, the willingness to transform achievements is limited by the unit achievement transformation environment. When the unit achievement transformation environment is poor , the individual’s willingness to transform achievements is inhibited, and the cognitive level of achievement transformation is reduced. Second, the unit environment has a positive moderating effect on achievement transformation willingness and achievement transformation output. When the environment of unit achievement transformation is better, the higher achievement transformation willingness, the greater the probability of achievement transformation output. It shows that a good achievement transformation environment of the unit is beneficial to improve the enthusiasm of medical and health personnel in the transformation of scientific and technological achievements, and at the same time, when the unit environment is poor, it will hinder achievement transformation cognition. The unit environment affects the output of results by influencing the willingness and cognition of individuals. Here we clarify the path of influence of the external environment on promoting the transformation of scientific and technological achievements, which complements the existing research.Therefore, to promote the transformation of scientific and technological achievements, we need to make efforts from both inside and outside, on the one hand, to guide individuals on the transformation of achievements enthusiasm, and constantly deepen the knowledge of the transformation of achievements. Second, we should improve the system and organisational construction of the unit environment, guide individuals to invest in the transformation of achievements through the system and organisational construction and strengthen the depth of individuals’ knowledge of the transformation of achievements through the popularisation of policies. To a certain extent, the unit environment is more important for achievement transformation. The following suggestions are put forward: First, optimize the construction of the environment for the transformation of scientific and technological achievements, express special policies and management methods to promote the transformation of scientific and technological achievements, improve the policy system for the benefit of medical and health personnel, and establish special management institutions and assessment methods for the transformation of scientific and technological achievements. The second to establish and improve the incentive mechanism and promotion methods for the transformation of scientific and technological achievements, incorporate the transformation of scientific and technological achievements into the evaluation criteria of professional titles, implement the disposal, income, and distribution rights of the transformation of scientific and technological achievements in medical and health institutions, and stimulate the enthusiasm of medical and health personnel for the transformation of scientific and technological achievements. The third is to increase the publicity and correct guidance of the transformation of scientific and technological achievements, increase the publicity of policies such as the transformation of scientific and technological achievements, strengthen the publicity of the transformation process of scientific and technological achievements, and improve the cognition of medical and health personnel regarding the transformation of scientific and technological achievements. Due to time and financial constraints, the study was inadequate in terms of the amount of data collected and the need for further research on data interrelationships. In the future, we will further explore the interactions between national and unit policies in terms of their impact on the transformation of individual achievements.S1 Data(SAV)Click here for additional data file.


As surface oxidation and decarburization occur during hot stamping processes, an Al-Si coating is often precoated on surfaces. The coating tends to melt into the melt pool during the laser welding of the matrix and reduce the strength of the welded joint; therefore, it should be removed. The decoating process by sub-nanosecond and picosecond lasers and process parameter optimization were conducted in this paper. The corresponding analysis of the different decoating processes, the mechanical properties and the elemental distribution was carried out after laser welding and heat treatment. It was found that the Al element has an influence on the strength and elongation of the welded joint. The high-power picosecond laser has a better removal effect than the lower power sub-nanosecond laser. The best mechanical properties of the welded joint were obtained under the process conditions of 1064 nm center wavelength, 15 kW power, 100 kHz frequency, and 0.1 m/s speed. In addition, the content of the coating metal elements (mainly Al) melted into the welded joint is reduced with increasing coating removal width, which significantly improves the mechanical properties of the welded joints. Al in the coating rarely melts into the welding pool when the coating removal width is not less than 0.4 mm, and its mechanical properties can meet the automotive stamping requirements for the welded plate. Lightweight automobiles play important roles in terms of energy, environment, safety and