Corinne Vannimenus
email: corinne.vannimenus@chru-lille.fr

Hélène Bricout

Olivier Le Rouzic

François Mouawad

Dominique Chevalier

Eric Dansin

Laurence Rotsaert

Gautier Lefebvre

Olivier Cottencin

Henri Porte

Arnaud Scherpereel

Asmaa El Fahsi

Florence Richard

Benjamin Rolland

Compared characteristics of current vs. past smokers at the time of diagnosis of a first-time lung or head and neck cancer: a cross-sectional study

Keywords: NCT01647425; Registration date: July 23, 2012 Tobacco use, Lung neoplasms, Head & Neck Neoplasms, Alcohol-related disorders

Background

Tobacco smoking is the most important risk factor for lung cancer [START_REF] Alberg | Epidemiology of lung cancer[END_REF], while tobacco and alcohol conjointly account for the occurrence of 67-84% of the head and neck (H&N) cancers [START_REF] Anantharaman | Population attributable risk of tobacco and alcohol for upper aerodigestive tract cancer[END_REF]. Continuing to smoke after the diagnosis of cancer is associated with higher risks of complications, secondary cancers, and death [START_REF] Toll | AACR Subcommittee on tobacco and Cancer. Assessing tobacco use by cancer patients and facilitating cessation: an American Association for Cancer Research policy statement[END_REF]. Moreover, in patients with a lung or H&N cancer, persistent smoking is associated with decreased quality of life, general health, and emotional and social functioning [START_REF] Gritz | First year after head and neck cancer: quality of life[END_REF][START_REF] Duffy | Effect of smoking, alcohol, and depression on the quality of life of head and neck cancer patients[END_REF][START_REF] Garces | Tobacco use outcomes among patients with head and neck carcinoma treated for nicotine dependence: a matched-pair analysis[END_REF]. Intensive smoking cessation programs are thus warranted in current smokers with a first tobacco-related cancer [START_REF] Karam-Hage | Tobacco use and cessation for cancer survivors: an overview for clinicians[END_REF].

In recent years, the implementation of tobacco control policies has enhanced the level of information on tobacco-related harm, which has promoted tobacco cessation [START_REF] Farrelly | The impact of tobacco control programs on adult smoking[END_REF], and subsequently reduced the incidence of tobacco-related cancers [START_REF] Jemal | Lung cancer trends in young adults: an early indicator of progress in tobacco control (United States)[END_REF]. Despite the impact of such policies, some individuals continue to smoke tobacco until they experience a first-time tobacco-related health problem, including a first-time tobacco-related cancer. In contrast, some other individuals who experience a tobacco-related cancer had already stopped tobacco use long before the cancer diagnosis. Thus, the profile of patients with a first-time tobacco-related cancer can be divided into three categories at cancer diagnosis: 1) current smokers (CSs); 2) former smokers (FSs); and 3) never smokers.

Many previous studies have compared the profile of current vs. former smokers at the time of cancer diagnosis. A comprehensive review has recently listed these studies [START_REF] Burris | Systematic review of tobacco use after lung or head/neck Cancer diagnosis: results and recommendations for future research[END_REF]. However, these studies essentially consisted of unadjusted analyses on the smoking status at cancer diagnosis, and, in most cases, they did not explore the contribution of the psychiatric history and other substance use patterns. Consequently, little is known about whether the smoking status at the time of diagnosis of a first-time lung or H&N cancer is related to specific social or psychiatric features, lifelong smoking patterns, or history of other substance uses. In the non-cancer population, it was found that the overall outcome of tobacco dependence is associated with the age of first cigarette, lifelong smoking patterns, and poorer psychosocial conditions [START_REF] Vangeli | Predictors of attempts to stop smoking and their success in adult general population samples: a systematic review[END_REF]. Moreover, concurrent psychiatric and other substance use disorders are also associated with a poorer outcome [START_REF] Goodwin | Predictors of persistent nicotine dependence among adults in the United States[END_REF][START_REF] Goodwin | Symptoms of alcohol dependence and smoking initiation and persistence: a longitudinal study among US adults[END_REF]. In patients with a first lung or H&N cancer, the role of these risk factors was never investigated. Enhancing the knowledge of the psychosocial determinants of the CS status among subjects with a first lung or H&N cancer could strengthen the impact of smoking cessation programs proposed to these patients.

In a multicenter one-year cohort study among 371 subjects with a first-time lung or H&N cancer (i.e., the ALTAK study), we conducted a cross-sectional study using the baseline assessment to investigate the differences in social factors, psychiatric condition, and other substance use patterns between current and pastsmokers at the time of the cancer diagnosis. The presentation of the study is provided according to the 'strengthening the reporting of observational studies in epidemiology' (STROBE) statement [START_REF] Von Elm | The strengthening the reporting of observational studies in epidemiology (STROBE) statement: guidelines for reporting observational studies[END_REF].

Methods

Study design and centers

Data used in this study originated from the baseline screening of the ALTAK cohort study, conducted among 372 subjects with a first lung or H&N cancer. Participants were recruited by otorhinolaryngologists, clinical oncologists, or pulmonologists of the participating centers, at the end of the consultation of cancer announcement. Physicians explained the study and received written consent for participation. The study took place between September 2012 and December 2014 in three different centers: 1) the Centre Oscar Lambret, i.e., the Regional Comprehensive Cancer Center of Lille; 2) the Department of Respiratory Diseases of the University Hospital of Lille; and 3) the Department of Otolaryngology-Head and Neck Surgery of the University Hospital of Lille.

The main objectives of the ALTAK cohort study were: 1) to measure the proportion of subjects that maintain tobacco smoking or alcohol abuse despite the occurrence of cancer; and 2) to identify the social and psychiatric features and addictive comorbidities that could constitute vulnerability factors for not stopping tobacco or alcohol after cancer diagnosis. More information on the study protocol can be found at https://clinicaltrials. gov/ct2/show/NCT01647425. Here, we have used the baseline data of the cohort to explore the determinants of the smoking status at time of cancer diagnosis.

Participants and measures

Inclusion criteria were: 1) age of 18 or more; 2) first lung or H&N cancer excluding mesothelioma and esophagus cancer; and 3) no history of any other cancer over the last five years. The type of cancer (lung or H&N), and the TNM classification grade [START_REF] Travis | The IASLC lung Cancer staging project: proposals for the inclusion of broncho-pulmonary carcinoid tumors in the forthcoming (seventh) edition of the TNM classification for lung Cancer[END_REF] were noted by the clinician who received the initial consent.

Participants were assessed by an addiction specialist in the week following the announcement of the cancer diagnosis. The information collected at baseline and used in the present study was: 1) socioeconomic conditions: age, gender, familial status, employment, and educational level; 2) cancer status: localization, TNM grade, Eastern Cooperative Oncology Group / World Health Organization (ECOG/WHO) score; 3) smoking status and smoking habits: CS, i.e., at last one smoking episode in previous month; FS, i.e., no smoking episode over the previous month; and lifelong non-smoker; 4) alcohol use patterns: use of alcohol during the last 12 months (yes/ no); misuse of alcohol during the last 12 months (yes/ no), defined by an average alcohol use exceeding the recommended national thresholds, i.e., ≥210 g of alcohol per week for a man and 140 g for a woman, and ≥ 50 g per occasion for a man and 40 g for a woman [START_REF]Good Practice Recommendations. Alcohol misuse: screening, diagnosis and treatment[END_REF], Alcohol Use Disorder Identification Test (AUDIT) [START_REF] Saunders | Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption-II[END_REF]; 5) Severity of use of cannabis using the Cannabis Abuse Screening Test (CAST) [START_REF] Legleye | Validation of the CAST, a general population Cannabis abuse screening test[END_REF], i.e., at least one positive item; and 6) Psychiatric assessment using the Mini International Neuropsychiatric Interview (MINI) [START_REF] Sheehan | The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10[END_REF], which is a validated structured interview for diagnosing mental health disorders.

Statistical analyses

Descriptive statistics of each variable are reported in Table 1. Quantitative values are presented as the mean (standard deviation [sd]) when normally distributed or as the median (interquartile range) when there is skewed distribution. Qualitative data are presented as n (percent). To compare smoker and ex-smoker groups, Student's t-test or the Kruskal-Wallis test were used for quantitative data, and the Chi-squared test or Fisher's exact test were used for categorical data. Logistic regression models were used

Ethics approval

The protocol of the ALTAK study (NCT01647425) was declared to and approved by the Comité de Protection des Personnes Nord-Ouest (#CPP12/09) and the Agence Nationale des Médicaments et produits de santé (#B111675-10).

Results

In total, 389 subjects were proposed to participate in the ALTAK study, of whom 371 accepted (response rate: 95. 4%). Among them, 163 (43.9%) were CSs at the time of cancer diagnosis, and 177 (47.7%) were PSs. The characteristics of these participants are summarized in Table 1, according to their smoking status. Bivariable comparisons between the CS and FS groups are also provided in Table 1.

Bivariable comparisons found that belonging to the CS group was significantly associated with younger age (p < 0.0001), being professionally active (p < 0. 0001), and being unmarried (p = 0.04). Moreover, the CS status was significantly associated with a H&N localization of the cancer, with no alteration in daily life activities at the time of diagnosis (p = 0.005), and with the absence of metastases (p = 0.008). With respect to recent substance use patterns, being CS was associated with smoking roll-up cigarettes (p < 0.0002) , with reporting alcohol misuse in the past 12 months (p = 0.007) as well as with the AUDIT (p = 0.002) and AUDIT-C (p = 0.01) scores. Finally, the CS status was significantly associated with the CAST score for cannabis use (p = 0.019). By contrast, the CS status was not found associated with sex (p = 0.14), educational level (p = 0.45), or living alone (p = 0.09). Furthermore, being CS was not related to the age of first cigarette (p = 0.95) and the presence of any psychiatric disorder according to the MINI (p = 0.07).

A separate multivariable analysis of the CS status was conducted among patients with lung and H&N cancer (see Table 2). In subjects with a lung cancer, the CS status was positively associated with ever use of hand-rolled cigarettes and negatively associated with age and ever use of cigarillos. There were trends for positive statistical associations between the CS status and positive MINI, never use of a pipe, and being single. In subjects with H&N cancer, the CS status was positively associated with the AUDIT score. Trends for positive statistical associations were found between the CS status and younger age, ever use of hand-rolled cigarettes, and never use of a pipe.

Discussion

The main objective of the study was to compare the sociodemographic features, psychiatric history, and substance use patterns, of CSs and FSs at the time of initial diagnosis of a first lung or H&N cancer. The main results of the multivariable regression models were that the CS status was associated with younger age and ever use of hand-roll cigarettes in subjects with a first lung cancer, and increased AUDIT score in subjects with a first H&N cancer. Overall, we found a prevalence of 43. 9% CSs, i.e., smokers over the preceding month. This figure is relatively consistent with the estimation provided by a recent literature review, which estimated approximately 50% the rate of CSs over the year preceding the diagnosis of a lung or H&N cancer [START_REF] Burris | Systematic review of tobacco use after lung or head/neck Cancer diagnosis: results and recommendations for future research[END_REF]. Though most of the studies have used a one-year period prior to cancer to define the CS status [START_REF] Burris | Systematic review of tobacco use after lung or head/neck Cancer diagnosis: results and recommendations for future research[END_REF], we chose to follow the recommendations of the National Cancer Institute that deem a one-month period to be more precise [START_REF]NCI-AACR cancer patient tobacco use questionnaire[END_REF].

Regarding the sociodemographic features of CSs, we have found in bivariable comparisons that being CS was significantly associated with younger age, being inactive, and being unmarried. Previous studies that explored the smoking status among subjects with a first lung or H&N cancer found relatively similar results. For example, Schnoll et al. found that only a single marital status was [START_REF] Duffy | Depressive symptoms, smoking, drinking, and quality of life among head and neck cancer patients[END_REF].

Another study by the same team of authors also found that active smoking at the time of diagnosis of an H&N cancer was associated with a single status, but not with age or education level [START_REF] Duffy | Health behaviors of head and neck cancer patients the first year after diagnosis[END_REF]. Though younger age was not consistently found as a substantial contributor of the CS status in previous studies among subjects with lung or H&N cancer, it is a well-known factor in the general population, both in the US and in Europe [START_REF]Trends in Tobacco Use[END_REF][START_REF]Attitudes of European towards tobacco[END_REF]. In this respective, our result could thus be reflective of this general finding. Moreover, the CS status was significantly more important among subjects with a H&N cancer, compared to those with a lung cancer.

Another important result was that the CS rate was much higher in the subjects with a first H&N cancer than in those with a first lung cancer. To our knowledge, our study was the first to directly compare these two types of populations. The risk of experiencing a lung cancer, especially adenocarcinoma, is still significantly increased compared with never smokers more than 30 years after smoking cessation [START_REF] Ebbert | Lung cancer risk reduction after smoking cessation: observations from a prospective cohort of women[END_REF]. In contrast, quitting tobacco smoking fosters a more rapid decrease in the relative risk of H&N cancer [START_REF] Marron | Cessation of alcohol drinking, tobacco smoking and the reversal of head and neck cancer risk[END_REF]. The gap observed in the CS rates between lung and H&N cancer populations may thus be attributable to this difference in longitudinal risk reduction among FSs.

More importantly, it was recently noted that almost no previous studies have addressed the relative rates of the types of tobacco ever used among CSs and FSs with a lung or H&N cancer and that it was a significant issue to explore [START_REF] Burris | Systematic review of tobacco use after lung or head/neck Cancer diagnosis: results and recommendations for future research[END_REF]. In this regard, our study is also the first to provide important findings on this subject. We have notably found that reporting ever smoking of roll-up cigarettes was highly associated with being a CS at the time of cancer diagnosis of a first lung cancer. In the French population, it has been previously found that 24.3% of smokers were used handrolling tobacco, while 7.5% of smokers use only this type of tobacco [START_REF] Guignard | Le tabagisme en France: analyse de l'enquête Baromètre santé 2010[END_REF]. These figures are difficult to compare to other countries, as the prevalence of roll-you-own smokers is very variable depending on countries and their specific regulations on tobacco [START_REF] Young | Prevalence and attributes of roll-your-own smokers in the international tobacco control (ITC) four country survey[END_REF]. Regardless, in France, compared to smokers of manufactured cigarettes, handrolling smokers reported much lower average personal incomes and higher rates of unemployment [START_REF] Guignard | Le tabagisme en France: analyse de l'enquête Baromètre santé 2010[END_REF]. This finding is consistent with other data out of France [START_REF] Curti | The use of legal, illegal and roll-your-own cigarettes to increasing tobacco excise taxes and comprehensive tobacco control policies: findings from the ITC Uruguay survey[END_REF]. In the general population, it was previously shown that quitting smoking is inversely associated with impaired social conditions [START_REF] Burris | Systematic review of tobacco use after lung or head/neck Cancer diagnosis: results and recommendations for future research[END_REF]. Our findings in patients with cancer could thus be explained by unexplored social factors, even if our analyses were adjusted for the level of education. Moreover, as early alterations in daily life activities and the presence of metastases at the time of cancer diagnosis were significantly associated with the FS status in bivariable comparisons, it could be suggested that the FS status is actually partially explained by symptom burden, in particular the fact that some people have become too sick to smoke before cancer was diagnosed. However, these two variables were involved in the step-by-step regression model, but they were not retained as relevant explanatory parameters by the modeling.

Finally, we identified that concurrent alcohol misuse, reflected by the AUDIT score, was significantly associated with the CS status only in patients with a H&N cancer (see Table 2), which could be underlain by the fact that alcohol and tobacco are combined risk factors for this type of cancer.

Several limitations should be acknowledged with regard to the present study. First, the study was multicenter, but the recruitment was regional. Some findings could thus be skewed by local features. Moreover, patients with esophageal cancers were not included in the study, and thus, the findings cannot be applied to all types of H&N cancers. Finally, we did not assess the use of non-smoking types of tobacco, notably chewing or snuff tobacco. However, this type of tobacco use is very rare in Europe [START_REF]Attitudes of European towards tobacco[END_REF]. The main objective of our study was to assess the lifelong types of tobacco used by the patients. This retrospective assessment could be found to be rather imprecise. However, a detailed and quantitative assessment of the specific periods of time during which each type of tobacco was used over the entire lifetime period would have been very difficult to carry out and would have suffered from memory bias and imprecision.

Conclusions

The study highlights important risk factors associated with a CS status at the time of diagnosis of a first lung or H&N cancer. Some risk factors are specific to H&N cancer (i.e., concurrent alcohol misuse), whereas some others are associated with both types of cancer, i.e., young age, ever use of hand-rolled cigarettes, and possibly some psychiatric comorbidities. These findings should warrant a specific screening of these risk factors in subjects with a first lung or H&N cancer, with the aim to treat comorbid conditions and to act on impaired social situations, together with treating cancer and offering tobacco cessation programs to the patients.

Table 1

 1 Descriptive statistics and univariate comparisons between current and past smokers at the time of the cancer onset < 0.20) associated with smoking status in a multiple logistic regression model, adjusted for age and sex. Significance levels were set at p < 0.05. The final multiple logistic regression model was also stratified by localization. Analyses were performed using the SAS software release 9.02 (SAS Institute INC, Cary, NC, USA).

	Past Smokers	Current Smokers	p-value

Table 1

 1 Descriptive statistics and univariate comparisons between current and past smokers at the time of the cancer onset (Continued) Abbreviations: AUDIT: Alcohol Use Disorder Identification Test, AUDIT-C: AUDIT "consumptions" i.e., the 3 first questions of the AUDIT, which pertain to the drinking levels, CAST: Cannabis Abuse Screening Test, ECOG: Eastern Cooperative Oncology Group, MINI: Mini International Neuropsychiatric Interview, version 5.0, TNM: Tumor/Nodules/Metastases, PTSD: Post-Traumatic Stress Disorder, SUD: Substance Use Disorder *a "0" score at the ECOG performance status means "Fully active, able to carry on all predisease activities without restriction"

	Past Smokers	Current Smokers	p-value

Table 2

 2 Association between patient characteristics and current smoking status. Logistic regression model adjusted for age and sex and stratified by localization

		Lung cancer			Head & neck cancer
		OR	95% CI	p-value	OR	95% CI	p-value
	Age	0.92	0.89-0.96	< 0.001	0.97	0.92-1.01	0.15
	Marital status
	Married or in couple	1			1
	Single or widowed	0.49	0.23-1.07	0.07	0.70	0.30-1.61	0.40
	Hand-rolled cigarettes
	Never use	1			1
	Ever use	2.88	1.32-6.30	0.008	1.98	0.93-4.25	0.08
	Cigarillos
	Never use	1			1
	Ever use	0.43	0.19-0.97	0.04	1.09	0.46-2.58	0.85
	Pipe
	Never use	1			1
	Ever use	0.46	0.16-1.37	0.16	0.37	0.14-1.00	0.05
	AUDIT	1.01	0.92-1.10	0.87	1.08	1.01-1.16	0.03
	Psychiatric disorder
	No	1			1
	Yes	1.89	0.86-4.13	0.11	1.36	0.60-3.11	0.46

AUDIT = Alcohol use disorders identification test

Acknowledgements

The authors wish to thank Françoise WEINGERTNER, Stéphanie CLISANT, and Yvette VENDEL for their significant organizational help. The ALTAK Study Group is composed of the following members: Corinne VANNIMENUS, Françoise WEINGERTNER, Hélène BRICOUT, Olivier LE ROUZIC, François MOUAWAD, Dominique CHEVALIER, Eric DANSIN, Stéphanie CLISANT, Laurence ROTSAERT, Gautier LEFEBVRE, Olivier COTTENCIN, Henri PORTE, Arnaud SCHERPEREEL, Asmaa EL FAHSI, Dienabou SYLLA, Florence RICHARD, and Benjamin ROLLAND.

Funding

ALTAK was funded by the Institut National du Cancer (INCa): Grant #RECF1764. The study design and the conduct of the study are independent and remain the full responsibility of the investigators.

Availability of data and materials

Data and materials can be requested at corinne.vannimenus@chru-lille.fr

Authors' contributions BR, HB, FR, and CV designed the study and obtained the grant. CV was the grant holder. CV, AEF, OC, OLR, FM, DC, ED, GL, HP, AS, and LR collected the data. BR, HB, and FR performed the statistical analyses. BR wrote the first draft of the manuscript. CV, HB, FR, OLR, FM, DC, ED, LR, GL, OC, HP, AS, AEF were involved in revising the manuscript critically. All authors have read and approved the final version of the manuscript, and have agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Ethics approval and consent to participate

The protocol of the ALTAK study (NCT01647425) was declared to and approved by the Comité de Protection des Personnes Nord-Ouest (#CPP12/ 09) and the Agence Nationale des Médicaments et produits de santé (#B111675-10). All participants gave their written consent for participating in the study.

Consent for publication

Not Applicable.

Competing interests

The authors declare that they have no competing interests.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Antoine Rouilly
email: antoine.rouilly@ensiacet.fr

Virginie Vandenbossche
email: virginie.vandenbossche@ensiacet.fr

Christine Raynaud
email: christine.raynaud@ensiacet.fr

Pablo Lopez Hurtado
email: pablo.lopez-hurtado@ensiacet.fr

The effect of water dosage on the properties of wet spray cellulose insulation

Keywords: Cellulose insulation, thermal conductivity, recycled paper, compression, moisture sorption, 2. Methodology Cellulose insulation, thermal conductivity, recycled paper, compression, moisture sorption

The thermal and mechanical properties of cellulose fibre insulation, installed via the wet spray projection method, were studied. The isotherms of loose fibres were determined using dynamic vapour sorption to study their behaviour with water. Wet spray cellulose samples with varying water dosage were subjected to compression, and thermal conductivity testing. Results showed density, modulus of elasticity, and thermal conductivity all increased with water dosage. These factors are to be considered for when applying wet-spray cellulose fibre insulation to ensure the properties of the material are consistent.

Introduction:

In the building sector, there is an increasing interest in construction materials that incorporate natural fibres, in order to reduce carbon emissions. One such material is cellulose, an insulation material that is made of ground newspaper fibres treated with fire retardant chemicals. A process of applying cellulose, known as the wet spray method, wherein fibres are sprayed into wall cavities with water, shows many benefits compared to the traditional "dry" method. The wet spray method provides a material that is evenly distributed, doesn't sag, and has better resistance to air infiltration. The issue with this process is the control of water dosage. Appliers of cellulose insulation might have trouble controlling the amount of water sprayed during installation. An excess of water might lead to a material that resists sagging but takes longer to dry. As well as this delay, the increase of applied water could affect the thermal and mechanical properties of cellulose insulation, which has yet to be studied.

Cellulose samples were sprayed into square moulds for mechanical and thermal conductivity testing. Samples were dried in ambient conditions and the mass of samples were logged daily. The drying behaviour of cellulose samples with different moisture content was studied. Loose cellulose insulation fibres were characterised with regards to their behaviour with water using dynamic vapour sorption isotherms. Compression tests, adapted from the standard EN 826 were made on 100x100x90mm3 samples. Thermal conductivity measurements, made on 150x150x50mm 3 samples were made at 10° C and 25°C, according to the standard NF EN 12667.

Results and Conclusion

Dynamic vapour sorption isotherms on cellulose insulation show the high affinity of cellulose to moisture, especially in the super hygroscopic region (relative humidity > 95%), the oswin model provides a good approximation of cellulose insulation's interaction with water. The delays caused by drying of cellulose insulation (at constant ambient conditions) were exposed, further supporting the need to control initial water dosage.

Density, compression resistance, modulus of elasticity and thermal conductivity of cellulose insulation all increased with initial moisture content. This is due mainly to compation of the material through increased water pressure and the hardening and strengthening of cellulose fibres as they dry. A linear relation was established between the mechanical and thermal properties and initial moisture content. A baseline of 14.05 kPa modulus of elasticity E and 0.62 kPa, and 1.34 kPa for E, σ5% , σ10% was defined as an approximation of the minimum resistance of the material ( at ambient humidity conditions) to prevent sagging. While the changes in thermal conductivity could be considered insignificant, there is still a loss in thermal efficiency of the material once an excessive amount of water has been used. Proper knowledge on the behaviour of these types of materials can improve its attractiveness for the use in new constructions and renovation projects.

Space for notes

Introduction:

In the building sector, there is an increasing interest in construction materials that incorporate natural fibres. Not only do these materials have a reduced environmental impact than more traditional materials, they also have good thermal acoustic, and moisture absorbing properties. One such material is cellulose, an insulation material that is made of ground newspaper fibres treated with fire retardant chemicals. Since it uses recycled materials and requires little energy to produce, it has less embodied energy than traditional materials such as mineral wool, and even materials based on cellulosic fibres such as wood fibre insulation [START_REF] Hammond | Inventory of Carbon & Energy Version 2.0 (ICE V2. 0[END_REF].

There are two main methods of applying cellulose fibre insulation: "loose fill" where the fibres are blown into attics or closed wall cavities using specialized equipment, and "wet spray" where water is atomized and sprayed while the fibres are blown into open wall cavities. The water makes the fibres adhere to the cavity, in order to prevent sagging and ensure a homogeneous distribution of the fibres. After spraying, the excess material is removed via an electric wall scrubber to ensure a flat surface. The wet-spray method also provides a better air tightness for a buildings envelope, preventing the loss of heat caused by air infiltration through voids [START_REF] Nahb Research | Air Infiltration of Wood Frame Walls[END_REF].

Pablo Lopez Hurtado Phd student Laboratoire de chimie agroindustrielle (LCA) INP ENSIACET France pablo.lopez-hurtado@ensiacet.fr

An issue with the wet-spray method of applying cellulose insulation is the control of water during spraying. If too little water is applied to the cellulose, the fibres might sag or unstick to the wall. Conversely if too much water is applied, the fibres will have a better cohesion to the wall cavity and to themselves, but the material will require more time to dry before a vapour barrier and/or drywall, depending on ambient conditions. In the work of Salonvaara et al [START_REF] Salonvaara | Impact of Weather on Predicting Drying Characteristics of Spray-Applied Cellulose Insulation[END_REF], the modelled drying of wet spray cellulose varied greatly depending on the month and location it was installed, with cellulose installed in winter months taking several weeks to reach a dry state. Incidentally, in the same study, wet spray cellulose that was intended to be installed at the minimum recommended water dosage of 40%, turned out to be installed at a dosage of 70%. This shows, albeit anecdotally, that professional installers might have difficulty controlling the initial water content of wet spray cellulose insulation.

Most research on cellulose insulation focuses on the loose-fill application. The influence of adsorbed humidity on thermal conductivity on loose fill cellulose fibres has been studied. A linear relation between moisture content and thermal conductivity has been established [START_REF] Véjelis | Performance of Loose-Fill Cellulose Insulation[END_REF][START_REF] Larson | Field and laboratory studies of the thermal resistance of moist building insulation systems[END_REF][START_REF] Sandberg | Determination of the effects of moisture content on the thermal transmisivity of cellulose fiber loose-fill Insulation[END_REF]. These studies consider only the influence of humidity contained within the loose fibres, and not how drying of fibres can influence these properties. It has been shown that once paper fibres dry, their strength increases, porosity decreases, and their moisture retention capacity decreases [START_REF] Hubbe | What happens to cellulosic fibres during papermaking and recycling? A review[END_REF]. These changes in the fibre structure during drying can also affect the thermal conductivity of cellulose insulation, which has yet to be studied.

For loose fill applications, methods have been developed to test the settling of loose fibres in attics [START_REF] Bomberg | Comments on Standardization of Density and Thermal Resistance Testing of Cellulose Fibre Insulation for Horizontal Applications[END_REF][START_REF] Svennerstedt | Analytical Models for Settling of Attic Loose-Fill Thermal Insulation[END_REF]. A model to study mechanical behaviour of loose fill fibres in a closed cavity is detailed in the work done by Rasmussen [START_REF] Rasmussen | Modelling Settling of Loose-fill Insulation in Walls, Part II Determination of Coefficients[END_REF][START_REF] Rasmussen | Modelling Settling of Loose-Fill Insulation in Walls. Part I[END_REF]. This model studies the creep behaviour of loose fibres in a closed wall cavity in order to predict the necessary installed density to prevent settling. The model used friction coefficients with the surface the cellulose fibres are installed on oriented strand board (OSB) closed wall cavities. In the case of cellulose insulation installed through the wet spray method, the fibres are rigid once they dry and adhere directly to the wall cavity. The measurements used on loose fill therefore do not apply to the wet spray application and there has yet to be a defined method to quantify the mechanical performance of materials fabricated with this method. The contribution of water on the mechanical behaviour of these fibres needs to be studied in order to determine a baseline mechanical resistance to ensure that the material will remain rigid and not settle.

In the present work, the influence of water dosage on the thermal and mechanical properties of cellulose fibre insulation manufactured through the wet-spray method was studied. The interactions of the fibres with water were first considered with dynamic sorption testing. The drying behaviour of projected cellulose insulation samples was then investigated. A method to test the compression resistance of the cellulose fibres was devised to study the influence of initial moisture content on its mechanical properties. The same was done with thermal conductivity testing via the guarded hot plate method.

Material and methods

2.1

Manufacture and preparation of samples Cellulose fibres of the brand Univercell Comfort were provided by SOPREMA (Bordeaux, France). The raw materials are pre-consumer newsprint paper from several providers from the south of France. In factory, the papers are ground into smaller fragments, which are then turned into loose fibres via a specialized fiberizer. Boric salts are then added as a fire retardant and antifungal agent. The fibres come compacted in a bag in order to optimize transportation costs. Once delivered onsite, the compacted fibres are fed to the blowing machine, which first separates them so they can be blown. A separate pump, connected to the blowing hose, pumps water which is then atomized through nozzles at the same time the fibres are blown into the cavity. In order to vary the initial moisture content of the samples, the pumped spray water pressure varied from 6 to 25 bars. The fibres were blown into wooden moulds of dimensions: 300x300x90mm

3 for mechanical tests.

The moulds were fitted with a removable 2.5mm rigid cardboard base covered with a coat of vinylic glue. Once the insulation sample was dry, it was carefully unmoulded and another 2.5mm cardboard was glued to the other side of the sample. Once the glue dried, the sample was then cut into nine 100x100x90 mm 3 pieces via a circular saw. The use of cardboard served two purposes:

to ensure that the 100x100mm² samples have good contact with the compression plates and that they were cut evenly without loss of the material. Thermal conductivity samples were projected on 150x150x50mm 3 moulds with a removable top for unmoulding. Once dry, samples were carefully separated from the moulds using a trowel. All samples were stored in a climactic chamber at 25°C and 60% relative humidity (RH). To measure the drying of CFI, the mechanical testing samples were weighed daily in order to measure the evaporated water until equilibrium moisture conditions at 60% RH (a mass variation of less than 1% in 24 hours) were reached. The equilibrium moisture content was then determined by taking 3g of fibres from the ambient dried sample and drying them at 100°C for two hours. Using the mass of the samples and the equilibrium moisture content, the initial moisture content as well as the drying of the material at 24 hour intervals was determined.

2.2

Dynamic vapour sorption Sorption isotherms were made by dynamic vapour sorption apparatus DVS Advantage from Surface Measurement Systems Ltd (London, United Kingdom). Loose fibre samples were placed into an aluminium sample holder connected to a microbalance. The samples were then subjected to a series of relative humidity variations from 5% to 95%, with 10% intervals, at a constant temperature of 25°C. The variations in mass due to moisture adsorption and subsequent desorption were then plotted against relative humidity.

2.3

Mechanical testing Compression tests, adapted from the standard EN 826, on the cut 100mm x 100mm x 90mm samples were made by means of an H5KT universal testing machine from Tinius Olsen (Surrey, England) equipped with either 100N or 500N sensors, depending on the material's resistance. Steel 100 x 100 mm² compression plates ensured direct contact with the samples. Compression was done at a speed of 10 mm/min. A pre-charge of 1 N was applied to ensure direct contact with the sample. Due to the fact that the material is highly compressible, no fracture or rupture was detected so instead the measured stress at 5% and 10% strain was logged for each sample. Compression tests stopped once 20% strain was reached. Since each sample had slight variations in dimensions of the order of ± 2mm, they were measured in order to accurately calculate their respective stress and strain.

2.4

Thermal conductivity measurements Thermal conductivity measurements were done according to the standard NF EN 12667. Samples of 150x150x50mm 3 were placed in a λ-Meter EP500e guarded hot plate apparatus from Lambda-Messtechnik (Dresden, Germany). Foam insulation was used around the samples to ensure the contact plates measured only the 150 x 150 mm² surface of samples. The contact plates applied a pressure of 50 Pa to ensure direct contact with the samples without compacting them. Measurements were made at 10 and 25° C average temperature with a temperature difference of 10°C between plates. Steady state was assumed to be reached when the value of thermal conductivity varied less than 1% in 60 minutes.

Results and discussion

Dynamic vapour sorption

Results from dynamic vapour sorption of cellulose fibres are shown in Figure 3. The isotherms show little hysterisis, less than 2% difference between sorption and desorption isotherms. One can see that in the hygroscopic range moisture sorption reaches around a maximum of 20% mass so the range of minimum water dosage of 40%-60% means that water within the cellulose after spraying is contained within the pores. It is possible however, to estimate the moisture sorption in the whole range using mathematical approximations. Many models exist such as Brunauer-

Fig. 2 compression testing setup

Emmett-Teller (BET) or Guggenhein, Anderson, de-Boer (GAB) models, but for porous solids such as cellulose it is recommended to use the Oswin model: [START_REF] Karoglou | Water Sorption Isotherms of Some Building Materials[END_REF] (1

)
Where Xe is the calculated moisture content, aw the relative humidity, T is the ambient temperature, and b0, b1, b2 are coefficients dependent on the material. These coefficients were determined by minimizing the standard deviation between the calculated values and the average between the measured sorption and desorption values. The Oswin model shows good relation with the values determined experimentally. The moisture content at saturation can be estimated when RH values approach 100%. At a RH of 99.999% the Oswin model gives a value of 279% moisture content, showing that, past the hygroscopic range, cellulose can absorb high quantities of water via capillary conduction.

Drying of cellulose insulation samples

The drying curves of projected 300x300x90mm 3 samples stored in 25°C at 60% RH with varying water pressure are shown in Figure 4. Evidently, an increase in water dosage increases the time for the material to reach an equilibrium dry state. In practice, installers of cellulose fibre insulation consider that when the material reaches around 20% moisture content, it is considered dry enough to allow the installation of a vapour barrier and drywall. For example, a water dosage of 70% can increase the time to reach 20% moisture to 58 hours versus the 19 hours needed when the minimum recommended dosage of 40% is applied, over three times the standard waiting time. It is worth noting that this applies only to 90mm thick insulation at the constant conditions of 25°C at 60% RH. In reality, the drying rates vary depending on thickness and ambient conditions. The thicker the specimen, the colder and more humid drying conditions are, the longer the drying times, which sometimes cause unacceptable delays in a construction project.

b X         -       = 0% 5%

3.3

Changes in density. As is shown in Figure 5, the final density of the material depends on the installed moisture content. The values shown are slightly higher than those found by Salonvaara et. al. [START_REF] Salonvaara | Impact of Weather on Predicting Drying Characteristics of Spray-Applied Cellulose Insulation[END_REF]. At the minimum moisture content of around 40%, density varies from 50 to 57 kg/m3. The results show a linear increase of density with initial moisture content up to 77 kg/m3. The increase in density has two likely causes: the increased pressure from the pulverised water, which causes compaction of the material as it is projected, and the strengthening and hardening of fibres as they dry. This further emphasises the need to control of water dosage since as the density increases, more of the material is used to insulate the same volume, which subsequently increases costs of installing the insulation. As it has been shown with other natural building materials [START_REF] Madurwar | Application of agro-waste for sustainable construction materials: A review[END_REF][START_REF] Nguyen | Effect of compaction on mechanical and thermal properties of hemp concrete[END_REF][START_REF] Elfordy | Mechanical and thermal properties of lime and hemp concrete ('hempcrete') manufactured by a projection process[END_REF] these variations in density can also cause changes in the thermal and mechanical properties of the material, as will be shown in the following sections.

Compression tests

Stress-strain curves of cellulose insulation with samples with different moisture dosages are shown in Figure 6. The lightweight material shows a quasi-linear elastic behaviour with no rupture at strains up to 20%. As was expected, the material shows an increase in its mechanical resistance with increasing moisture content.

Figures 7 and8 show the relation between water content calculated elasticity modulus E, and the calculated stress at 5% and 10% strain (σ5% σ10%) respectively. While all the values show a good linear relation with moisture content, the best indicator seems to be the stress measured at 10% strain σ10%. This could be due to the fact that as the material is compacted, the heterogeneous voids it are filled, giving a more linear and constant reading of the applied stress at higher deformation. In order to define a « minimum resistance » of wet spray cellulose insulation to ensure that the material will not sag or tear once projected, the measured values of the modulus of elasticity E and compressive stresses σ5% σ10% at around 40% moisture content are averaged. This gives an average of 14.05 kPa, 0.62 kPa, and 1.34 kPa for E, σ5% , σ10% respectively. These values could potentially be used as a reference point if, for example, a raw material (recycled newsprint) of different quality is used, or if the amount and/or type of additives are changed.

3.5

Thermal conductivity testing Figure 9 shows the variation of dry thermal conductivity at with installed water dosage average temperatures of 10°C and 25°C (λ10 and λ25). As with mechanical properties, the value of dry thermal conductivity also increased with installed water content, although in this case there the difference is much smaller, making the results more prone to inconsistency. Thermal conductivity values varied from 37 to 43 mW/m.K, for measurements made at 10°C and around 40 to 46 The high scatter could be due to the heterogeneity of the samples, or to loss of heat through voids between the contact plate and the sample. Since the material is highly compressible it was difficult to ensure perfect contact between the plates and the samples without compressing the samples, which would increase its density and thermal conductivity. While this increase in values of λ with applied moisture content is slight, it is still unfavourable to a wall's thermal performance. It is in the cellulose installers' best interest to use the lowest feasible water dosage in order to ensure optimum insulation capacity of the material.

Conclusions

As the results have shown, the increase of water not only delays construction after installation, but also increases the density and thermal conductivity wet sprayed cellulose insulation. The increase in density and drying time with increased water dosage remain important factors to consider when applying cellulose insulation. A method to determine the mechanical behaviour of wet sprayed cellulose was devised. The compression tests give an indication of how the installed moisture content strengthens the material in order to prevent sagging or tearing of the material. A baseline of 14.05 kPa modulus of elasticity E and 0.62 kPa, and 1.34 kPa for E, σ5% , σ10% was defined as an approximation of the minimum resistance of the material ( at ambient humidity conditions) to prevent sagging. While the changes in thermal conductivity could be considered insignificant, there is still a loss in thermal efficiency of the material once an excessive amount of water has been used. In a practical sense, it would be pertinent to have a quality control system which the wet spray water dosage was measured in a test sample before applying to an entire wall. This will ensure that the minimal dosage (40%) of water is employed in order to reduce drying times, minimize density and thermal conductivity, while maintaining a rigid material that will not settle or tear. Wet spray technology not only applies to cellulose fibres, but new methods of spraying hemp and flax fibres are being implemented for the installation novel eco-friendly building materials, and it is important to ensure that they are installed in the most efficient manner. It is through proper knowledge and testing of these innovative and eco-friendly materials, which will make them more prevalent in the building sector, thus helping reduce carbon emissions of new constructions and renovation projects.

Fig. 1 :

 1 Fig. 1: 300x300x90mm 3 sprayed samples (left) and cut 100x100x90mm 3 sample for compression testing (right)

Fig. 3 :

 3 Fig. 3: Sorption and desorption isotherms, with Oswin model approximation

Fig. 4 :Fig. 5 :

 45 Fig. 4: Drying of cellulose samples, with varying water pressure

Fig. 6 :

 6 Fig. 6: Stress-strain curves of projected cellulose insulation samples with varying moisture content

Fig. 7 :Fig. 8 :

 78 Fig. 7: Influence of installed moisture content on modulus of elasticity E, with linear regression line

Fig. 9 :

 9 Fig. 9: Influence of installed moisture content on thermal conductivity values λ10 and λ25, with linear regression lines

Acknowledgements

The work in this paper is financed by the consulting firm Greenbuilding, as well as by grants provided by the French A.N.R.T. and Paris Région Entreprises.


Maud Ranchet

Abiodun John C Morgan

Emmanuel Akinwuntan

Hannes Devos

A E Akinwuntan

Cognitive determinants of visual search in patients with Parkinson's disease

de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

BACKGROUND OBJECTIVE

METHODS

RESULTS

CONCLUSION ACKNOWLEDGEMENT  Visual search impairments in patients with

Parkinson's Disease (PD) [START_REF] Archibald | Visual exploration in Parkinson's disease and Parkinson's disease dementia[END_REF][START_REF] Horowitz | Visual search deficits in Parkinson's disease are attenuated by bottom-up target salience and topdown information[END_REF]  They may affect activities of daily living [START_REF] Devos | Driving and off-road impairments underlying failure on road testing in Parkinson's disease[END_REF][START_REF] Uc | Impaired visual search in drivers with Parkinson's disease[END_REF]  Table 1. Partial correlations between cDT and neuropsychological performance  We thank the American Parkinson's Disease Association for funding this research. We also thank Adam Bruetsch, MS, for his help in data analysis.  PD patients were slower than controls to detect correctly the target (7s. ± 2 vs 5 s. ± 1, p = 0.004)

 PD patients missed more targets than controls (median (Q1-Q3) : 0(0-2) vs 0(0-0), p = 0.04)

Figure 1 .

 1 Figure of Rey Dot cancellation test

  Figure of Rey, score -0.76*** -0.17


M C Ulrich

Remillieux

M Lott

C Payan

V Garnier

P Y Le Bas

T J Ulrich

M C Remillieux

Three-dimensional modeling and numerical predictions of multimodal nonlinear behavior in damaged concrete blocks

Three-dimensional modeling and numerical predictions of multimodal nonlinear behavior in damaged concrete blocks

I. Introduction

Geomaterials exhibit mechanical softening under dynamic loading, usually combined with hysteresis and slow-dynamics effects [START_REF] Johnson | Resonance and elastic nonlinear phenomena in rock[END_REF]TenCate et al., 2000). These effects are reversible and deterministic. From a micro-structure standpoint, a recent study has established a correlation between micro-crack density and softening effects (Payan et al., 2014a,b). From an energy balance point of view, it means that some potential energy disappears when the material is loaded dynamically and is slowly recovered when the material is at rest. These properties are relevant to various natural processes and industrial applications including the onset of earthquake and avalanches in geophysics [START_REF] Johnson | Nonlinear dynamics, granular media and dynamic earthquake triggering[END_REF], the aging of civil infrastructure [START_REF] Eiras | Dynamic acousto-elastic test using continuous probe wave and transient vibration to investigate material nonlinearity[END_REF][START_REF] Payan | Applying nonlinear resonant ultrasound spectroscopy to improving thermal damage assessment in concrete[END_REF][START_REF] Vu | Concrete cover characterisation using dynamic acousto-elastic testing and rayleigh waves[END_REF], the design of acoustic meta-materials with extreme stiffness [START_REF] Diani | A review on the mullins effect[END_REF][START_REF] Wang | Extreme stiffness systems due to negative stiffness elements[END_REF], or the assessment of bone fragility in the medical field [START_REF] Haupert | Non destructive characterization of cortical bone micro-damage by nonlinear resonant ultrasound spectroscopy[END_REF].

The dynamic response of these materials has been first modeled by [START_REF] Guyer | Hysteresis, discrete memory, and nonlinear wave propagation in rock: A new paradigm[END_REF] using the Preisach formalism, which is a phenomenological description borrowed from the field of electromagnetics. This model has then been refined to include slow-dynamics effects through thermally activated random transitions between the open and closed states of the hysteretic elements of the Preisach system [START_REF] Delsanto | Modeling nonclassical nonlinearity, conditioning, and slow dynamics effects in mesoscopic elastic materials[END_REF][START_REF] Nobili | Temperature effects on the elastic properties of hysteretic elastic media: Modeling and simulations[END_REF].

More recently, [START_REF] Pecorari | A constitutive relationship for mechanical hysteresis of sandstone materials[END_REF] proposed a hysteretic model sharing some features with the Jiles-Atherton model (also borrowed from the field of electromagnetics), which he enhanced to capture the slow-dynamics effects. It is also worth mentioning the soft-ratchet model of slowdynamics originally proposed by [START_REF] Vakhnenko | Strain induced kinetics of intergrain defects as the mechanism of slow dynamics in the nonlinear resonant response of humid sandstone bars[END_REF] and recently modified by [START_REF] Favrie | Fast and slow dynamics in a nonlinear elastic bar excited by longitudinal vibrations[END_REF] to include classical nonlinearity and viscoelasticity. All these models, however, have been derived in the one-dimensional (1D). Three-dimensional (3D) effects are an essential part of the dynamic response observed in geomaterials and cannot be ignored [START_REF] Egle | Measurement of acoustoelastic and third-order elastic constants for rail steel[END_REF][START_REF] Payan | Applying nonlinear resonant ultrasound spectroscopy to improving thermal damage assessment in concrete[END_REF][START_REF] Payan | Determination of third order elastic constants in a complex solid applying coda wave interferometry[END_REF][START_REF] Tournat | Probing weak forces in granular media through nonlinear dynamic dilatancy: clapping contacts and polarization anisotropy[END_REF]. [START_REF] Lyakhovsky | Non-linear damage rheology and wave resonance in rocks[END_REF] proposed a twodimensional continuum damage rheology model capturing hysteretic nonlinearity and some of the features observed in nonlinear resonance experiments. A similar model was used by [START_REF] Hamiel | Brittle deformation and damage-induced seismic wave anisotropy in rocks[END_REF] to describe stress-induced anisotropy in damaged geomaterials. Note that in these models, damage is not recoverable and slow-dynamics effects are not considered. The recent modeling work of [START_REF] Berjamin | Nonlinear waves in solids with slow dynamics: an internal-variable model[END_REF] includes slow-dynamics effects, but although it can be naturally extended to 3D analysis, the simulations are carried out only for a 1D case. Lott,JASA 4 Attempting to develop a predictive tool to link the microstructural properties of the material to the nonlinear elastic response observed experimentally is a challenging task. Despite a high sensitivity to microstructures, amorphous condensed matter arrangement, and environmental conditions (e.g., temperature, pressure) (Lott et al., 2016;[START_REF] Payan | Determination of third order elastic constants in a complex solid applying coda wave interferometry[END_REF]TenCate et al., 2000), the elastic nonlinear parameters seem to depend on the choice of the experimental setup in much of the previous work reported in the literature. For instance, [START_REF] Renaud | Anisotropy of dynamic acoustoelasticity in limestone, influence of conditioning, and comparison with nonlinear resonance spectroscopy[END_REF] showed that material softening effects in Berea sandstone may vary by up to an order of magnitude depending on the probing direction while the material is isotropic. In the work of Payan et al. (2014a,b) on concrete, two techniques were used to estimate a parameter of nonlinearity. The two techniques showed the same trends but the magnitudes of the measured parameter differ by an order of magnitude. These experimental data where derived using the most common 1D approximation. However, a complex strain field leads to a 3D problem from a mechanical point of view and using a 1D approximation to describe this problem may lead to erroneous conclusions.

Recently, Lott et al. (2016[START_REF] Lott | Nonlinear elasticity in rocks: A comprehensive three-dimensional description[END_REF] show that conditioning can be properly accounted in 3D using a single scalar nonlinear parameter into the appropriate set of elasticity equations using uncoupled single mode resonance type of experiments, i.e., shear and compressional. The aim of this paper is to study the validity of this model to nonlinear resonance experiments, involving strong coupling between shear and compressional motion types. Numerical simulations are compared to experimental data from nonlinear resonances in gradually thermally damaged concrete blocks. Using a single scalar nonlinear parameter appropriately introduced in elasticity equations, the validity of the model is demonstrated and discussed.

II. Theoretical framework

In continuum mechanics, the parameters needed to compute the linear dynamic response of an elastic body are the mass density, the linear elastic tensor, and the damping parameters. If the geometry of the sample is complex and/or the material is heterogeneous, numerical techniques (e.g., finite-element method) should be used and the distribution of these parameters should be known for all computation cells discretizing the sample. In this paper, we study consolidated granular materials, which may be described as a disordered network of mesoscopic-sized "hard" Lott, JASA 5 elements (e.g., grains with characteristic lengths ranging from tens to hundreds of microns) cemented together by a "soft" bond system (e.g., amorphous silica, calcite) [START_REF] Guyer | Nonlinear mesoscopic elasticity: Evidence for a new class of materials[END_REF]. Despite the complexity of the structure, the linear elastic response of these materials at macroscopic scale is well captured by the model of a continuum. This continuum may have heterogeneous properties under dynamic loading as a combined result of the complex spatiotemporal distribution of the strain field in the sample and the strain-induced material softening [START_REF] Payan | Applying nonlinear resonant ultrasound spectroscopy to improving thermal damage assessment in concrete[END_REF][START_REF] Remillieux | Resonant ultrasound spectroscopy for materials with high damping and samples of arbitrary geometry[END_REF][START_REF] Renaud | Anisotropy of dynamic acoustoelasticity in limestone, influence of conditioning, and comparison with nonlinear resonance spectroscopy[END_REF]. Material softening is thought to originate from the microscopic-sized defects (e.g., micro-cracks) in the "soft" subsystem and at the interfaces between the "hard" and "soft" subsystems (Payan et al., 2014a). To incorporate these defects in the macroscopic continuum model, we consider a volume dV that is small enough to satisfy the requirements of the numerical schemes but large enough to ensure a constant micro-crack density from one volume to the next. Furthermore, we assume that the defects are randomly distributed and oriented within the volume dV, with a length-scale much smaller than the typical acoustic wavelengths used in this study. With dV being on the order of 1mm 3 , the above criteria are satisfied.

The approach used in this paper is similar to the one used by [START_REF] Zubelewicz | Overall stress and strain rates for crystalline and frictional materials[END_REF] in transient numerical simulations of rock fractures. Each contact within the medium brings softening effects through nonlinear cohesive mechanisms. These effects are then integrated over an elementary volume dV and used for a mesoscopic mechanical implementation within a continuum with possible heterogeneous properties.

Recently, the authors (Lott et al., 2016[START_REF] Lott | Nonlinear elasticity in rocks: A comprehensive three-dimensional description[END_REF] proposed a general formulation to include material-softening effects in the equations of elasticity. This formulation is an extension of that proposed by Hughes and Kelly [START_REF] Hughes | Second-order elastic deformation of solids[END_REF]. The tensorial product between the strain and stress vector bases, δij=ni stress ⊗nj strain , is the natural basis for the elastic tensor and should now include softening effects as,

Λ 𝑖𝑗 = 𝛿 𝑖𝑗 (1 -αΔ𝜀 𝑖𝑗 * ), (1)
or equivalently in matrix form as,

𝚲 = 𝑰 3 -𝛼𝜺 * , (2)
Lott, JASA

6
where ni is the principal strain direction, Δεij * the strain amplitude, the star symbol denotes the basis formed by the principal strain axes, and α is a scalar quantifying the softening effect. The stiffness tensor is then expressed as,

𝐶 𝑖𝑗𝑘𝑙 * = [𝜆 + 2(𝑙 -𝜆 -𝑚)𝑇𝑟(𝜀) + 2(𝜆 + 𝑚)(𝜀 𝑖 * + 𝜀 𝑘 * ) -2𝜇𝜀 𝑖 ]Λ 𝑖𝑗 Λ 𝑘𝑙 + [𝜇 + (𝜆 + 𝑚 -𝜇)𝑇𝑟(𝜀) + 2𝜇(𝜀 𝑖 + 𝜀 𝑗 + 𝜀 𝑙 )](Λ 𝑖𝑘 Λ 𝑗𝑙 + Λ 𝑖𝑙 Λ 𝑗𝑘 ) + 1 2 𝑛 ∑ (Λ 𝑗𝑣𝑘 𝑖𝑣𝑙 + Λ 𝑗𝑣𝑙 𝑖𝑣𝑘 )𝜀 𝑣 𝑣 (3)
where λ and μ are the Lamé constants and l, m, n are the Murnaghan constants [START_REF] Murnaghan | Finite deformations of an elastic solid[END_REF]. Practically, the material-softening law is applied in the basis formed by the principal strain axes. This basis is obtained from an eigen decomposition of the strain field ε measured in the geometric basis. This decomposition, ε = P ε*P -1 , is always possible because the strain tensor is always real and symmetric. Once the softening law has been applied to the stiffness tensor in the basis formed by the principal strain axes, the following transformation is used to express the conditioned stiffness tensor in the geometric basis: Cijkl = PirPjsPktPluC * rstu. This result is equivalent to classical acoustoelasticity theory when the term quantifying softening is equal to the identity matrix.

In this study, the validity of the model will be assessed using nonlinear resonance experiments or more commonly referred to in the literature as nonlinear resonant ultrasound spectroscopy (NRUS). In these experiments, a sample is subjected to sequences of periodic signals at various frequencies around a resonance frequency and at increasing amplitudes while, for each periodic signal, data are recorded when the sample vibrates at or near a steady state. Under these conditions, the effects of the first-order term of nonlinearity in the classical description, i.e., terms involving β in 1D and (l, m, n) in 3D, average to zero over one cycle of the harmonic excitation. This is not the case with the second-order term of nonlinearity δ but the proposed model does not go beyond the first order. As a result, Eq. ( 3) can be simplified by removing the terms involving third-order elastic constants (i.e., only the linear version of the elastic tensor is used to apply the softening law),

𝐶 𝑖𝑗𝑘𝑙 * = 𝜆Λ 𝑖𝑗 Λ 𝑘𝑙 + 𝜇 (Λ 𝑖𝑘 Λ 𝑗𝑙 + Λ 𝑖𝑙 Λ 𝑖𝑗𝑗𝑘 ). (4)
Finally, each cell (dV) of the sample can be conditioned by the strain amplitude at that cell. This means that the stiffness tensor is no longer uniform over the volume of the sample but depends on the local strain tensor. The sample experiences softening with a complex distribution (i.e., that of the strain field), which in turns lowers its resonance frequencies. Because of the heterogeneity, the resonance frequencies have to be computed numerically.

III. Numerical application to experimental data

The validity of the model is examined against experimental data collected during resonance experiments. The samples are those described by [START_REF] Payan | Quantitative linear and nonlinear resonance inspection techniques and analysis for material characterization: Application to concrete thermal damage[END_REF]. The three samples used in this study consist of concrete blocks with dimensions 6 × 10 × 10 cm 3 . One sample is kept intact and used as a reference. The other two samples are thermally damaged at 120 and at 250°C using a slow increase then decrease in temperature to prevent from eventual mechanical damage induced by thermal gradients. Thermal damage allows the density of micro-cracking within the concrete samples to be increased as needed. Below 300° C, microcracks are essentially caused by drying as well as differential thermal dilatation between cement paste and aggregates. In concrete the most brittle zone is the interface between the aggregates and the cement paste. This zone, commonly referred to as Interfacial Transition Zone (ITZ), is the most porous and crystallized region. It is thus quite natural to assume that most of the thermal damage will occur in the ITZ. With an arbitrary grain distribution, thermal damage of concrete can reasonably be considered as isotropic.

A. Experimental protocol and results

The

B. Numerical protocol

The relatively large mass added by the transducer is accounted for in the model by an aluminum cylinder with a perfect contact between the transducer and the sample. The following protocol is applied (Fig. 2) to describe the numerical process. The simulations are carried out using the "Structural Mechanics" module of the commercial finite-element software package Comsol® Multiphysics.

• Step 1 : A first eigenvalue problem is solved to compute the resonance frequencies of the samples with linear elastic properties (before the material-softening law is applied), which were already measured by [START_REF] Payan | Quantitative linear and nonlinear resonance inspection techniques and analysis for material characterization: Application to concrete thermal damage[END_REF] of strain amplitudes in the samples are recovered from the linear model, based on the laser measurement at a single point.

•

Step 2 : In the second step of the numerical protocol, a frequency-domain simulation is conducted by imposing a normal force on the free flat surface where the transducer is mounted. The amplitude of the normal force is tuned to match the particle velocity at the measured position on the sample.

•

Step 3 (Fig. 2) : The strain tensor is extracted at all nodes of the mesh discretizing the sample and used for the conditioning step. As the media is initially considered isotropic and homogeneous, the initial local stiffness is independent of the choice of basis and usually written Cijkl = λ δijδkl + μ (δikδjk + δilδjk). Using Eq. ( 1) and Eq. ( 4), the material softening effect is applied to the stiffness tensor Cijkl * trough the tensors Λij in the eigen basis.

•

Step 4 (Fig. 2) : The conditioned elastic tensor is then transposed back to the "geometrical" basis. After this numerical procedure, the sample, initially homogeneous and isotropic, becomes heterogeneous and anisotropic.

• Step 5 : A final eigenvalue problem is solved to compute the resonance frequencies of the samples with conditioned elastic properties. Steps 2 to 5 are repeated for several amplitudes to provide a curve of the relative shift of the resonance frequency.

IV. Results and discussion

Predicted and measured material softening in NRUS are shown in Fig. 3 for the three samples.

The values of α0 used in the simulations to match the experimental data are reported in Table .     II.

Sample α0

Reference 300

120°C 520 250°C 1000

Table . II. Values of the parameter α0 used in the NRUS simulations for the three concrete samples.

Note that this value increases by more than 300% between the reference sample and the most damaged sample, which seems to be consistent with the evolutions of the nonlinear parameters reported in the literature. To highlight the efficiency of the present model, the "apparent" nonlinear parameters are measured by linear regression of the relative frequency shift as a function of the strain amplitude for the three modes studied. This apparent nonlinear parameter changes with the mode order and the type of strain (e.g., volumetric and deviatoric) used in the analysis. For each mode and each sample, the apparent nonlinear parameters obtained with volumetric and deviatoric strains are reported in Fig. 4. Tying this apparent nonlinear parameter to a 1D description will lead to erroneous conclusions including that the nonlinearity is dispersive (i.e., depends on the order of the mode) or is dependent on the type of strain involved (e.g., shear or compressional components). It is important to stress that the nonclassical nonlinearity should be handled by a local parameter appropriately integrated within the elasticity equations.

Numerical simulations using a single scalar parameter α0 reproduce well the experimental observations, independently from the type of strain used or the mode order employed in the Lott, JASA 11 nonlinear analysis. There are some discrepancies between numerical simulation and experiments for some cases, but it does not seem to be consistent with the type of mode or a particular sample. Discrepancies are most likely due to the complexity of the experiment and the presence of a large transducer mounted at various positions on the sample to excite the various modes. Also, the sample do not have the perfect parallelepiped geometry used in the model. Even if the sample size was precisely measured using a caliper, parallelisms deviations are not accounted for in the simulations.

For the third mode, all the frequency shifts flatten a little bit at increasing amplitude (Fig. 3).

This behavior may be induced by some hidden resonant peaks which could appear at high amplitude. This can happen especially at "high" frequency when the resonance frequency density becomes high. Even if the location of the transducer was chosen so as to favor a given mode shape, other nearby resonances may alter these curves.

More importantly, the simulation results indicate that, in the case of concrete the nonlinear behavior of the material for both compressional and torsional motions is well captured by a single local scalar parameter. These results are in agreement with the fact that the distribution of defects in the thermally damaged concrete samples is isotropic. is also reported for comparison.

V. Conclusion

A tensorial interpretation of the softening effects under dynamic stress was integrated in a numerical scheme using a single scalar parameter. The key feature of the model relies on locally applying a softening law to the elastic tensor in the eigenbasis of the strain field and transforming this tensor back to the geometrical basis once the softening has been applied.

Numerical simulation results were compared to nonlinear multi-modal resonance experiments on thermally damaged concrete samples. In these samples, it was well adapted to predicting nonlinear behavior of their complex mode shapes involving coupling between shear and compressional components. This is in good agreement with the fact that an isotropic distribution of defects is expected in these materials.

It also shown that without accounting for these issues, the derived apparent nonlinear parameter can lead to erroneous interpretations. In this study, one could conclude to frequency dispersion Lott, JASA 14 or strain type dependences of nonlinearity. However, none of these statements are supported by the appropriate description of nonlinearity in the elasticity equations.

Future improvements of the model will aim at accounting for textured type of microcracking using the more general framework of a vectorial nonlinear parameter. Indeed, experimental data reported in the literature (Remillieux et al. 2016;[START_REF] Lott | Nonlinear elasticity in rocks: A comprehensive three-dimensional description[END_REF] show that many sedimentary rocks (e.g., Berea sandstone) exhibiting preferred oriented micro cracking features would require such a description. is also reported for comparison.

  FIG. 1. (Color online) Experimental (a) first, (b) second and (c) third NRUS curves for the 120°C damaged sample. Insets are the corresponding modal shapes.

  FIG. 3. (Color online) Experimental and numerically predicted resonances curves for the whole set of samples and modal shapes.

FIG. 1 .

 1 FIG. 1. (Color online) Experimental (a) first, (b) second and (c) third NRUS curves for the 120°C damaged sample. Insets are the corresponding modal shapes.

FIG. 4

 4 FIG. 4. (Color online) Experimental and numerically derived apparent nonlinear parameters. α0

Table . I

 . FIG. 2. Scheme of the numerical and experimental protocols. . Resonance frequencies obtained experimentally and numerically with linear RUS.

							Lott, JASA
	120°C 9.95 9.96 (+0.1%) 16.86 16.81 (-0.3%) 23.30 23.79 (+2.1%)
	250°C 9.43	9.53 (+1%) 15.97 14.739 (-7.7%) 22.31 22.30 (-0.1%)
			Resonance frequencies f0 (kHz)
	Sample		Mode 1		Mode 2		Mode 3
		Exp	Num	Exp	Num	Exp	Num
	Ref	10.16 10.09 (-0.7%) 17.33 17.36 (+0.2%) 24.02 24.43(+1.7%)
							10

Table .

 . Table. I. Resonance frequencies obtained experimentally and numerically with linear RUS. II. Values of the parameter α0 used in the NRUS simulations for the three concrete samples.

							Lott, JASA
	TABLES FIGURE CAPTION
			Resonance frequencies f0 (kHz)
	Sample		Mode 1		Mode 2		Mode 3
		Exp	Num	Exp	Num	Exp	Num
	Ref	10.16 10.09 (-0.7%) 17.33 17.36 (+0.2%) 24.02 24.43(+1.7%)
	120°C 9.95 9.96 (+0.1%) 16.86 16.81 (-0.3%) 23.30 23.79 (+2.1%)
	250°C 9.43	9.53 (+1%) 15.97 14.739 (-7.7%) 22.31 22.30 (-0.1%)
				Sample	α0
				Reference 300
				120°C	520
				250°C	1000

Acknowledgments

This work was supported by the French National Research Agency through the ENDE program (Grant No. ANR-11 RSNR 0009) and the U.S. Department of Energy through the Fossil Energy program (Grant No. FE-634-15-FY15).


Xi Liu
email: xi.liu@sb-roscoff.fr

Béatrice Loriod
email: beatrice.loriod@inserm.fr

Stefano Caffarri
email: stefano.caffarri@univ-amu.fr

Erwan Corre
email: erwan.corre@sb-roscoff.fr

Jean-Philippe Mevy

Trans-C

The Transcriptome of downy oak (Quercus pubescens Willd.) in Response to Climate Change

Keywords: RNA-seq, Genome-guided de novo transcriptome assembly, Gene expression, Oak, Global change, Cross-cutting approach, Photosynthesis, Metabolomics

Assembly Preprocessing

Trimmomatic [START_REF] Bolger | Trimmomatic: A flexible trimmer for Illumina Sequence Data[END_REF] : adapter removing, quality trimming and filtering % of paired reads surviving vary from 89% to 93%, with no notable difference between the samples: 1.7Md pair reads pass the cleaning

In silico reads normalization

Trinity [START_REF] Grabherr | Full-length transcriptome assembly from RNA-Seq data without a reference genome[END_REF] : normalization by set then global normalization • %selection by read set vary from 16% to 26% (360M pair reads in total), e.g. reads selected after normalization in summer samples > spring samples  summer samples display higher transcriptomic diversity • 86M paired reads after final step of global normalization comparison of different assembly metrics. Reads were assembled in FR orientation, K-mer was set or estimated at 25. BinPacker was used by activating option -d. HiSta2 [START_REF] Sirén | Indexing graphs for path queries with applications in genome research[END_REF] and Samtools [START_REF] Li | Genome Project Data Processing Subgroup (2009) The Sequence alignment/map (SAM) format and SAMtools[END_REF] were used in upstream for Trinity genome-guided de novo assembly. 155986 sequences in Trinity genome-guided assembly possesses the TPM value superior to 1 cross all the samples.

De novo assemblies

• Trinity de novo should have generated more than 124070 sequences • BinPacker generated longer sequences and assembled more residues than the other assembler tested • Trinity genome-guided using genome from close species Q. robur assembled an higher number of transcripts than other assemblers

Pseudo-mapping reads back to the assemblies Figure 1 | Comparison of pseudoalignment rate between different assemblies. Kallisto [START_REF] Bray | Near-optimal probabilistic RNA-seq quantification[END_REF] analysis with FR strand-specific paired-end pseudoalignment option. We also mapped reads back to a public reference transcriptome, but the pseudo-mapping rate was just around 40%. Trinity genome-guided de novo assembly displays the best pseudoalignment rate compare to the other de novo assemblers for the diploidic species assembly.

Trinity genome-guided de novo assembly evaluation

Contig Ex90N50 Statistic : Ex90N50 is 1544bp and corresponds to 34572 transcripts BUSCO [START_REF] Simão | BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs[END_REF] : C:87 The thresholds of statistical tests were fixed at Padj<1e -3 and log 2 FC≥2. 5724 and 4153 DEG were detected by DESeq2 [START_REF] Love | Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2[END_REF] and edgeR [START_REF] Robinson | edgeR: a Bioconductor package for differential expression analysis of digital gene expression data[END_REF] respectively (detail shown in black and grey). Abbreviations of the conditions: e and p for summer and spring, C and E for control and water stress. Vennerable [START_REF] Swinton | Venn diagrams in R with the Vennerable package[END_REF] .

Differential analysis

Genetic expression in response to the aridification varies with the season, according to edgeR results, 4 transcripts from 42 were expressed independently to the season.

Plasticity of photosynthetic machinery: light reactions

Conclusion and Perspective

This project has identified genetic, biochemical, chemical and physiological markers of plant adaptation to climate change in a cross-cutting approach. It has been carried out around several disciplinary fields: Genomics, Biochemistry, Ecophysiology, Chemistry, Bioinformatics and Modeling, opening perspectives for more ambitious projects. The water deficit significantly activates the galactose metabolism pathway

Enrichment of the metabolic pathway

Targeted Metabolomics: Differential Analysis

  summer -spring) x 2 treatments (water stress -control) x 10 trees Sequencing Illumina Next-Seq 500: 150 bp paired-end x 40 libraries (≈50M reads/sample)

Figure 2 |

 2 Figure 2 | Venn diagram of edgeR results. Venn diagram were realized with R packagesVennerable[START_REF] Swinton | Venn diagrams in R with the Vennerable package[END_REF] .

5 .Figure 3 |

 53 Figure 3 | Enrichment analysis based on GO functional categories for transcripts that were significantly at p-value<0.01 (a) up-regulated and (b) down-regulated in response to Q. pubescens drought treatment during summer.

Figure 4 |

 4 Figure 4 | Chlorophyll fluorescence parameter measurements during summer: Kinetics of Photosystem II quantum yield (a), photochemical quenching (b) and Non-photochemical quenching coefficients (c).

Figure 5 |Figure 6 | 8 .

 568 Photosynthetic pigments

Figure 7

 7 Figure 7 | Metabolite markers pathway enrichment analysis and pathway impact values from the pathway topology analysis.

Table

Table 2 | Differentially expressed genes (DEG) in response to the aridification.

 2

Table 3 |

 3 Metabolite markers in response to drought throughout the seasons: Exclusion (E)versus Control (C) and spring versus summer.

Pyroglutamic acid identified as a metabolic marker of drought. Sugars as Xylulose and Sorbitol are seasonal metabolite markers