Edge computing is a novel network architecture that is in proximity to the end devices in an Internet of Things (IoT). As the IoT becoming a major factor in our daily life, provisioning a low response time of the services to IoT users through edge computing is an important problem. Caching necessary program data for the task in an edge node effectively reduces the response time of the computation task. However, due to the increase of IoT users and devices, it is noteworthy that limited-resource edge nodes would receive a number of tasks, having a heavy burden of processing the requests. Therefore, the limited resource and caching space at cloudlet need the careful design of the caching algorithm to utilize the space of multiple edge nodes and relieve the burden of computations. In this paper, we propose a cooperative program caching system that makes different edge nodes cooperatively store program data and cache the replicas of the data requested frequently to handle a number of requests from IoT users. In particular, we develop a cooperative caching algorithm that caches the appropriate number of data replicas depending on the number of requests on each cloudlet and the popularity of the data to minimize the response time. The simulation results show that the proposed cooperative caching algorithm can effectively reduce the response time for IoT users compared to other existing algorithms. The realization of Internet-of-Things (IoT) envisions ubiquitous connectivity among billions of smart devices over the future Internet. The IoT is being assimilated into human lives from healthcare, smart homes, intelligent transportation, and industrial manufacturing to smart cities , 2. Howeprogram data caching. It may take seconds to load all necessary programs from the cloud. Hence, caching program data in the cloudlets can reduce the delay caused by loading the program from the cloud. That is, the popular program data is cached at the cloudlet and then, there is no need to load the program if the task is executed at the cloudlet which caches the program data. We refer to the caching input and output data of computation tasks as content caching. However, the input and output data are hardly reused in the IoT scenario having short life time of the input and output data  is a weight and We denote let i as :p¯j=(1-h). The hit ratio is defined as the probability of finding the program required for the task in the cache of cloudlets. We then can express the hit ratio as:Using the average popularity, i ∈ I(1 − xij) becomes zero if one of the cloudlets i ∈ I caches the program data j. The binary variable xij is decided by CDA in CS when it performs the caching decision. The details about the caching decision process will be explained in Section 5.2.The above equation means the probability of finding of at least one cloudlet that caches the required program data in the IoT edge. The last part of i, the transmission time between IoT users and the cloudlet i, tij can be expressed as:ri is the average transmission rate at the cloudlet i and sj is the size of input data of the task that requires the program j. Since the size of the result is usually very small, the delay to receive the result is negligible [k will be allocated to a bandwidth β for transmitting its task. We denote Pik and cik as the transmit power of and channel gain from IoT user k to i, respectively. Let σ is Gaussian noise, the transmission rate beteen rik achieved at IoT user can be written as If an IoT user transmits the task to an optimal cloudlet gligible , 30. EacTmiss is the sum of total transmission time and execution time between IoT user and the cloud when the task is executed in the cloud.Then, we now can get the total transmission time including the cases of the task is executed in the cloudlet or the cloud, i. The tasks have different computing workloads following the distribution of the general service rate. Hence, we model the waiting time of requests at the cloudlet as an M/G/1 queuing system [When the task requests arrive at the cloudlet, each cloudlet is supposed to process one task at a time. A large number of task requests are sent to the cloudlet and so the tasks must be queued . We assug system .j can be distributed into multiple cloudlets in our considered architecture. Hence, we can express the expected arrival rate of task request requiring j to the cloudlet i, λij as:Yj is the number of cloudlets that contain the data j in a cooperative network which is given by Yj = ∑i ∈ Ixij. λ is the total arrival rate of task requests to the region (i.e λ = ∑i ∈ I∑j ∈ Jλij). We then define the service time to process a task requiring program j at i ascj and fi are the computational computing workload of request requiring program j and the computing power of cloudlet i, respectively.The multiple arrivals of task requests requiring program i as:Then we calculate the average number of task requests at i as:We use Pollaczek-Khinchine formula to get the average queue length and use Little’s law to obtain the average waiting time of the request at the cloudlet Our main work is to make a caching decision for the cloudlets to reach the minimum total response time. The total response time, which is the interval between the moment when an IoT user sends a request and when it receives the result, is a sum of the transmission time and the waiting delay at the cloudlet.By considering the waiting time at the cloudlet with the transmission time, the total response time of a task As RTTs (round-trip time) among cloudlets in the same cooperative network are set to be small in the clustering process, the time taken for finding the optimal cloudlet is neglected .bj the size of program data, we formulate the caching problem to decide where to be cached  with the aim to minimize the total response time of the system as:i.Denoting with The main objective of 0–1 multiple knapsack problem is to maximize/minimize the function with respect to the decision variable that cannot exceed an upper bound. To prove that our problem is same as 0–1 multiple knapsack problem, we expand the proposed problem formulation as xij under the constraint of the caching capacity of the cloudlet. Hence, our minimization of the total response time problem is proven as a 0–1 multiple knapsack problem, which is proven as NP-complete.As shown in To address the proposed problem, we not only suggests the process of executing task at the optimal cloudlet but also introduce a distributed delay-aware caching algorithm in the following section.In this section, we design the details of our clustering process and heuristic caching algorithm to minimize the total response time by caching appropriate number of same data into multiple cloudlets.To prevent the request is sent to a far cloudlet which can cause an unexpected long transmission time, CS groups the cloudlets into clusters based on the RTT among them. For collecting RTT among cloudlets, CS sends lists of IP addresses to its cloudlets. Using the lists, cloudlets measure the RTT (e.g. ping mechanism using IP) among themselves. Then cloudlets return the measured RTT to the CS.tcl to limit the size of the cluster . The larger size of the cluster results in a higher Tr, but a greater number of cloudlets. For the clustering process, CS performs the following process:In the clustering algorithm, we introduce a control parameter, CS first finds a random cloudlet that is not included in any cluster, then makes this cloudlet as a start of a new clusteri that is connected to the cluster by 1 hop. Cloudlet i can be included in m if it does not belong to any other cluster and if the RTT among cloudlet i and the other cloudlets in the cluster is less than tcl. Otherwise, the cloudlet i cannot be assigned to the cluster.CS finds the cloudlet CS keeps expanding the cluster until there is no cloudlet that can be added to the cluster.CS repeats the above process until there is no cloudlet that does not belong to any cluster. The clustering algorithm occurs at a moment when a new cloudlet is deployed in the system. After the clustering process is completed, CS starts caching data into its cluster using our proposed caching algorithm.Algorithm 1 Caching AlgorithmInput:1: I, J, X: matrix of xij  Initialize:2: J in descending order based on pj  Sort program data set of for eachj ∈ Jdo3: i that has the largest 4:  Obtain xij ← 15:  end for6: Tw using Eq 107: Calculate 8: whilei ∈ Ido9: for eachi ∈ Ido10:  for eachj ∈ Jdo11:   if all i ∈ I is full then12:    13:     Terminate the Caching Algorithmelse ifthen14:    xij = 115:     end if16:    17:    Calculate ifthen18:    19:     else20:    xij = 021:     end if22:    end for23:   end for24:  ifthen25:  26:   Terminate the Caching Algorithmelse27:  28:   end if29:  end while30: θ which is an adjustable threshold to control the cache storage of cloudlets and the complexity of the algorithm. The algorithm is terminated when the reduction of waiting time during the caching process is less than θ. The larger value of θ may save the storage of cloudlets but caches less number of replicas may lead to more waiting time.The 0–1 knapsack problem in The CDA component in CS executes the following caching algorithm:j ∈ J, CS caches program data j into the cloudlet i which has the largest remaining storage .The algorithm is terminated if none of cloudlet can cache the data j into the cloudlet i is less than θ  for each cloudlet assuming the IoT user requests a task per second. The capacity of each cloudlet is set to range from 20—40% of the total size of unique data in the system so that the storage capacity of the  [We set the cloud’s computation capability is set to 2 times of the cloudlet . The del 0.015 s , 27, 36,20 data) .CC)). The second algorithm caches one replica for the popular data in the cooperative network (denoted as replica caching (RC)).We compared our proposed algorithm to the other two methods. The first algorithm is the cooperative caching algorithm where the popular data is cached into the one cloudlet for each cooperative network , the demand for tasks requests requiring popular data  is higher than when α is low. Accordingly, the waiting time at the cloudlets that contain the popular data gets higher. We thus can say that the proposed algorithm can achieve a relatively lower delay on various values of α by caching multiple replicas of the data that have higher popularity and arrival rate in the cluster.In β between IoT users and cloudlet i to examine how transmission rate affects the total response time. The average delay of the three algorithms decreased with the higher transmission rate due to less transmission delay between the. IoT user and cloudlet. We also observe that all the three algorithms achieve higher response time with larger λi because the waiting time is increased due to the increase in the number of requests. As shown in CC and RC are less tolerable to the higher arrival rate compared to the proposed algorithm. Especially, the total response time of the two comparing methods are highly increased when the arrival rate (λi) is bigger than 8. This is because CC and RC cache the one or two data for each program data in the cooperative network so that the requests requiring the same program data are concentrated to one or two cloudlets leading to the long waiting time at the cloudlet.We plot cj): 75 × 106 and 200 × 106 cycles. We see from cj is 75 × 106 cycles, the proposed algorithm still shows a better total response time for all the different arrival rates. As shown in CC and RC is highly increased from λi = 7. When cj is increased to 200 × 106 cycles, our proposed algorithms shows average of 28% and 19% a better total delay than CC and RC when λi is relatively low(i.e. λi ≤ 7). Then the total response time of the proposed algorithm significantly increases when λi gets larger than 7. As shown in CC and RC are significantly increased.In sj. The proposed algorithm shows an average of 25% and 20% better total response time than the CC and RC. The control of waiting time is also important to minimize the total response time. i increases since more requests are held in each cloudlet. The ratio difference between the three algorithms shows that the waiting time has a large effect on the total response time. The waiting time of the proposed algorithm is relatively smaller than CC and RC also indicating that the waiting time can be reduced by caching replicas into multiple cloudlets and distributing the task requests.In i = 5, 7 and 10 requests per second. We set the number of clusters as 10. We observe that as the number of cloudlets increases, the total response time decreases for all the three methods, while the proposed algorithm outperforms the other two methods. This is because the proposed algorithm can cache more program data in the cooperative network when there are more cloudlets, resulting in the task requests being distributed to more cloudlets. As shown in In this paper, we have considered the cached-enabled IoT-edge system architecture, where the cloudlet can cache the program data for executing the task from IoT users. Caching the program data effectively reduces the total response time caused by loading the necessary program for the task. Considering the limited computation capacity and the storage of the cloudlets, we studied the cooperative caching architecture to handle the numerous task request from the IoT users. We then formulate the caching problem with the objective to minimize the total response time. For the problem formulation, we model the waiting time of task requests at the edge cloudlet as an M/G/1 queuing system. Based on the proposed architecture, we suggest the caching algorithm that caches the replicas of the popular program data into multiple cloudlets to reduce the total response time. Extensive simulation shows that the proposed caching algorithm with the clustering process achieves a lower response time compared to tje other two existing methods. Finally, we conclude the paper with some future working directions for the program caching in the IoT-Edge system. It is interesting to consider the task with various types of applications that have different deadlines. We also can consider using the machine learning method to predict the popularity of the program data in the region.S1 File(PDF)Click here for additional data file.


The Proportional-Integral-Derivative (PID) controller is a key component in most engineering applications. The main disadvantage of PID is the selection of the best values for its parameters using traditional methods that do not achieve the best response. In this work, the recently released empirical identification algorithm that is the Arithmetic Optimization Algorithm (AOA) was used to determine the best values of the PID parameters. AOA was selected due to its effective exploration ability. Unfortunately, AOA cannot achieve the best parameter values due to its poor exploitation of search space. Hence, the performance of the AOA exploit is improved by combining it with the Harris Hawk Optimization (HHO) algorithm which has an efficient exploit mechanism. In addition, avoidance of trapping in the local lower bounds of AOA–HHO is enhanced by the inclusion of perturbation and mutation factors. The proposed AOA–HHO algorithm is tested when choosing the best values for PID parameters to control two engineering applications namely DC motor regulation and three fluid level sequential tank systems. AOA–HHO has superiority over AOA and comparative algorithms. PID conThe P controller is used for stabilizing the gain and producing a constant steady-state errorThe I controller is used to eliminates or decreases the steady-state errorThe D controller is used to decrease the rate of change of error, overshoot and settling time.The main advantages of PID controller are concluded as in the following :The P coPID controller is used to regulate many industrial process such as pressure, temperature, flow rate, feed rate, weight, speed and position . There aHeuristic optimization algorithms can be used to tune PID's parameters that have been classified as numerical methods and have been popular in the literature. Stochastic optimization methods such as heuristic algorithms  was suitMeta-heuristic algorithms have successfully improved many engineering problems in fields as diverse as bioinformatics –17, MotoAs shown in Fig. The objective function used to improve process performance is the minimum integral to absolute error (IAE). It is the sum of the differences between the desired response (h(t)) and the actual response (y(t)) which is represented as in Eq.  1].1\do.1\do1].1p, Ki and Kd) as shown in Fig. g  which produce the best IAE is updated with the best solution founded during updating of solutions.The procedure of estimating the values of PID’s parameters  , dynamicFor other systems such as controlling the voltage regulator, Teaching Learning Based Optimization (TLBO) algorithm was used to optimize the parameters of PID controller . DiffereThe theory of No-Free-Lunch (NFL)  which stArithmetic Optimization Algorithm (AOA)  is a popA lot of researches were done on AOA; a version of AOA released was used for multiobjective optimization . AOA wasThis paper presents a hybrid between AOA and Harris Hawk Optimization (HHO)  which haHHO was used for enhancing the exploitation of many meta-heuristic algorithms such as Nelder–Mead simplex optimization algorithm , grasshoEnhanced AOA's exploitation by incorporating HHO for optimized PID controller design.Avoidance of local AOA minima is enhanced based on the inclusion of disruption and mutation operators.A DC motor and three liquid level tanks were used in pilot tests to test the performance of the developed AOA–HHO for the optimized design of the PID controller.The main contributions of this work are listed as follows:The rest of the paper is organized as follows: Sect. In this section, the procedure of AOA  and HHO AOA uses arithmetic operators  to update solutions. To explore the search space, it depends on the multiplication and division operators, while the addition and subtraction operators are used for exploitation. The control parameter that balances diversification and intensification of search space is the accelerated Math Optimizer entclass1pt{minimawhere Diversification of the search space based on division and multiplication factors is performed due to the high distribution of the generated values which are represented according to Eq.  for a coN), best  is the initial energy of prey, and it has a value between  which is assigned randomly, (t) is the current iteration number, and (T) is the total iterations number. For The HHO exploration stage is represented by the initial attack of the prey as it has a high energy which decreases during escape to a low energy level and can be attacked which represents the exploitation stage as shown in Eq. .6\documeThe exploration stage is carried out on two mechanisms: first, the falcons settle according to the positions of other falcons and the location of the prey. Second Mechanism Falcons can settle into a random position within the range of other falcons. Equation 7 simulates the exploration phase.1, r2, r3 and r4 and are random generator numbers within the range .where During the exploitation phase Hawks surround the rabbit while it tries to escape and is tired and then pounced by the hawks. This process is simulated as in Eq. .8\docume5), r5 is a parameter its value is selected randomly within the range .where (J) simulates the rabbit's jump power randomly through escaping and J = 2(1-rThe rabbit (the prey) escapes in a zigzag pattern simulated using mega-flying. The hawks search for the best direction of attack to catch the hare so that the hawks decide the next attack according to Eq. .9\documeLevy's flight function is used to simulate the random and irregular attacks of hawks to capture prey according to Eq. .10\documwhere s is a random value generated within the range  and LF is the levy flight function represented according to Eq. .11\documwhere β is a set constant as a value (1.5) and u and v are randomly generated values within the range . The position of the falcon is estimated according to Eq. .12\documZ and X are estimated according to Eq. 15) updatAlgorithm (2) represents the steps of HHO algorithm.The main advantage of AOA is efficient exploration due to division and multiplication operators due to their strong ability to generate values with high distribution. However, it produced poor performance for PID controller's parameters estimation because it is trapped in local minima and has poor exploitability. Hence, this is the impetus to enhance avoidance of local minima by using the disruption operator and the mutation operator. Its poor exploit is improved by incorporating the exploitation scheme of the HHO algorithm  where its main advantage is the different efficient exploitation mechanisms that balance the search focus on narrow areas and the avoidance of trapping in the local minima. The disruption factor and mutation operator are described in subsections The disruption operator inspired by an astrophysical theory posits that “when a group of gravitationally bound particles  is very close to a massive object (with a mass of M), the group becomes torn apart. Similar to this, when a solid body, held together by gravitational forces, approaches a much larger body” . The diss in Eq. .18\documXpast represents current value of the solution to be updated, X is the value after updating the solution, and α is a random number generated within the range . The disable factor has successfully improved many meta-algorithms in many applications such as feature selection [where election , 69, optelection , image telection  and photelection .The mutation factor is used to enhance the diversity of the search space and to avoid falling into local lower bounds where two well-known factors are the Cauchy mutation (CM) and the Gaussian mutation (GM). The mutation factor has been used to enhance the diversity of several heuristic algorithms in the literature that has motivated their use –78.CM operator has better ability of efficient search than GM operator according to previous research , 79, 80.The CM operator’s density function is represented as follows as shown in Eq. :19\documwhere g is the constant parameter with value (1)  and randThe enhancement of AOA was performed by embedding the CM operator in the exploration updating mechanism of AOA as in Eq. .20\documwhere CM is the mutation factor and was estimated based on Eq. . Then thPromoting trapping avoidance in the local minima based on the use of CM operator.Enhancing the diversification of the search space based on the disruption factor.Enhancing the exploitation system based on the mechanism of exploiting of the HHO algorithm.The main advantages of the proposed AOA–HHO algorithm are inferred in the following:The integral of the absolute error (IAE) function represented in Eq.  was usedExperimental tests were carried out on two systems: the first was DC motor speed control, and it was common in many related studies , 32, 81.d): it is the time required for the response to achieve half of the final value for the first time.Delay time (tp): it is the time required for the response to reach the first peak of the overshoot.Peak time (tr): it is the required time for the response to rise from 10% to 90 of its final value.Rise time (ts): it is the time required for the response curve to reach and stay within a range about the final value of size specified by absolute percentage of the final value .Settling time (tp): it is the maximum peak value of the response curve measured from unity.Overshooting The step response characteristics as settling time, rise time and overshooting.The frequency response of the systems.The fitness function that was used to evaluate solutions based on IAE according to Eq. . The meaThe speed regulation of electrical DC motor  was conta represents armature resistance, La represents inductance of armature winding, J represents the equivalent moment of inertia of motor and load referred to motor shaft, D is the equivalent friction coefficient of motor and load referred to motor shaft, K represents Motor torque constant, and Kb represents back EMF constant.The values of the parameters of DC motor which was used as a case study are listed in Table The transfer function of DC motor closed-loop speed control systems is expressed in Eq. .21\documTable As shown in Table For overshoot measurement, AOA–HHO provides overshoot very smaller than that of AOA but not the optimum due to that of GWO and SCA is smaller as shown in Fig. For rise time, AOA–HHO produces the smallest rise time according to results of Table This results implies that AOA–HHO has the superiority over than AOA and other algorithms for finding the smallest IAE and reasonable overshoot, set time and rise time.Figure In addition, the magnitude margin of AOA–HHO has not any gain, while that of AOA and CMA-ES has a gain which implies that it produces larger overshoot which is guaranteed as shown in Fig. Three cascaded liquid level tank system was used to test the performance of improved DE with PSO  for estiParameters setting of PSO, SCA, GWO, ASO, CMA-ES, AOA and the proposed AOA–HHO algorithm are listed in Table As shown in Table For overshoot, AOA–HHO cannot produce the minimum value, but it is better than that of AOA by difference 50%. SCA produces the minimum overshoot, while it produces high value of IAE. GWO produces the largest overshoot, while it produces reasonable value of IAE. The reason is that the single objective is minimizing IAE not the specification of the response, which can be enhanced in the future work by handling the problem as multi-objectives.For rise time, AOA–HHO produces reasonable rise time not the minimum but better than that of AOA by difference 65 s. PSO produces the minimum rise time, while AOA produces the largest value of rise time.For set time, AOA–HHO produced 160.363 s of set time which is larger than that of AOA which has value of 2.65 s. CMA-ES produced the largest value of set time, while AOA produced the minimum value of set time.Figure As shown from the results of the two case studies, AOA–HHO has the superiority over than AOA and other algorithms. The reason is that tuning the parameters of PID controller is a continuous optimization problem which has huge number of allowable values in determined search space. Hence, the balance between exploration and exploitation is an important for achieving the optimal values. In AOA–HHO, Cauchy mutation operator enhances the avoidance of trapping in local optima, while disruption operator enhances the exploration capability of AOA. These two operators enhance the diversification of the AOA–HHO. Regarding the exploitation, HHO was integrated which has an efficient exploitation schemes Fig. .Fig. 10BIn this work, an enhanced version of AOA is presented to improve the estimation of PID controller parameters. The improvements were made by incorporating the efficient exploitation mechanism of the HHO algorithm instead of exploiting the AOA. In addition, trapping avoidance in the local minima of the proposed AOA–HHO algorithm was enhanced by including disruption and mutation factors which enhance the exploration capability. The AOA–HHO has been tested to select the best parameters of the PID controller for controlling two engineering applications that are DC motor regulation and three cascading liquid level tank systems. The single objective function was an integral part of the absolute error (IAE) function.AOA–HHO has outperformed AOA in terms of IAE and response specification such as overshoot, rise time and set time in controlling dc motor, while for controlling level of three cascaded liquid tanks only set time of AOA is better that that of AOA–HHO. The frequency response of AOA–HHO was measured which implies it produces reasonable bandwidth and gain magnitude margin better than that of AOA and other comparative algorithms. From the experimental study, AOA–HHO has the superiority over AOA and other comparative study for estimating efficient parameters of PID controlling which leads to efficient IAE.


Postural abnormality is one of the main symptoms of Parkinson’s disease (PD). The erector spinae muscles play an important role in maintaining an upright posture, but the fatigability of the erector spinae in patients with PD is unknown. The purpose of this study was to compare the trunk extension maximum voluntary contraction (MVC) and the fatigability of the erector spinae between female patients with PD and healthy volunteers.Th participants of this cross-sectional pilot study comprised 19 patients with PD and nine healthy volunteers matched for sex, age, and physical characteristics as a control group. The MVC of all participants was measured, and after sufficient rest, the Sørensen back endurance test was conducted to the point of exhaustion. The muscle activity of the erector spinae during the Sørensen back endurance test was measured using surface electromyography. The median frequency (MF) slope, which is an index of fatigability, was calculated from the recorded surface muscle activity by means of power spectrum analysis using a Fast Fourier transformation.Nine of the 19 patients with PD were unable to perform the Sørensen back endurance test, and a lower proportion of the PD group were able to perform it compared with the control group. The MVC of those patients with PD who were able to perform the Sørensen back endurance test was lower than that of the control group, and the time for which the pose could be maintained was shorter. There was no significant difference between the MF slope on the left and right side in the PD group, and it was higher on both sides than in the control group.This is the first study to demonstrate a reduction of maximum muscle strength and great fatigability of the erector spinae in patients with PD. This discovery strongly underlines the need for paraspinal muscle training from an early stage with the aim of preventing the progression of postural abnormality in patients with PD. Postural abnormality is one of the main symptoms of Parkinson’s disease (PD). This most commonly takes the form of trunk anteflexion, but scoliosis is also seen. The erector spinae muscles are essential to trunk movement and the maintenance of an upright posture, and weakness of these muscles exacerbates postural abnormality . The ereA previous magnetic resonance imaging (MRI) study of the paraspinal muscle mass of patients with PD reported that they were asymmetrical, with greater muscle atrophy on the side on which the PD symptoms first became evident than on the opposite side in eight of 10 patients . In anotOne method of evaluating the fatigability of the erector spinae is to use electromyography (EMG) to measure muscle activity during the Sørensen back endurance test , 8, in wIn a systematic literature review aimed at examining the validity and applicability of methods for the assessment of erector spinae muscle fatigability in everyday clinical rehabilitation practice, the Sørensen back endurance test combined with surface electromyography spectral analysis has been shown to be the most widely used and the comparatively most optimal modality currently available to assess objective erector spinae muscle fatigability. However, patients who have severe erector spinae muscle weakness might not be able to maintain the pose for even just a few seconds . TherefoAgainst this backdrop, we hypothesized that maximum muscle strength is severely diminished and fatigability of the erector spinae is high from an early stage in patients with PD. The objectives of this pilot study were (1) to verify whether the Sørensen back endurance test can be used to evaluate muscle fatigability of the erector spinae in patients with PD, and (2) to measure the fatigability of the erector spinae on the side on which PD symptoms first appeared and the opposite side in patients with PD, to compare the results with data on the erector spinae of healthy volunteers.13,14,) This study was approved by the Research Ethics Committee of Wakayama Medical University . All methods were carried out in accordance with relevant guidelines and regulations. Written informed consent was obtained in advance from all participants.This was a cross-sectional pilot study that was conducted following our previously reported measurement protocol.. is higher in females overall. The inclusion criteria thus were: age ≥ 65, female sex, and modified Hoehn & Yahr (H-Y) Stage < 3 PD. The exclusion criteria were: (1) spinal anteflexion of ≥45° (camptocormia) [Nineteen patients diagnosed with PD and undergoing outpatient treatment at the Department of Neurology of Wakayama Medical University Hospital took part in this study. The cross-sectional area of the erector spinae is larger in elderly males than in elderly females , and theocormia)  or laterocormia) , (2) spiAll individuals in the PD group had been diagnosed by the same neurologist before their participation in the study. The doctor who examined them confirmed their modified H-Y Stage, duration of disease, and the side on which their PD symptoms first appeared. During the screening, they also confirmed that they could perform the Sørensen back endurance test in the correct position. All patients with PD performed measurements of maximum muscle strength during trunk extension and the Sørensen back endurance test during the on phase. The control group comprised nine healthy older women aged ≥65. All individuals in the control group were examined by a single rehabilitation doctor, who confirmed that they were in good health and that their participation in the study was appropriate.After a 15-minute resting period, the subjects lay prone on two examination beds of adjustable height. Their legs were positioned so that their anterior superior iliac spines were aligned with the edge of one of the examination beds, and their hips, knees, and ankles were fixed to the bed with strong straps. The height of the other examination bed was adjusted so that it supported the trunk at 0° trunk extension. A handheld dynamometer  was fixed at the midpoint of a line joining the inferior angles of the bilateral scapulae when both elbows were directed outwards, and both hands were placed on the back of the head . The skin was wiped clean with alcohol before the electrodes were applied. Two silver–silver chloride electrodes (diameter 10 mm) were positioned 20 mm apart, with the leading electrode attached 3 cm laterally to the first lumbar vertebra so that it was parallel to the direction of the muscle fibers. Based on the Standards for Reporting EMG Data  approvedp < 0.05 considered significant.Data were expressed as medians and interquartile ranges (IQR). The proportions of participants in the PD and control groups who were able to perform the Sørensen back endurance test were compared using Fisher’s exact test. The physical characteristics of the patients with PD who were able and unable to perform the Sørensen back endurance test and those of the control group participants were compared using the Kruskal-Wallis test. PD-related parameters among patients with PD who were unable to perform the Sørensen back endurance test were compared using the Mann-Whitney U test. Because a number of previous studies have reported comparisons using the left erector spinae , 12, 14,p = 0.026). The patients with PD who were able to perform the Sørensen back endurance test, those who were unable to perform it, and the control group participants were similar in terms of age, height, weight, and body mass index. There was no significant difference between those who were able and unable to perform the Sørensen back endurance test in terms of either modified H-Y Stage or disease duration. The participants’ physical characteristics are shown in Table Of the 19 patients in the PD group, 10 were able to perform the Sørensen back endurance test, but the other nine were incapable of holding their trunk in the horizontal position from the very beginning. All nine members of the control group were able to perform the Sørensen back endurance test, and the difference in the proportion of participants in each group capable of performing this test was significantly lower in the PD group (p < 0.001)  . Neither MVC nor holding time was significantly associated with modified H-Y Stage or disease duration (p ≥ 0.05).The MVC values and Sørensen back endurance test results for the PD group are presented for the 10 patients who were able to perform the Sørensen back endurance test. Trunk extension isometric MVC was significantly lower in the PD than the control group (PD group: 0.57 (0.52–0.71) Nm/kg; control group: 1.26 (1.19–1.60) Nm/kg, 01) Fig. . Holding01) Fig. . There wp < 0.001)  .The calculated MF values of the bilateral erector spinae attenuated significantly over time among both the 10 patients in the PD group and all nine control group participants (01) Fig. . There w37) Fig. . HoweverThe main finding of this study is that only 53% of patients in the PD group were able to perform the Sørensen back endurance test, a significantly lower proportion than in the control group, which consisted of healthy individuals matched for age, sex, and physical characteristics (100%). The trunk extension MVC values of those patients in the PD group who were able to perform the Sørensen back endurance test were also significantly lower than those of the control group participants, and their Sørensen back endurance test holding times were significantly shorter. In addition, although there was no difference in the MF slope of the erector spinae between the side on which symptoms originally appeared and the opposite side in patients with PD, it was significantly attenuated in both compared with the erector spinae of healthy individuals.Around half of the patients with PD in this study were unable to perform the Sørensen back endurance test. According to previous reports, the Sørensen back endurance test requires approximately 40% MVC . The facAccording to a previous study that combined histopathological testing and frequency power spectrum analysis , MF atteThis study has a number of limitations. The first is the small sample size. However, because the patients with PD included in this study were all older women with a modified H-Y Stage < 3, and since we compared their results with those of healthy individuals matched for age, sex, and physical characteristics, we consider the clinical significance of our data high. The second limitation of the current study is that in our investigation of differences in MF slope between the PD and the control group, the severe reduction in erector spinae muscle strength in the patients with PD may have increased the relative load during the Sørensen back endurance test for the PD group. As this was a cross-sectional study, however, it is impossible to determine whether the difference in MF slope between the two groups was due to changes in the muscle fiber composition of the erector spinae or to differences in the relative intensity of the Sørensen back endurance test. In either case, however, this is the first study to demonstrate that the fatigability of the erector spinae, which contributes greatly to postural maintenance, is greater in patients with PD.We found that only 53% of modified H-Y Stage < 3 patients with PD were able to perform the Sorensen back endurance test, and that trunk extensor muscle strength was greatly reduced and the fatigability of the erector spinae was higher in the PD group. However, there is no universal agreement with regard to the appropriate assessment of erector spinae muscle fatigability with the Sørensen back endurance test. Test subjects exhibited significantly longer holding times during the modified Sørensen back endurance test on a 45-degree Roman chair than on the original Sørensen back endurance test. Moreover, moderate and significant correlation between both tests was observed for holding time, and there was no difference in MF slope derived from erector spinae between both tests . TherefoOur findings suggest that there is a marked decline in the quality of the erector spinae on both sides from the initial stage of PD, and that symmetrical strengthening of the endurance of the bilateral erector spinae from the early stage of the disease is required. An effective method of muscle strength training for the erector spinae in patients with PD has yet to be established. The trunk extension MVC of patients with PD is severely reduced, and we conjecture that high-intensity training may be clinically problematic in many cases. With respect to setting the intensity of muscle strengthening training, it has recently been suggested that low-intensity training to the point of exhaustion may activate both type 1 and type 2 fibers, leading to the same degree of muscle enlargement as high-intensity training . As soonTo our knowledge, this is the first study to use surface electromyography power spectrum analysis to investigate the fatigability of the erector spinae in patients with PD. We found that only 53% of modified H-Y Stage < 3 patients with PD were able to perform the Sørensen back endurance test and that trunk extensor muscle strength was greatly reduced and the fatigability of the erector spinae was high in the PD group. Our findings strongly support the necessity of paraspinal muscle training at an early stage to prevent postural abnormality in patients with PD.


The quality testing and approval procedure for most pharmaceutical products is a streamlined process with standardized procedures for the determination of critical quality attributes. However, the evaluation of semisolid dosage forms for topical drug delivery remains a challenging task. The work presented here highlights confocal Raman microscopy (CRM) as a valuable tool for the characterization of such products.CRM, a laser-based method, combining chemically-selective analysis and high resolution imaging, is used for the evaluation of different commercially available topical acyclovir creams.We show that CRM enables the spatially resolved analysis of microstructural features of semisolid products and provides insights into drug distribution and polymorphic state as well as the composition and arrangement of excipients. Further, we explore how CRM can be used to monitor phase separation and to study skin penetration and the interaction with fresh and cryopreserved excised human skin tissue.This study presents a comprehensive overview and illustration of how CRM can facilitate several types of key analyses of semisolid topical formulations and of their interaction with their biological target site, illustrating that CRM is a useful tool for research, development as well as for quality testing in the pharmaceutical industry. Semisolid dosage forms represent the majority of drug products administered to human skin. Such dosage forms generally contain a combination of different excipients forming a three-dimensional matrix that incorporates the active pharmaceutical ingredient (API or drug) as well as providing specific functions relevant to delivering the drug to the site of action  therapy or by enhancing penetration for systemic  therapy) , 2. The These considerations are relevant to new (innovator) drug products as well as to generic products, which are expected to demonstrate that they are bioequivalent to a reference listed drug (RLD) product , or to the currently available reference product. A demonstration of bioequivalence (BE) between a test and reference product traditionally involves evidence that there is no significant difference in the rate and extent to which a drug will become available at the site of action. Pharmacokinetics (PK)-based evidence is often used to support such a demonstration of BE, although other types of evidence comparing the test and reference product can also support a demonstration of BE. The formulation of a generic product can be compared to that of the reference product using three concepts that describe the components, composition, and physicochemical or structural arrangement of matter in the dosage form. The qualitative (Q1) characteristics of a formulation describe its components (ingredients), the quantitative (Q2) characteristics of a formulation describe its composition (formula), and the physicochemical and structural Q3) characteristics of a formulation describe the manner in which the underlying matter is arranged  characte.A demonstration that a proposed generic product is Q1 and Q2 the same as the reference product, and that it also has similar Q3 characteristics, can mitigate the risk of multiple potential failure modes that can alter product performance, and can support a demonstration of bioequivalence for generic products. The Q3 characteristics of a product may be influenced not only by the components and composition of the formulation, but also by the manufacturing process, the storage conditions, dose dispensing, dose administration, or other processes . Thus, aTo assess and/or compare the critical quality attributes of a generic and/or reference product, an array of physical and chemical characterization methods may be employed. State-of-the-art analytical tools for the characterization of semisolid topical formulations include Q1 and Q2 characterization as well as tests for Q3 characteristics that can include various rheological analyses to evaluate the deformation of the microstructure in response to stress, thermogravimetric analysis (TGA) to monitor physical and chemical changes as a function of increasing temperature, and differential scanning calorimetry (DSC) for the assessment of temperature-dependent phase transition processes –9. A proin vitro permeation testing (IVPT) using excised skin mounted in Franz  diffusion cells or Bronaugh (flow-through) diffusion cells  the United Kingdom (UK) and Austria, as well as two ‘generic’ products. The acyclovir cream products were analysed with regard to their product compositions, assessing the microstructure of the creams, the polymorphic form of acyclovir in the creams, the spatial distribution of the API and other excipients in the creams, and the penetration behavior of the cream into excised human skin.et al.  was used as a reference material, as well as for the preparation and analysis of the different polymorphic forms of the API. Polymorphic forms I and II were prepared according to Lutker et al. . In shoret al. . Other r® (acyclovir) cream, 5% products from US , from the United Kingdom  and Austria . The ‘generic’ products were Aciclostad®  and Aciclovir 1A Pharma®  acyclovir cream, 5%, both commercially available in Austria. While most of the products were packaged exclusively in tubes, the Zovirax® UK product was available in a tube as well as in a pump dispenser, and both packaging configurations of this product were studied. All analyses of the products were conducted before the respective expiration dates. Further information on the qualitative and quantitative composition of the products can be obtained via publicly available sources (Three innovator (reference) and two ‘generic’ acyclovir cream products containing 5% acyclovir (w/w) from different manufacturers were evaluated. The innovators (reference products) were Zovirax sources –32.+ confocal Raman microscope from WITec  which was coupled to a laser with a wavelength of 785 nm. The laser power was adjusted to 20–50 mW depending on the experimental setup. Analysis of the semisolid products, themselves (not on the skin), was carried out with a lower laser power to minimize agitation of the system by thermal stress, whereas a higher intensity laser power was utilized for the penetration studies into human skin. Using a 50 × objective with a numerical aperture of 0.8, and a pinhole of 100 µm. Raman spectra in a range of 400–1780 cm−1 were recorded with a spectral resolution of 4 cm−1, lateral resolution of 0.50 µm and axial resolution of 2.05 µm. For the analysis of the topical creams, a sample was evenly spread on a glass slide using a coverslip. Single spectra were recorded by choosing an acquisition time of 10 s (10 accumulations per spectrum). For the acquisition of two-dimensional image scans, bright field images of the formulations were recorded and Raman analysis of the same area was performed. Scans were recorded with a step size of 0.5 µm and an acquisition time of 0.2 s per spectrum.All experiments were carried out using an Alpha300RProcessing of all recorded Raman spectra was performed using the ProjectFOUR software . Raman spectra were first treated with a cosmic ray removal and a background subtraction using a polynomial fit. To identify the main spectral contributions within the products, the distribution of starting materials and to assess homogeneity of the cream base, a hierarchical cluster analysis  was applied, where single spectra with similar features are grouped into clusters. To create images based on the spectral information, each cluster was assigned to a specific compound, for example the drug and different excipients were identified based upon their unique Raman spectra. Such clusters comprised an averaged basis spectrum that is characteristic for each compound. Subsequent basis analysis used these basis spectra to fit them to the scanned area, resulting in a color-coded image showing the distribution of the respective basis spectra in the scan region. By combining the images after the fitting, false-colour images were created displaying each compound in a different color.stratum corneum was cleaned with purified water and adipose tissue was removed using a scalpel. The skin tissue was stored in polyethylene bags at -26 °C until further use. For the penetration studies, sections of 25 mm in diameter were punched out of the frozen skin and were allowed to thaw between two filter papers soaked in phosphate-buffered saline (PBS) at room temperature. Afterward, skin samples were cleaned and dried with cotton swaps.Full thickness human skin was obtained from Caucasian patients undergoing plastic surgery . Skin donors gave their written consent and the utilization of the tissue in this study was approved by the medical association of Saarland, Germany (application number 204/08). After excision of the tissue, the 2) was applied using circular motions for 30 s onto the clean surface of the skin using a finger covered with a rubber glove. The products were always dosed so that the complete surface of the skin sample was covered. After different time points (4 h and 24 h), the remaining product was removed and the skin surface was carefully cleaned with purified water using cotton swabs and wiped dry afterwards. Raman analysis of skin penetration was performed using the same Raman confocal microscopy setup as described above. The penetration of product into the skin was investigated by recording line scans with a step size of 2 µm from the skin surface downward (in the direction of the z-axis). Each Raman spectrum was treated with a cosmic ray removal procedure and background subtraction was performed, followed by a normalization of the peak associated with the formulation  based upon the peak associated with the skin  to account for depth-related attenuation of the Raman signal intensity. The normalized intensity of the peak associated with the formulation was then plotted against the penetration depth to create a penetration profile.For the penetration studies, a small amount of a semisolid product . The skin section was transferred to a glass slide and dried before analysis. To account for z-shifts in focus during Raman measurements, a topographic map was acquired of the sample surface using white light interferometry prior to the acquisition of the Raman scans, using the CRM setup and image acquisition parameters described above.Full thickness human skin samples were obtained from patients  undergoing abdominoplasty at hospitals in Brisbane  and were refrigerated immediately after surgery. Utilization of the tissue was approved by the Metro South and University of Queensland Human Research Ethics Committees  and was carried out in compliance with guidelines of the National Health and Medical Research Council of Australia and FDA RIHSC. Skin samples were further processed by removal of subcutaneous fatty tissue and immersion of full thickness skin in 60 °C water for 60 s, afterwards the epidermal layer was teased off the dermis as described previously . Epiderm2; receptor volume of approx. 3.5 ml). Sheets of epidermal tissue were placed between the receptor and donor compartments for equilibration. The receptor solution which consisted of PBS pH 7.4 and 0.01% sodium azide, was stirred with a magnetic stirrer bar. The skin surface temperature was maintained at approximately 32 °C by immersing the receptor compartment in a water bath at 37 ± 0.5 °C. Integrity of the test membrane was assured by measuring the resistance across the epidermis with a digital multi-meter as described before (2 of pre-weighted amounts of test formulations (acyclovir creams (5%)) were applied to the membranes by spreading evenly with a syringe plunger which was weighed before and after the procedure. Samples of 200 μl samples were withdrawn at various times over a 48-h period from the receptor phase and replaced with equal amounts of fresh pre-warmed receptor medium. API concentrations in the samples were determined via HPLC.IVPT studies across human epidermis were carried out in Pyrex glass Franz-type diffusion cells (diffusion area of 1.33 cmd before . Membran2) over time (h) was determined and the flux through the epidermis was calculated and expressed as μg/cm2/h.Every test formulation was characterized in IVPT studies by a total of 3 replicates from 6 skin donors. The cumulative amount of API permeated through the epidermis . First, individual Raman spectra were acquired for each cream to identify the components in the creams, with a special focus on acyclovir. As differences in the polymorphic form of a drug in a dosage from can have a significant effect on its therapeutic performance attributes, like its bioavailability (BA) , differe® UK Pump) in (a) and a comparison of the individual Raman spectra of different polymorphic forms of the API, acyclovir, in (b). The Raman spectrum of the acyclovir formulation (a) depicts an array of peaks that are attributed to specific molecular bonds of the chemicals in the cream system. Based on the position and shape of the peaks, the ingredients that contribute to the characteristic Raman spectrum of the formulation can be determined. Highlighted in Fig. −1) and the API . The region around 650 cm−1 proved to be highly significant for the differentiation of the polymorphic forms of acyclovir  with one of the test products evaluated (Aciclostad®), the difference in PG content becomes obvious. The highlighted area in Fig. −1 in the ‘generic’ product reaches an intensity of approximately 100,000 CCD counts, the intensity of PG in the reference product is about 3.5 times as high. Such Raman data can be used for the relative quantification of specific compounds in comparable formulations, and if calibrated to a reference standard, it is possible to quantify specific compounds using this technique. Quantification of PG in both products was independently carried out in another study using thermogravimetric analysis (TGA) which confirmed a similar ratio of PG in these formulations, with approximately 13% of PG in the ‘generic’ product and 42% of PG in the reference product. These findings concur with publicly available information on PG content for reference products (40% PG) and Aciclovir 1A Pharma® (15% PG)  –31. No iOptical microscopy can provide insights into the microstructural composition of the formulation and can give information about the shape and size of solid or liquid objects like crystals and globules, if present. However, optical microscopy alone cannot provide information about the chemical composition of the formulation that is being investigated. In this context, confocal Raman microscopy has the advantage that the sample can be investigated optically, and at the same time, a specific position within the imaged sample can be analysed regarding its chemical composition without the need for extensive sample preparation or destruction.® Austria) and a ‘generic’ formulation (Aciclovir 1A Pharma®), both containing 5% acyclovir. Bright field microscopy analysis of the reference product  Raman spectra corresponding to the acyclovir crystals and the cream base of the reference product imaged in Fig. During the acquisition of a Raman scan in the x–y or x–z direction, information from large areas of a sample can be obtained and used for chemical analysis. These area scans are used to investigate the microstructure of the system and to evaluate the homogeneity of the formulation base (vehicle). By choosing a high number of pixels for the area of the sample that is being investigated, Raman spectroscopy can reach a resolution of up to 200 nm, depending on the technical setup. Comparing all the individual Raman spectra that are acquired within the area of the scan, a semisolid system can be investigated for its compositional homogeneity in a way that requires neither extensive sample preparation procedures nor destruction of the sample. Further, this experimental setup allows for the monitoring of compositional changes following the application of mechanical and thermal stress.® UK pump) was investigated by using a pump (as the container closure system) for dispensing the product. To evaluate the influence of the mechanical stresses of pumping the cream through a nozzle, the same cream was evaluated prior to pumping (cut open from inside the pump canister) as well as after the application of the mechanical stress and shear forces of being pumped out.The assessment of potential failure modes is a critical aspect of the analysis of pharmaceutical product quality, and the acquisition of a three dimensional Raman scan therefore represents an interesting approach by which to study experimentally simulated product use conditions that can reveal failure modes for product performance; for example, the temperature of the product can be experimentally increased or decreased, and/or mechanical stress can be applied to the product while observing any changes under the microscope. The effect of mechanical stress on an acyclovir cream, 5% formulation (Zovirax® UK pump) were investigated by light microscopy and with corresponding Raman scans after pumping (a) and before pumping (b). The results are depicted in Fig. Samples of a commercially available acyclovir cream, 5% product  and a ‘generic’ (Aciclostad) acyclovir cream, 5% product was assessed with confocal Raman microscopy. Figure in vivo human skin temperature) for 30 min. The bright field microscopic images show drying-related changes in the optical appearance of the creams, but the Raman scans show no apparent changes in chemical composition compared to unstressed samples. In both the reference (a) and the ‘generic’ (b) product, the drug crystals (yellow) are clearly visible in the cream base (black) and show similar morphological properties to those seen in the unstressed products. Following the thermal stress, no disintegration of the cream base could be observed in either the reference, or the ‘generic’ product. Furthermore, no differences in Raman spectra between the API before and after application of thermal stress could be observed, which demonstrates the likely stability of these products during product use.Additionally, the influence of thermal stress on a reference (Zoviraxin vitro permeation test (IVPT) using excised human skin mounted in diffusion cells, where the rate and extent to which an API permeates into and through the skin is determined  of topical formulations has conventionally been characterized by an termined , 39. ConAfter the application of a topical formulation or product upon excised human skin, different acquisition modes can be applied to the sample in order to investigate the interaction of the formulation components with the tissues at the skin surface, and in deeper skin layers. Using stacked virtual cross sections of the skin in the x–z direction, and after various data analysis steps as well as the creation of a false color images, CRM can enable the visualization of the presence of the API as well as other formulation components at different depths in the skin. Alternatively, the acquisition of single line scans  can provide a faster, semi-quantitative analysis of the penetration of the API as well as other formulation components to different depths in the skin, which could then be characterized at successive points in time to monitor how the amount of API (for example) changes over time, thereby characterizing the rate and extent to which the API (or other formulation components) becomes available at a particular depth in the skin. Such cutaneous PK profiles could be characterized at each of multiple depths in the epidermis and compared between topical products to evaluate relative BA and BE.et al. , shown in the red, exhibits higher PG intensities than the other products in the outermost skin layer (to a depth of approximately 10 µm), and while the various reference products tend to exhibit greater penetration of PG than the ‘generic’ products, the results illustrate more generally how the penetration kinetics of a given compound in a topical product can be compared and differentiated among products. Also, while only two time points were evaluated in this study (4 h and 24 h), these results demonstrate that it is feasible to utilize CRM to monitor changes in the penetration kinetics at a selected depth in the upper epidermis as a function of time, which can thereby produce cutaneous PK profiles that can be compared between topical products. As a further demonstration of the utility of CRM for this purpose, the cutaneous PK results characterized by CRM at 4 h and 24 h were compared to cutaneous PK results for the same topical products evaluated in an IVPT study performed in an independent laboratory , shown in the red, exhibits substantially greater penetration than the other products, confirming the results obtained from CRM.To illustrate the utility of CRM to compare the cutaneous PK of topically penetrating compounds between different formulations or products, the penetration of six commercial acyclovir topical products was assessed by measuring the intensity of a PG-associated peak, as described above. Two time points (4 h and 24 h) were investigated by CRM and the resulting penetration profiles for all the acyclovir products are compared in Fig. Although the non-invasive character of CRM is notable because of its potential to be developed for eventual clinical use with human subjects, the method is also highly compatible with destructive tissue preparation techniques to achieve a more comprehensive analysis of a sample. The freeze drying of biological tissues and their analysis by CRM has the added benefit of preserving the original state of the tissue while simultaneously intensifying Raman scattering by eliminating water from the sample . FreezinThe combination of white light reflectance measurements and confocal Raman microscopy allows for the mapping of the sample surface (Fig. This work illustrates the power and utility of Raman spectroscopy and microscopy as valuable techniques for the chemically-selective physicochemical and structural characterization of semisolid dosage forms. The chemically-selective nature of the method allowed for an in-depth investigation of different acyclovir creams, 5% products, comparing a set of reference products with each other and with ‘generic’ counterparts. Raman spectroscopy and microscopy techniques were able to characterize differences in the physicochemical and structural attributes of the products. The significance of this work is that differences in potentially critical physicochemical and structural quality attributes between reference and prospective generic products can be associated with potential failure modes for BE, and the results described here demonstrate that Raman spectroscopy and microscopy can provide detailed information about the components of a formulation, the arrangement of matter and structural features in the dosage form, the polymorphs of a substance that may be present in a topical product, and other attributes that can be used to directly compare the physicochemical and structural similarity of a prospective generic product to its reference product, thereby potentially mitigating the risk of specific failure modes for BE. In addition to characterizing and comparing product quality attributes, CRM was also demonstrated to be a useful tool for evaluating and comparing product performance, by characterizing the penetration kinetics of compounds from topical semisolid products into the upper layers of human skin. The correlation of cutaneous PK results characterized by CRM with corresponding IVPT results for the same products highlights the usefulness of CRM as a method for profiling the penetration and distribution of topically applied compounds into the skin. In addition, this work illustrated that CRM can simultaneously, and non-invasively, monitor the penetration and/or distribution of topical formulations into the skin, thereby providing a more comprehensive approach by which to compare topical products and to study the mechanisms of topical drug delivery. Although CRM has been implemented for the analysis of interactions of topical formulations with the human skin tissue in several studies, the here presented work not only evaluated the penetration and permeation abilities of commercial formulations but further describes a systematic evaluation of the topical products by CRM. The here presented study thereby provides a novel and promising approach by which to develop and evaluate prospective generic topical dermatological drug products.


Vacuum-steam thawing is one of the methods used for defrosting food, realized in the atmosphere of water vapour under the conditions of reduced pressure. The water vapour formed in vacuum with the temperature of 20 °C fills the defrosting chamber and condenses on the surface of the defrosted product. The condensated steam has the role of thermal energy carried enabling product thawing. The study presents a modification of this method, introducing an additional stage of sublimation-dehydration vacuum steam thawing (SRVST). The study was carried out for different variants of initial sublimation degree (in the range from 0 to 15%) of a slice of pork loin (m. longissimus lumborum) assessing the final effect of the process of vacuum-steam thawing. Thawing kinetics was determined with the SRVST method, degree of sample defrosting and level of their rehydration. Based on the results it was demonstrated that the use of 12% sublimation dehydration of a meat sample enables its complete defrosting (reaching the temperature not exceeding the cryoscopic temperature). Numerous thawing methods are available12. The most well known methods of meat raw materials thawing are traditional methods—air thawing and water or brine immersion thawing. This thawing method is rather prolonged (it may last for up to 3 days), requires ensuring large storage surface area and it forms a significant microbial hazard due to the possibility of cross contamination15. The defrost chambers for contact or steam–air defrosting are an alternative to this method. In the recent years, a continuous interest has been expressed in the study on finding new defrosting technologies, such as the use of high pressure microwave, ultrasonic and infrared17. Research on dielectric, radio wave and high-voltage electrostatic field thawing has been conducted20. A series of studies concerns modifications of known methods, i.e. vacuum-steam, sublimation contact or sublimation-vacuum-steam thawing22. The latter method is covered by the present study.Considering that frozen foods, in particular meat and fish, are used in food processing, the thawing operation is necessary. Along with freezing and storage, this process has a significant impact on the quality of food products. It should be conducted conditions ensuring the most complete restoration of the original characters of the product. To this end, overheating of the product surface during its thawing and defrosting drip loss should be limited, which are causes of significant quality losses and physical, biochemical and microbiological changes of the product23. A favorable outcome of this method is the fact that thawing with vacuum steam takes place at the temperature of 20 °C. In this manner, overheating of the surface of defrosted food products is avoided, which takes place in the case of defrosting in normal pressure with steam with the temperature of 100 °C27. In the 1970s industrial solutions for vacuum-steam thawing were executed. However, this technology was withdrawn due to the negative phenomenon of significant drip loss. Authors have modified this method of vacuum-steam defrosting by introducing an additional stage of preliminary dehydration of the material. It was assumed that during ice sublimation from products with cellular structure, ice would sublimate in an easier manner from the channels and intercellular space than from the inside of cells. Thus, an inner porous structure is formed29. The modification was named sublimation-dehydration vacuum steam thawing (SRVST).Following the methodology of steam thawing, the thermal energy is provided by means of water vapour condensation on the surface of the defrosted food products. This heat, required for the phase change of ice into water in a frozen raw material is obtained from the phase change from steam to water. The steam thawing variant consists in the application of underpressure for the process, known as vacuum-steam thawing (VST). The product defrosted using this method is place in a vacuum chamber, from which air is pumped away. An open vessel with water is located on the bottom of the chamber, or the chamber is linked to an external tank. As a result of this underpressure (approx. 2400 Pa), water starts boiling at room temperature (approx. 20 °C). In order to maintain the water in the boiling state it must be heated. This is normally done by heating with steam, sometimes through a water heat exchanger or electric heaters. The condensation heat is used by the frozen product, resulting in its quick defrosting (approx. 120 g of condensing water defrosts 2 kg of frozen product)30. Different process operations, i.e. cutting, heating, grinding, pressing and in particular freezing–thawing of meat result in numerous unfavorable qualitative changes that depend on the level of weight loss. Under optimum conditions for freezing, storage and thawing of pork, the weight losses related to the defrosting drip loss reach 10%, while in the case of deviations they can reach even 18%31. This is caused by the brief defrosting time and absence of rehydration of the thawed aqueous phase. Storage of meat at a temperature of − 20 °C results in freezing about of the 80% water it contains32, then 60% of frozen meat is ice (75% water content × 80% frozen water = 60% ice in the meat). According to Eq. (t) needed for meat defrosting (m = 0.6 · mm) is a product of the mass of meat (mm) and mass fraction quantity ice contained it (0.6) multiplied by the heat of ice-water phase change (ct = 335 kJ/kg).Water accounts for about 75% of lean pork meatp = 2260 kJ/kg. Thus, the amount of steam (mp) needed to defrost a certain mass of meat was determined by Eq.  in relation to the weight of the meat (mm) is:For the check, the weight of the steam required to defrost , the material will be entirely defrosted.Based on the above circumstances a hypothesis was drawn up stating that if approximately 9% of ice is sublimated from frozen meat, then after the introduction of steam in thus created porous structure of meat, it will be defrosted in its entire volume with the bypassing of heat penetration from the surface. During vacuum-steam defrosting steam condenses on the surface of the defrosted material, and the heat penetrates the material based on the conductivity principle. However, the application of sublimation dehydration in the initial stage of vacuum-steam defrosting will result in the penetration (absorption) of water vapour into the porous structure of the defrosted material (at the stage of chamber steaming) and its condensation within the material. The condensing steam transfers the heat from the condensation phase change, resulting in even thawing of the material throughout its volume, thus limiting surface defrosting and defrosting drip loss.r).The aim of the study was to demonstrate the possibility of sublimation application as a preliminary stage of meat tissue defrosting with vacuum-steam method and determination of the effect of water sublimation on the level of defrosting of a meat portion. Based on the hypothesis made, application of sublimation would result in formation of a porous structure of the defrosted material, which would enable steam absorption and thus shorten the defrosting process. Based on the research, the influence of the degree of water sublimation on the thawing level of meat sample and the degree of rehydration were determined as well as the characters of these interactions. The intermediate aim of the work was to reduce the time thawing of meat sample while maintaining the quality of the raw material, determined by the level of initial weight recovery—level of rehydration  with a weight of 100 kg, collected from the lumbar part (m. longissimus lumborum). The carcass was stored in a coldstore for two days after the slaughter. Meat sample was prepared by crosswise cutting of the muscle fibers to a thickness of approx. 20 mm and weight 100 g ± 5 g . In this manner, 21 samples of meat were prepared (3 repetitions for each sublimation variant). The samples with thermocouple tip inserted into them6 were convection frozen to a temperature of − 30 °C and were stored at this temperature for a period of 2 weeks. After this time the samples were defrosted using sublimation-dehydration vacuum steam thawing.The research material consists of the The vacuum chamber consisted of a cylindrical vessel (1) covered with a glass plate (2) enabling observation of the process, connected with a vacuum pump (3). The chamber steaming was realized using the steam obtained from a heated water tank (4) connected with the chamber (1) via a duct with valve. The frozen meat sample (5) was placed in a vacuum chamber under a weight sensor (7). The measurement signals from the thermocouple (6)  and weight sensor (7)  collected by an analog–digital card (8) transferred to a computer and processed using MatLAB software. The measured values (3 replications for each variant) were archived in the computer memory. During sublimation two IR lamps (9) with 2 × 5 W were switched on, providing heat to the sublimated material (5).View of the experimental system and diagram with measurement elements significant for the contents of the present paper are presented in Fig. s [%] = 0; 2; 5; 8; 10; 12; 15). At the same time, the sample weight loss due to its sublimation dehydration was monitored. After obtaining the appropriate sample weight, the IR lamps were switched off, the vacuum pump suction valve was closed and the valve to the water tank was opened, resulting in chamber steaming. As a result of heating the water tank, temperature in the chamber during its steaming was maintained at the level of 20–30 °C. In this period, water vapour absorption by the sublimated (porous) material and its defrosting occurred. The steaming was completed (by closing the influx of steam) at the moment of observation of steam on the defrosted meat (appearance of water droplets on the surface), at the same time determining the steam absorption time by the defrosted sample. Subsequently, the chamber was decompressed and the obtained sample was assessed for the level of its defrosting.A frozen meat sample with thermocouple was suspended on the weight measurement sensor. The thermocouple and the weight sensor were connected to the measurement chain and then the chamber was closed with the cover. The vacuum-steam defrosting process was preceded by the preliminary stage of meat dehydration. To this end, the vacuum pump was started with water tank valve closed. After vacuum at the level of 50 Pa was obtained, IR lamps were switched on and sublimation process was conducted until the assumed dehydration level was obtained (Ss) was determined using the Eq. (i) and the initial sample weight (mo), and the weight of the sublimated ice results from the difference between initial sample weight and after the dehydration stage (ms):The sublimation dehydration level  was done by identifying the defrosted field (temperature above 0 °C), non-defrosted field (temperature below 0 °C) and temperature inside the sample (reading from thermocouple). To this end, the defrosted sample was cut centrally, obtaining two measurement samples with thickness of approx. 10 mm. The measurement of the area of the defrosted and non-defrosted surface was done using two methods. Using a thermovision camera , determining the temperature distribution on the sample cross-section after the thawing process, and on the basis of the sample hardness evaluation, separating the boundaries of the frozen zone from the defrosted zone. The second test was performed by puncturing the meat sample with a needle, separating hard—frozen—from soft—defrosted fields. Then, a series of digital photos of the prepared samples were taken, which were subjected to image analysis in MatLAB environment. The analysis needed additional identification of the boundaries the marked field (the outline was made by joining the puncture sites). The MatLAB algorithm, at the basis of the appointed edges, allows to determine the size of the surface area taking into account its irregular shape. These values were used to calculate the frozen area. Measurement results were used to calculate the degree of defrosting St according to Eq. (The defrosting level (St) in relation to the total cross-section surface area (Fc) and temperature increment level (ΔT) in relation to the observed range of cryoscopic temperature (ΔTcr) relative to the frozen field (Ff). A more extensive description of the identification of ΔT and ΔTcr is presented in the discussion of results regarding the kinetics of thawing , determined using equation no. 5, as a relationship of the weight after completion of the defrosting process (after rehydration) (me), in regards to the initial sample weight (mo).Quality of sample after thawing was assessed using the indicator characterizing the level of initial weight recovery—level of rehydration (Ss), defrosting level (St) and rehydration level (Sr) were based on the interval estimation theory with the use of Student t-test for the confidence interval α = 0.05, according to equation no. 6.Measurement uncertainty Δ for the values: sublimation dehydration level (SSs. The obtained results of mass measurement were averaged and listed on graphs as relationships between the level of thawing (St) and level of rehydration (Sr) on the level of sublimation (Ss). For the obtained results, standard deviations of dispersion were determined towards the obtained mean values. A HSD Tukey post hoc test was used to check the significance of the influence of sublimation dehydration on level of thawing and sample weight after thawing. Additional statistical analyses were conducted to determine the nature of the level of dehydration on the level of thawing St = f(Ss) and sample weight after thawing Sr = f(Ss) by determining the regression functions for this purpose. Each statistical test was carried out in the Statistica 13.1 program.The study was conducted in three replications for each sublimation dehydration variant An example of the recorded changes of sample weight during their sublimation for individual dehydration levels is presented in Fig. s = 8%; 10% and 12% a minor repeated weight loss was observed. This may be caused by too low volume of the porous layer created at the sublimation stage. Condensing water vapour and the drip loss generated during thawing are not fully absorbed by the dehydrated tissue and as the thawing process proceeds, they escape to the outside of the sample, causing weight loss.For each variant of assumed dehydration level, the final meat sample weight was determined, which constitute the criterion for the completion of the sublimation stage. For dehydration of SSs sublimation level variants in time.Figure c temperature for each of the analyzed variants was maintained in the range between − 28 and − 22 °C. The moment of temperature decrease at the first sublimation stage stems from the repeated freezing of samples. After this stage, temperature of each of the analyzed dehydration variants ranged between − 28 and − 26 °C. The thermal energy necessary to perform sublimation was provided using IR lamps, which after the period of approx. 1000 s resulted in a minor temperature increase of the defrosted sample, followed by its stabilization at the level of approx. Tc = − 23 °C. This is particularly visible for the dehydration variants SS = 5–15%.At the sublimation stage, Tcr determined the range of temperatures assumed as cryoscopic (from − 5 to 0 °C). The chart presents result for dehydration variants SS = 8; 10; 12 and 15%, because for the remaining variants  the obtained temperature values were not within the assumed cryoscopic range. The steaming stage duration was different for each analyzed sublimation dehydration variant, which is visualized with the course of the measurement curve. The end of the line determines the moment of commencement of water drip from sample surface. The presented temperature change curves show that for the dehydration level of SS = 12% the sample was completely defrosted at the moment of drip appearance. It assumes internal temperature of approx. − 1 °C. For lower dehydration levels (8 and 10%) remains frozen inside, with temperatures below—4 °C. In turn, for SS = 15% the sample defrosts before complete rehydration of the dehydrated structure occurs and at final moment of the process the temperature reaches positive values, Tc = 5 °C. The presented kinetics also indicate the defrosting rate. The time in which meat at its geometric center reaches the temperature of 0 °C, is the shorter the greater is the level of ice crystals sublimation.Figure Figure t) in relation to the total cross-sectional area (Fc) and the size of the frozen surface (Ff). The thermovision method turned out to be insufficient and it introduced a measurement error resulting from the rapid temperature variability of the sample surface during observation. Thus, further analysis results were obtained based on the results of the puncture method, which turned out to be more unambiguous.The result of the measurements was the determination of the size of the defrosted surface (Ft) and level of primary weight recovery—rehydration level (Sr) for all tested dehydration variants.Figure s = 15% dehydration approx. 8% product weight loss is observed. However, it should be emphasized that this value, according to literature, lies within the normal range for the process of freezing and thawing31.It was observed that with increased sublimation dehydration the level of sample defrosting increases. This relationship (within the tested variable range) can be explained with an exponential function. The obtained results further indicate that with the increase of sublimation dehydration level the level of rehydration is reduced in a linear fashion. In the case of Ss = 0%)11. This is caused by the latent heat released by the steam condensing within the meat sample. Moreover, it was observed that efficiency of this process also depends on the degree of ice crystal sublimation in the frozen product. The degree of sublimation affects the number of channels (spaces) being formed in the material necessary for the migration of water particles at the steaming stage. The greater the number of the channels (pores), the lower will be the resistance of the exchange of heat and steam weight migrating from the outside to the inside of the material. Thus, not only the rate of thawing will be increased, but also the rehydration time will be prolonged (example variant Ss = 15%) and the weight losses will be reduced. Thus, this confirms the hypothesis made on the possibility of vacuum-steam thawing of meat using the preliminary phase of sublimation dehydration.For the assumed variants (with the exception of the 0% zero sample) a sublimation stage characterized by a decrease of weight of the tested samples is visible. At the moment the chamber is steamed, the water vapour diffuses inside the system and gives up heat. As a result of this, the sample weight increases—rehydration occurs. At the moment when steam condensation was observed on the material surface (drip occurred and the sample weight started to reduce), the steaming stage was interrupted. Temperature changes within the sample centers for these two stages of defrosting are presented in Figs. 22. The obtained experimental study results generally confirmed this hypothesis, because SS = 12% dehydration enabled obtaining meat defrosting at the level of 96 ± 0.5%. The main cause for the obtained difference (at the level of 3%) may be creation of a heterogeneous porous structure throughout the entire volume of the defrosted meat sample at the sublimation stage. For the above sublimation variant the rehydration level had a similar value of 96 ± 2%. In defrosted meat (Ss = 12% variant) no additional defrosting drip loss or discolorations could be observed, the meat was mildly moist on the surface, did not exhibit drip and it was characterized by natural elasticity. Lower dehydration level (SS < 12%) did not result in complete meat sample defrosting. The amount of ice sublimated in this variant was insufficient to create the appropriate amount of channels and spaces, which resulted in reduced volume of steam penetrating to the frozen product as well as emission of condensation heat. However, dehydration at the level of SS = 15% turned out to be too high. The number of channels (pores) produced for this dehydration variant caused the diffusion of a large volume of water vapor into the thawed sample, and thus a quick thawing process from the inside and overheating of the material. For this sample, the moment of starting water dripping from the surface of the sample (an observable criterion for the end of the thawing process) corresponded to the temperature exceeding 0 °C (the temperature even reached 5 °C), so significantly higher than necessary.The analysis of the heat balance of vacuum-steam thawing of meat shows that it is enough to sublimate the mass of ice from the sample, constituting 9% of its mass, in order to, by replenishing this loss with diffusing water vapor, defrost completely the ice remaining in the meatm. longissimus lumborum), which was comminuted by cutting the muscle fibers cross-wise and thus obtaining cooking elements with thickness of approximately 20 mm and weight 100 g ± 5 g. The material was frozen at a temperature − 30 °C and after two weeks it was thawed using the suggested SRVST defrosting method. The method was verified experimentally and based on the obtained study results the following conclusions were drawn.The study presents a modification of the vacuum-steam thawing method for meat by means of introducing an additional sublimation dehydration stage prior to steaming of the vacuum chamber (SRVST sublimation-rehydration vacuum steam thawing). The selected test subject was the longest muscle of a fattening pig dorsum, from the lumbar part  and at a higher rate. The unfavorable phenomenon of defrosting drip loss is not observed when thawing with this method.An optimum level of sublimation dehydration exists, enabling defrosting. If the degree of dehydration is too low, the amount of channeling (pores) in the material is too small for the migration of water molecules, resulting in a reduction in the diffusible water vapor volume and thus less condensation heat released. In such a case the thawing rate decreases. However, if the degree of dehydration is too high, there is a risk of overheating of the sample as a result of uncontrolled temperature rise inside the thawed material.t = f(Ss) and sample weight after thawing Sr = f(Ss). The developed relationships  fit well with empirical data. The values of the determination indices for the determined equations are high (R2 = 0.97 − 0.99), which allows viewing the equations as a mathematical description of these relationships. Further analyses in this field could be based on the use of the developed equations to model the process .The conducted regression analysis enabled determining the relationship of the effects of the level of dehydration on thawing level SFurther research on the development of this method of defrosting is valid, taking into account, inter alia, process parameters, i.e. pressure in the chamber, water vapour volume or process control. Application of this thawing method should also be tested with regards to other products, i.e. fruit and vegetables, or fish blocks, taking into account their dimensions. It is also necessary to conduct further research to determine the process parameters in commercial conditions.


E directed away from the surface. Our aim is to answer the question of an increased penetrability of electrons at the collector side of a nanometric tunnel diode when covered by carbon atoms, a purely quantum mechanical effect related to the value of the workfunction Φ. To obtain Φ at a non-zero electric field we have extrapolated back to the electrical surface the straight line representing the linear increase in the potential energy with distance outside the metal-vacuum interface. We have found that under the presence of E the workfunction Φ = Evac − EF of the (100) pure tungsten surface has a minor dependence on E. However, the carbon-covered tungsten (100) surface workfunction Φ(C − W) has a stronger E dependence. Φ(C − W) decreases continuously with the electric field. This decrease is ΔΦ = 0.08 eV when E = 1 V/nm. This ΔΦ is explained by our calculated changes with electric field of the electronic density of both pure and carbon-covered tungsten. The observed phenomena may be relevant to other surfaces of carbon-covered tungsten and may explain the reported collector dependence of current in Scanning Field Emission Microscopy.We have performed density functional VASP calculations of a pure and of a carbon-covered (100) tungsten surface under the presence of an electric field  Several experiments at ETH  under thA very brief review on the relative importance of the emitter and collector workfunctions is necessary here. The original Fowler-Nordheim equation  referredE-dependent. Explicit numerical calculations by Jensen [The description given above is correct but not complete. In all the theoretical works mentioned above the Sommerfeld model for a metal was used and the workfunction of an emitter was taken as a constant characteristic of the metal under study. The same holds true for the relatively recent generalizations of Forbes  to nonmey Jensen  showed tThe above effects are expected to be more pronounced when foreign atoms are present on the investigated surface and may constitute the basis for the interpretation of the experiments mentioned in the Introduction. However, there is an additional complication in these experiments that deserves an explanation: whereas the current-voltage I-V measurements required a ΔΦ = −0.5 eV to be explained, Gundlach oscillations measurements  gave a vIn this paper, we examine the electronic processes at a tungsten (100) collector surface when it is pure and when covered by carbon that leads to the corresponding field dependence of its workfunction. We also note that the effect of carbon on the (100) surface of tungsten as an emitter has recently been investigated  but the E is pushing the electrons into the surface, were allowed to relax although no changes were recorded beyond the second layer. Note that due to the periodic boundary conditions, a triangular well is formed in front of the charge layer facing the back surface where electrons are pulled out of the metal. The energy cut-off for the expansion of the wavefunction was 317 eV and the condition for convergence of lattice geometry was that the change in the cohesive forces was less than 0.01 eV/A0. Purely electronic iterations were terminated when the difference in energy was less than 10−4 eV. Convergence of the DFT-VASP calculations are in general difficult as other workers have noted [E of 1 V/nm. Unfortunately, we were not able to go to higher fields, but it transpired that this was enough to draw our conclusions. We note that when convergence has been achieved, a minute electron density corresponding to 1/100 of an electron remains in the triangular well in front of the back charge layer and a corresponding charge is missing from the back tungsten surface, see We have not used analytical methods as in  but havevac − EF) = 3.98 eV. This value is smaller than the experimental value of 4.3–4.4 eV but this is mostly due to the Perdue exchange and correlation (XC) potential used in the present version of VASP. For the variation of the calculated tungsten workfunctions of most tungsten surfaces with respect to the XC functional used see [vac − EF) = 3.93 eV, i.e., 0.05 eV lower. The previous comments of The calculated band diagram of the clean (100) tungsten surface at ε = 0 is shown in used see . The corE = 1 V/nm. Instead the energy at every point outside the W (100) surface increases linearly in accordance with the applied electric field. The answer to this problem can be found in the work of Lang and Kohn [vac as the value of the VASP energy at the electrical surface, see We now proceed to the band structure calculations of the clean and carbon-covered (100) tungsten surfaces when an electric field is pushing the electrons into the solid. A problem arises in these cases with the definition of the work function. The quantity (Evac-EF) cannot be used immediately since there is no constant vacuum energy outside the metal surface under investigation, see and Kohn  and Forband Kohn  on the dE = 1 V/nm. However, when we examine the corresponding figure of the carbon-covered tungsten surface, E = 1 V/nm. We have verified that for values of the electric field up to the value of ε = 1 V/nm this change was proportional to the field. We expect therefore that at the more usual values of E = 4–5 V/nm at which field emission is performed the expected ΔΦ would be around 0.4 eV. This would be a substantial change of the workfunction of the carbon-covered tungsten collector surface by the field and it would affect exponentially any narrow gap diode. Bearing in mind the underestimates that the Perdue potential is producing of the workfunctions, ΔΦ might actually be higher.Using the above definitions we observe from E = 1 V/nm) − ρ. The positions of the atoms are also shown in this figure. The red thin lines denote the atoms of pure tungsten. The rightmost dashed thicker black line denotes the carbon atoms of carbon-covered tungsten while the thinner black dashed lines denote the positions of the relaxed tungsten atoms of carbon-covered tungsten. In the case of pure tungsten, there is an accumulation of charge density (red line) just outside the plane of tungsten nuclei and also a depletion layer immediately further out from the accumulation one. Obviously the incoming electrons have “squeezed” the host electronic density into the metal, note that this diagram gives the change in electronic density. A similar “squeezing” occurs in the case of the carbon-covered tungsten (black line), only in this case the “squeezing” is more intense and its accumulation layer has moved into the metal, i.e., to the left of the surface nuclei. Therefore, the incoming electrons will find it easier to enter the metal since they will be penetrating a less charged region compared to pure tungsten. Hence, a reduction in the workfunction should be expected as it does. In a more traditional way, one can view this process as a reduction in surface dipole moment.The electronic processes responsible for the above changes are described in the following The above process could be expected to hold for all carbon-covered tungsten surfaces since they are the result of purely coulombic interactions. We tentatively argue that they may also be responsible for the observed decrease in the workfunction of the carbon-covered tungsten collector 110) surface in [10 surfacWe have shown numerically that the workfuction of carbon-covered tungsten acting as a collector is electric field-dependent whereas that of pure tungsten is not to any significant value. This effect was shown to be the result of the reorganization of the electronic density of pure tungsten due to the presence of both the carbon adatoms and the electric field. The observed phenomena at the collector side might play a role in experiments where emission is observed to depend on the collector atomic structure.