There was an immense need for studies evaluating the dental health status in Syrian children, especially under the current circumstances of the Syrian crisis. No contemporary data was available. The aim of this study was to assess the current dental health status in children aged 8 to 12 years in Damascus city.The study was a cross-sectional epidemiological school-based oral health survey using stratified random cluster sampling. A total of 1500 children were clinically examined. For each child, personal information together with DMFT and dmft indices were recorded. Statistical analysis was undertaken to investigate the effects of different factors on caries prevalence. ANOVA, and Chi Square tests were both utilised.The caries prevalence for the whole city was at (79.1%). The mean DMFT was (2.03 ± 1.81) and the mean dmft was (2.47 ± 2.94). Of the DMFT index mean value, (91.14%) was for decayed and missing permanent teeth. Of the dmft index mean value, (89.1%) was for decayed and missing deciduous teeth. The most affected teeth were the permanent first molars (1.58 ± 1.51). There is a statistically significant relationship between the used indices means and the children’s distribution as to the city’s localities.Dental caries was higher than expected. Health promotion programmes are essential and of critical importance in order to improve the dental health status. Oral health is considered as a very important indicator that can be employed to indicate the general health status for persons . It alsoTherefore, dental health is a fundamental important aspect of the person’s general health. The presence of dental caries is a great indicator for the later development of many oral health related diseases that cause pain and sometimes impairment, and this is besides being the first cause for most teeth losses worldwide .The aim of this study was to assess the current status of the dental health in children aged 8 to 12 years in Damascus city and to help enabling health-care professionals to improve the oral health status amongst the whole population.The study was a cross-sectional epidemiological school-based oral health survey and was conducted in Damascus city in Syria. The field practical part of the study was conducted from September 2016 to January 2017. The study design and methods took into consideration the World Health Organisation’s (WHO) guidelines published as the “Oral Health Surveys; Basic Methods” in its 5th edition . DamascuEthical Approval was obtained from the Ethics Committee and the Board of Scientific Research at the Faculty of Dentistry at Damascus University. Official written permissions were also obtained from the authority bodies . Also, informed consent was obtained from children’s parents/carers in order to recruit their children in this study.The sample size was estimated at a precision level of (0.05) to be (1278). Still, the precision level was raised to (0.03) to increase the study’s quality and reliability making the sample size reach (1444) children. The number was rounded up to (1500) for easier calculations. The confidence interval was at (95%). The multi-stage cluster sampling method was used to select the sample objects. The study sample was comprised of (1500) children of which (745) were females (49.7%) and (755) were males (50.3%). The schools were randomly selected from the lists of schools provided by the Ministry of Education for each locality.Children aged 8 to 12 years old and residing in Damascus city in the time of the study.Having no personal reasons that prevent the children from participating (whether for the children themselves or their carers).Children having any active infectious diseases or any medical conditions that suggest special extra precautions for the children’s own safety and health as well as for the examiner’s.All children were examined by a single examiner (MAB). Personal information, DMFT and dmft indices were recorded as a whole and in details for each tooth as well. In addition, the participating children were taught how to brush their teeth well and were given oral hygiene instructions to improve their overall oral health. Contact was made with the parents/carers of those children in need for treatments and they were referred to the nearest dental office or dental care centre. The diagnostic kit used for the examination included oral mirrors, dental explorers, dental tweezers, and periodontal probes. Also, a head-held light was used. The children were examined at their schools.The raw data was processed using IBM SPSS Statistics version 23. Descriptive statistics study was done to reach the mean values for the used indices. Moreover, ANOVA, and Chi Square tests were implemented to study the relationships between the indices means and the distribution according to the localities.Caries prevalence rate for the whole city was (79.1%). The highest caries prevalence rate in the localities was seen in Dummar sector reaching (90.4%) while the lowest was recorded in Barzeh and Rekn Al-Dien sector and it reached (66.7%). The mean DMFT for the whole city was (2.03 ± 1.81). The highest DMFT mean in the localities was seen in Al-Mazzeh sector reaching (2.58 ± 2.25) while the lowest was recorded in Barzeh and Rekn Al-Dien sector and it reached (0.93 ± 1.34). The mean dmft for the whole city was (2.47 ± 2.94). The highest dmf mean in the localities was seen in Dummar sector reaching (4.71 ± 2.95) while the lowest was recorded in Al-Mazzeh sector and it reached (0.80 ± 1.68).The ft out of the dmft percentage was (10.9%), and the FT out of the DMFT percentage was (8.86%), both too low. In other words, over (90%) of both the DMFT and dmft indices mean values combined were for decayed and missing teeth. The teeth with the most lesions were the first permanent molars, with a mean of decayed first permanent molars of (1.58 ± 1.51) for the whole city. The highest mean for the decayed permanent first molars in the localities was seen in Dummar sector reaching (2.08 ± 1.66) while the lowest was recorded in Barzeh and Rekn Al-Dien sector and it reached (0.84 ± 1.24). The mean of missing first permanent molars for the whole city was (0.13 ± 0.74).Table Malnutrition, the