## 4 Conclusions  
The procedure developed in this research proved to be effective to calibrate acoustic emission parameters (amplitude, counts, and energy) with respect to the equilibrium moisture content of Scots pine. Indeed, amplitude and counts can be used as proxies for perceptibility of fracture events in relation to the equilibrium moisture content gradient experienced by the samples after a natural drying process. If the dryness is almost complete, amplitude and counts easily detect the acoustic emissions released by brittle events and vice versa. Energy can be used to derive the coefficient of energy attenuation rate that allows to directly relate the energy loss (gain) with the low (high) equilibrium moisture content gradient experienced by the samples after a natural drying process. In addition, this research has proven that acoustic emissions allow to:  
* identify pre-existing macro or micro cracks in samples, which act as an open joint, reducing accumulated stress without emitting new acoustic emission events. * point out damage caused by moisture variations, i.e., when the increasing ductility of the material generates no elastic energy. This opens interesting perspectives for the use of the acoustic emission technique as a preventive conservation tool, as it allows to record events related to natural drying processes or the presence of internal defects. The fields of application are multiple: architecture, engineering studies, cultural heritage, and more. In fact, acoustic emissions can be interpreted as a new way of understanding the state of conservation of a hygroscopic material and can be used for in situ monitoring. Moreover, through an in-depth study, the analysis proposed in this work can yield feedback on any wooden material, starting from the smallest artifacts to historic and non-historic buildings, which can be evaluated using the acoustic emission non-destructive technique. B.B. : interpretation of data and analyses, data discussion and writing--original draft preparation, conceptualization. F.F. : data discussion, conceptualization, supervision, review and editing writing. A.M.S. : data discussion, conceptualization, supervision, review and editing writing. A.M.S. : data discussion, conceptualization, supervision, review and editing. A.  
ing and writing. C.B. : conceptualization, funding acquisition, methodology, project administration, resources, supervision, review and editing and writing. All authors have read and agreed to the published version of the manuscript. This research was funded by the Norwegian Research Council through the SyMBoL Project (project no. 274749). [PERSON] is indebted to the Erasmus+ Traineeship exchange program. [PERSON] is indebted to the technical staff of the Mechanical and Industrial Engineering (MTP) department of NTNU and the NTNU wood center. Special thanks to [PERSON], [PERSON], and [PERSON], which Post Doc position was financed by SyMBoL, which contributed to perform the calibration tests conceived by [PERSON] as principal investigator and coordinator of the SyMBoL Project. C.B. and A.M.S. acknowledge the support of the Norwegian Research Council through the SyMBoL Project (project no. 274749) and of the Erasmus+ Traineeship exchange program. The authors declare no conflict of interest. This section reports the Equations (A1)-(A7) regarding the multiple regressions tested. Furthermore, Figure A1 shows the eight models in scatter-plots graphs and Tables A2 and A1 provides the statistical parameters and the coefficients related to all the equations tested.