2.2.2. MPC Constraints

The constraints on the system state and the control inputs have the following form:

$$\begin{bmatrix} -p\_{B,x}^{\max} \\ -p\_{A,x}^{\max} \\ -p\_{S,z}^{\max} \\ -p\_{B,x}^{\max} \\ -\hat{p}\_{A,x}^{\max} \\ -\hat{p}\_{S,z}^{\max} \end{bmatrix} \leq \varkappa(k) \leq \begin{bmatrix} p\_{B,x}^{\max} \\ p\_{A,x}^{\max} \\ p\_{S,z}^{\max} \\ \hat{p}\_{B,x}^{\max} \\ \hat{p}\_{A,x}^{\max} \\ \hat{p}\_{S,z}^{\max} \end{bmatrix} \tag{11}$$

$$\begin{bmatrix} -\dot{\boldsymbol{p}}\_{\boldsymbol{B},\boldsymbol{x}}^{\text{max}}\\ -\dot{\boldsymbol{p}}\_{\boldsymbol{A},\boldsymbol{x}}^{\text{max}}\\ -\dot{\boldsymbol{p}}\_{\boldsymbol{S},\boldsymbol{x}}^{\text{max}} \end{bmatrix} \leq \boldsymbol{\mu}(\boldsymbol{k}) \leq \begin{bmatrix} \dot{\boldsymbol{p}}\_{\boldsymbol{B},\boldsymbol{x}}^{\text{max}}\\ \dot{\boldsymbol{p}}\_{\boldsymbol{A},\boldsymbol{x}}^{\text{max}}\\ \dot{\boldsymbol{p}}\_{\boldsymbol{S},\boldsymbol{x}}^{\text{max}} \end{bmatrix} \tag{12}$$

The motion of the mobile base is left unconstrained (*p*max *B*,*x* = ∞). The maximum velocity and acceleration of the mobile base, *p*˙ max *B*,*x* and *p*¨max *B*,*x* , respectively, are known and directly enforced by these constraints. The maximum values of the robot arm velocities and accelerations in the task space (*p*˙ max *A*,*x* , *p*˙ max *S*,*z* , *p*¨max *A*,*x* and *p*¨max *S*,*z* ) must be determined experimentally, as they depend on the current arm configuration and the velocity and acceleration limits of each joint, which are not considered by the MPC algorithm. Instead, the joint space constraints are enforced at the level of the task space control algorithm.

#### *2.3. Manipulator Task Space Control*

Joint velocities *q*˙ are selected through task space control and are used to control the robot arm (*q* represents joint positions). As mentioned earlier, the MPC algorithm only considers the *x* and *z* coordinates of the spray frame position. In the planning phase (phase of the MPC algorithm), the position of the spray frame in the *y* direction (*pS*,*y*) is assumed to be constant, and its roll, pitch and yaw angles are not considered (*φT*, *θT* and *ψT*, respectively, as shown in Figure 6).

**Figure 6.** The orientation of the spray frame depends on the joint configuration of the robot arm. Roll, pitch and yaw angles are referred to as *φT*, *θT* and *ψT*, respectively.

To achieve the assumption of constant *pS*,*y*, the desired task space velocity in the *y* direction, *p*˙*S*,*y*, is computed with a proportional controller

$$
\dot{p}\_{S,y} = K\_{P,y}(p\_{S,y}^d - p\_{S,y}) \tag{13}
$$

where *pd S*,*y* is a desired value of *pS*,*y* and *KP*,*y* is the controller gain.

The desired linear spray frame velocity can be achieved with different angular velocities. To achieve the largest possible linear spray frame velocities, only the roll angle is controlled directly, while the pitch and yaw angles are not considered. The desired roll angle velocity is calculated with a proportional controller

$$
\dot{\Phi}\_T = -K\_{P,\phi} \phi\_T \tag{14}
$$

where *KP*,*φ* is the controller gain and the desired roll angle is zero.

The desired task space velocity is four-dimensional and considers *x*, *y*, *z* position coordinates and the roll angle of the *LS* frame,

$$\mathbf{v}\_d^{4D} = \begin{bmatrix} \dot{\boldsymbol{p}}\_{A,x}^{\mathcal{M}} \\ \dot{\boldsymbol{p}}\_{S,y}^{\mathcal{M}} \\ \dot{\boldsymbol{p}}\_{S,z}^{\mathcal{M}} \\ \dot{\boldsymbol{\Phi}}\_T \end{bmatrix} \tag{15}$$

*p*˙ *M A*,*x* and *p*˙ *M S*,*z* are provided by MPC, and *p*˙*S*,*y* and *φ*˙*T* are provided by proportional controllers (13) and (14), respectively. The four-dimensional task space velocity depends on the joint velocities as follows:

$$
v^{4D} = \mathcal{I}^{4D} \dot{q} \tag{16}$$

where *J*4*D* is the task space Jacobian.

In general, there are multiple solutions for *q*˙ that achieve the desired task space velocities. For this reason, an additional criterion by which the joint commands are selected is introduced. The desired joint velocities *q*˙ *d* that drive the robot arm to a desired pose *qd* are computed by another proportional controller,

$$
\dot{\boldsymbol{q}}\_d = \boldsymbol{K}\_{\mathcal{P}, \boldsymbol{q}} (\boldsymbol{q}\_d - \boldsymbol{q}) \tag{17}
$$

where *KP*,*q* is the controller gain.

Finally, the joint velocity commands are selected by solving the following QP problem:

$$\begin{aligned} \min\_{\dot{\boldsymbol{q}}} & \quad \left\| \boldsymbol{J}^{4D} \dot{\boldsymbol{q}} - \boldsymbol{\boldsymbol{v}}\_{d}^{4D} \right\|^{2} + \boldsymbol{w}\_{\mathcal{P}} \left\| \dot{\boldsymbol{q}}\_{d} - \dot{\boldsymbol{q}} \right\|^{2} \\ \text{s.t.} & \quad \dot{\underline{q}} \le \dot{\underline{q}} \le \overline{\dot{q}} \end{aligned} \tag{18}$$

where *q*˙ and *q*˙ are the lower and upper bounds of the joint velocities, respectively, and *wp* is the arm pose weight.

### **3. Results**

Two experiments were conducted to evaluate the presented approach: a spraying demonstration in a vineyard and an external validation in an indoor environment equipped with Optitrack cameras. Both experiments were performed with the following optimization weights: *Wy* = 800, *wp*¨*B*,*x* = 80, *wp*¨*A*,*x* = 8, *wp*¨*A*,*z* = 8, *wpA*,*x* = 1. Parameter values were determined experimentally, as described in Section 2.2.1. Values of proportional controller gains used in the experiments were *KP*,*y* = 0.9, *KP*,*φ* = 0.1 and *KP*,*q* = 1.5. These values were also determined experimentally. The velocity of the reference lawnmower trajectory used in all experiments was 0.3 m/s. A prediction horizon of 40 steps was used, with a sampling period of *T* = 0.1 s. The optimization problems for the MPC and task space control were both solved using the BPMPD interior point solver for convex QP problems [36]. The average computation times of the MPC and task space control optimization problems were 3.998 ms and 0.201 ms, respectively, for 600 trials. This allows the presented approach to be used in a real-time scenario, even with larger prediction horizons. All experiments were performed on an Intel Core i7-10710U CPU @ 1.60 GHz.

#### *3.1. Equipment*

The control equipment used in the experiments is shown in Figure 7. All the software was run on an Intel NUC 10 PC with a Ubuntu 20.04 operating system. The Robot Operating System (ROS) was used as the middleware for controlling the robot arm, the mobile vehicle and the spraying agent pump.

**Figure 7.** Communication diagram of the equipment used in the vineyard spraying experiments.

The Kinova Gen3 7 DoF robot arm uses an ethernet connection to communicate with ROS drivers running on the PC. As can be seen in Figure 3, low-level control of the robot arm is achieved via joint velocity commands *q*˙ . Encoder measurements from the robot arm are used as process feedback. As feedback for the MPC algorithm, the robot arm components of the spray frame position *pA*,*x* and *pA*,*z* are calculated at every step of the control loop, using forward kinematics and joint position measurements *q*. For the task space control algorithm, joint position data from the encoder are also used as feedback, to calculate the task space Jacobian *J*4*D*.

Mobile vehicle flipper tracks are actuated by Maxon EC 45 brushless motors, which are controlled using EPOS 70/10 brushless motor drives. EPOS drives communicate with the PC via a CAN bus. ROS drivers for the EPOS drives are used to control the velocities and gather encoder data of each motor. The mobile base component of the spray frame position *pB*,*x* is calculated using encoder data odometry and is used as feedback for the MPC algorithm.

Finally, the spraying agent pump is controlled with an Arduino Nano microcontroller board and is either turned on or off based on the current position of the spray frame with respect to the row description.


**About the Editor**

**Michele Roccella** holds a Degree in Medicine and Surgery and a Specialization in Child Neuropsychiatry at the University of Palermo (Italy). He obtained the title of PhD in Neuropsychopathology of Learning Processes in Developmental Age at the Second University of Naples (Italy). He holds the Diploma Interuniversitaire de Myologie des Universites Aiax-Marseille ` II et Paris VI Pierre et Marie Curie (France). He is currently Associate Professor of Child Neuropsychiatry at the Department of Psychological, Pedagogical, Physical Exercise and Training at the University of Palermo. Since November 2019, he has been Director of the School of Specialization in Child Neuropsychiatry at the Department of Promotion of Maternal-Child Health, of Internal and Specialized Medicine of Excellence "G. D'Alessandro" (PROMISE) of the University of Palermo (Italy). He is the author of several monographs and over 500 publications in national and international journals. He has been awarded several prizes and awards, including that of the Russian Academy of Sciences in Moscow (Russia). Research activities and interests: neurodevelopmental disorders; gender dysphoria; the study of neuropsychological functions in children with epilepsy and in chromosomal–genetic syndromes.