other aspects ,2,3,4. HThe Al element in the Al-Si coating will melt into the melt pool during laser welding of the base material, which can greatly reduce the strength of the joint. Studies have shown that the Fe-Al intermetallic compounds can easily form because the Al-Si coating flows with the weld metal along the fusion line during laser welding. Lin et al. conducted an experiment to obtain full-penetration laser welds of Al-Si coated steel in conduction mode . Yoon etTo solve this problem, scholars have performed a lot of work on coating treatments ,14,15. KIn order to study the effect of different laser removal processes on the removal of the coating and then understand the influence of the removal process on the mechanical properties of the welded joint, sub-nanosecond and picosecond lasers were used to remove the Al-Si coating. The optimal removal width was determined by analyzing the mechanical properties and element distribution of the welded joint.The material used in this study is commercial aluminum-silicon coating 22MnB5 steel with a thickness of 1.2 mm, specimen coatings of 15–24 µm, mainly pure aluminum ; its chemical composition is shown in An optical microscope  was used to observe the macroscopic morphology of the welded seam area and the surface of the plate after the laser decoating. WDW100 electronic universal testing machine was used for tensile testing of the welded joints along the direction perpendicular to the weld itself, with the tensile specimen spacing of 70 mm. A specimen with a gauge size of 50 mm × 12.6 mm is shown in This experiment aimed to investigate the impact of laser power, laser frequency and scanning times on the mechanical properties of the welded plate after laser stitching. A sub-nanosecond laser was used for laser decoating experiments with a fixed power of 15 W, a scanning speed of 1000 mm/s, a spot size of 50 μm, a laser frequency of 50 kHz or 100 kHz, and a parallel linear continuous scanning mode. The 100 kHz high-frequency (HF) and the 50 kHz low-frequency (LF) scan numbers (labeled group A) were controlled to investigate the effect on the depth of decoating. The specific experimental parameters are shown in As can be seen from The A3-8 group parameters were chosen to conduct a decoating test with a 1 mm de-coating width. This was performed to investigate the mechanical properties of the welded joint. After welding and heat treatment, tensile tests were carried out to study the mechanical properties and the morphology of the weld seam. Group B specimens were welded to four welded plates, and three tensile specimens were taken from each plate to measure the average of their mechanical properties a. As canThe microstructure evolution is shown in As mentioned above, the research findings suggest that a laser with a higher peak power effectively vaporizes the plated metal instantly, thus minimizing the occurrence of a molten state and reducing the intrusion of the plated metal into the substrate. For this reason, a picosecond laser was chosen for the coating removal test (Group C) due to its narrow pulse width, higher single-pulse energy, and shorter heating time. These factors work synergistically to inhibit the tendency of the metal material to melt and to avoid the residue of compounds on the surface of the sheet due to the melting of the base material and plated metal. The experiments were carried out using both a primary removal (C1) process and a removal + cleaning (C2) process by the picosecond laser; the corresponding parameters are shown in As can be seen in It can be seen from In conclusion, the above findings show that the higher power picosecond lasers can remove the coating more effectively than nanosecond lasers. Using a one-time removal method, the C1 process combination using a high power of 15 W and a slow speed of 0.1 m/s had a better effect than the C2 process combination of removal + cleaning.In order to study the influence of the decoating width on the mechanical properties of welded joints, the properties of welded joints were analyzed in terms of tensile strength, metallography, hardness and weld composition distribution. The minimum value for the decoating width of the weld was obtained to meet the requirements of the mechanical properties of the joint and improve production efficiency. The decoating width (d) was set 0.2 mm, 0.4 mm, 0.6 mm and 0.8 mm, and the laser parameters was selected according to C1 in From From The metallographic and hardness analyses were carried out for further analysis on each group of specimens, and the hardness measurements of the welds and base material are shown in As can be seen from The results of As shown in (1)High-power picosecond lasers are more effective for removing coating than low-power sub-nanosecond lasers. Under the removal parameters of 1064 nm center wavelength, 15 kW power, 100 kHz frequency and 0.1 m/s speed, the mechanical properties of the welded joint meet the application requirements.(2)The content of coating metal elements (mainly Al) melted into the welded joint is reduced with the increasing coating removal width, which can significantly improve the mechanical properties of the welded joints.(3)The Al element of the coating rarely melts into the melt pool when the coating removal width is not less than 0.4 mm, and its mechanical properties can meet automotive stamping requirements.