increased consumption of carbohydrates and added artificial sugars found in cheap and low-quality foods, having no water fluoridation, the absence of many primary health-care services, the bad financial situation for plenty, and the crisis situation by itself , are all factors which have negatively attributed to the oral health situation  for the whole population. With such factors taking effect, it is extremely important to know the ground situation we are standing on before implementing any large-scale interventions or adopting nationwide strategies. For these reasons Damascus city was chosen as a location for our research. Damascus now has got residents from various other destinations all around Syria. Many of them fled from their home towns to Damascus because of the war, which makes Damascus a city that has got the full spectrum of the Syrian population not only for being the capital but also for having somehow better situations. Therefore, we can say that our conclusions and results are truly representative of the children’s dental health in Damascus and can be a good indicator as well for the children’s dental situation in Syria generally speaking.Table Despite the fact that the biggest share of these variations could be due to the differences in ethnicities, regions, environments, the age groups studied, time of the survey, and various other conditions, but it is also worth mentioning that plenty of studies proved that the presence of dental caries in the primary dentition is a very important predictor for having caries in the mixed and permanent dentitions. The same way it goes for the mixed dentition being also a predictor for the permanent dentition –15. TherOf the DMFT index mean value, (91.14%) was for decayed and missing permanent teeth. Of the dmft index mean value, (89.1%) was for decayed and missing deciduous teeth. In other words, the ft mean was equal to only (10.9%) of the dmft mean and the FT mean was equal to (8.86%) of the DMFT mean. These percentages are too low and could be due to the lack of knowledge regarding the necessity and importance of treating children’s teeth. Also, it may be the result of the bad financial situation leaving no ability for the families to cover the dental treatment costs.The teeth with the most lesions were the first permanent molars, with a mean of decayed first permanent molars of (1.58) for the whole city. On the other hand, the mean of missing first permanent molars for the whole city was (0.13). These high numbers indicate the ignorance of parents regarding the importance of the first permanent molars as well as the absence of any preventive measures like fluoride varnish and pits and fissures sealants. Moreover, it could be the reason of the parents not knowing that these teeth in particular are permanent teeth and the most important of all teeth as well, and possibly mistaking them for deciduous teeth. Also, it could be the result of the widespread misconception that primary teeth are of no importance, which along with mistaking the first permanent molars for primary teeth may have been the main factors that contributed to this problem.P-value was 0.000 and therefore it is statistically significant . So, it can be concluded that there is an assessed relationship between the localities in which the children reside and the caries prevalence. In other words, more attention and special preventive measures should be taken in the areas with the top caries prevalence rates. Also, it can be said that the same way it goes in management as most important first, any therapeutic or preventive nation-wide interventions should target the areas that are most in need first even within the same city.As shown in Table P-values for both indices were 0.000 and signifying the presence of statistical differences and significance (again very significant since they are less than 0.01). Consequently, it can be concluded that there is an assessed relationship between the localities in which the children reside and the means for both indices, the DMFT and the dmft, which also indicates that there is more immense need for extensive preventive interventions in the localities that are with the highest means and hence they should be targeted first as part of any future awareness or interventional programmes.From Table All participating children were given thorough advice on the best ways to care for their “smiles” and keep good oral health. These good oral hygiene instructions were passed to the children individually when examining each child and also in groups with the help of visual aids and illustrations. Teachers and school supervisors were also requested to pay good attention to the students’ health and hygiene generally and to the oral health in specific. One of the present study’s limitations that should be mentioned in here is not having carried out a test-retest.Caries prevalence rates as well as both dmft and DMFT indices means were all high indicating that the dental health has reached a low level. Hence, we can say that the oral health status is also low due to the bad dental situation which in turn requires special care and coordinating all the efforts seeking the better. There is an immense need for comprehensive preventive programmes as well as increasing the awareness about oral health generally and dental health in specific. Any awareness or preventive programmes should target the localities with higher caries levels first.Chronological limitations: The practical field part of the study was conducted in 2017 and 2016. Such studies are a continuous need and therefore it is highly advisable that this study is repeated within a period of 3 to 4 years. Spatial Limitations: The study was undertaken in Damascus and there is a necessity for carrying out studies like this present study in other Syrian cities. Logical Limitations: It is worth mentioning that no test-retest was carried out and this can be considered a limitation for the study. However, repeating such an examination procedure could have caused the children group to be re-examined some irritation and disturbance and could have affected their cooperation negatively in the dental clinic later on even slightly.


Information leaflets have been shown to significantly improve awareness of the symptoms of gynaecological cancers and to reduce perceived barriers to seeking medical help. This record-based, parallel, randomised control trial study aimed to assess whether receipt of a leaflet would change the behaviour of women experiencing symptoms indicative of gynaecological cancers by prompting them to visit their general practitioner (GP).15,538 women aged 40 years or over registered with five general practices in Northamptonshire, UK were randomised to two groups using the SystmOne randomise facility. Those in the intervention group received an educational leaflet from their general practice explaining the symptoms of gynaecological cancers and advising symptomatic women to visit their GP. The control group were not contacted. Electronic records were interrogated to extract sociodemographic data and details of GP consultations for symptoms, tests, referrals and diagnoses relating to gynaecological cancers in the 4-month period following the mail-out of the leaflets.p = 0.28). There was a significantly lower mean time to first presentation in the symptomatic intervention group  compared to the control group  . Survival analysis did not reveal a difference between the patterns of presentation in the two cohorts (Log Rank (Mantel-Cox) χ2 = 1.42; p = 0.23).7739 records were extracted from the intervention group and 7799 from the control group. 231 (3.0%) of the women in the intervention group, and 207 (2.7%) of the controls, presented to their GP with a relevant symptom during the 4-month period following leaflet distribution. The slightly higher rate in the intervention group did not reach statistical significance at the 5% level .Listed on the ISRCTN registry with study ID  Gynaecological cancers  have a combined UK incidence second only to breast cancer . EarlierLeaflets can increase cancer awareness and knowledge –12. HoweAn information leaflet detailing the symptoms of gynaecological cancers and encouraging women to present to their general practitioner with any concerns was developed using focus groups with experts, cancer survivors and the public . It was This study aimed to investigate whether being sent this leaflet affects the rate and timing of presentation to primary care for symptoms indicative of gynaecological cancers.The research was conducted in five general practices across Northamptonshire, UK, chosen to include a range of socio-geographical factors and practice sizes. All practices used the SystmOne electronic patient record system. Registered female patients were eligible for inclusion if they were 40 years or over  and were not on the oncology and palliative care, learning difficulties or mental health registers.Participants for the control and intervention (leaflet) groups were selected at random, without replacement, using the random selection facility within SystmOne from those women meeting the selection criteria. Approximately equal proportions of women were selected from each practice population, with equal numbers of control and intervention group participants. Those in each group were flagged using project-specific Read codes.The leaflet was developed by Morris et al. (2016)  through the leaflet] will inform you about an important health message: gynaecological symptoms should be taken seriously at every age, and discussed with your doctor if they don’t go away”.The leaflet was mailed to the home address of each patient selected for the intervention arm in June 2014, along with a covering letter from their GP which introduced the research project and included the sentence “I hope it [The primary outcome is the period prevalence rate for women over 40 presenting with relevant signs and symptoms within four months following distribution. We estimated the time to presentation up to four months following leaflet distribution for women seen with relevant signs and symptoms. We also calculated the proportion of women over 40 who were subsequently referred urgently for specialist assessment together with the time to urgent referral and noted gynaecological cancer diagnoses recorded during the study period, for descriptive analysis only.Previous research from surveys completed using Computer Assisted Personal Interviewing (CAPI)  indicateA SystmOne query was constructed using a list of over 200 Read codes which included all relevant codes relating to the symptoms in the leaflet (130 codes), diagnostic tests ordered, test results and referrals relating to gynaecological symptoms and possible gynaecological cancer diagnoses, together with demographic information.Patients were identified by a unique, non-identifiable project number before data was extracted for a four month period, starting the day after the mail-out date for the leaflet for each practice. Read codes were grouped under higher order categories reflecting either the leaflet content (e.g. in relation to groups of symptoms) or meaningful clinical groupings that allow for variation in codes used between different GPs.Ethnicity recording in general practice is known to be problematic . 44.6%  for comparison of time to presentation and referral (there is no censored data for these outcomes).Comparison of time from date of leaflet distribution to symptom presentation was subsequently investigated using Kaplan-Meier survival analysis. The start time for the event (recorded symptom) for both groups was the leaflet distribution date for the intervention group. This start date was therefore treated as a random date for the control group. This approach assumes that the presentation rate (per 4 month period) for the control group would be independent of when that time period began; the analysis investigates whether there is a difference in the distribution of presentations between the two groups. The number of days for those not having a recorded symptom by the record extraction date was censored at 4 months (123 days).All statistical analyses were performed using two-tailed tests with statistical significance taken at the 5% level.7739 records were extracted from the 8029 