**6. Conclusions**

It is now apparent that conventional antimalarials deploy ROS, ultimately responsible for their parasiticidal activity. However, the evolutionary dynamism of *Plasmodium* seeks to systematically counteract the antimalarial activity mediated by ROS. Given this observation, it is unsurprising that the time required for *P. falciparum* to acquire resistance to antimalarial drugs, whose mode of action is based on the generation of ROS, is becoming increasingly shorter. In this way, the development of artemisinin resistance to new endoperoxide-based hybrid molecules indicates a shared pathway of resistance to the K13 propeller gene mutation [143]. To ensure the continued relevance of ROS-producing antimalarials, the ROS-managing machinery of the parasite could be thwarted to preserve and enhance the activities of the antimalarials. ACTs with newer molecules that disrupt the resistance mechanism of the parasite should be sought. Such molecules, companion drugs of artemisinin, could target key antioxidant enzymes linked to glutathione-dependent and thioredoxin-dependent systems, phosphatidyl inositol 4-kinase enzyme (PI4K), and mRNA translation pathways in *Plasmodium* [69,144–147]. ROS generation thus remains a key element in the strategy in the fight against *Plasmodium* and sustainable malaria control.

**Author Contributions:** Conceptualization and review process, C.O.E., J.-M.A., K.R. and F.B.-V.; figure and table preparation, C.O.E., J.-M.A., K.R. and F.B.-V.; review and editing of final manuscript, C.O.E., J.-M.A., K.R. and F.B.-V. All authors have read and agreed to the published version of the manuscript. **Funding:** This work was supported through a PhD fellowship program to C.O. Egwu from Alex-Ekwueme Federal University, Ndufu-Alike, Ikwo (AE-FUNAI), Nigeria and Campus France, France. CNRS (Centre National de la Recherche Scientifique, France), Université Paul Sabatier, Toulouse III (France) and the IRD (Institut de Recherche pour le Développement, France) participated to the funding of the work.


*2.1. Patients and Data Source*

We initially identified 430,541 infants who were born in 2013 and examined their infant health check-up records for the 1st to 6th visits from the National Health Insurance Service (NHIS) database. Healthcare claims including diagnostic codes of almost all Korean residents, approximately 98% covered by NHIS and 2% by medical aid, were linked to health check databases. The data, including gestational age and birth weight, were also grouped according to the International Classification of Diseases-10 codes (ICD-10: P07.01, P07.02, P07.09-14, P07.19, P07.20, P07.23, P07.29, P07.30, P07.39) [8]. The data were entered by the hospital or obtained from self-report questionnaires used by the national health screening program. Based on the birth statistics [9], the total number of births in 2013 was 436,455, and the number of infants who lived to be at least 1 year of age was 435,150, which shows that this study population 430,541 covered 99% of national births.

The national health screening program for infants and children in Korea, launched in November 2007 is a kind of population surveillance system that consists of history taking, physical examination, anthropometric measurements, screening for visual acuity, and administration of Korean Developmental Screening Test (K-DST), oral examination, and questionnaires with anticipatory guidance [10]. The questionnaire contains the birth weight, preterm, vision, hearing, nutrition (meal, milk, snacks), multimedia, and safety education. We used only the information of birth weight and preterm status in questionnaire from family.

The period for national health screening program (1st to 6th visits) was divided and classified as follow; 6 months for 4–6 months of age, 12 months for 9–12 months of age, 24 months for 18–24 months of age, 36 months for 30–36 months of age, 48 months for 42–48 months of age, and 60 months for 54–60 months of age. The age at exam was defined as chronologic ages.

For growth assessment, the National health screening program checks anthropometric parameters including body weight, height, and HC serially at every follow-up. The percentile of growth was assessed using the Korean growth curve, which provides sex specific data. Poor growth was defined as measurements below the 10th percentile of weight, height, and head circumference individually.

The K-DST is used an effective screening tool for infants and children with neurodevelopmental disorders and has been used since 2011. It is used to verify whether infants are developmentally appropriate or neurodevelopmentally delayed in six domains: gross motor, fine motor, cognition, communication, social interaction, and self-control.

The K-DST is conducted to screen children according to their corrected age before 36 months of age as recommendation and after that age, it is allowed to take tests according to chronological age. There is no K-DST at first visit, and at 5th, 6th visit (42–48, 54–60 months of age) the participants take the test papers according to their chronological

age. The participants take the tests papers at the time of their clinic visit and get the result as four categorized groups based on the standard deviation (SD) scores; the scores above 1 SD are defined as 'high-level', those between −1 and 1 SD as 'peer-level', those between −2 and −1 SD as 'follow-up test', and those below −2 SD as 'further evaluation' [11]. Additional positive questions that take into account clinically important diseases, such as cerebral palsy, language delay, and autism spectrum disorders, that should be referred for 'further evaluation' are also included in the questionnaire. To evaluate the ability of the K-DST to identify infants with developmental delay, critical cutoff scores for 6 domains were set below −1 SD [12,13]. Suspected developmental delay was defined as a K-DST result of 'further evaluation' and 'follow-up test'.

In this study, growth and developmental results were analyzed according to five stratified birth weight groups (<1000 g, 1000–1499 g, 1500–1999 g, 2000–2499 g, and 2500–4500 g). LBW infants and VLBW infants were defined as having a birth weight below 2500 g and 1500 g, respectively. Preterm infants were defined as infants born before 37 weeks of gestation.

#### *2.2. Statistical Analyses*

The cohort was stratified according to the birth weight or the age of checkup. The characteristics of the subjects were expressed as means and standard deviations for continuous variables and as percentages for categorical variables. Correlations for height, weight and HC between 6 months and 60 months of ages as time periods were computed using Pearson's correlation coefficient. Multiple logistic regression model was used to determine the independently associated factors with among infants with odds ratios (OR) and 95% confidence intervals (CI). Multivariate longitudinal data analysis was done using multivariate repeated measured model (PROC MIXED and GENMOD). All statistical analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC, USA). *p*-values < 0.05 were considered statistically significant.

### *2.3. Ethics Statement*

In this study, all identifiable variables, including claim-, individual-, and organizationallevel identification numbers, were re-generated in random by the NHIS database to protect the patients' privacy. This study used NHIS data (NHIS-2019-1-569) maintained by the NHIS. The study protocol was approved by the Institutional Review Board of Gangnam Severance Hospital (No. 3-2019-0147). Informed consent was waived.

#### **3. Results**

#### *3.1. Growth Outcome*

Among 430,541 infants, born in 2013 and included in the study, 219,576 (51%) were male. The numbers of infants, who underwent health checks ranged from 286,331 (67%) to 347,153 (81%). The highest number of infants (*n* = 347,153, 81%) were included in the health check at 24 months of age. The highest number of preterm infants underwent the health check at 36 months (*n* = 26,338, 93%). The distribution of a number of infants who participated in the infant health check according to birth weight group were shown in Table 1.

Data are presented as Number (%).

The mean percentile of weight, height, and HC according to age at health check was seen in Figure 1. Longitudinal analysis showed a significant difference in height, weight, and HC according to age, birth-weight group, and the combination of age and birth weight, respectively (*p* < 0.0001). The lower birth weight group showed a lower mean percentile of weight, height, and HC. There was a significant difference in height, weight, and HC between the low birth weight infants (<1000 g, 1000–1499 g, 1500–1999 g, 2000–2499 g) and the reference group with birth weight of 2500–4500 g according to age at health checkup.

**Figure 1.** Mean growth percentile of infants according to age at check-up by birth-weight group. (**a**) Height. (**b**) Weight. (**c**) Head circumference (HC). Significant differences in height, weight, and HC between the low birth weight infants groups and the reference group according to age at health checkup were shown. *p*-values were significant in height, weight, and head circumference between each low birth weight group and the reference group compared at age of health check-up.

A total of 10,227 (7.4%) infants had a poor HC growth at 60 months of age, 10,950 (7.92%) infants had poor height growth, and 12,481 (9.03%) infants had a poor weight growth. Using longitudinal analysis, this study found a significant difference in the incidence of poor height, weight, and HC growth according to age at health check, birthweight group, and combination of age and birth weight, respectively (*p* < 0.0001) (Figure 2). The lower birth-weight groups showed a higher incidence of poor weight, height, and HC growth. There was a significant difference in height, weight, and HC between the low birth weight group (<1000 g, 1000–1499 g, 1500–1999 g, and 2000–2499 g) and the reference group with birth weight of 2500–4500 g according to age at health checkup.

**Figure 2.** The incidence of poor growth (below 10th percentile) according to age at check-up by birth-weight group. (**a**) Height. (**b**) Weight. (**c**) Head circumference. A higher incidence of poor weight, height, and HC growth in the lower birth-weight groups was noted. A significant difference in height, weight, and HC between the low-birth-weight groups and the reference group according to age at health checkup were shown. *p*-values were significant in height, weight, and head circumference between each low-birth-weight group and the reference group compared at age of health check-up.

The Pearson correlation coefficient of the growth percentiles (the height, weight, and HC percentile) at 6 and 60 months of age obtained using correlation analysis is shown as Figure 3. Figure 3a was the results for the whole study population. Among the infants below 1000 g of birth weight, only weight showed a highly positive correlation (coefficient = 0.72) between 6 and 60 months of age, height (coefficient = 0.65) and HC (coefficient = 0.64) showed a moderate positive correlation. Pearson correlation coefficient analysis between 6 and 60 months of age was performed only among the infants who fell below 10th percentile in terms of height, weight, and HC at 60 months of age, and the results were shown in Figure 3b. Among the infants below 1000 g of birth weight, weight, height, and HC showed a weakly positive correlation; otherwise, there was no association.

**Figure 3.** Pearson correlation coefficient between 6 months of age and 60 months of age for birth-weight groups among whole population (**a**) and among infants who were below the 10th percentile of height, weight, and HC at 60 months of age (**b**).