The fracture toughness of sand concrete is affected by aggregate characteristics. In order to study the possibility of exploiting tailings sand, available in large quantities in sand concrete, and find an approach to improve the toughness of sand concrete by selecting appropriate fine aggregate. Three distinct fine aggregates have been used. After characterizing the fine aggregate used, the mechanical properties were tested to characterize the toughness of sand concrete, the box-counting fractal dimensions were calculated to analyze the roughness of fracture surfaces, and the microstructure was tested to observe the path and width of microcracks and hydration products in sand concrete. The results show that the mineral composition of fine aggregates is close, but their fineness modulus, fine aggregate angularity (FAA) and gradation vary considerably; FAA has a significant impact on the fracture toughness of sand concrete. The higher the FAA value, the more resistant it is to crack expansion; with the FAA values of from 32 s to 44 s, the microcrack width in sand concrete was reduced from 0.25 um to 0.14 um; The fracture toughness and microstructure of sand concrete are also related to the gradation of fine aggregates, the better gradation can improve the performance of the interfacial transition zone (ITZ). The hydration products in the ITZ are also different because more reasonable gradation of aggregates reduces the voids between the fine aggregates and the cement paste and restrains the full growth of crystals. These results demonstrate that sand concrete has promising applications in the field of construction engineering. Sand concrete is a new type and special composite material ,2,3, whiThe fracture toughness of concrete is usually improved by adding supplementary cementitious materials, inert fillers, reactive fillers and fibers or by improving curing methods. For instance, Madani Bederina et al.  studied The crack propagation directly affects the fracture energy and fracture toughness. The fracture process of sand concrete with different aggregates is shown in In order to study the effect of fine aggregate characteristics on the fracture toughness of sand concrete, aggregates with different fineness modulus, FAA and aggregate gradation were selected as raw materials. The brittleness coefficient of sand concrete specimens with different fine aggregates was measured and compared with traditional concrete. Moreover, the complexity of the fracture surface and the evolution of the microstructures of sand concrete specimens were analyzed by means of box-counting fractal dimensions and Scanning Electron Microscope (SEM), respectively. This research will contribute to a better understanding of how the characteristics of fine aggregate affect the fracture toughness of sand concrete ,24,25.Fine aggregates here are defined as grain sizes smaller than 2.36 mm. The used fine aggregates are gold tailing sand (GTS) from Tong-guan county, iron tailing sand (ITS) from Shangluo City and river sand (RS) from Xi’an City shown in . The res3 and a specific surface area: 446.5 m2/kg.Ordinary Silicate Cement, 42.5 grade of conch brand, was used in experiments. The physical characteristics of the cement used are a specific density: 1030 ± 20 kg/mThe admixture used is a superplasticizer with 28% of dry matter content in liquid form, and the water-reducing capacity was greater than 25%.The mix proportions for specimen preparation in this study were summarized in In order to analyze the effect of particle characteristics of fine aggregates on the toughness of sand concrete, the physical properties of three kinds of fine aggregates were conducted. The size distributions, fineness modulus, apparent density, bulk density, void ratio and powder content of the fine aggregates were tested following the national standards of GB/T 14684-2011 (Standard of Sand for Construction) used in China. And the FAA determination device required by the cited JTD E42-2005 standard.X-ray Diffraction (XRD) analyses were performed to detect the phase compositions of fine aggregate. Firstly, fine aggregates were grounded into powder, passed through 200 mesh sieves, and then dried for 24 h in a drying oven at 105 °C. Finally, characterized the composition and content of fine aggregate using a D8 ADVANCE X-Ray Diffractometer. The measurement conditions of XRD were a tube voltage of 30 kV and a tube current of 20 mA. Scans were repeated continuously from 15° to 80° with 0.1°/s using Cu target (wavelength is 1.54178 Å).According to the strength test of cement mortar with GB/T 17617-2005. The specimens were tested for compressive strength and flexural strength at the curing periods of 7 and 28 days by means of using the DYE-300 automatic universal testing machine. The loading rate is 2400 N/s, and the flexural loading rate is 50 N/s. The sizes of the specimens were all 40 mm × 40 mm × 160 mm.The complexity of the concrete fracture surface can be characterized by the box-counting fractal dimension ,27. The The macroscopic mechanical properties of sand concrete are closely related to the microstructure of sand concrete. So, the microstructure of the specimens of SC1 and OC1 were tested by Hitachi S-4800 Scanning Electron Microscope. The specimens were first immersed in absolute ethanol solution for 24 h in order to terminate the hydration reaction. Regular pieces of a 5-mm size were cut, polished and then kept in an oven for 24 h at 105 ± 5 °C. Finally, the microstructures of the specimens were tested after gold coating.2, Al2O3 and Fe2O3. The river sand is constantly washed in water, and its mineral composition is relatively single; while tailings sand exists in the field environment, its mineral composition is more complex. Therefore, the quartz content of river sand is higher than that of quartz in tailings sand.The mineral compositions of the fine aggregates are shown in The size distributions of the fine aggregates are shown in The micromorphology of the fine aggregates is shown in D is the particle size (mm), P(D) is a fraction of the total solids being smaller than size D, minD is the minimum particle size (mm), maxD is the maximum particle size (mm) and q is the distribution modulus. The value of q is between 0.23 and 0.37. The q value of the target curve in the close packing model is fixed at 0.23 based on the properties of fine aggregates [R2, as shown in Equation (2)).mixP is mixed fine aggregates, the tarP is the target grading calculated from Equation (1), n is the number of points used to calculate the deviation and R2 = 0.86) was highest compared to the target curve, while the correlation coefficient of GTS(R2 = 0.64) and RS (R2 = 0.60) were lower compared to the target curve. As a result, ITS showed the most reasonable aggregate gradation, while RS showed the most undesirable aggregate gradation. This suggests that the gradation is closely related to the particle size distribution of fine aggregate. Finally, it should be noted that the basic difference between these aggregates lies in physical characteristics, grain shape, granularity and particle size distributions.The gradation characteristics of different fine aggregates also affect the fracture toughness of sand concrete. Hence, in this study, the modified Andreasen close packing model  is utiligregates . The graThe results of the compressive strength and flexural strength of sand concrete with different fine aggregates are shown in The brittleness coefficient  reflects the deformation resistance of concrete and can characterize the toughness of concrete simply and intuitively. The lower the brittleness coefficient, the better the resistance to deformation. According to the GB/T50010-2010 code for the design of concrete structures, the brittleness coefficient of ordinary concrete is between 8:1 and 11:1, and it becomes higher with the increase of concrete strength grade. The box-counting fractal dimensions of different concrete fracture surfaces are illustrated in The microstructure and properties of ITZ are one of the most important influencing factors on the mechanical properties of concrete ,35,36. TThe propagation paths of microcracks in different sand concrete and ordinary concrete are shown in The adhesion between the aggregate and the cement paste also affects the fracture toughness of the concrete. The widths of microcracks in the ITZ between the aggregate and cement paste in sand concrete with different fine aggregates and ordinary concrete are shown in The hydration products of sand concrete with different aggregates and ordinary concrete are shown in (1)The fracture toughness of sand concrete is related to the characteristics of the aggregate. However, the brittleness coefficients of sand concrete with different aggregates are between 5:1 and 6.5:1 at different strength grades, and the brittleness coefficient of sand concrete is much lower than that of ordinary concrete. Sand concrete exhibits good fracture toughness than ordinary concrete.(2)The effect of particle fineness of fine aggregates on the fracture toughness of sand concrete is not significant.(3)The fracture toughness of sand concrete is strongly affected by the FAA. As the FAA value increases from 32 s to 44 s, the fractal dimension of the fracture surface of sand concrete increases from 2.25 to 2.69, and the average flexural strength increases by 13.65% under the same compressive strength.(4)The fracture toughness, microstructure and hydration products of sand concrete are also related to the gradation of fine aggregates. A good grading distribution can improve the performance of ITZ. When the correlation coefficient of the gradation compared to the target curve increased from 0.60 to 0.86, the microcrack width of ITZ decreased by about 38.55%, and there was also a difference in the hydration products produced. Therefore, the better the gradation of fine aggregates, the better the crack resistance of sand concrete.From the data of experimental in this study, the following conclusions can be drawn: