Evaluation of risk factors for retinal damage due to chloroquine and hydroxychloroquine

Background/ Aims: To evaluate risk factors for retinal damage due to the intake of chloroquine and hydroxychloroquine. Methods: In a retrospective chart review, patients receiving or having received one of the drugs were classified as affected by maculopathy or retinopathy or as not affected on the basis of the documented findings. Uncertain cases were excluded. The risk factors as postulated by the American Academy of Ophthalmology (AAO) and additional factors like diagnosis of underlying disease, total dose, nicotine abuse and the sum of the AAO risk factors were compared between both groups. Results: 51 patients with a history of or ongoing treatment with chloroquine (23 individuals) or hydroxychloroquine (28 individuals) were included. Most of the postulated risk factors were expectedly elevated in the affected group. Significant differences applied to age, duration of intake and the sum of AAO risk factors. Surprisingly, positive smoking history was more frequent in the not affected. The toxic threshold of the daily chloroquine dose was exceeded by most of the patients. Conclusions: Age and the duration of intake are major risk factors. Smoking seems to be negligible. The sum of AAO risk factors can give an estimation of the individual risk profile. Individual and weight-adapted dosing is especially essential for chloroquine.

Introduction

Chloroquine and hydroxychloroquine are effective and safe drugs for the treatment of autoimmune diseases. Nevertheless, they bear the risk of irreversibly damaging the retina. The incidence of chloroquine maculopathy supposedly lies between 1 and 6 %, of hydroxychloroquine maculopathy below 1 %. [START_REF] Yam | Ocular toxicity of hydroxychloroquine[END_REF] According to a report by the American Academy of Ophthalmology (AAO) the following risk factors are assumed to play key roles in the development of the disease: [START_REF] Marmor | Recommendations on screening for chloroquine and hydroxychloroquine retinopathy: a report by the American Academy of Ophthalmology[END_REF] • High daily dosage per kilogram body weight (>6.5 mg/kg of hydroxychloroquine and >3 mg/kg of chloroquine) • Long duration of intake (> 5 years)

• High body fat level • Liver or kidney disease • Concomitant retinal disease • Age >60 years Ophtalmologic screening intervals should be based on the risk profile. Currently, annual examinations are recommended for any patient who fulfills at least one of the above mentioned criteria. Screening intervals of low risk patients depend on their age and range from once in ten years to annually. However, there are cases of retinal damage even in low risk patients. On the other hand some high-risk patients are completely unaffected. [START_REF] Johnson | Hydroxychloroquine therapy in massive total doses without retinal toxicity[END_REF] Furthermore, a recently published case from our department confirmed the variability of the retinotoxic cumulative dosage. [START_REF] Ruther | Chloroquine/hydroxychloroquine: variability of retinotoxic cumulative doses[END_REF] In this retrospective study we reevaluate assumed major risk factors in a patient sample of our department.

Methods

We reviewed the files of all patients who presented at our department between 2002 and 2008 for evaluation of retinal damage due to chloroquine or hydroxychloroquine. Examinations were performed by the authors RK and SJ. Basically, the individuals were classified as affected or not affected according to the documented examinations and a classification scheme: Affected:

•

Results

51 patients were included in the analysis. Due to uncertain diagnosis in spite of thourough examinations 9 patients with a history of hydroxychloroquine intake were excluded. Three patients were excluded due to the intake of both drugs which conflicted with the analysis in our setting. Finally, of the 28 patients taking hydroxychloroquine only 2 were affected by maculopathy while of the 23 chloroquine patients 16 had the disease.

In 31 (61 %) of 51 patients information on all above mentioned parameters could be acquired. In 20 patients information was incomplete. Nevertheless, information on age, sex, diagnosis, duration of intake, total dosage and daily dosage was complete in all included patients. A summary of the results can be seen in the Table.

SUBSAMPLE ALL PATIENTS ALL PATIENTS CHLOROQUINE BOTH DRUGS AFFECTED NOT AFF. AFFECTED NOT AFF.

[%] [%] [%] [%] [%]

# ). This significant difference also applied to the chloroquine subgroup (p=0.033, Figure 1) A Pearson analysis yielded no correlation between age and duration of intake or total dose respectively. This applied both to the entire sample (p=0.063 and 0.604) as well as to the chloroquine subgroup (p=0.288 and 0.657).

Diagnosis (underlying disease)

The affected group suffered more frequently from rheumatoid arthritis compared to lupus erythematosus than the not affected group.

Body weight and BMI

Concerning the entire group median BMI was equal between affected and not affected patients and median body weight was even higher in the not affected patients. In the chloroquine subgroup both body weight and BMI of the not affected were lower than of the affected. The two parameters did not exhibit significant differences between groups, neither in the complete sample (p=0.866 and 0.646 respectively) nor in the chloroquine subgroup (p=0.145 and 0.142 respectively).

Duration of intake

Affected patients took the medication significantly longer than the not affected patients (8 [1.5 to 38] years vs. 3 [0.08 to 13.5] years, p=0.002, Figure 2). This applied only to the complete sample and not to the chloroquine subgroup (6.33 [1.5 to 38] years vs. 5.5 [3 to 13.5] years, p=0.421).

As could be expected, the Pearson analysis exhibited a highly significant correlation between total dose and duration of intake for the entire sample (p<0.001) as well as for the chloroquine subgroup (p=0.001).

Smoking

There were more patients with a history of or ongoing nicotine abuse in the not affected group (Figure 3). Differences were not statistically significant (p=0.167 [entire group] and 0.877 [chloroquine subgroup]).

Liver and renal disease

There were higher proportions of patients with a history of or present liver or kidney disease in the affected group (Figure 3). The differences did not reach a significant first sign of retinal damage overdiagnosis impends with the risk of discontinuating a drug that is safely and effectively controlling the underlying disease. [START_REF] Levy | Incidence of hydroxychloroquine retinopathy in 1,207 patients in a large multicenter outpatient practice[END_REF] While all chloroquine patients could be included in this analysis 9 hydroxychloroquine patients had to be excluded whose borderline findings made an unequivocal classification impossible. Despite thorough and repeated examination and the above mentioned classification scheme a secure diagnosis of maculopathy was possible in only 2 of originally 37 hydroxychloroquine patients. Some of the excluded patients had maculopathy that was impossible to discern from ARM. Others had isolated mfERG changes without any further sign of retinal damage. This confirms the concern of Marmor: While the mfERG basically allows earlier diagnosis of functional retinal alterations care has to be taken to not exclusively rely on the mfERG. [START_REF] Marmor | The dilemma of hydroxychloroquine screening: new information from the multifocal ERG[END_REF] Isolated mfERG changes occuring under therapy with either drug may be reversible and not necessarily imply maculopathy. [START_REF] Lai | Multifocal electroretinographic changes in patients receiving hydroxychloroquine therapy[END_REF] Maybe the additional employment of fundus autofluorescence imaging or high resolution optical coherence tomography could have enabled a definite diagnosis in some of the excluded patients but we did not dispose of either device. [START_REF] Kellner | Fundus autofluorescence and mfERG for early detection of retinal alterations in patients using chloroquine/hydroxychloroquine[END_REF][START_REF] Kellner | Spectral domain optical coherence tomography detects early stages of chloroquine retinopathy similar to multifocal electroretinography, fundus autofluorescence and near-infrared autofluorescence[END_REF][START_REF] Pasadhika | Effects of chronic exposure to hydroxychloroquine or chloroquine on inner retinal structures[END_REF]

Sex

The fact that no male patient suffered from toxic retinal damage owes to the epidemiology of autoimmune diseases which predominantly affect women and consequently to the sex distribution in our sample. We cannot conclude if female sex is a risk factor for retinal damage due to (hydroxy-) chloroquine.

Age

Affected patients were significantly older than not affected patients. The Pearson analysis ruled out a relation between age and duration of intake or total dose so that advanced age itself can be regarded as an independent risk factor for developing toxic retinal damage.

Diagnosis of underlying disease

The ratio of rheumatoid arthritis to lupus erythematosus was higher in the affected patients. We could not confirm earlier reports that allocated a higher risk of retinal damage to lupus patients. [START_REF] Voipio | Incidence of chloroquine retinopathy[END_REF]

Body weight and BMI

No significant difference applied to either parameter. Only in the chloroquine subgroup body weight and BMI of the affected individuals expectedly lay above the not affected individuals. In clinical practice of course only BMI should be considered as it reflects the relation of body weight to body height.

Duration of intake

Statistical analysis proved that the duration of drug intake is a relevant risk factor. Pearson analysis especially showed that in spite of a high correlation between duration of intake and total dosage, the former can be regarded as an independent risk factor.

Smoking, liver and renal disease

It would not primarily be expected that nicotine abuse was more frequent in the not affected individuals especially when epidemiological studies on ARM proved smoking as an independent risk factor. [START_REF] Swaroop | Unraveling a Multifactorial Late-Onset Disease: From Genetic Susceptibility to Disease Mechanisms for Age-Related Macular Degeneration[END_REF][START_REF]Risk factors associated with age-related macular degeneration. A case-control study in the age-related eye disease study: Age-Related Eye Disease Study Report Number 3[END_REF][START_REF] Vingerling | Age-related macular degeneration and smoking. The Rotterdam Study[END_REF] Analysis of larger patient groups are necessary to clarify this issue. As expected, affected patients suffered more frequently from liver and renal diseases. Although the differences lacked statistical significance both factors should be taken into account when deciding on screening intervals.

Sum of AAO risk factors

The combination of AAO risk factors gives an estimate of the individual risk profile even though we disregarded accompanying retinal diseases. For exact discrimination between affected and not affected individuals, patients showing signs of retinal disease that was not clearly of toxic origin were excluded from the analysis. Nevertheless this important factor should be considered in clinical practice. The cut off for "high body fat level" was set at a BMI of 25 as it marks the limit of normal weight. Only 3 patients had a BMI above 30 (obesity), two being not affected hydroxychloroquine patients and one being an affected chloroquine patient.

Only two individuals exhibited no risk factor at all, both taking hydroxychloroquine. According to the AAO, this would mean annual examinations for the vast majority of our patients.

Dose-related parameters

Total dose

Affected patients had taken a insignificantly higher total dose of chloroquine as well as a higher total dose in relation to ideal weight than not affected patients. In most publications total dose is not assumed to be a relevant risk factor. [START_REF] Ruther | Chloroquine/hydroxychloroquine: variability of retinotoxic cumulative doses[END_REF][START_REF] Araiza-Casillas | Factors associated with chloroquine-induced retinopathy in rheumatic diseases[END_REF][START_REF] Rynes | Ophthalmologic safety of long-term hydroxychloroquine treatment[END_REF][START_REF] Tobin | Hydroxychloroquine. Seven-year experience[END_REF] Nevertheless, our analysis suggests to be aware of the cumulative dose when following up for retinal toxicity. [START_REF] Bernstein | Ophthalmologic considerations and testing in patients receiving long-term antimalarial therapy[END_REF]

Daily dose

It is striking that the majority of our chloroquine patients -affected as well as not affected -took daily doses above the risk threshold. Few practicioners seem to be aware of this threshold when prescribing the drug. On the other hand the clinical relevance of this strict threshold recommendation is challenged as most of the not affected patients also took doses above the cut off. In case of hydroxychloroquine, few patients exceeded the risk threshold and none of them suffered from maculopathy.

Our dosage findings confirm that the relation to ideal weight is essential. But even then the definition of a realistic and relevant threshold remains difficult.

Sources of imprecision

The following factors may be sources of imprecision:

• The relatively small sample size, especially the low number of affected patients in the hydroxychloroquine group.

• The fraction of patients with incomplete data.

• Having been collected retrospectively, relevant data -especially body weight and dosage -is prone to recall bias. • Smoking habits and accompanying renal or liver diseases are difficult to quantify. The retrospective nature of this study limited the differentiation on never vs. ever and present vs. absent. • Regarding daily dosage, we accounted for the highest dosage ever taken over a period instead of calculating the mean daily dose. By doing so we might have overemphasized short periods of high daily doses over long periods with lower dosing. • Referral bias: Most patients of our department were referred by ophthalmologists who previously suspected retinal damage. This especially leads to distortion of incidence data.

Conclusion

As expected, most of the analysed risk factors -with exception of smoking, daily dose and daily dose per body weight -were elevated in the affected individuals. Age and duration of intake can be regarded as major risk factors. The toxic threshold for daily chloroquine dose was exceeded by most patients emphasizing the need of individual weight-adjusted dosing. We could not confirm that lupus patients are at higher risk of developing maculopathy. Smoking history is probably negligible. The combination of risk-factors as postulated by the AAO turned out to be a good estimation of the individual risk profile.

According to the AAO, the existence even of a single risk factor implies annual examinations. Only two of our patients exhibited no risk factor at all and we suppose that a similar relation applies to the entirety of chloroquine and hydroxychloroquine patients. Furthermore, while we could confirm the importance of most risk factors, there also are affected patients with low risk profiles (Figure 4) and especially short duration of use (Figure 2). Bearing in mind that early stage maculopathy may develop unperceived by the patient, only annual screening for all patients from the very beginning of therapy ensures a timely diagnosis of toxic retinal damage.

The question remains if there are relevant risk factors that have been missed so far. The focus of attention already turned on genetics: Missense mutations of the ABCA4 gene were reported to be more frequent in patients than in controls. [START_REF] Shroyer | Analysis of the ABCR (ABCA4) gene in 4aminoquinoline retinopathy: is retinal toxicity by chloroquine and hydroxychloroquine related to Stargardt disease?[END_REF] Further research will show if other genes play substantial roles in toxic retinal damage.

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FiguresFigure 1 :

 1 Figures

Figure 5 :

 5 Figure 5: Boxplots showing the comparison of total dose per body weight and total dose per ideal weight between affected and not affected chloroquine patients. Dosage of affected patients lay above the not affected patients only when related to ideal weight.

  In case of an equivocal mfERG: fulfilment of at least two of the remaining criteria.Unequivocal paracentral amplitude decrease in the multifocal ERG was a necessary criterion for classification as affected. Only in case of an equivocal mfERG fulfilment of at least two of the remaining criteria was sufficient for classification as affected.

	• Uncertain cases were excluded from the study. All other patients were classified as
	not affected.
	If a patient presented more than once in our department the data of the first visit that
	enabled a definite diagnosis was considered.
	Patients were inquired about dosage, weight, body height, smoking habits and renal
	or hepatic diseases.
	The following parameters were compared:
	• Age
	• Sex
	• Diagnosis of underlying disease
	• Body weight
	• Body mass index (= body weight [kg] / (body height [m]) 2 )
	• Daily dosage..
	o ..per body weight
	o ..per ideal body weight (according to Broca)
	ideal weight for women [kg] = (body height [cm] -1) *0.85
	ideal weight for men [kg] = (body height [m] -1)*0.9
	• Duration of intake
	• Total dosage..
	o ..per body weight
	o ..per ideal body weight (according to Broca)
	• Nicotine abuse (ever vs. never)
	• History of or ongoing reduction of excretory renal or liver function (present vs.
	absent)
	• Sum of risk factors according to AAO (see introduction for list) with exception
	of accompanying retinal disease
	The sum of risk factors according to AAO (see introduction for list, one point for
	fulfilment of each risk factor) was calculated for all patients on which information
	Fulfilment of the following criterion: concerning the required parameters was available. High body fat level was defined as a BMI>25 kg/m 2 . Accompanying retinal disease was discarded as patients with o Reproducible bilateral paracentral amplitude decrease in the multifocal signs of retinal damage that was not definitely toxic were excluded from the analysis electroretinogram (mfERG) and exclusion of other causes like age to ensure unequivocal diagnosis. related macular degeneration (ARM) With exception of all dose related parameters analysis was conducted twice: 1.
	including all patients and 2. including only the chloroquine patients. Dose-related • PLUS fulfilment of at least one of the following criteria: parameters were only compared in the chloroquine group. A separate analysis of o Reduced best corrected visual acuity (only if all other possible causes hydroxychloroquine patients was not performed due to the small number of affected were ruled out) patients in this group. o Typical fundus morphology (bull´s eye maculopathy or peripheral The Mann-Whitney U-test was used for statistical comparison. P-values below 0.05 retinochoroidal atrophy) o Reproducible central or paracentral scotoma in the automated were regarded as statistically significant.
	threshold perimetry

Table :

 : Summary of resultsSex5 males and 46 females were included in the study. No male was affected by the disease.

	PATIENTS		51		18 35.3	33 64.7	16 31.4	13.7
	DRUG	# Hydroxychl. intake	28	54.9	2 11.1	26 78.8
	Age	# Chloroquine intake	23	45.1	16 88.9	7 21.2	16 100.0	100.0
	AFFECTED yes/no Median age of all patients was 53.57 (17.64 to 84.23) years. Median age of affected # Affected 18 35.3 18 100.0 16 100.0 # Not affected 33 64.7 33 100.0 AGE Median Age [y] 53.6 61.3 48.5 61.7 patients was 61.25 (38.85 to 77.87) years and of not affected patients 48.5 (17.64 to 39.3 # Age > 60 21 41.2 12 66.7 9 27.3 12 75.0 84.23) years. Age difference was statistically significant (p=0.018	100.0 28.6
	SEX	# males	5	9.8	0	0.0	5 15.2	0	0.0	14.3
		# females	46	90.2	18 100.0	28 84.8	16 100.0	85.7
	BODY WEIGHT	Median body weight [kg]	66.0		65.0		69.0		65.0	54.8
		# Body weight unknown	18	35.3	7 38.9	11 33.3	7 43.8	14.3
	BMI	Median BMI [kg/m2]	23.9		23.9		23.9		23.9	18.7
		# BMI unknown	19	37.3	8 44.4	11 33.3	8 50.0	14.3
		# BMI>25	10	19.6	1	5.6	9 27.3	1	6.3	14.3
	DIAGNOSIS	# Rheumatoid Arthritis	18	35.3	9 50.0	9 27.3	9 56.3	0.0
		# Lupus	14	27.5	4 22.2	10 30.3	3 18.8	42.9
		# other	19	37.3	5 27.8	14 42.4	4 25.0	57.1
	DURATION OF USE	Median duration of use [y]	4.0		8.0		3.0		10.0	5.5
		# Duration of use > 5 years	23	45.1	13 72.2	10 30.3	11 68.8	42.9
	DAILY DOSAGE	Median daily dosage [mg]							250.0	250.0
	DOSE/ BODY WEIGHT Median daily dose/ body weight [mg/kg]							3.79	4.85
		# Daily dosage > toxic threshold	14	27.5	7 38.9	7 21.2	7 43.8	71.4
		# Unknown	19	37.3	7 38.9	12 36.4	7 43.8	28.6
	DOSE/ IDEAL WEIGHT Median daily dose/ ideal weight [mg/kg]							4.5	4.2
		# Dose per ideal weight > threshold	17	33.3	7 38.9	10 30.3	7 43.8	71.4
		# Unknown	20	39.2	8 44.4	12 36.4	8 50.0	28.6
	TOTAL DOSE	Median total dose [g]							604.5	548.0
	SMOKING	# Smoking y	21	41.2	6 33.3	15 45.5	5 31.3	42.9
		# Smoking n	9	17.6	5 27.8	4 12.1	4 25.0	28.6
		# Unknown	21	41.2	7 38.9	14 42.4	7 43.8	28.6
	LIVER DISEASE	# Liver disease y	7	13.7	4 22.2	3	9.1	3 18.8	28.6
		# Liver disease n	23	45.1	7 38.9	16 48.5	6 37.5	42.9
		# Unknown	21	41.2	7 38.9	14 42.4	7 43.8	28.6
	RENAL DISEASE	# Renal disease y	5	9.8	3 16.7	2	6.1	1	6.3	0.0
		# Renal disease n	25	49.0	8 44.4	17 51.5	8 50.0	71.4
		# Unknown	21	41.2	7 38.9	14 42.4	7 43.8	28.6
	RISK FACTOR SUM	Mean Number of risk factors (AAO)	1.9		2.6		1.6		2.6	2.2

level neither in the entire sample nor in the chloroquine subgroup (p=0.207 and 0.81 for liver disease and p=0.244 and 0.456 for renal disease).

Sum of AAO risk factors

Affected patients had a significantly higher sum of risk-factors according to the AAO (Mean sum of risk factors=2.6 +/-0.97 vs. 1.58 +/-1.02, p=0.015, Figure 4). The significance did not apply to the chloroquine subgroup (2.63 +/-1.06 vs. 2.2 +/-1.3, p=0.497).

Dose-related parameters

Due to the differing toxicity and pill weight (250 and 200 mg) of chloroquine and hydroxychloroquine all dose-related parameters were only analysed in the chloroquine subgroup. No separate analysis of the hydroxychloroquine subgroup was done as it would be hampered by the small amount of affected individuals. The dose-related parameters showed no statistically significance in any case (Figure 5 and Figure 6). All parameters, except daily dose and daily dose per body weight were higher in the affected group.

• Total dose: 604. Of the affected chloroquine patients 43.7% took daily doses above the risk threshold of 3 mg/kg body weight, 12.5% lay below the threshold, subsumption of 43.8% was impossible due to missing body weight and height data.

Of the not affected chloroquine patients 71% were overdosed, non lay below the threshold while in 29% missing body dimensions precluded dose calculation. The data on daily dose per ideal weight was very much comparable.

Speaking of hydroxychloroquine: Two of our 28 patients recieved a daily dose above the risk level of 6.5 mg/kg/d and both patients were unaffected. Relating dosage to the ideal weight, 5 of 28 patients were above the cut off yet all of them being unaffected. The affected patients all received doses below the risk level.

Discussion

Problem of establishing a definite diagnosis

The first issue encountered in this analysis is the difficulty of establishing a definite diagnosis. Since the toxic effect of both drugs may outlast their cessation early diagnosis of maculopathy is essential. 5;6 On the other hand, when trying to catch the

Competing Interest

Competing Interest: None declared.


M A Rehman Siddiqui

Muhammad Amer Awan

Andrew Fairhead

Hatem Atta

Ultrasound velocity in heavy ocular tamponade agents and implications for biometry

Keywords: Biometry, Heavy Silicone Oil, Cataract Surgery

come

Ultrasound velocity in heavy ocular tamponade agents

and implications for biometry.

Introduction:

Heavy silicone oil is an important adjunct to treat complicated retinal detachments including rhegmetogenous retinal detachments with large inferior retinal breaks and proliferative vitreoretinopathy (PVR). [START_REF] Wong | A pilot study on the use of a perfluorohexyloctane/silicone oil solution as a heavier than water internal tamponade agent[END_REF] Cataract development or progression of already existing cataract is a known complication of conventional silicone oil and heavy silicone oil. [START_REF] Casswell | Silicone oil removal. I. The effect on the complications of silicone oil[END_REF][START_REF] Li | Clinical complications of Densiron 68 intraocular tamponade for complicated retinal detachment[END_REF] In case of accelerated cataract formation during the oil tamponade period a combined oil removal and lens extraction followed by the implantation of an intraocular lens (IOL) is desirable. Therefore, a precise biometry is required for IOL power calculation even in oil filled eyes, especially if the original vitreo-retinal disorder did not allow for accurate biometry prior to the tamponade use.

Ultrasound (US) biometry can be performed in silicone oil-filled eyes but the speed of sound is slower hence the axial length (AL) appears longer in silicone oil filled compared to vitreous filled eyes. This issue can be addressed by employing a conversion factor (CF) to ascertain the true AL of an eye. [START_REF] Murray | Biometry of the silicone oil-filled eye[END_REF] As far as we know there are no studies looking at the speed of sound in the heavy ocular tamponade agents.

The primary aim of our study was to evaluate velocity of US in heavier ocular tamponade agents. We also aimed to estimate CF for these agents and to determine the potential impact of using CF for conventional silicone oil (SO) 1000 cSt on postoperative refraction.

Methods:

We included five tamponade agents; silicone oil (SO) 1000 cSt , SO 5000 cSt (Medicel AG, Widnau, Switzerland), Oxane HD (Bausch & Lomb, Toulouse, France), Densiron 68 (Fluoron Co, Neu-Ulm, Germany)and F-Decalin (Fluoron Co, Neu-Ulm, Germany) and measured speed of sound in these materials in vitro. An US transducer (Panametrics model 5052PR; centre-frequency 5MHz) was used to measure the speed (Figure 1). Although a higher frequency than 5MHz is used for biometry, ultrasound velocity is regarded as being non-dispersive in most media, so these measurements should not be affected by frequency. Time of flight (T 1 ) was measured between the transducer and bottom of the container and remeasured (T 2 ) after reducing the separation by 1 cm. The speed of sound in the particular material was calculated from the difference between T 2 and T 1 . All measurements were repeated over a temperature range of 18-42°C. The system was validated for water. The speed of sound in water was measured as 1487±10 m/s at 22 o C and 1482.8 ±10 m/s at 20 o C, whereas the true values are 1488 and 1482 respectively. We calculated CF of tamponade agent using this formula: Conversion factor (CF) = Speed of sound in tamponade agent/ Speed of sound in vitreous humour Where speed of sound in vitreous humour = 1532 m/s [START_REF] Hoffer | Ultrasound velocities for axial eye length measurement[END_REF] We also calculated deviation from intended refraction if the standard CF for SO 1000 cSt was used in biometry for IOL power estimations.

Results:

The speed of sound ranged from 645±8 m/s to 976±10 m/s depending on the tamponade agent. However in case of heavy ocular tamponade agents there were significant differences in the speed. In Densiron 68 and F-Decalin, the speed of sound was markedly reduced to 914±10 m/s and 645±8 m/s respectively (Table 1). The temperature dependence of speed of sound varied between -2.2 and -3.6 m/s/°C depending on the particular oil (Figure 2). With 95% confidence, the true speed is believed to lie within ± 5m/s of these values. The CF was calculated for these agents that ranged from 0.421 to 0.637 (Table 1). The deviation from intended refraction was between 0.38 to 30.15 dioptres depending on the tamponade agent by using CF for SO 1000cs (Table 2).

Discussion:

Heavy ocular tamponade agents differ significantly in their ability to make contact with the inner surface of the vitreous cavity, which is determined by their specific gravity and interfacial tensions, and their viscosity and is critical to maintain the integrity of the tamponade over a longer period of time. [START_REF] Wetterqvist | Tamponade efficiency of perfluorohexyloctane and silicone oil solutions in a model eye chamber[END_REF] In recent years, a marked decrease in the complication rate and an improvement in the anatomical and functional outcomes could be achieved with the introduction of new heavy tamponades, in particular new heavy silicone oils. [START_REF] Heimann | Heavy tamponade 1: a review of indications, use, and complications[END_REF] Measurement of AL can be challenging in eyes filled with heavy tamponade agents. There are different techniques that can be utilised to measure AL in the eyes filled with heavy tamponade agents. Recently Roessler et al have shown accuracy and reproducibility of AL measurement in the eyes filled with conventional silicone oil and heavy silicone oil by using partial coherence laser interferometry (PCI). [START_REF] Roessler | Accuracy and reproducibilty of axial length measurement in eyes with silicone oil endotemponade[END_REF] In few studies reliable AL measurements in silicone oil-filled eyes or incomplete silicone oil-filled eyes were determined by using magnetic resonance imaging and x-ray computed tomography. [START_REF] Takei | Measurement of axial length of eyes with incomplete filling of silicone oil in the vitreous cavity using x ray computed tomography[END_REF]10 Although PCI can give reliable and accurate biometry estimations in normal eyes, it has limitations in patients with dense cataracts, corneal scarring and emulsified oil. [START_REF] Dietlein | Signal quality of biometry in silicone oil-filled eyes using partial coherence laser interferometry[END_REF] Other option is intraoperative biometry by A-scan US, following removal of heavy silicone oil. This method has shown comparable postoperative refractive results to PCI for eyes filled with silicone oil. [START_REF] El-Baha | Comparison of refractive outcome using intraoperative biometry and partial coherence interferometry in silicone oil-filled eyes[END_REF] Issues about sterilization of the biometry machine and prolongation of the operative procedure are likely to limit its benefits.

Preoperative US biometry can achieve accurate IOL power calculations in cases of heavy ocular tamponade agents if the velocity of US beam in these agents is known. A CF can then be calculated and inserted in the formula. Our study shows a significant reduction in speed of sound in heavy tamponade agents that can lead to an error in predicted AL from 1.16 mm to 12.06 mm (if a CF of standard SO 1000 cSt is used).

In terms of refractive outcomes, the predicted refraction can vary between 2.9 D and 30.15 D with same CF depending on the tamponade agents. Murray et al have demonstrated accurate prediction of required IOL power with US biometry by using CF of 0.71 for conventional SO 1300 cSt and their mean difference in actual and predictive refractive target was 0.74 to 1.31 D depending on placement of IOL. [START_REF] Murray | Biometry of the silicone oil-filled eye: II[END_REF] By using the CF values for the specific tamponade agents we can avoid refractive surprises. Our study findings are derived from an in vitro model and further studies are required to test the accuracy of these CF values in clinical practice.

It is important to take into account the variability in velocity of US in different tamponade agents when performing biometry. US machines should be adjusted for various heavy ocular tamponade agents when calculating IOL power.

Table 1 : It shows speed of ultrasound in different ocular tamponade agents and their conversion factors. Type of silicone oil Speed (m/s) at 37°C Conversion factor

 1

	SO 1000	976±10	0.637
	SO 5000	970±10	0.633
	Oxane HD	930±10	0.607
	Densiron 68	914±10	0.597
	F-Decalin	645±10	0.421

Table 2 : It illustrates axial length (AL) measurements of various ocular tamponade agents and impact of using conversion factor for SO1000 on AL and refraction if we assume theoretical AL of 23.5mm.

 2

	Oil	AL measurements (mm)		Error (***)
		AL SO (**)	Adjusted with	AL (mm)	Refraction (D)
			CF SO1000
	SO 1000	36.89	23.5	0.00	0.00
	SO 5000	37.12	23.65	0.15	0.38
	Oxane HD	38.71	24.66	1.16	2.9
	Densiron 68	39.36	25.07	1.57	3.93
	F-Decalin	55.82	35.56	12.06	30.15

(**) Calculated AL of tamponade filled eye when no CF was used.

(***) Errors in true AL measurements and desired refraction if CFSO1000 was used for other tamponade agents.

Legends:


Ph. D Suzelle F Barrington
email: suzelle.barrington@mcgill.ca

M. Sc.; Bijaya Adhiraki

Ph. D José Martinez

Susan King

Bijaya K Adhikari

Effectiveness of three bulking agents for food waste composting

Keywords: Food waste, bulking agents, composting formula, temperature, C and N losses Food waste, bulking agents, composting formula, temperature, C and N 37

Rather than landfilling, composting the organic fraction of municipal solid wastes (MSW) recycles the waste as a safe and nutrient enriched soil amendment, reduces emissions of greenhouse gases and generates less leachate. The objective of this project was to investigate the composting effectiveness of three bulking agents, namely chopped wheat (Triticum) straw, chopped mature hay consisting of 80 % timothy (milium) and 20 % clover (triphullum) and pine (pinus) wood shaving. These bulking agents were each mixed in duplicates at three different ratios with FW and composted for 10 days using prototype invessel composters to observe their temperature and pH trends. Then, each mixture was matured in vertical barrels for 56 days to measure their mass loss and final nutrient content and to visually evaluate their level of decomposition. Chopped wheat straw (CWS) and chopped hay (CH) were the only two formulas which reached thermophilic temperatures during the 10 days of active composting when mixed with FW at a wet mass ratio of 8.9 and 8.6:1(FW:CWS and FW:CH), respectively. After 56 days of maturation, these two formulas were well decomposed with no or very few recognizable substrate particles, and offered a final TN exceeding the original. Wood shavings (WS) produced the least decomposed compost at maturation, with wood particles still visible in the final product, and with TN lower than the initial. Nevertheless, all BA produced compost with an organic matter, TN, TP and TK content suitable for use as soil amendment.

Introduction

39

For urban centres and rather than landfilling, in-vessel composting is a popular 40 method of recycling the food waste (FW) portion of municipal solid waste (USEPA, 41 2000). Composting is a biological process which reduces the volume and mass of solid 42 organic wastes, while producing a safe, stabilized and nutrient enriched soil amendment 43 (Pace et al., 1995;Haug, 1980;[START_REF] Mato | Composting of <100 mm fraction of municipal 407 solid waste[END_REF]. When landfilled along with municipal 44 solid waste (MSW), the organic fraction is mostly responsible for the emission of three different mixing ratios, resulting in three different initial moisture contents. The 85 performance of each compost formula was evaluated from its ability to reach 86 thermophilic temperatures and to maintain a pH between 6 and 8 during the active 87 composting stage, to lose the most dry and wet mass during the maturation phase, to 88 decompose to the extent that no substrate particles are visible and, once matured, to offer 89 a final moisture content under 50% with an acceptable level of nutrients (organic matter, 90 TN, TP and TK). Similar to the horizontal in-vessel system, six urban prototype composters were 95 used to test the compost formulas. These composters were built of double wall 96 polyethylene tubing measuring 1.0 m in length and 0.3 m in inside diameter (Fig. 1). The 97 tubing's corrugated exterior wall glued to a smooth inner wall produced an insulation 98 value of 1 m 2 °C/W. Measuring 25 mm in inside diameter and perforated at every 150 99 mm, a pipe was inserted horizontally at the bottom of each composter to provide an inlet 100 for cold air expected to flow by convection into the composting mixture and, once 101 warmed, to exit through a 25-mm diameter opening at the top end of the composter (Fig. For each BA, mixtures were formulated to obtain a moisture content ranging from 118 20% to 40% (Tables 2, 3 and4 [START_REF] Diaz | Composting and 396 Recycling, Municipal Solid Waste[END_REF]. For each formula tested, the 134 temperature was measured daily at the center of the compost pile, using a long-stem 135 thermometer (PTC Instruments, Los Angeles, California, USA, model 8500D-II). On 136 alternate days, five samples each weighing 5 g were randomly collected from each 137 composter for pH determination. The leachate produced during the process was not 138 measured and collected for analysis. After testing a BA, the composters were emptied, 139 cleaned and filled once more with the mixtures of another BA. 140 Once actively composted, the mixtures were emptied into individual cylindrical 141 plastic bins, measuring 360 mm in diameter and 300 mm in depth. These rested on 142 wooden blocks for drainage and natural aeration (Fig. 2). All formulas were matured in 143 these cylinders for 56 days, which corresponded to the recommended 2 months of 144 maturation [START_REF] Haug | The practical handbook of compost engineering[END_REF]. After maturation, each mixture was weighed, visually 145 examined for decomposition and substrate breakdown, and sampled to determine 146 moisture (MC), organic matter (OM), total Kjeldahl nitrogen (TKN), total phosphorus 147 (TP) and total potassium (TK). These parameters assessed the suitability of each compost 148 mixture for use as agricultural soil amendment [START_REF] Mato | Composting of <100 mm fraction of municipal 407 solid waste[END_REF]. 169

The pH was determined using a pH/Ion meter (Orion, Boston, Massachusetts, 170 USA, model 450) and a pH probe. All samples were soaked for 24 h without shaking at 171 5°C, in just enough distilled water to produce a solution in which to place the probe, 172 which corresponded to 20 and 50 ml for 10 g of FW and BA, respectively.

The free air space (FAS) was computed from the wet bulk density and wet 174 particle density of the BA and FW materials. The wet particle density was determined by 175 placing 5 g of material in a graduated cylinder and submerging with kerosene. After 176 initially verifying the density of kerosene (0.78 kg/L) and determining the mass of 177 kerosene added, the particle density was calculated (Barrington et al., 2002b). This wet 178 particle density was then used to compute the FAS of the compost components:

179

FAS (%) = 100 × (1 -(BD / PD) (3)
180
where BD is bulk density in (kg/L) and PD is the wet particle density determined using 181 kerosene (kg/L). The initial pH of all CWS mixtures was in the range of 6 to 6.5 (Fig. 6a), as a 244 result of the organic acids contained in the FW (Table 1). The pH of these mixtures had 245 all reached a value near 8.0 by day 7, as the microbial activity degraded the organic acids 246 [START_REF] Diaz | Composting and 396 Recycling, Municipal Solid Waste[END_REF] and as the nitrate added by the N amendment was denitrified and 247 added OH - [START_REF] Loehr | Pollution control for agriculture[END_REF]. Except for the 40% DM mixture which had already reached 248 alkaline conditions on day 2, there were no significant differences in pH values among 249 the mixtures (P<0.05). The 40% DM mixture (FW/BA ratio of 2:1) reached alkaline 250 conditions earlier than all other CWS mixtures because of its lower FW and therefore 251 faster depletion of organic acids, and; because of its higher amendment in nitrogen, 252 which led to more denitrification leading to alkaline conditions.

253

Compared to CWS, CH formulas exhibited a slightly lower pH because of its 254 slightly acidic nature (Table 1). During the trial, the pH of all mixtures was not 255 significantly different (P<0.05), starting near 6.0 and slowly climbing on day 7 to a value 256 near 7.0 (Fig. 6b). Compared to CWS, the CH mixtures were also amended with a 257 smaller mass of NH 4 NO 3 , leading to less denitrification.

258

With WS, the initial pH of all mixtures was low (near 5.5) because of the acidic 259 nature of the BA (Table 1). Only the 20% DM mixture (FW/WS ratio of 7.8:1) achieved 260 a significantly higher pH (Fig. 6c The mass reduction for the CH mixtures after 56 days of maturation was found to 300 be proportional to the initial MC, because, again, most of the mass reduction was 301 associated with the evaporation and leaching of moisture (Table 5). The 20% CH mixture 302 (FW/BA ratio of 8.6:1) lost 84% of its wet mass, including 0.67 kg of water per kg of 303 initial wet compost (Table 6). The CH mixture with 20% DM also lost 285 g of C/kg of 304 initial dry matter, an amount superior to that observed with CWS for the same initial DM.

305

The wet mass reduction obtained with the WS mixtures was relatively low, at 306 26% and 40%, for the 40% and 30% DM (FW/BA ratios of 1.5:1 and 2.9:1), respectively, Note: WW -wet weight basis; DM -dry weight basis; DW -dry weight basis; BD -bulk density under a pressure of 6 kPa; FAS -free air space under a pressure of 6 kPa; numbers in parenthesis is the volumetric ratio. Note: FW/BA -food waste to bulking agent ratio on a wet mass basis; MC -moisture content; OMmoisture content; BD -bulk density at a pressure of 6 kPa; DW -dry weight; the number in parenthesis is the % TKN(DW) of mixture before starting the composting process; * based on 1.0 kg of initial mixture on a wet mass basis; ** moisture lost per kg of dry matter lost; ***according to Tognetti et al. (2006).

WM-7-244 response

Response to reviewers' comments

Reviewer 1

The introduction was shortened and modified with more recent references more appropriate to the topic.

CWS was modified in the nomenclature

In table 6, the MC is 66% and the OM is 51 % of the dry mass; these do not have to add up to 100%.

Reviewer 2

All grammar corrections were carried out and the reference section was updated as well as corrected.

The word "recipe" was changed for "formula".

The Latin words were added for the BA types.

The degree of decomposition was evaluated visually. This was added to the text of the methodology and results.

The best compost mixture was defined under the objectives (lines 87-91).

Line 48 Jeanne Mance was irrelevant and removed.

Other relevant studies: the literature review was modified to this effect.

The type of food waste was described on line 106-107.

A statistical analysis section was added.

The P < 0.5 was corrected to P < 0.05 or P < 0.005, where concerned.

The significant differences in temperature regime were identified in the first section of the results.

The amount of dry and wet masses lost during the composting process is indicated in Tables 5 and6. Table 6 has been modified to show the amount of water, C and N lost.

  Experimental set-up and substrates 94

  composter was filled to 2/3 capacity with the mixture of FW and BA. 103 The FW was obtained from the composting centre of the Jeanne Mance Park, 104 located in the Plateau area of the city of Montreal, Canada. Delivered within 2 days of 105 being produced by the local residents, this FW was made up of raw and cooked vegetable 106 and fruit residues and was further checked for foreign material upon reception. The bulking agents were obtained from the experimental cattle complex of the 108 Macdonald Campus of McGill University, Montreal, Canada. The straw (Triticum) and 109 mature hay consisting of 80% timothy (milium) and 20% clover (triphullum) were 110 produced on the farm, while the pine (pinus) wood shavings were purchased from a local 111 supplier. Before preparing all formulas, the straw and hay were chopped to a length 112 varying between 5 and 25 mm. The WS already offered a small particle size in the range 113 of 5 to 10 mm in length and width, by 1 to 2 mm in thickness. All bulking agents and the 114 food waste were characterized (

  ). Each compost mixture was prepared by individually 119 weighing the FW and BA, manually mixing the materials in a tray and then loading the 120 mixture into duplicate composters. Ammonium nitrate (NH 4 NO 3 ) was added as required 121 by the formulas to balance the C/N ratio between 20 and 25. For chopped wheat straw 122 (CWS), the mixtures offered a dry matter content of 40%, 35%, 30%, 25% and 20%. For 123 chopped hay (CH) and wood shaving (WS) as BA, the mixtures offered a dry matter 124 content of 40%, 30% and 20%. During the 10 days of active composting, each in-vessel 125 prototype was rolled daily to ensure the restructuring of the compost material and to 126 maintain a uniform decomposition as observed when sampling for pH every 2 days. of the four testing sessions, a BA was randomly selected and 130 three of its formulas were tested in duplicate, once randomly assigned to one of the six 131 in-vessel prototype composters. Once filled, each mixture was monitored for temperature 132 and pH, during a 10-day active composting period, because temperature and pH are 133 excellent composting process indicators

  methods (APHA, 1995), the FW, BA and matured 152 composts were characterized for dry matter (DM), carbon (C), pH, TKN, TP, TK and 153 C/N ratio. Dry matter was determined by drying at 103°C for 24 h (Scientific John by 154 Sheldon Manufacturing Inc., Cornelius, Oregon, USA) and expressed as: 155 DM (%) = (oven dry sample weight/wet sample weight)of the dried samples was determined by burning at 550 0 C in 158 a muffle furnace (Blue M Electric Company, Blue Island, USA) for 4 h. Carbon content 159 was determined by dividing the volatile fraction by 1.83 (Barrington et al., 2002a): 160 C (%) = (100 -% ash)/ 1and TK were determined by digesting the samples with sulfuric 163 acid and 50% hydrogen peroxide at 500 0 C for 15 min. The TKN of the digested samples 164 was quantified by measuring its NH 3 -N content at a pH of 13, using a NH 3 sensitive 165 electrode (Orion, Boston, Massachusetts, USA, model BCN). Because of the low nitrate 166 and nitrate levels of all materials, TN was equated to TKN. The TP and TK of the 167 digested samples were quantified colorimetrically, at a pH of 7, using a 168 spectrophotometer (Hach, Model DR 5000, Loveland, Colorado, USA).

(

  used to randomly test one BA and three duplicate formulas 185 at any one time. The temperature and pH regime measured for each duplicate FW and BA 186 mixture were averaged and the standard deviation of their value was calculated using 187 Excel (Microsoft, 2003). ANOVA was used to compare the effect of treatment (BA/FW 188 ratio) on temperature and pH, for each BA, where time was designated as a block. The 189 significant treatments and blocks were identified using Duncan's Multiple Range test 190 Effect of bulking agent to food waste ratio 194 Of the compost mixtures using CWS, Fig. 3a and b illustrate the measured 195 temperature fluctuations over time as compared to that of ambient air.

FigFig. 4 .

 4 Fig. 1. Experimental in-vessel composter. Perforated 5cm tubing for aeration

Fig. 5 .

 5 Fig. 5. Temperature variation with time for the food waste (FW) and wood shavings (WS) formulas where the vertical bars are standard deviation.

Table 1

 1 ).

	115
	116
	117	2.2. Compost formulas

  35°C against an ambient temperature of 12 to 20°C. The WS formulas did not perform as 220 well as those with CWS and CH. Among all WS formulas, that with 20% DM was the 221 most active but lacked aeration with a low 21% FA as compared to the recommended

	197 243	mixtures with a DM of 25% and 20% (FW/BA ratios of 5:1 and 8.9:1) reached 3.2. The effect of pH
	198	significantly higher temperatures (P< 0.05) as compared to those with a DM content of
	199 222	40%, 35% and 30% (FW/BA ratios of 2:1, 2.5:1 and 3.4:1), but only from days 3 to 5.
	200 223	Compared to the low DM mixtures of 20% and 25%, which reached the thermophilic minimum of 26% (Eftoda and McCartney, 2004).
	201 224	range of 50°C within 3 days of active composting, two other mixtures with a FW/BA Besides moisture content, the observed temperature regimes were affected by
	202 225	ratio of 2.5:1 and 3.4:1 (30% and 35% DM) performed as well from days 0 to 2 available C and O 2 . With anaerobic digestion, the biodegradable C for different organic
	203 226	inclusively. After 2 days, these higher DM mixtures likely lost moisture below that wastes is well established: 0.80 to 0.95 for cereal, vegetable and fruit wastes; 0.50 to 0.70
	204	required to sustain a high microbial activity. Wetting these formulas would likely have for wheat straw; 0.50 for mature grass hay, and; 0.20 to 0.30 for wood residues (Loehr,
	205	helped reach thermophilic temperatures. The 40% DM formula resulted in the lowest
		temperature regime, never exceeding 40°C.
	211
	212	and 40% DM), compost temperatures remained below 38°C, as compared to CWS
	213 236	mixtures with a FW/BA ratio of 5:1 and 3.4:1 (25% and 30%) which reached 45°C after
	214 237	1 day. Therefore, and as compared to CWS, CH did not sustain as active a microbial biodegradability, but lacked available O 2 because of its low FAS of 21% (Table 4). Based
	215 238	activity for the 30% DM mixture. on previous work (Eftoda and McCartney, 2004; Tognetti et al., 2006) and the present
	216 239	For the WS illustrated in Fig. 5, only the FW:WS ratio of 7.8:1 (20% DM) results, wood residues such as WS should be used in combination with other BA, where
	217 240	produced a significantly higher temperature regime (P<0.05) compared to the other the low C biodegradability of wood residues help maintain a porous structure while the
	241	formulas, but no mixture reached the thermophilic range. While the temperature of the other BA provides additional C besides the waste being composted.
		The compost

206

As illustrated in Fig.

4

for CH, only the 20% DM mixture (FW/BA ratio of 8.6:1) 207 demonstrated a statistically higher temperature regime compared to the other mixtures 208 (P< 0.005), from days 1 to 6 inclusively. As for the CWS mixture with a FW/BA ratio of 209 8.9:1, the CH mixture with a FW/BA ratio of 8.6:1 reached the thermophilic range of 210 50°C on 3 days. For the other CH mixtures with a FW/BA ratio of 3.3:1 and 1.8:1 (30% 218 FW:WS ratio of 7.8:1 reached 37°C on day 4, that of the other mixtures remained under 227 1984). Accordingly, CWS offered the most biodegradable carbon and therefore supported 228 the strongest microbial activity. All CWS formulas exhibited high FAS exceeding 30%, 229 and therefore had sufficient structure for aeration (Table 2). Compared to the CWS 230 mixtures with the same DM, CH offered a weaker biological activity, except for the 20% 231 DM with a high FW:BA ratio, where the FW provided the available C. Again, all CH 232

formulas had exhibited FAS exceeding 30%, and accordingly, the proper structure for 233 aeration (Table

3

). The WS mixtures demonstrated the lowest microbial activity, in 234 parallel with the low C biodegradability of the BA. The FW:BA ratio of 7.8:1 offered the 235 most microbial activity, again because of its high FW content increasing the C

Table 1

 1 Characteristics of experimental food waste (FW) and bulking agents (BA)

	Parameters	Food waste	Chopped wheat	Chopped hay	Wood shavings
		(FW)	straw	(CH)	(WS)
			(CWS)
	pH	4.1 (0.2)	7.0 (0.6)	6.6 (0.5)	5.6 (0.3)
	Dry matter, %	12.2 (1.3)	89 (1.3)	91 (1.4)	80 (0.2)
	Carbon, %	47.4 (3.1)	50.4 (1.0)	51.7 (0.6)	54.5 (0.02)
	TKN, %	2.0 (0.3)	0.5 (0.08)	0.9 (0.12)	0.08 (0.01)
	C/N ratio	24 (3.0)	103 (16)	59 (9)	676 (11)
	Wet bulk density, kg/m 3	410 (92)
	Particle size, mm	10-100	5 -25	5 -25	5 -10
	Loose (no compression)		16	43	84
	Medium manually		38	75	116
	compressed (3kPa)
	Manually compressed (6kPa)		68	109	151
	Machine compressed (as		127	-	211
	packaged by supplier)
	Note: Numbers in parenthesis is the standard deviation.

Table 2

 2 Trial formulas of food waste (FW) and chopped wheat straw (CWS)

	Formula	FW:CWS	FW:CWS	NH 4 NO 3	NH 4 NO 3	C/N before	C/N after	DM	BD	FAS
	Number	WW	DW	% WW	% DW	amending	amending	%	kg/m 3	%
	1	2.0:1 (1:5)	-	1.80	-	-	20.2	40	175	73
	2	2.5:1 (1:4)	1:3.1	1.43	4.1	57	20.9	35	202	70
	3	3.4:1 (1:3)	1:2.4	1.15	3.8	53	20.9	30	253	64
	4	5.0:1 (1:2)	1:1.5	0.87	3.5	45	20.9	25	378	49
	5	8.9:1 (1:1.3) 1.2:1	0.59	3.0	39	20.9	20	560	30
	Note: WW -wet weight basis; DM -dry weight basis; DW -dry weight basis; BD -bulk density under a
	pressure of 6 kPa; FAS -free air space under a pressure of 6 kPa; numbers in parenthesis is the volumetric
	ratio.

Table

Table 3

 3 Trial formulas of food waste (FW) and chopped hay (CH)

	Formula	FW:CH	FW:CH	NH 4 NO 3	NH 4 NO 3	C/N	C/N	DM	BD	FAS
	Number	WW	DW	% WW	% DW	before	after	%	kg/m 3	%
						amendment	amendment
	1	1.8:1	1:4.31	0.70	1.7	41	21	40	283	67
		(1:3)
	2	3.3:1	1:2.23	0.49	1.6	35	21	30	344	60
		(1:1.6)
	3	8.6:1	1.12:1	0.29	1.4	27	21	20	570	39
		(1.5:1)
	Note: WW -wet weight basis; DM -dry weight basis; DW -dry weight basis; BD -bulk density under a
	pressure of 6 kPa; FAS -free air space under a pressure of 6 kPa; numbers in parenthesis is the volumetric
	ratio.

Table 4

 4 Trial formulas of food waste (FW) and wood shaving (WS)

	Formula	FW:WS	FW:WS	NH 4 NO 3	NH 4 NO 3	C/N before	C/N after	DM	BD	FAS
	Number	WW	DW	% WW	% DW	amendment	amendment	%	kg/m	%
									3
	1	1.5:1	1:4.48	2.3	5.7	123	21.02	40	520	52
		(1:2.3)
	2	2.9:1	1:2.32	1.5	5.0	79	21.36	30	599	40
		(1:1.2)
	3	7.8:1	1.14:1	0.74	3.7	46	21.36	20	750	21
		(2:1)

Table 5

 5 Mass reduction of test formulas for various bulking agents after 56 days of maturation

	FW:CWS	% MR	MC	FW:CH	% MR	MC	FW:WS	% MR	MC
		DW	WW	%		DW	WW	%		DW	WW	%
	2:1	-	62	-	1.8:1	-	57	-	1.5:1	-	26	-
	3.4:1	-	70	-	3.3:1	-	69	-	2.9:1	-	40	-
	5:1	39	77	35	8.6:1	52	84	40	7.8:1	50 71	66
	8.9:1	68	86	54
	Note: MR -mass reduction; DW -dry weight basis; WW -wet weight basis; MC -moisture content.

Table 6

 6 Nutrient content and C, N and water losses for the mature compost

	Parameter	Suggested ***		Food waste to bulking agent mixture
			FW:CWS	FW:CH	FW:WS
	FW/BA		5:1	8.9:1	8.6:1	7.8:1
	MC, %	<40	35	54	40	66
	OM, % DW	>25	39	42	40	51
	TKN, % DW	>0.6	3.72 (2)	3.04 (2.4)	2.6 (1.97)	0.95 (2.4)
	TP, % DW	>0.22	0.29	0.24	0.41	0.25
	TK, % DW	>0.25	3.09	3.16	3.07	2.9
	BD, kg/m 3	-	630	630	630	460
	C lost, g/kg*		55	42	57	10
	N lost, g/kg*		1.0	3.2	2.7	4.0
	H 2 O lost, kg/kg*		0.73	0.67	0.74	0.61
	H 2 O lost, kg/kg**		9.5	6.7	7.1	61

gradually from days 3 to 7. Denitrification activity was likely initiated on day 3 along

with an increase in microbial activity reflected by higher temperatures. When analyzing 265 the compost after 56 days of maturation, the WS mixtures had lost the most nitrogen. For CWS after 56 days of maturation, the 20% DM formula (FW/BA ratio of 269 8.9:1) demonstrated a dark brown colour and no recognizable substrate particles. The 270 25% DM mixture (FW/BA ratio of 5:1) was also highly decomposed and of a dark brown 271 colour; however, some of the wheat straw was not fully decomposed.

272

Although dark brown in colour, none of the CH mixtures were fully decomposed 273 after 56 days of maturation because a limited amount of hay particles were still visible.

274

The hay used in this trial was mature and coarse when harvested and therefore less 275 biodegradable than straw and hay cut early. Nevertheless, the CH mixture with a 20% 276 DM (FW/BA ratios of 8.8:1) offered the least recognizable BA particles.

277

After 56 days of maturation, the WS mixtures (FW/BA ratios of 1.5:1, 2.9:1 and In terms of N losses, the CWS with an initial 25% DM experienced the least 322 losses at 1.0 g/kg of initial wet compost mass (4 g/kg of initial dry mass), followed by the 323 CH and CWS with an initial 20% DM losing 2.7 and 3.2 g of N/kg of initial wet compost 324 mass (13.5 and 16.0 g/kg of initial dry mass). The WS with an initial 20% DM lost the 325 most N, at 4.0 g/kg of initial wet compost mass (Table 6). For CWS, the 25% DM 326 formula lost less N compared to that with 20% DM, likely because of less leaching. The CWS (20% and 25% DM), CH (20% DM) and WS (20% DM) matured 330 composts offered an OM content exceeding 40% and TKN, TP and TK levels exceeding 331 2.5%, 0.25% and 3.0%, respectively, on a dry matter basis (Table 6). These parameters are within the range required for agricultural use as soil amendment, according to 333 Tognetti et al. (2006).

334

The mature CWS and CH formulas offered a TN which exceeded their original 335 content by 85% and 25%, respectively, whereas the mature WS formula offered a TN 336 which was 60% lower than its original. The high nitrogen losses obtained with the WS 346 Because all bulking agents with an initial 20% DM exhibited over 50% and 70% 347 dry and wet mass losses, respectively, once matured, composting can be said to reduce 348 the storage space required and lower the transportation cost, compared to the raw FW 349 mass. Finally, with a final DM under 50%, these composts are less attractive to insects 350 [START_REF] Connell | Manure management practices to control fly problems[END_REF]. Figure 6 was not deleted, as we feel that it is important in illustrating differences and variation in pHs. Also this paper does not have an extensive number of figures.

Reviewer 4

Section on page 4, lines 69-71 was removed. The entire introduction was modified and better adapted to the topic.

The filling of the composters to 2/3 capacity has no impact on the % of mass lost.

The daily rolling of the prototypes was to restructure the compost and keep it homogeneous; text corrected; line 127-129.

Dashed lines are introduced in the figures to differentiate between treatments; the practice of using solid lines for models is not standard.


Julien Provost
email: provost@lurpa.ens-cachan.fr

Jean-Marc Roussel
email: roussel@lurpa.ens-cachan.fr

Jean-Marc Faure
email: faure@lurpa.ens-cachan.fr

Testing Programmable Logic Controllers from Finite State Machines specification

This paper shows, on the basis of experiments, that execution of conformance tests of programmable logic controllers with minimum-length test sequences built from specifications in FSMs may yield spurious results. A new approach to build test sequences is then proposed to remove, or at least strongly lessen, this issue.

I. INTRODUCTION

Conformance test is a model-based functional test technique whose aim is to check whether an implementation behaves correctly with respect to a specification. In this paper, the implementation is a PLC (Programmable Logic Controller) which executes cyclically a control algorithm and it will be assumed that the specification is described in the form of a Finite State Machine (FSM) with inputs and outputs. Industrial specifications of logic control are obviously not described as FSMs but it has been shown [START_REF] Provost | Translating Grafcet specifications into Mealy machines for conformance test purposes[END_REF] that any specification in the IEC 60848 standardized language [2] can be translated into this formalism. Moreover, the approach proposed in the previous reference can be applied to other industrial specification languages; the assumption on the specification model is then quite realistic.

Generally speaking, conformance test comprises two phases (Fig. 1):

• Construction of a test sequence from the specification model. • Execution of this sequence on the implementation to obtain a conformance verdict. Many significant results have been obtained in the domain of construction of test sequences from FSMs; the interested reader is referred to [START_REF] Lee | Principles and methods of testing finite state machines -a survey[END_REF] for a good synthesis. Execution of a test sequence is not so widely addressed in the literature; contributing to fill this gap is the overall objective of this paper which is based on experimental results obtained with a specific test-bench for PLCs.

Construction of a test sequence requires a test objective and an optimization criterion be previously defined. In the sequel of this paper, the objective is to fire at least once each transition of the FSM; the coverage rate of transitions is then equal to 100%, what is mandatory for critical systems. The usual optimization criterion of the test sequence is minimum-length, to limit the duration of the execution. The first contribution of this paper is to show, on the basis of experiments, that a sequence built with this criterion (minimum-length test sequence) may lead to spurious results, however: implementation errors may be not detected while correct controllers may be declared nonconform.

A detailed analysis of these experimental results has permitted to pinpoint the origin of these issues: synchronous events issued from the test-bench may be interpreted as asynchronous by the controller under test; hence, the input sequence used by the PLC to compute its outputs is not really that defined during test sequence construction. This can be avoided by using a SIC (Single Input Change) test sequence, in which the value of only one input can change at one and the same time; synchronous input values changes are then not possible. Nevertheless, it is not always possible, with the test objective selected, to build such a sequence from an FSM, as explained in [START_REF] Provost | SIC-testability of sequential logic controllers[END_REF]. To limit the error risk during test execution in this case, the second contribution of this work is a method to construct a sequence, termed maximum consecutive SIC (mc-SIC) sequence, that comprises a set of consecutive SIC test steps to explore entirely the SIC-testable part of the FSM.

The outline of this paper is the following. The next section is a brief reminder on conformance test of FSMs. Section III describes the experiments which were performed by using a minimum-length test sequence and discusses the results obtained. Construction of a mc-SIC test sequence is detailed in section IV; the minimum-length and mc-SIC test sequences are then compared. Last, prospects for other strategies to construct test sequences that limit the risk of spurious results during test execution are sketched in the last section.

II. BACKGROUND A. PLCs behavior specification with FSMs

Among the numerous formalisms developed to describe the behavior of discrete event systems (DES), finite state machines (FSMs) with inputs/outputs, e.g. Mealy machines, are well suited to formal specification of PLCs that receive and send logic data from/to the plant. This formalism cannot be used by control engineers obviously, but it is possible to translate models in industrial standardized languages in this kind of formal models, as presented in [START_REF] Provost | Translating Grafcet specifications into Mealy machines for conformance test purposes[END_REF].

The contributions of this work will be illustrated with a simple example: a logic controller with 3 logic inputs (a, b and c), and 3 logic outputs (U , V and W ) (Fig. 2). The specification of this controller is given figure 3. The input and output alphabets of this FSM are respectively the controller inputs valuations (v I ) and outputs valuations (v O ) (Table I). As the state space comprises 5 states (s 1 = s Init : initial state, s 2 , s 3 , s 4 and s 5 ), the transition and output functions δ(s, v I ) and λ(s, v I ) of the FSM are defined for 40 (5 • 2 3 ) couples (s, v I ). A couple (v I , v O ) is associated to each transition of the machine; the first element of this couple represents the inputs valuation which provokes the transition from the source state, the second element the outputs valuation emitted when this transition is fired. The target state s t reached when firing, from a source state s s a transition labeled v I /v O is defined through the transition function (s t = δ(s s , v I )), while the emitted outputs valuation is defined through the output function (v O = λ(s s , v I )). In this example, the specification is complete (the transition function is completely defined), minimal (there are no equivalent states) and every state is reachable.

Input alphabet

Output alphabet This section recalls briefly the principle of the conformance test of FSM; the reader is referred to [START_REF] Lee | Principles and methods of testing finite state machines -a survey[END_REF] for further details.

i 0 i 1 i 2 i 3 i 4 i 5 i 6 i 7 o 0 o 1 o 2 o 3 o 4 o 5 o 6 o 7 a 0 1 0 1 0 1 0 1 U 0 1 0 1 0 1 0 1 b 0 0 1 1 0 0 1 1 V 0 0 1 1 0 0 1 1 c 0 0 0 0 1 1 1 1 W 0 0 0 0 1 1 1 1
The problem of conformance test of FSM can be described as follows: Let S be a known machine (the specification) and I an unknown machine (the implementation under test) which can be only observed through its inputs and outputs, determine In order to solve this problem, it is generally assumed that the specification is minimal and strongly connected (each state is reachable, immediately or not, from any other state). Then, the equivalence between an implementation I and a specification S consists in verifying that none of the following errors happens during the test of I:

• Output error: s s being the active state, when the input i occurs, I produces the output o instead of the expected output o. • Transfer error: s s being the active state, when the input i occurs, the transition labeled i/o is fired but the arrival state is s t instead of s t . The test sequence is constructed from S and must permit to detect these two kinds of errors, for each state and each transition. Hence, each elementary test corresponds to a transition s s i/o -→ s t of S and is defined as follows: 1) Go to s s (synchronization). 2) Apply input i and check whether the emitted output is o.

3) Check whether the arrival state is s t (identification).

C. Minimum-length test sequence construction

The construction of a test sequence, using the transition tour method [START_REF] Naito | Fault detection for sequential machines by transitions tours[END_REF], can be automated to obtain a minimum-length test sequence. This optimization problem is a particular solution of a well-known problem in graph theory: the Chinese Postman Problem [START_REF] Mei-Ko | Graphic programming using odd or even points[END_REF]. The general formulation of this problem is the following: Find a minimum-length closed walk that traverses at least once each edge (or arc) of the graph that describes the structure of the FSM. As this graph is directed, but not weighted, the optimization problem is simplified.

For the example given figure 3 this sequence contains 40 test steps (Table II) and fulfills the test objective (coverage rate of the transitions equals 100%). In practice, each elementary test permits to test sequentially two arcs of the FSM:

(s s , v I , s t , v O ) and (s t , v I , s t , v O )
. This is possible because the inputs of the PLC under test can be scanned several times 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 ss: s 1 s 2 s 3 s 2 s 2 s 4 s 3 s 2 s 4 s 3 s 2 s 4 s 4 s 4 s 1 s 2 s 4 st: s 2 s 3 s 2 s 2 s 4 s 3 s 2 s 4 s 3 s 2 s 4 s 4 s 4 s 1 s 2 s 4 s 1 a: 1 0 1 0 1 0 1 0 0 1 0 1 0 1 1 0 1 b: 0 1 0 0 1 1 0 1 0 0 1 0 0 1 0 1 0 c: 0 1 0 0 0 1 0 0 1 0 0 0 0 1 0 0 1 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 s 1 s 2 s 5 s 3 s 2 s 5 s 3 s 2 s 5 s 5 s 5 s 1 s 2 s 5 s 1 s 3 s 2 s 2 s 5 s 3 s 2 s 5 s 3 s 2 s 5 s 5 s 5 s 1 s 2 s 5 s 1 s 3 s 2 s 1 1 1 0 1 0 0 1 0 1 0 1 1 0 1 0 1 1 0 0 1 0 0 1 0 0 0 0 1 0 0 1 1 0 1 0 1 1 0 1 0 0 1 0 0 1 0 1 0 1 0 1 35 36 37 38 39 40

s 1 s 3 s 1 s 3 s 1 s 3 s 3 s 1 s 3 s 1 s 3 s 1 0 1 0 1 0 1 0 1 1 0 0 1 1 1 0 1 0 0

III. EXPERIMENTATION

This section focuses on execution of the conformance test of a PLC from a minimum-length test sequence. The experimental conditions are first given. As spurious test results may be obtained, an explanation is then proposed and verified by complementary experiments. The last sub-section provides some guidelines for conformance test from FSM.

A. Experimental conditions

The test-bench used in this work is built from a remote input/output module (RIOM) with 16 logic inputs and 16 logic outputs that can be remotely set/reset from a computer via a Modbus TCP/IP network (Fig. 4). Each output of this RIOM is connected upstream from an input of the logic controller under test, while each of its inputs is connected downstream from an output of this controller. This open solution provides high flexibility at a very low cost.

A modular PLC (Phoenix Contact ILC 170 ETH 2TX) was selected for these experiments. I/O scanning can be cyclic or periodic and the programming environment complies with the IEC 61131-3 standard [START_REF]Programmable controllers -Part 3: Programming languages[END_REF]. The control algorithm is implemented in the form of a Structured Text code obtained automatically from the specification according to the method proposed in [START_REF] Machado | Logic controllers dependability verification using a plant model[END_REF]. This solution allows either to generate an a priori correct code or to artificially introduce implementation errors. Once programmed, the controller is disconnected from its programming environment for the entire test execution.

Once the controller initialized, test execution consists, for each step of the test sequence, in:

• sending to the controller the input signals that correspond to this step; • waiting for outputs stabilization;

• reading the values of the output signals emitted by the controller under test; • comparing these values to the expected ones and delivering a verdict; • recording the results. It matters to underline that the test-bench cycle is not synchronized with the PLC I/O scanning cycle so that the test conditions be as close as possible to the operation conditions of a closed-loop DES; the behavior of a plant is indeed not synchronized with that of its controller.

B. Results and discussion

The first experiments with short test sequences were conclusive. Unfortunately, erroneous detections of non-conformance, which led to reject correct controllers, and non-detections of non-conform controllers occurred during experiments with longer test sequences. These issues appeared whatever the PLC.

A detailed analysis of the results files showed that these issues occurred always for test steps where several input values were changed simultaneously by the test-bench, e.g. steps 2 or 3 of table II; test steps where only one input value was changed never caused such issues. An explanation was then put forward: synchronous input changes generated by the bench may be seen as asynchronous by the controller (Fig. 5) because all inputs are not read simultaneously. The input values used by the implementation to compute its outputs are then different from those planned.

C. Experimental verification

To verify this explanation, the following experiment has been then carried out:

• The test-bench sends to the controller a set of 8 signals that vary simultaneously and in an identical manner (from 0 to 1, then from 1 to 0) with a period far greater (more than 10 times) than the maximal PLC cycle time. Hence, the changes (rising and falling edges) of these 8 signals are strictly synchronous. • When the controller detects the first change of one of its inputs, the current value of each input is copied on the corresponding output (8 outputs are used, each one associated to an input). Thus, the value of the output vector is equal to the value of the input vector at the moment when the first inputs change has been detected. • The test-bench reads the emitted output values and compares them with the expected values, which should be identical to the input values sent to the controller if no inputs reading error (synchronous changes seen asynchronous) has occurred. A counter is incremented when an error is detected, i.e. when the outputs vector differs from the inputs one. Table III gives the error rates according to the PLC operating mode (cyclic or periodic I/O scanning) and the distribution of the inputs on the PLC internal components (all inputs connected on the main module, connected on the secondary module, or distributed on both main and secondary These figures were obtained from series of 200,000 experiments for each configuration and each distribution.

These results validate clearly the proposed explanation. As the PLC scanning cycle is not synchronized with the testbench cycle, synchronous events issued from the bench may be seen asynchronous. In the case of inputs distributed on several modules (last two lines of table III), the errors rate is strongly increased due to the communication between the modules that induces extra delays.

The difficulty to implement theoretical results issued from DES theory on real PLCs has already been underlined in [START_REF] Fabian | PLC-based implementation of supervisory control for discrete event systems[END_REF] when attempting to implement supervisors.

D. Guidelines for conformance test from FSM specifications

These experiments have clearly showed that using a minimum-length test sequence obtained from an FSM to test a PLC may yield spurious results. This approach relies indeed on the implicit assumption that all inputs changes generated by the test-bench are correctly detected by the controller under test, even if several input values are simultaneous modified, which is not always true. To overcome this issue, several solutions can be imagined:

• synchronization of the test-bench with the controller under test; • test execution for the configurations of the controller that lessen the error rate (slow periodic inputs scanning and inputs distribution on a single module); • multiple executions of the same test and statistical analysis of results; • construction of a test sequence, termed Single Input Change (SIC) test sequence, that does not include simultaneous changes of the input values.

The first solution requires additional communication between the test-bench and the controller be introduced and, above all, does not represent the operation conditions of a real closed-loop DES, as mentioned above. The second and third solutions are not really suitable for controllers of highly critical systems because they imply statistical analyses of results. Hence, the last one shall be privileged and is discussed in the next section.

h h h h h h h h h h h

IV. SIC-TESTABILITY AND MC-SIC TEST SEQUENCE GENERATION

A. Formal definition of test sequences

During test execution, a test sequence is seen as an ordered list of couples (inputs valuation, expected outputs valuation) which represents its external view:

(v 0 I , v 0 O ), (v 1 I , v 1 O ), ..., (v n I , v n O ) ∈ (V I × V O ) * (1)
These two valuations are not independent, however. The outputs valuation is that associated to the transition which goes from a source state s s to a target state s t for the inputs valuation. Hence, an elementary conformance test step et is defined by the following 4-tuple:

et = (s s , v I , s t , v O ) ∈ S × V I × S × V O where s t = δ(s s , v I ) v O = λ(s s , v I ) (2)
Thus, a test sequence is an ordered list of elementary test steps, and a consistent test sequence T S is a test sequence such as the source state of the k th elementary test step is equal to the target state of the (k -1) th step.

T S = [(s 0 , v 0 I , δ(s 0 , v 0 I ), λ(s 0 , v 0 I )), • • • , (s n , v n I , δ(s n , v n I ), λ(s n , v n I ))] | ∀k > 1, s k = δ(s k-1 , v k-1 I ) (3)

B. Properties of test sequences

A test sequence T S may be: P1: initializable, i.e. the source state of the first test step is the initial state of the FSM, and the input valuation v 0 I is such that this state is stable (the target and source states are identical):

s 0 = s Init δ(s 0 , v 0 I ) = s 0 (4)
P2: complete, i.e. there is at least one test step for each element of the transition function:

∀(s, v I ) ∈ (S × I), (s, v I , δ(s, v I ), λ(s, v I )) ∈ T S (5)
P3: based on a SIC test sequence.

To express formally this latter property, the SIC relation between two inputs valuations must be first defined. The definition below is based on the representation of an inputs valuation by the subset of logic inputs that only contains the inputs that are True (also noted 1) for this valuation. Thus, two inputs valuations v I and v I satisfy a SIC relation iff 1 :

dim((v I \v I ) ∪ (v I \v I )) = 1 (6)
For example, the inputs valuations used in steps 3 and 4 of the test sequence given table II

satisfy a SIC relation since dim(({a}\{}) ∪ ({}\{a})) = dim({a} ∪ {}) = 1
Unfortunately, any FSM does not always permit to construct a test sequence that satisfies these three properties. Thus, before considering the construction of a SIC test sequence, the SIC-testability of the FSM -ability of this FSM to satisfy the three properties previously pinpointed -must be checked.

C. Checking SIC-testability of an FSM

A detailed presentation of the algorithm to check whether a specification is SIC-testable or not can be found in [START_REF] Provost | SIC-testability of sequential logic controllers[END_REF]. For room reasons, only its principles and an illustration are presented in this paper. This algorithm is based on the following two observations:

• An elementary test step (s s , v I , s t , v O ) is SIC-testable if it can be included into an initializable SIC test sequence. If the elementary test step (s s , v I , s t , v O ) is SIC-testable, the elementary test step (s t , v I , s t , v O ) is also SIC- testable. • If the elementary step (s t , v I , s t , v O ) is SIC-testable, it is
always possible to add to the test sequence an elementary step (s t , v I , δ(s t , v I ), λ(s t , v I )) where v I and v I satisfy a SIC relation. On these bases, the set of elementary test steps which are SIC-testable can be obtained by a fixed-point calculation on the elementary test steps; this calculation begins with the set of elementary steps which start from the initial state of the FSM and satisfy δ(s Init , v 0 I ) = s Init . At the end of this iterative calculation, the FSM is SIC-testable iff the final set contains all elementary test steps that can be defined from its behavior description; it is then possible to build a SIC and complete (and also consistent and initializable) test sequence. Otherwise, this final set defines the SIC-testable part of the FSM.

1 dim(A) is the dimension of set A. An input valuation can be represented either by a minterm or by the set of input variables that are True (noted 1) for this valuation (see table IV). @ @ @ @ @ @

D. Illustration on the example

Table IV gives a tabular representation of the transition function of the example. In this Huffman table [START_REF] Huffman | The synthesis of sequential switching circuits[END_REF], each cell represents an elementary behavior (δ(s s , v I ) = s t ), whose source state s s , inputs valuation v I and target state s t are respectively given by the corresponding line, column and content of the cell.

Circled cells represent stable couples (s, v I ), i.e. couples (s, v I ) such as δ(s, v I ) = s, and non-circled cells couples that imply a change of the active state (δ(s s , v I ) = s t = s s ).

An initializable and complete test sequence starts from a circled cell of the first line (s Init = s 1 ) and covers all cells of the table. To be consistent, the test sequence must be built according to the following two rules: R1: From circled cells, only horizontal changes of cells are possible. Indeed, the inputs valuations of two successive test steps can be different, but the source state of the second step must be identical to the target state of the first one. R2: From non-circled cells (source and target states of the associated test step are different), only one vertical change is possible. Indeed, these cells represent nonstable couples (s, v I ), the change of the active state leads to the circled cell that represents δ(s, v I ). To build a SIC test sequence, rule R1 must be restricted: R3: Since a SIC test sequence does not include simultaneous changes of input values, an horizontal change must correspond to a couple of inputs valuations which satisfy a SIC relation. Rule R3 implies that in the case of a controller with n logic inputs, only n cells among (2 n -1) can be reached from a circled cell.

Table IV also presents the result of the fixed point calculation for the example. The number k of the iteration during which the test step was found SIC-testable is indicated at the top-left corner of each cell. For example, the elementary test step associated to the cell (s 1 , {a, b, c}) is obtained at iteration 0 (initialization). The test steps associated to cells (s 1 , {b, c}) and (s 3 , {b, c}) are obtained at iteration 1, since {a, b, c} and {b, c} satisfy a SIC relation, and so on. Calculation stops at the fifth iteration. The final set contains only 37 test steps; the steps that do not belong to this set are represented by grayed cells. Hence, the FSM is not SIC-testable; its SIC-testable part is given by the cells which are not grayed.

E. Construction of the mc-SIC test sequence

When the FSM is not SIC-testable, a maximum consecutive SIC (mc-SIC) test sequence must be built to limit the risk of spurious results during test execution. This sequence is composed of an initializable minimum-length SIC test sequence, which is computed from the SIC-testable part, followed by a minimum-length MIC test sequence, obtained from the non-SIC-testable part. Both sequences start from and end on the initial state of the FSM; there is no gap between the final state of the SIC sequence and the initial state of the MIC sequence.

The construction of the SIC sequence is based on a directed graph whose nodes represent all couples (s, v I ) that can be defined on the SIC-testable part. For a controller with n logic inputs, the arcs between the nodes are defined as follows:

• only one arc starts from a node that corresponds to a couple (s, v I ) such as δ(s, v I ) = s; the target node of this arc is the node that corresponds to (δ(s, v I ), v I ); • n arcs start from a node that corresponds to a couple (s, v I ) such as δ(s, v I ) = s; the target nodes of these arcs correspond to couples (s, v I ) such as v I and v I satisfy a SIC relation. The minimum-length SIC test sequence can then be obtained by using the results of graph theory on a well-known problem: the Traveling Salesman Problem [START_REF] Dantzig | Solution of a large-scale traveling-salesman problem[END_REF]. The general formulation of this problem is the following: Find a minimumlength closed walk that traverses each node of the graph at least once.

The inputs valuations for a mc-SIC test sequence of the example are given Table V. This test sequence contains 45 SIC test steps, to test the 37 couples (s, v I ) of the SIC-testable part, and 5 MIC test steps, to test the 3 couples (s, v I ) of the non-SIC-testable part. Comparison to Table II shows that the use of a mc-SIC test sequence instead of a MIC test sequence increases the length of the test sequence (50 test steps instead of 40) but strongly reduces the number of test steps where synchronous changes of several inputs occur (only 3 couples (s, v I ) are tested in these conditions with the mc-SIC sequence, instead of 35 with the MIC sequence). Then, the test execution on a PLC will last a bit longer, but the risk of erroneous verdicts is widely lessened.

V. CONCLUSIONS AND PROSPECTS

The experiments presented in this paper have shown that minimum-length is not always the right criterion to build a test sequence for conformance test of PLCs; test execution with such sequences may yield spurious results. SIC, if the specification is SIC-testable, or mc-SIC test sequences must be privileged to remove or lessen this risk and to improve the confidence level in test results. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 ss: s 1 s 2 s 2 s 4 s 4 s 3 s 3 s 2 s 5 s 1 s 1 s 3 s 3 s 2 s 5 s 5 s 1 st: s 2 s 2 s 4 s 4 s 3 s 3 s 2 s 5 s 1 s 1 s 3 s 3 s 2 s 5 s 5 s 1 s 2 a: 1 0 0 0 0 0 1 1 1 1 0 0 1 1 1 1 1 b: 0 0 1 0 0 0 0 0 1 1 1 0 0 0 0 1 0 c: 0 0 0 0 1 0 0 1 1 0 0 0 0 1 0 0 0 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 s 2 s 5 s 5 s 5 s 3 s 1 s 2 s 4 s 1 s 3 s 3 s 1 s 3 s 3 s 2 s 4 s 4 s 5 s 5 s 5 s 3 s 1 s 2 s 4 s 1 s 3 s 3 s 1 s 3 s 3 s 2 s 4 s 4 s 1 1 1 0 0 1 1 1 1 0 0 1 0 0 1 1 1 1 0 0 0 1 1 0 1 1 1 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 1 1 1 1 1 0 0 0 0 1 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 s 1 s 2 s 2 s 4 s 3 s 1 s 1 s 2 s 2 s 5 s 3 s 1 s 3 s 2 s 3 s 2 s 2 s 2 s 4 s 3 s 1 s 1 s 2 s 2 s 5 s 3 s 1 s 3 s 2 s 3 s 2 s 1 1 0 0 0 1 1 1 0 0 0 1 0 1 0 1 1 0 0 1 1 1 0 0 0 0 1 1 0 0 1 0 1 0 0 0 1 1 1 0 0 1 1 1 0 0 1 0 1

Fig. 1 .

 1 Fig. 1. Test sequence construction (a) and execution (b)

Fig. 2 .

 2 Fig. 2. Inputs/Outputs of the controller

Fig. 3 .

 3 Fig. 3. Graphical representation of the FSM

Fig. 4 .

 4 Fig. 4. Experimental device

Fig. 5 .

 5 Fig. 5. Possible interpretations of synchronous changes of 2 inputs

TABLE II INPUTS

 II VALUATIONS FOR THE MINIMUM-LENGTH TEST SEQUENCEduring one test step if the duration of the step is greater than several PLC scanning cycles.

TABLE V INPUTS

 V VALUATIONS FOR THE MC-SIC TEST SEQUENCEOn-going work focuses on construction of other kinds of test sequences for non-SIC-testable specifications, e.g. test sequences where the number of MIC test steps is minimized according to the number of inputs changes in the steps, and on construction of non error-prone test sequences for other test objectives.

ACKNOWLEDGMENT

This work is funded by the French National Research Agency (TESTEC project, Ref. TLOG 07-022)