> To analyze the relation between the growth at 6 months and 60 months, the risk of poor growth in the infants below 10th percentile of growth at 6 months was compared to the infants within 10–90th percentile of growth. The infant below the 10th percentile of HC and height at 6 months of age, respectively, showed the higher risk of HC and height below the 10th percentile at 60 months of age (HC, OR (95% CI) 1.62 (1.32–1.98); Height, 1.64 (1.38–1.95)). However, weight status at 6 months showed no significant association with the risk of weight below the 10th percentile at 60 months of age.

#### *3.2. Developmental Outcome*

The incidence of suspected developmental delay result at 60 months of age was 10% (29,020). In particular, further evaluation was recommended for 4572 (1.5%) infants, and the 'follow-up test' for 24,448 (8.5%) infants. According to the birth-weight group, K-DST results were presented in Table 2. The smaller birth weight group had a greater number of 'further evaluation' results. The infants below 1000 g of birth weight were only 0.2% of the screened population, but among them, 14.8% of this group had 'further evaluation' and 21.0% of this group had 'follow-up test' recommendations. The lower birth-weight groups showed a higher incidence of suspected developmental delay.

There is a significant difference in the incidence of suspected developmental delay results between the infants with poor weight, height, and HC growth and above 10th percentile at 60 months of age by birth weight group (Table 3). The infants with poor weight, height, and HC growth demonstrated higher frequency of suspected developmental delay results at 60 months of age.

Lower birth weight, male sex, poor HC, poor height, and poor weight were confirmed as factors associated with suspected developmental delay results at 60 months of age using multivariate logistic regression analysis (Table 4). Infants with poor HC at 60 months of age had more suspected developmental delay results (OR 1.81, 95% CI 1.66–1.98), and the infants who weighed less than 1000 g at birth had more suspected developmental delay (OR 5.05, 95% CI 3.79–6.73) compared to infants with 2500–4500 g birth weight.

Data are presented as Number or Number (%). BW, birth weight.

**Table 3.** Poor growth outcomes (below 10th percentile) at 60 months of age according to birth-weight group among the infants with suspected developmental delay results.

Data are presented as No. (%). BW, birth weight; WT, weight; HT, height; HC, head circumference.

**Table 4.** Multivariate logistic regression analysis for the suspected development delay results at 60 months of age.

HC, head circumference; HT, height; WT, weight; BW, birth weight.; OR, odds ratio; CI, confidence interval.


**6. References**

222 Recent Advances in Nanofabrication Techniques and Applications

We have investigated long-term reliability of fabricated DFB LDs. Figure 15 shows the timedependent change in the threshold current of phase-shifted LDs with the output power of 10 mW at the ambient temperature of 358 K. The number of samples is 18. The change in the threshold current after 5000 hours is less than ±1%, indicating that the phase-shifted DFB

> 0 1000 2000 3000 4000 5000 6000 Time [hour]

Fig. 15. Time-dependent change in the operation current of the DFB LDs with the output

We have successfully demonstrated fabrication of phase-shifted DFB LDs by utilizing NIL process, which have comparable characteristics and their uniformities to ones fabricated by conventional EBL process. Fabricated DFB LDs have shown high stability of characteristics in long-term reliability test. We have also demonstrated the feasibility of the VARI-mold, which can be used for the fabrication of DFB LDs with various wavelengths, indicating that we can drastically reduce the cost of molds in our mass production phase in the near future. Considering the results above, we conclude that NIL is a promising candidate of the production technique for phase-shifted DFB LDs featuring low cost and high throughput. NIL is expected to be used as a fabrication process for many applications. However, there are still some difficulties with its use as a mass-production process, for example, defects and low throughput in patterned media, defects and poor alignment accuracy in semiconductor lithography, and the necessary of increasing field size and throughput in displays. Although those difficulties may be common to the fabrication of DFB LDs, they would not be insurmountable problems. Even if defects in the imprinted pattern influence the yield of LDs, failed chips could be easily rejected because each dye is as small as approximately 300 m. There is no need for a larger field size than a 3-in.-diameter circle, because the diameter of compound semiconductor substrates used for LDs is 3 inches or smaller. Regarding alignment accuracy, an error of up to approximately 5 m is acceptable. Even if throughput is limited to less than one wafer per hour, NIL would still

LDs fabricated in this study have high stability in lasing characteristics.

power of 10 mW at the ambient temperature of 358 K.

have a higher throughput than EBL.

0

Change in threshold current [%]

5

10

**3.5 Reliability**

**4. Conclusion**

**12**

*1USA*

*2Republic of Korea*

**Guided-Mode Resonance Filters**

**Fabricated with Soft Lithography**

*Korea Advanced Institute of Science and Technology, Daejeon*

*2Department of Materials Science and Engineering,*

Kyu J. Lee1, Jungho Jin2, Byeong-Soo Bae2 and Robert Magnusson1 *1Department of Electrical Engineering, University of Texas at Arlington, Texas*

Methods of microscale and nanoscale patterning can be applied to fabricate a variety of optical devices. Periodic layered structures are found in integrated optics, communication systems, spectroscopy, lasers, and in many other important optical systems. Diffractive optical elements and photonic crystals consist of fine periodic patterns affecting the spectrum, polarization, phase, and amplitude of light. Often, holographic interferometry, or direct electron-beam patterning, is used to define the periodic structure. As an alternative method, soft lithography is effective for fabricating and transferring periodic patterns and structures as reported in recent papers (Xia & Whitesides, 1998) (Xia et al., 1999) (Schmid & Michel, 2000) (Odom et al., 2002) (T.-W. Lee et al., 2005) (Tang et al., 2003) (Rogers & Nuzzo, 2005) (D.-H. Lee et al., 2007). Accordingly, using methods and processes associated with soft lithography, new narrow-band resonant optical filters fabricated in hybrimer compounds

In this work, a new material system for fabricating the resonant optical filters is employed. Hybrimers are typical organic-inorganic hybrid materials fabricated using a sol-gel process (Choi et al., 2005) (Kim et al., 2006) (Kim et al., 2005). Hybrimers have several advantageous properties, including high modulus, low surface tension, low shrinkage, and high etching resistance. In particular, they have excellent optical properties including high transparency (>90% in the visible region), controllable refractive indices, low optical loss (<0.2 dB/cm), low birefringence (~10-4), and low viscosity compared to common ultraviolet (UV)-curable polymers (Kim et al., 2005) (T.-H. Lee et al., 2006). These materials possess thermal stability beyond 300 ºC. The versatile properties of hybrimers offer new options for practical applications related to microoptical devices. In the case of the fluorinated hybrimer used in this work, an organoalkoxysilane precursor functionalized with a perfluoroalkyl chain is used in the sol-gel reaction to lower the surface tension of the final compound. Hybrimers qualify both as molds and as resists in nanoimprint lithography (Kim et al., 2006). Significantly, there is no additional chemical treatment needed to release the mold due to the presence

**1. Introduction**

are presented.

of fluorine molecules in the hybrimer compound.


*3.1. Liquid CO2 Injection Process*

When the CO2 liquid was injected from the bottom of the cell, a CO2 liquid plume moved upward because of a buoyancy force. Eventually, the CO2 liquid front reached the CO2 hydrate stability zone, and then CO2 hydrates formed. The CO2 hydrate-bearing sediment layer then obstructed the upward flow of the CO2 liquid. While water and CO2 were consumed in the CO2 hydrate formation process in the hydrate stability zone, the CO2 hydrate-bearing sediment layer prevented CO2 supply. Thus, a pressure difference between the upper and lower part of the cell appeared. The P-wave velocity and electrical resistance monitoring results indicated the formation of CO2 hydrates and the blockage of the CO2 flow. Detailed experimental results are shown in the following sections.

#### 3.1.1. Temperature and Pressure

Figure 4 shows the pressure of each layer in the cell over time. The CO2 liquid was injected at 1300 min after data logging started. The pressure in each layer was scattered until 5000 min because of a difference in pressure between the injection pressure and backpressure (i.e., ~0.6 MPa, refer to Section 2.3.2), and volume change of pore fluids due to CO2 dissolution into pore water. The pressure in each layer was very similar to one another because the pore space was well connected throughout the sample. CO2 hydrates started to form when the injected CO2 reached the CO2 hydrate stability zone (herein, between layers A3 and A4; Figure 3). Then, the pressure in layers A1, A2, and A3 rapidly dropped to 3.3 MPa after 5000 min while the pressure of layers A4 and A5 were nearly constant and identical to the injection pressure. The difference in pressure between the upper and lower part of the cell was induced by the sealing (i.e., pore clogging) effect of the CO2 hydrate bearing-sediments layer.

**Figure 4.** Pressure of the cell with lapsed time during CO2 injection.

The sealing capacity of the CO2 hydrate-bearing sediment layer gradually increased during the growth of CO2 hydrates in the pore space of the sample. Meanwhile, water and CO2 were consumed during CO2 hydrate formation. For a constant-volume process, the consumption of CO2 and water during CO2 hydrate formation leads to a pressure decrease because the molar volume of the CO2 hydrates is smaller than the original molar volume of the consumed fluids. For the lower part of the cell (represented by layers A4 and A5) the pressure was preserved because CO2 was supplied continuously from the bottom of the cell during the experiment. For the upper part of the cell (represented by layers A1, A2, and A3), however, the pressure decreased because the CO2 hydrate-bearing sediment layer prevented the CO2 to be supplied from the lower part of the cell.

Figure 5 shows the pressure–temperature evolution during the CO2 injection test. Note that layers A2 and A3 were in the CO2 hydrate stable condition while the others were not. The pressure of the upper part of the cell (i.e., layers A1, A2, and A3) decreased when the sealing capacity of the CO2 hydrate-bearing sediment layer increased to a level that prevented flow. Note that there were no CO2 hydrates in layer A2 because the injected CO2 did not reach it, even though this layer is in the CO2 hydrate stability zone. Meanwhile, the lower part of the cell (i.e., layers A4 and A5) maintained a constant pressure level. Then, the pressure of the upper part of the cell gradually increased. There are two mechanisms for the pressure recovery of the upper part of the cell: (1) The uppermost CO2 hydrates dissociated with the pressure decrease. Therefore, pressure was recovered restrictively via emitted CO2 and water from the CO2 hydrates, and (2) CO2 hydrate saturation is limited by capillary pressure, which is determined by the pore size [23].

**Figure 5.** The pressure–temperature relationship during CO2 injection. (**a**) 4680–8100 min, (**b**) 8100– 25,300 min.

In the central part of the CO2 hydrate-bearing sediment layer, CO2 hydrates grew until the CO2 hydrate saturation reached maximum CO2 hydrate saturation. Thus, the consumption of CO2 and water diminished because any additional formation of CO2 hydrates was restricted. Finally, the pressure of the upper part of the cell increased to 5.2–5.5 MPa. However, the pressure of the upper part of the cell was still lower than that of the lower part of the cell. The repetitive ascending and descending pressure could be due to the continuous repetition of the CO2 formation and dissociation process at the CO2 hydrates front.

#### 3.1.2. P-Wave Velocity

Figure 6 shows the results of the P-wave velocity measurements during the CO2 injection process. Before the water injection process, the cell was partially saturated, and the P-wave velocity was about 900 m/s. When the sediment sample was saturated by distilled water, the P-wave velocity of all the layers was about 1600 m/s. Then, when the CO2 liquid was injected, the P-wave velocities of the lower part of the cell (i.e., layers A4 and A5) decreased because the bulk modulus of the CO2 liquid was much lower than that of the water [24,25]. Meanwhile, the P-wave velocity of layer A3 gradually increased because of the stiffening effect induced by CO2 hydrate formation. This P-wave velocity increase in layer A3 indicates that the CO2 hydrate bearing-sediment layer is between layers A3 and A4. On the other hand, the P-wave velocity of layer A1 and A2 did not change during CO2 injection. This is evidence that the CO2 hydrate-bearing sediment layer prevents any upward flow of the CO2 liquid.

**Figure 6.** P-wave velocity of the unconsolidated sediment sample during CO2 injection. (**a**) layer A1, (**b**) layer A2, (**c**) layer A3, (**d**) layer A4, (**e**) layer A5. P-wave velocity of layers A1 and A2 did not change during CO2 injection because the CO2 hydrate-bearing sediment layer prevented the upward flow of CO2 liquid.

#### 3.1.3. Electrical Resistance

Figure 7 shows the normalized electrical resistance (*R*/*R0*) during the CO2 injection process, where *R* is the measured electrical resistance and *R0* is the initial electrical resistance of the distilled water-saturated sample at each layer (i.e., layers B1–B4). For the lower part of the cell (i.e., layers B3 and B4), the electrical resistance decreased with CO2 injection because of the dissolution of CO2.

**Figure 7.** Normalized electrical resistance *R*/*R0* of the unconsolidated sediment sample during CO2 injection. (**a**) layer B1, (**b**) layer B2, (**c**) layer B3, (**d**) layer B4.

Electrical resistance increased in-situ in the marine sediments because the conductive pore water (i.e., brine) was replaced by CO2, which is a nonpolar molecule. This electrical resistance increase induced by the CO2 replacement was weakened by the dissolution of CO2 and the surface effect of the mineral grains [26]. For typical brine, the effect of CO2 dissolution on electrical resistance is negligible because the concentration of salt (i.e., NaCl) is much larger than the ionic concentration increased by CO2 dissolution [27]. However, if the salt concentration is low (e.g., onshore sediments), electrical resistance of in-situ sediments can decrease during the CO2 permeation [28]. In this experiment, the effect of dissolved CO2 was dominant on electrical resistance because the pore water was distilled.

Meanwhile, the electrical resistance of the upper part of the cell (i.e., layers B1 and B2) showed minor changes during CO2 injection. This is additional evidence demonstrating that CO2 liquid did not reach the upper part of the cell. Based on the change of the pressure, P-wave velocity and electrical resistance, we can presume that the CO2 hydrate formation front is located between layers A3 and B3. Meanwhile, CO2 hydrates formation was not observed in the electrical resistance data. The electrical resistance of in-situ water-saturated sediments increased when CO2 hydrates formed

because the electrical resistance of CO2 hydrates is higher than pore water [29,30]. In this study, however, the change in electrical resistance was insignificant in spite of the presence of CO2 hydrates, because distilled water was used as pore water in this experiment. This is the one of the limitations of this experiment.

#### *3.2. Depressurization Process*

#### 3.2.1. Temperature and Pressure

Figure 8 shows the pressure of each layer in the cell over time. The pressure of the cell was reduced step-wise using a back-pressure regulator. Pressure differences between the upper and lower part of the cell remained, even though CO2 was vaporized. This pressure discrepancy indicated that the sealing capacity of the CO2 hydrate-bearing sediment layer was preserved. When the CO2 hydrate dissociated completely, the pressure of each layer became equal.

**Figure 8.** Pressure of the cell with lapsed time during depressurization.

Figure 9 shows the pressure–temperature relationship during the depressurization test. The pressure of the cell dropped with the pressure release using the back-pressure regulator. When the pressure of layers A4 and A5 reached the CO2 vapor pressure, their pressure and temperature relation moved along the CO2 vapor pressure (Figure 9a). The path of the pressure and temperature relationship of layers A4 and A5 was similar to that of the isometric process because the flow of fluids was obstructed by the remaining CO2 hydrate-bearing sediment layer (Figure 9b). Then, the pressure and temperature relationship of layer A2 moved along the CO2 hydrate equilibrium line (Figure 9c). This is evidence that the CO2 hydrates re-formed and dissociated in layer A2. In the previous CO2 injection process, CO2 liquid did not reach layer A2 because of the sealing effect of the CO2 hydrate-bearing sediment layer, which was located between layers A3 and B3. However, CO2 was supplied to layer A2 when the existing CO2 hydrates partially dissociated by depressurization. CO2 hydrates then re-formed because layer A3 is in the CO2 hydrate stability zone. Then, CO2 hydrates in layer A3 dissociated by additional depressurization. During the dissociation of CO2 hydrates in layer A3, a self-preservation effect was observed in the pressure and temperature relationship as seen in previous experimental studies on CO2 hydrate dissociation [12,31]. Finally, CO2 hydrates completely dissociated with step-wise depressurization (Figure 9d).

**Figure 9.** The pressure–temperature relationship during depressurization. (**a**) 0–980 min, (**b**) 980–1770 min, (**c**) 1770–3300 min, (**d**) 3300–8700 min.

#### 3.2.2. P-Wave Velocity

Figure 10 shows the results of the P-wave velocity measurements taken during the depressurization process. The sealing effect of the original CO2 hydrate-bearing sediment layer reduced because some portion of the original CO2 hydrates dissociated. Thus, the P-wave velocity of layer A1 decreased because CO2 intruded the upper part of the cell. On the other hand, the P-wave velocity of layers A2 and A3 suddenly increased because CO2 hydrates formed using the CO2 supply from the lower part of the cell. Note that layers A2 and A3 were in the CO2 hydrate stability zone until 3300 minutes (refer to Figure 9). Meanwhile, the P-wave velocity of layers A4 and A5 decreased because CO2 vaporized during depressurization. When the pressure was lower than the equilibrium pressure of the CO2 hydrates (i.e., 4000–6000 min, refer to Figure 9d), the P-wave velocity of layers A2 and A3 suddenly decreased because reformed CO2 hydrates in these layers dissociated.

**Figure 10.** P-wave velocity of the unconsolidated sediment sample during depressurization. (**a**) layer A1, (**b**) layer A2, (**c**) layer A3, (**d**) layer A4, (**e**) layer A5.


**3. Results**

The results of applying the social learning analytical framework are categorized in the following three tables: materials, meanings and competences (See Tables 1–3). Within each, these codes are used: I—interactions between social learning processes and SPT elements in TD coproduction, EP—emergent property of coproduction and SLO—social learning outcome.

**Table 1.** Social learning analytical framework results—materials.

**Table 3.** Social learning analytical framework results—competences.


**Abstract**

The composition and production technology of the cheese are extremely diverse. There are a wide variety of microbial species on their surface, with a much smaller number inside of the product. The microbiota of the cheese may be composed of beneficial microorganisms, spoilage and foodborne pathogens. Identification and characterization of the microorganisms present in these products are important nutrition, food safety and technological aspects. During our work we evaluated the prevalence of allochthonous bacteria and microscopic fungi in traditionally processed cheeses from northeastern region of Transylvania, with classical microbiological culture methods. Based on the results the microbiota of the analysed cheeses was highly diversified. The identified bacteria with the highest prevalence from different selective media, were as follows: *Escherichia coli*, *Enterococcus durans*, *Enterococcus faecalis*, *Shigella flexnerii*, *Proteus vulgaris*, *Stenotrophomonas maltophilia*, *Staphylococcus equorum subsp. equorum, Staphylococcus equorum subsp. linens, Halomonas alkaliphila, Kocuria rhizophila, Hafnia paralvei, Bacillus licheniformis* and *Klebsiella michiganensis.*

**Keywords:** microbial diversity, traditionally processed cheeses, starter culture, allochthonous bacteria


**2. Description of the database**

*Data Integrity and Quality*

governance.

malignant tumors.

logical data.

numerous independent e-health service providers (hospital, primary services, regional governments). Therefore, to assure the quality of the data, new processes are required from origin to final service generation through an appropriate data

quality and curation [9] and to deploy new advanced services [2].

We can expect that new technologies such as blockchain will reduce this problem, introducing data interoperability, and security [4] and by the adoption of international standards for EHRD (Reference Model, ISO/DIS 13606–2, OpenEHR) [5–8]. However, we are just in the time when leveraging the power of health data to improve clinical or administrative decisions still requires an important effort to ensure the requested data quality. In this regard, many research studies discuss different approaches to improve

There have been several works addressing this problem of data analysis and curation of health information systems [10–13]. This chapter focuses on data quality analysis of electronic medical records and, in particular, of the database of the colorectal cancer screening programme of the Spanish region of Aragón.

The colo-rectal cancer (CRC) screening program of Aragón started in 2014 and, as many other similar programs in the world, is based on the result of a fecal immunohisto-chemical test (FIT) and is focused on medium risk population (ages between 50 and 69 years, without family history of CRC and without the presence of colon diseases, colectomy, or irreversible terminal diseases such as Alzheimer's). The result of this test determines whether it is necessary to perform a colonoscopy (positive cases) or the patient will be screened again after a predefined period. The objective of the program is to diagnose the colo-rectal cancer in its early stage

One of the difficulties/limitations that this type of programs usually encounters is the insufficient offer of colonoscopies, or the excessive demand derived from positive FIT cases in the invited population. It is necessary therefore to analyze the historical information to define a set of data-based risk indicators than can support the decision-making process in public health services, trying to set the least harmful criteria for selecting the patients who will finally undergo the colonoscopy. It is then clear the importance of the quality of the information stored concerning the clinical data of the patients participating in the program as well as the information of the tests carried out, the results of the colonoscopies and the associated patho-

Data collection, if performed by humans, is prone to filling errors. These potential errors can be reduced by a proper design of the database and of the user interface, avoiding redundancies, keeping consistency and checking known correlations. Therefore, it is necessary to establish "good practice" guidelines for data collection and management. With the aim of improving the redesign of the current platform, we carried out an exhaustive analysis of the data collected in the Aragón's regional colo-rectal screening program from 2014 to 2018. This analysis revealed considerable data noise, so we proposed a list of recommendations to improve their quality. We also carried out a curation process of the available data in order to have a

The recommendations arose from the identification of a series of assumptions and restrictions that the platform should contain to comply with the integrity, coherence and consistency of the data and, therefore, to mitigate the noise. They covered from the default value of each variable, its range, its mandatory character and the redundancy control, to other types of suggestions that include possible constraints on their values, relationships between variables, creation of new variables that may facilitate the analysis and possible warnings or alerts that could help the

clean source of information that would allow proper future analyses.

and/or to remove precancer polyps before they may evolve to potential

**22**

user to perform a correct data filling.

All the information of the CRC screening program in the region of Aragón (Spain) is stored in a centralized database that is fed from other external databases and from the personal information of the patient that is filled by hospital staff through a user-interface (UI) tool. This UI is a web application on which the patient information is displayed and managed. The information that contains comes from the different public hospitals in Aragón: San Jorge Hospital, Barbastro Hospital, Miguel Servet University Hospital, Lozano Blesa University Clinical Hospital, Ernest Lluch Hospital, Obispo Polanco Hospital of Teruel and Alcaniz Hospital. Therefore, the staff who use the platform have different roles, belong to different hospitals and have different degree of training. This means that the application must be as intuitive as possible, as well as to comply with sufficient checks to handle the data relationships correctly, reducing possible errors as much as possible during the data collection. This translates the problem to the good design of the database.

Furthermore, it is quite common in public institutions to have several contracts with different private companies in a short period of time. This usually implies waste of time in understanding, adapting and changing the structure to the way of working of each of company. Therefore, it makes even more sense to establish a good database design and architecture that allows its correct growth and maintenance.

In particular, this section explains the characteristics of the database of the colo-rectal cancer screening program of Aragón between 2014, when the program started, and 2018. In the following sections, the inconsistences found in its design and, therefore, in the data quality are exposed and a series of recommendations (and "good practices") are proposed to comply with data integrity, coherence and consistency as much as possible.

The existing database model is here explained in inverse order to the actual development of the database. First the final result is explained (relational model) and then the underlying model (entity-relationship model) is discussed [14].

#### **2.1 Relational model**

The database tables analyzed contain the following data information which is extracted from different sources of information:

CRC, presence of colonic disease, colectomy, irreversible disease (e.g., Alzheimer), previous negative FIT result, or previous negative colonoscopy outcome. This information is automatically dumped into the table from different health system databases, such as OMI-AP (clinical information of patients attended in primary care), CMBDH (clinical information of patients attended in hospital), HP-His (clinical information of ambulatory patients) and BDU (User Database).

	- Fecal immunochemical test (FIT): The result of this test comes from several laboratories, whose information is automatically uploaded to the table. This implies the need for a homogenization process for the information provided by the different labs, which might also provoke misunderstandings and associated errors.
	- Colonoscopy: The anatomo-pathological results of this test comes from several pathology laboratories, whose information is translated to the tables by health staff, which may also imply additional errors. Regarding the findings, the tables distinguish between the information about polyps and cancer lesions detected in the colonoscopy.

The whole information regarding the test procedure, preparation, exploration and findings is analyzed and entered into the platform by health professionals with different roles.

In summary, the information in the database comes from different external databases whose information is automatically dumped as well as from data filling by hospital staff with different roles. In these situations where several agents are involved and different information is crossed, we must ensure a good database design, proper data integration and an appropriate data checking and validation.


**4. Irradiation in textiles**

Irradiation processes have several commercial applications, in the coating of metals, plastics and glass, in printing, wood finishing, film and plastic cross linking and in the fields of adhesive and electrical insulations. The advantages of this technology are well known energy saving (low-temperature process), low environmental impact, simple, economical and high treatment speed. Despite these advantages, there have been few applications of radiation curing in the textile industry, such as non woven fabric bonding, fabric coating and pigment printing (Ferrero and Monica, 2011). Radiation treatment on fabric and garments can add value in colouration. Modification of the surface fiber can allow more dye uptake; its fixation at low temperature and increase wettability. Cotton knitwear pilling can be eliminated from the surface of the fabric by radiation treatment without affecting the strength of the fiber (Kim *et al.*, 2005).Effect of UV radiation in natural as well as synthetic dyeing using irradiated cotton fabric has given significant results.

#### **4.1 Effect of UV and gamma radiation on the fabric dyed with natural dyes**

There is a remarkable difference in colour strength when different extracts of irradiated and un-irradiated turmeric powder were used to dye the irradiated and un-irradiated fabric (Afifah *et al.*, 2011). The methanol solubilized extract gave more colour strength than aqueous (heat) solubilized and alkali solubilized extract as displayed in Fig. 2. The low colour strength using alkali solubilized extract is due to alkaline degradation of curcumin into products like vaniline, vanilic acid, feruloylmethane, ferulic acid and other fission products, which sorb on the fabric along with colourant and impart dull redder shades(Tonnesen and Karlsen,1985a). While using (heat) aqueous solubilized extract, the colourant being insoluble in water may undergo hydrolytic degradation and the actual colourant concentration becomes low onto the fabric as a result low colour strength is observed (Tonnesen and Karlsen, 1985 b). By using methanol solubilized extract, the actual colourant get significant chance to sorb onto fabric and impart yellow colour with dark shades.

The irradiation of fabric is also another factor which affects the colour strength of the fabric. Previous studies show that UV irradiation adds value to colouration and also increases the dye uptake ability of the cotton fabrics through oxidation of surface fibers of cellulose(Millington , 2000; Javed *et al* ., 2008). The colourants from Methanol solubilized extract reach the vicinities of fibres and upon investigation of colour strength using spectraflash SF 650, dark yellow shade was observed. In the case of un-irradiated fabric, the insoluble impurities get significant chance to sorb on the matrix along with colourant which showed the dull redder shades.

Effect of Radiation on Textile Dyeing 9

**(b)**

**RP/RC RP/NRC RC/NRP NRP/NRC Sample codes**

> Aqueous Alkaline

**100Gy 300Gy 500Gy 700Gy 900Gy**

**100Gy 300Gy 500Gy 700Gy 900Gy**

Fig. 3. Effect of gamma radiation on the colour strength of the cotton dyed with

(a) ethanolic (b) aqueous extracts obtained form irradiated and un-irradiated Eucalyptus powder. NRP-un-irradiated powder, RP – irradiated powder, RC- irradiated cotton fabric,

**Colour strength (%)**

**(a)**

NRC-un-irradiated cotton fabric

**RP/RC RP/NRC RC/NRP NRP/NRC Sample codes**

0

URP/RC

RP/URC

**Sample Codes**

The colour strength changes significantly in aqueous than in alkaline media. The fabrics dyed in aqueous extract of turmeric powder were darker yellow in shades than that of

Fig. 4. Effect of gamma radiation on the colour strength of the cotton dyed with extracts obtained form irradiated and un-irradiated turmeric powder using aqueous and alkaline media (Where URP-un-irradiated powder, RP – irradiated powder, RC- irradiated cotton

RP/RC

URP/URC

20

40

60

80

**Colour Strength (%)**

fabric, URC-un-irradiated cotton fabric )

100

120

140

160

**Colour strength (%)**

Fig. 2. Effect of UV radiation on the colour strength of the irradiated and un-irradiated cotton dyed with heat solubilized, alkali solubilized and methanol solubilized extract of irradiated and un-irradiated turmeric powder (Where URP-un-irradiated powder, RP – irradiated powder, RC- irradiated cotton fabric, URC-un-irradiated cotton fabric )

Gamma rays are ionizing radiations that interact with the material by colliding with the electrons in the shells of atoms. They lose their energy slowly in material being able to travel through significant distances before stopping. The free radicals formed are extremely reactive, and they will combine with the material in their vicinity. Upon irradiation the cross linking changes the crystal structure of the cellulose, which can add value in colouration process and causes photo modification of surface fibers. The irradiated modified fabrics can allow: more dye or pigment to become fixed, producing deeper shades, more rapid fixation of dyes at low temperature and increases wet ability of hydrophobic fibers to improve depth of shade in printing and dyeing (Millington, 2000).

The influence of gamma radiation on the colour strength values of the fabric dyed with natural dyes extracted from eucalyptus bark has been shown in Fig. 3. High colour strengths and dark brown shades of the fabric dyed in ethanolic extract were obtained as compared to aqueous extracts. The low colour strength and un-evenness in shade in aqueous extract is due to presence of insoluble impurities that might come on the fabric along with colourant.(Vankar *et al.*, 2000) The results shown in Fig. 3. demonstrate that irradiated fabric dyed using alcoholic extract gave more colour strength than un-irradiated fabric. Previous studies showed that gamma irradiation causes dislocation and fragmentation of fabric fibers (Foldvary *et al.*, 2003) however, only soluble colourant free from impurities get maximum chances to sorb on the fabric. But un-irradiated fabric contained less dye and yielded greener shade.

Colour Strength (%)

URP/URC

of shade in printing and dyeing (Millington, 2000).

greener shade.

URP/RC

RP/URC

Sample Codes

un-irradiated cotton dyed with heat solubilized, alkali solubilized and methanol

Gamma rays are ionizing radiations that interact with the material by colliding with the electrons in the shells of atoms. They lose their energy slowly in material being able to travel through significant distances before stopping. The free radicals formed are extremely reactive, and they will combine with the material in their vicinity. Upon irradiation the cross linking changes the crystal structure of the cellulose, which can add value in colouration process and causes photo modification of surface fibers. The irradiated modified fabrics can allow: more dye or pigment to become fixed, producing deeper shades, more rapid fixation of dyes at low temperature and increases wet ability of hydrophobic fibers to improve depth

The influence of gamma radiation on the colour strength values of the fabric dyed with natural dyes extracted from eucalyptus bark has been shown in Fig. 3. High colour strengths and dark brown shades of the fabric dyed in ethanolic extract were obtained as compared to aqueous extracts. The low colour strength and un-evenness in shade in aqueous extract is due to presence of insoluble impurities that might come on the fabric along with colourant.(Vankar *et al.*, 2000) The results shown in Fig. 3. demonstrate that irradiated fabric dyed using alcoholic extract gave more colour strength than un-irradiated fabric. Previous studies showed that gamma irradiation causes dislocation and fragmentation of fabric fibers (Foldvary *et al.*, 2003) however, only soluble colourant free from impurities get maximum chances to sorb on the fabric. But un-irradiated fabric contained less dye and yielded

Fig. 2. Effect of UV radiation on the colour strength of the irradiated and

solubilized extract of irradiated and un-irradiated turmeric powder (Where URP-un-irradiated powder, RP – irradiated powder, RC- irradiated cotton fabric, URC-un-irradiated cotton fabric )

RP/RC

Heat Solubilized

Alkali Solubilized

Methanol solubilized

Fig. 3. Effect of gamma radiation on the colour strength of the cotton dyed with (a) ethanolic (b) aqueous extracts obtained form irradiated and un-irradiated Eucalyptus powder. NRP-un-irradiated powder, RP – irradiated powder, RC- irradiated cotton fabric, NRC-un-irradiated cotton fabric

Fig. 4. Effect of gamma radiation on the colour strength of the cotton dyed with extracts obtained form irradiated and un-irradiated turmeric powder using aqueous and alkaline media (Where URP-un-irradiated powder, RP – irradiated powder, RC- irradiated cotton fabric, URC-un-irradiated cotton fabric )

The colour strength changes significantly in aqueous than in alkaline media. The fabrics dyed in aqueous extract of turmeric powder were darker yellow in shades than that of

Effect of Radiation on Textile Dyeing 11

Reactive Disperse

> Reactive Disperse Mixed

 0 mint 30 mint 60 mint 90 mint **Irradiation Time**

Fig. 6. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric

Reactive Disperse Mixed

**C olor S trength (% )**

(a) (b)

The un-irradiated and irradiated cotton fabric for the period of 30, 60 and 90 min was dyed, the results of fabrics have been shown in Figure 7. (a,b) shows that irradiated fabric and irradiated dyes for 90 min has maximum affinity for dye to attach on it. Oxidation of cellulose upon UV radiation significantly increases the dye uptake in the substrate due to the interstices available in the case of irradiated fabric surface (Michael and EL-Zaher, 2005).

Fig. 7. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric dyed with un-irradiated multifunctional triazine (a) and irradiated reactive and dianix

 0 mint 30 mint 60 mint 90 mint **Irradiation Time**

The above Fig. 6. shows that the fabric irradiated for 90 min. has maximum affinity for dye substrate to attach. The fabric irradiated for 30 and 60 minutes show even shades having good colour strength. This improvement might be due to the oxidation of cellulose in to carboxylic acid group upon exposure of cellulose to UV radiation which interacts more

dyed with un-irradiated reactive and disperse dye

towards the dye material to form covalent bond.

 0 mint 30 mint 60 mint 90 mint **Irradiation Time**

disperse and mixed dye (b)

**Color Strength (%)**

**C o lo r S tren g th (% )**

fabrics dyed in alkaline extract. The low colour strength was due to alkaline degradation of curcumin into water-soluble products like vaniline, vanilic acid, feruloylmethane, ferulic acid and other fission products, which gave dull redder shades (Tonessen and Karlsen, 1985a). Tonessen and Karlsen reported that below pH 7, curcumin existed in yellow colour and is insoluble in water (Tonessen and Karlsen, 1985b). Due to insolubility, the colourant might have tendency to get absorbed completely on the fabric without passing through the medium and shows darker yellow shades. Hence irradiated fabrics dyed in aqueous media gave more colour strength than un-irradiated fabrics due to oxidative degradation of cellulose fibres. Treatment of fabric by high-energy radiation causes either dislocation and fragmentation or slight loss in mass of fabric (Foldvary *et al.*, 2003; Takacs *et al.*, 2000). However, only colourants get maximum chance to sorb on fabric than insoluble impurities. So more colour strength is obtained in case of irradiated fabric dyed using aqueous extract of irradiated turmeric powder. Thus it is found that if irradiated fabric dyed with aqueous extract of irradiated turmeric powder, maximum colour strength and darker yellow shade was obtained.

#### **4.2 Effect of UV and gamma radiation on the fabric dyed with synthetic dyes**

UV irradiation effects the colour strength values and shades of fabric dyed with synthetic dyes. Using suitable dye and fabric, the process of irradiation can produce large variation in shades.

Fig. 5. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric dyed with irradiated stilbene based reactive dye

The data displayed in Fig 5. shows that irradiated fabric for 120 min. gave maximum colour strength as compared to un-irradiated fabric. The fabric irradiated for 120 min. showed even shade with better colour strength. The reason might be the oxidation of cellulose upon exposure to UV radiation. Michael and EL-Zaher in 2005 reported that the UV treatment of cellulose fibre created spaces between fibres which imbibed more dye and as a result the interaction between dye and cellulose fabric becomes more significant. The dye molecules rush rapidly onto the fabric and as a result darker shades were obtained (Tayyba, 2010).

fabrics dyed in alkaline extract. The low colour strength was due to alkaline degradation of curcumin into water-soluble products like vaniline, vanilic acid, feruloylmethane, ferulic acid and other fission products, which gave dull redder shades (Tonessen and Karlsen, 1985a). Tonessen and Karlsen reported that below pH 7, curcumin existed in yellow colour and is insoluble in water (Tonessen and Karlsen, 1985b). Due to insolubility, the colourant might have tendency to get absorbed completely on the fabric without passing through the medium and shows darker yellow shades. Hence irradiated fabrics dyed in aqueous media gave more colour strength than un-irradiated fabrics due to oxidative degradation of cellulose fibres. Treatment of fabric by high-energy radiation causes either dislocation and fragmentation or slight loss in mass of fabric (Foldvary *et al.*, 2003; Takacs *et al.*, 2000). However, only colourants get maximum chance to sorb on fabric than insoluble impurities. So more colour strength is obtained in case of irradiated fabric dyed using aqueous extract of irradiated turmeric powder. Thus it is found that if irradiated fabric dyed with aqueous extract of irradiated turmeric powder, maximum colour strength and darker yellow shade

**4.2 Effect of UV and gamma radiation on the fabric dyed with synthetic dyes**

UV irradiation effects the colour strength values and shades of fabric dyed with synthetic dyes. Using suitable dye and fabric, the process of irradiation can produce large variation in

> 0 min 30 min 60 min 90 min 120 min 150 min **Irradiation time**

Fig. 5. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric

The data displayed in Fig 5. shows that irradiated fabric for 120 min. gave maximum colour strength as compared to un-irradiated fabric. The fabric irradiated for 120 min. showed even shade with better colour strength. The reason might be the oxidation of cellulose upon exposure to UV radiation. Michael and EL-Zaher in 2005 reported that the UV treatment of cellulose fibre created spaces between fibres which imbibed more dye and as a result the interaction between dye and cellulose fabric becomes more significant. The dye molecules rush rapidly onto the fabric and as a result darker shades were

was obtained.

**Color Strength (%)**

obtained (Tayyba, 2010).

dyed with irradiated stilbene based reactive dye

shades.

Fig. 6. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric dyed with un-irradiated reactive and disperse dye

The above Fig. 6. shows that the fabric irradiated for 90 min. has maximum affinity for dye substrate to attach. The fabric irradiated for 30 and 60 minutes show even shades having good colour strength. This improvement might be due to the oxidation of cellulose in to carboxylic acid group upon exposure of cellulose to UV radiation which interacts more towards the dye material to form covalent bond.

Fig. 7. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric dyed with un-irradiated multifunctional triazine (a) and irradiated reactive and dianix disperse and mixed dye (b)

The un-irradiated and irradiated cotton fabric for the period of 30, 60 and 90 min was dyed, the results of fabrics have been shown in Figure 7. (a,b) shows that irradiated fabric and irradiated dyes for 90 min has maximum affinity for dye to attach on it. Oxidation of cellulose upon UV radiation significantly increases the dye uptake in the substrate due to the interstices available in the case of irradiated fabric surface (Michael and EL-Zaher, 2005).

Effect of Radiation on Textile Dyeing 13

RP/RC RP/NRC NRP/NRC

> 0.50% 1.00%

100 200 300 400 500 **Doses(Gy)**

cotton fabric dyed with Irradiated and un- irradiated reactive blue dye powder

Fig. 9. Effect of gamma irradiation on the colour strength of the irradiated and un-irradiated

The result displayed in Fig. 10. reveal that colour strength values decrease with increase in absorbed doses. The more colour strength is because of photo modified surface of cellulose which may have more affinity for dye substrate (Mughal *et al.*, 2007). The results show that the dyeing performed using 200Gy dose gives maximum colour strength with darker shades. At sufficient higher dose insoluble impurities along with dye molecule become fixed and causes uneven shades, while below optimum dose, surface of cellulose do not stimulate much to interact significantly with dye material. Thus dyeing performed using cotton fabric irradiated to an absorbed dose of 200Gy gave better colour strength

> 100 Gy 200 GY 300 Gy 400 Gy 500 Gy **Absorbed doses**

Fig. 10. Effect of gamma irradiation on the colour strength of irradiated cotton fabric dyed

0

20

40

60

80

**Colour strength(%)**

(Toheed Asghar, 2009).

**Colour strength (%)**

with Irradiated reactive black dye powder

100

120

140

The dye molecules rush rapidly on to the fabric and as a result darker shades were obtained (Sajida Parveen, 2009, Afifah Kausar, 2009; Afifah *et al.*, 2011). Previous study carried out by K.R. Millington suggested that photo modification of surface fiber may attain more dye or pigment to become fixed producing deeper shades. UV radiation causes more rapid fixation of dyes increases wettability of hydrophobic fibers to improve depth and shade in printing. For knitted wool and cotton fabrics, the problem of pilling can be eliminated.

Fig. 8. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric dyed with un-irradiated and irradiated 5 % (a) and 1% (b) Reactive Blue dye

The result shown in Fig. 8. (a & b) indicate that colour strength values of 5% solution of dye powder are more as compared to colour strength values obtained in case of 1 % solution. The optimized time for irradiating cotton fabric is 30 minutes as shown in Fig. 8. (a & b).At this time, oxidation of cellulose generates carboxylic acid group which helps in significant interaction of dye with oxidized a surface and show darker shades. Irradiation for less time does not activate the surface to interact with dye molecules to such an extent. While irradiation for long time may either facilitate insoluble impurities to rush onto modified fabric due to availability of wide interstices /gaps among the fibers which may cause dull and uneven shades having low colour strength (Saddique, 2008).

*Gamma radiation* shows a promising influence in textile dyeing since irradiated fabric dyed with synthetic dye gave a prominent difference The result shown in Fig. 9. indicate that colour strength values change remarkably using irradiated fabric which results in darker colour strength and more bluer shades than that of un-irradiated fabrics. This low colour strength is due the stuffing of insoluble impurities present in the dye solution on to the fabric.

Results given in Fig. 9. show that the dyeing performed using irradiated fabric treated with 300Gy absorbed dose gave maximum colour strength with darker bluer shades. At higher doses, low colour strength is obtained, which may be due to the degradation or dislocation of crystal moieties on cellulosic material (Foldvary *et al.* 2003; Takacs *et al.*2000). While at low dose, fabric surface does not activate enough to fix dye onto it and does not able to make firm interaction with dye material.

The dye molecules rush rapidly on to the fabric and as a result darker shades were obtained (Sajida Parveen, 2009, Afifah Kausar, 2009; Afifah *et al.*, 2011). Previous study carried out by K.R. Millington suggested that photo modification of surface fiber may attain more dye or pigment to become fixed producing deeper shades. UV radiation causes more rapid fixation of dyes increases wettability of hydrophobic fibers to improve depth and shade in printing.

**C oluo r Stren g th (% )**

Fig. 8. Effect of UV irradiation time on the colour strength of the irradiated cotton fabric

The result shown in Fig. 8. (a & b) indicate that colour strength values of 5% solution of dye powder are more as compared to colour strength values obtained in case of 1 % solution. The optimized time for irradiating cotton fabric is 30 minutes as shown in Fig. 8. (a & b).At this time, oxidation of cellulose generates carboxylic acid group which helps in significant interaction of dye with oxidized a surface and show darker shades. Irradiation for less time does not activate the surface to interact with dye molecules to such an extent. While irradiation for long time may either facilitate insoluble impurities to rush onto modified fabric due to availability of wide interstices /gaps among the fibers which may cause dull and uneven shades having low colour strength (Saddique,

*Gamma radiation* shows a promising influence in textile dyeing since irradiated fabric dyed with synthetic dye gave a prominent difference The result shown in Fig. 9. indicate that colour strength values change remarkably using irradiated fabric which results in darker colour strength and more bluer shades than that of un-irradiated fabrics. This low colour strength is due the stuffing of insoluble impurities present in the dye solution on to the

Results given in Fig. 9. show that the dyeing performed using irradiated fabric treated with 300Gy absorbed dose gave maximum colour strength with darker bluer shades. At higher doses, low colour strength is obtained, which may be due to the degradation or dislocation of crystal moieties on cellulosic material (Foldvary *et al.* 2003; Takacs *et al.*2000). While at low dose, fabric surface does not activate enough to fix dye onto it and does not able to make

dyed with un-irradiated and irradiated 5 % (a) and 1% (b) Reactive Blue dye

20 30 40 50 60 **Irradiation Time (min)**

RP/RC RP/NRC NRP/RC NRP/NRC

For knitted wool and cotton fabrics, the problem of pilling can be eliminated.

RP/RC RP/NRC NRP/RC NRP/NRC

**Colour Strength (%**

2008).

fabric.

firm interaction with dye material.

 **)**

> 20 30 40 50 60 **Irradiation Time (min)**

Fig. 9. Effect of gamma irradiation on the colour strength of the irradiated and un-irradiated cotton fabric dyed with Irradiated and un- irradiated reactive blue dye powder

The result displayed in Fig. 10. reveal that colour strength values decrease with increase in absorbed doses. The more colour strength is because of photo modified surface of cellulose which may have more affinity for dye substrate (Mughal *et al.*, 2007). The results show that the dyeing performed using 200Gy dose gives maximum colour strength with darker shades. At sufficient higher dose insoluble impurities along with dye molecule become fixed and causes uneven shades, while below optimum dose, surface of cellulose do not stimulate much to interact significantly with dye material. Thus dyeing performed using cotton fabric irradiated to an absorbed dose of 200Gy gave better colour strength (Toheed Asghar, 2009).

Fig. 10. Effect of gamma irradiation on the colour strength of irradiated cotton fabric dyed with Irradiated reactive black dye powder

Effect of Radiation on Textile Dyeing 15

Abdul Fattah, S., E. El-Khatib, A.Z.K Antouch and I.El-Zawawi. 2010. Finishing of wool

Afifah Kausar. 2009. Effect of UV irradiation time on the colour strength of the irradiated

Afifah,K., I.A.Bhatti, S.Adeel and E.Osman. 2011. Influence of UV radiations on the

Deo, H.T and B.K. Desai., 1999. Dyeing of cotton and jute with tea as natural dye. Journal

Ellison, M.S. 2003. "Piezoelectricity in Natural and Synthetic Silks". Spring Symposium,

Ferreo, F. and M. Periolatto. 2011. UV curing for surface modification of textile fabric. J.

Ferrero. F and Monica. P. 2011. Ultraviolet Curing for Surface Modification of Textile

Foldvary, C.M., E. Takacs and L. Wojnarovits. 2003. Effect of high energy radiation and

Gulrajani, M. L. 1992. Introduction to dyes. Indian institute of technology, New Delhi: 1-2. Hunger, K.2003. Industrial Dyes: Chemistry, Properties, Application. Wiley –Vch-Verley

Javed, I., Bhatti, I.A., Adeel, S., 2008.Effect of UV radiation on dyeing of cotton fabric with extracts of henna leaves. Indian Journal of fiber and textile research, 33,157-162. Jun, Z., and Chen, G.Q., 2006. The study of the Structures of Silk Fibers Grafted with

Jun, L., Y. Min and H. Hongfei. 2001. Solvent effect on grafting polymerization of NIPAAM

Kim, T.K., M.K. Kim and Y.A. Son. 2005. Degradation of the diazo by the sulfur-containing

Kiran. M. 2009. Effect of UV radiation on dyeing of cotton and polyester fabric.

Michael, M.N., and El-Zaher, N.A. 2005. Investigation into the effect of UV/ozone treatment on the dyeing properties of natural dyes on natural fabrics. Colourage. 52:83-88. Millington K.R. 1998 (c): U.S.A. Patent. Application of UV surface treated in textile industry.

Millington, K.R. 1997.Wool and Wool blend fabric treated: US Patent Document: 5,595,572:1-8. Millington, K.R. 1998(a): Use of UV Radiation to reduce pilling of knitted wool and cotton.

amino acids of wool fibers. Dyes and Pigment, 78: 67-127.

fabric with metal ion and silver nano particles to acquire antimicrobial and UV

cotton fabric dyed with irradiated multifunctional triazine reactive and dianix

extraction and dyeing of cotton fabric with *Curcuma longa* L. Indian J. Fibre and

Advanced Flexible materials and structure: Engineering with fibers. June 30- July 2,

alkali treatment on the properties of cellulose. J.Radiation Physics and Chemistry.

Hexaflurobutyl Methacrylate, International Forum of textile and Engineering for

on cotton cellulose via-pre irradiation method. Rdiation Physics and Chemistry.55:

Red Tech 98 North Americas: UNEB Conference Proceeding Chicago ILLINOIS

**7. References**

properties. R.J.T.A. 14(1):53-64.

Textile Research (In Press)

Loughborough, England

Fabrics. 11: 0-1

67: 505–508

625-628.

America.

disperse and mixed dye. M.Phil. Thesis. 45-48

Society Dyers and Colourists.115:224-227.

Nano science and Nanotechnology/11(xx):

GmbH kGA, Weinheim, Germany

Doctoral candidates, China.

M.Phil.Thesis. 27:30

J.Textile Research 68(6): 413-421.

#### **4.3 Effect of UV and gamma radiation on wool and silk and polyester**

Studies on wool keratin have been previously performed in order to evaluate the effect of UV radiation. Chemical changes induced by short term UV radiation are confined to fibers at surface where as it is unable to penetrate into the fabric. The colour changes i.e. green followed by yellow in wool keratin due to UV radiation have been observed also (Millington, 2000).There are several processes to reduce the pilling yet no process can guarantee the zero pilling in wear. But Millington reported that it is only UV radiation which can reduce the pilling through siro flash technology followed by oxidation with hydrogen peroxide in germicidal UV Tubes. After using such techniques and then dyeing with UV irradiated wool fabric, the characterization of wool fabric meets standard marks by ISO. Thus the continuous UV reduction of the fabric followed by batch oxidation is of great commercial value. (Millington, 1998a; Millington, 1998b; Millington, 1997).

When wool fabric is exposed to UV radiation, it exhibits some physical and chemical changes on its surface. This interaction not only modifies the fabric of wool but also improve the shades particularly grey and black. It also helps in even dyeing, deeper shades, chlorine free printing and improve the photo bleaching of wool (Millington, 1998c). Now a days, UV curing technology is being used for the modification of wool surface that helps in finishing as well as deepening the shades of wool when dyed using reactive dyes. By using UV curing technology, there are no risks involved to any loss of fabrics fibers in weight as well as in its physical appearance. This technology also do not cause any hazardous use of chemicals, smoothness of surface, unpilling as well as deep hues (Ferrero and Periolatto, 2011; Abdul Fattah *et al.*, 2010).

#### **5. Conclusion**

Radiation processes has several commercial applications starting from curing of fabrics, finishing, improvement of shades and characterization of dyed fabrics. The advantage of this technology are well known such as improvement in shades , enhanciong colour fastness , colour stregnth , low cost effective and reduction of the concentration of the dye. All these results have been seen from our above experiments. Radiation curing of silk, wool and cotton fabric to reduce pilling , their finishing and mercerization processes has also been improved. Thus both UV and gamma radiation has improved the textile sttuff according to standards of ISO , EPA and FAO.

The use of eco-friendly technnology giving eco–label products under the influence of high energy radiations that may give new orientation for other dyes such as vat, reactrive azo and other brands. Similarly improvement of fibers of wool , silk , nylonn , Polyester cotton (P.C). etc., for dyeing to get good shades, even and lavelled dyeing, accepatable fastness properties yet are underway.So the dyers and colourists should try such techniques inorder to get better results and alternating methods for any risks related to human health.

#### **6. Acknowledgement**

The authors are thankful to Dr. H. F. Mansour, Dr. Eman Osman, Dr. Nagia Ali and Dr. Khaled El Negar from Natioanal Textile Research Centre, Cairo Egypt, Dr. M. Zuber, Professor of Applied Chemistry, GC Univeristy Faisalaabd Pakistan for valuable discussion during this work. We are grateful to Abher Rashid, T. Bechtold and Peter Hauser for their technical help.

#### **7. References**

14 Textile Dyeing

Studies on wool keratin have been previously performed in order to evaluate the effect of UV radiation. Chemical changes induced by short term UV radiation are confined to fibers at surface where as it is unable to penetrate into the fabric. The colour changes i.e. green followed by yellow in wool keratin due to UV radiation have been observed also (Millington, 2000).There are several processes to reduce the pilling yet no process can guarantee the zero pilling in wear. But Millington reported that it is only UV radiation which can reduce the pilling through siro flash technology followed by oxidation with hydrogen peroxide in germicidal UV Tubes. After using such techniques and then dyeing with UV irradiated wool fabric, the characterization of wool fabric meets standard marks by ISO. Thus the continuous UV reduction of the fabric followed by batch oxidation is of great

When wool fabric is exposed to UV radiation, it exhibits some physical and chemical changes on its surface. This interaction not only modifies the fabric of wool but also improve the shades particularly grey and black. It also helps in even dyeing, deeper shades, chlorine free printing and improve the photo bleaching of wool (Millington, 1998c). Now a days, UV curing technology is being used for the modification of wool surface that helps in finishing as well as deepening the shades of wool when dyed using reactive dyes. By using UV curing technology, there are no risks involved to any loss of fabrics fibers in weight as well as in its physical appearance. This technology also do not cause any hazardous use of chemicals, smoothness of surface, unpilling as well as deep hues (Ferrero and Periolatto, 2011; Abdul

Radiation processes has several commercial applications starting from curing of fabrics, finishing, improvement of shades and characterization of dyed fabrics. The advantage of this technology are well known such as improvement in shades , enhanciong colour fastness , colour stregnth , low cost effective and reduction of the concentration of the dye. All these results have been seen from our above experiments. Radiation curing of silk, wool and cotton fabric to reduce pilling , their finishing and mercerization processes has also been improved. Thus both UV and gamma radiation has improved the textile sttuff according to

The use of eco-friendly technnology giving eco–label products under the influence of high energy radiations that may give new orientation for other dyes such as vat, reactrive azo and other brands. Similarly improvement of fibers of wool , silk , nylonn , Polyester cotton (P.C). etc., for dyeing to get good shades, even and lavelled dyeing, accepatable fastness properties yet are underway.So the dyers and colourists should try such techniques inorder to get better results and alternating methods for any risks related to human

The authors are thankful to Dr. H. F. Mansour, Dr. Eman Osman, Dr. Nagia Ali and Dr. Khaled El Negar from Natioanal Textile Research Centre, Cairo Egypt, Dr. M. Zuber, Professor of Applied Chemistry, GC Univeristy Faisalaabd Pakistan for valuable discussion during this work. We are grateful to Abher Rashid, T. Bechtold and

**4.3 Effect of UV and gamma radiation on wool and silk and polyester**

commercial value. (Millington, 1998a; Millington, 1998b; Millington, 1997).

Fattah *et al.*, 2010).

**5. Conclusion**

health.

standards of ISO , EPA and FAO.

**6. Acknowledgement**

Peter Hauser for their technical help.

**2**

*Australia*

+ 2Na2SO3 + 2H2O

**Dyeing Wool with Metal-free Dyes –**

**Application of Vat Dyes to Wool**

John A. Rippon, Jackie Y. Cai and Shaun M. Smith

*CSIRO Materials Science and Engineering,*

**The Use of Sodium Borohydride for the**

O-

S

O-

Na<sup>+</sup> Na<sup>+</sup>

Vat dyestuffs are pigments that must be pre-treated with a reducing agent, such as sodium hydrosulphite, to make them water-soluble immediately before they are used for dyeing (Latham, 1995; Trotman, 1984). The reduction step converts the pigment form into a leuco compound. This owes its name to the Greek word for colourless, because many vat dyes are very pale in colour when in the reduced state, due to the lower level of conjugation of double bonds. A schematic of this reaction for the dyestuff Vat Red 1 is shown in Figure 1.

Na2S2O4

Vat Red 1 Leuco Compound

4NaOH <sup>S</sup>

Fig. 1. Structure of Vat Red 1 and formation of the sodium salt of the leuco compound.

In strongly alkaline conditions, the leuco forms of vat dyestuffs are anionic and soluble in water. They can be exhausted onto cotton from long liquors under alkaline conditions in the presence of an electrolyte, such as sodium chloride or sodium sulphate (Latham, 1995; Trotman, 1984). After adsorption by the substrate, the leuco form of the dye is oxidised back to the insoluble coloured pigment inside the fibre. This can be done by exposure to air, or with an oxidising agent such as hydrogen peroxide. Wool is usually dyed with anionic dyestuffs from acidic dyebaths, where the amphoteric wool fibres are positively charged as a result of protonation of amino and carboxyl groups. Under alkaline conditions, however, fewer amino groups are protonated and, depending on the pH, the net charge on the fibres may be neutral or even negative. The effect of this is that conventional acid, premetallised and reactive wool dyes have a lower substantivity for wool under alkaline conditions than under acidic conditions. In contrast to this behaviour, however, even under strongly alkaline conditions, the anionic leuco form of a vat dyestuff has a relatively high substantivity for wool (Bird, 1947; Hug, 1948; Luttringhaus, Flint & Arcus, 1950; Weber, 1951) and wool/cotton blends (Lemin & Collins, 1959). This results in high levels of dyebath

**1. Introduction**

S

S

exhaustion at pH values as high as pH 9 and above.

O

O


*Edited by Sylvie Manguin and Vas Dev*

*Towards Malaria Elimination - A Leap Forward* was started to mark the occasion for renewed commitment to end malaria transmission for good (the WHO's call for 'Malaria Free World' by 2030). This book is dedicated for the benefit of researchers, scientists, program and policy managers, students and anyone interested in malaria and other mosquito-borne diseases with the goal of sharing recent information on success stories, innovative control approaches and challenges in different regions of the world. Some main issues that emerged included multidrug-resistant malaria and pandemic risk, vaccines, cross-border malaria, asymptomatic parasite reservoir, the threat of Plasmodium vivax and Plasmodium knowlesi, insecticide resistance in Anopheles vectors and outdoor malaria transmission. This book is one little step forward to bring together in 17 chapters the experiences of malaria-expert researchers from five continents to present updated information on disease epidemiology and control at the national/regional level, highlighting the constraints, challenges, accomplishments and prospects of malaria elimination.

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Towards Malaria Elimination - A Leap Forward

Towards Malaria Elimination

A Leap Forward