originally identified as the intervention group and 7799 were extracted from the 8029 flagged as controls. This discrepancy is likely to be due to records becoming unavailable (e.g. because of moving from the practice or death) in the time between initial group identification and data extraction. The CONSORT flow diagram is shown in Fig. The data is available from the Zenodo repository .There was no difference between groups as assessed by age or IMD at baseline (see Table p = 0.28).Of the 7739 women in the leaflet (intervention) group, 231 had relevant symptoms recorded by their GP in the four-month period following the leaflet distribution (3.0%). For the 7799 women in the control group, 207 had symptoms recorded in that period (2.7%). Although there is a slightly higher rate in the intervention group, this does not reach statistical significance at the 5% level . These results are shown in Table The number of days from the date of the leaflet distribution to the date of the first presentation for a symptom indicative of a gynaecological cancer was calculated to investigate whether receipt of the leaflet may have an effect on the delay in symptom reporting by women. For those presenting with a relevant symptom, the mean time to presentation (from the leaflet distribution date) for the control group was 65.2 days (sd = 35.0 days). The intervention group mean time to presentation was nearly 8 days shorter . This difference was statistically significant .There was an approximately constant presentation rate over the 4-month period for the control group, whereas the intervention group showed a higher rate of presentations in the 20 days following leaflet distribution, after which the rate was approximately the same as for the control group. This difference did not reach statistical significance (Log Rank (Mantel-Cox) χn = 66) were urgently referred compared to 0.7% of the women in the control group (n = 51). This difference did not reach statistical significance at the 5% level .In the intervention group, 0.8% of the women .The number of days from leaflet distribution to the date of any urgent referral was calculated and compared between the intervention and control groups. The means were 67.7 days (sd = 36.9 days) for the control group and 57.1 days (sd = 37.1 days) for the intervention group. Although this showed a 10-day reduction in the mean time to urgent referral for the intervention group, it did not reach statistical significance : two in intervention group patients, and one in the control group.p = 0.28)). Average time from receiving the leaflet to presentation for those with relevant symptoms was 8 days earlier in the cohort receiving the leaflet than in the control group (where the start time was the date of leaflet distribution to the comparable intervention group) ). It was not possible to confirm a difference in survival functions when both were compared across the 4 -week follow up (Log Rank (Mantel-Cox) χ2 = 1.42, p = 0.23).This study is one of the first of its kind to use a randomised controlled trial to quantify the impact of an educational leaflet on rates of, and time to, presentation for possible cancer symptoms in primary care. The differences in rate of gynaecological symptom presentation between intervention and control group were in the direction expected, but not statistically significant  was launched in the United Kingdom as part of a strategy to improve cancer outcomes. The key hypothesis underpinning NAEDI was that delays lead to cancer patients being diagnosed with more advanced disease and thus experiencing poor 1-year and 5-year survival rates. An investigative phase was followed by piloting and then definitive regional, disease -focused campaigns directed towards raising public awareness of symptoms and signs of common cancers . The modAttempts have been made to evaluate process and outcome, with urgent cancer referrals most often used as a proxy outcome. Where effects have been noted it remains difficult to be clear what impact the components of different campaigns might have, and in particular the value of local distribution of leaflets. Evidence that a low-intensity intervention such as leaflet distribution may decrease the patient interval for potential cancer symptoms lends support to pursuing this type of approach as part of a wider strategy for reducing the time to cancer diagnosis. This study does not provide reliable estimates for the likely impact on GP consultations or urgent referrals, but these could be derived in a larger randomised trial or observational study.This study is one of the first to attempt to systematically quantify the impact of an educational leaflet on rates of, and time to presentation for potential cancer symptoms in primary care. There was some evidence for increased rates of presentation in the three weeks after receiving the leaflet, but this was not statistically significant. There was a significant difference in time to presentation, with women in the intervention group presenting with symptoms just over a week faster than those in the control group. The evidence that this low-intensity intervention may decrease time to presentation for potential cancer symptoms lends support to pursuing this type of approach as part of a wider strategy for reducing the time to cancer diagnosis.


The authors of “Health Information Technology in Healthcare Quality and Patient Safety: Literature Review” :e10264) mistakenly provided revised figures that were not identical in every way to the original ones in the paper that they were meant to replace.During proofreading, the authors were asked to provide updated versions of The incomplete versions of The correction will appear in the online version of the paper on the JMIR website on January 3, 2019, together with the publication of this correction notice. Because this was made after submission to PubMed, PubMed Central, and other full-text repositories, the corrected article also has been resubmitted to those repositories.


EMG characteristics were measured. All the participants adapted to the vibrations and showed changes in the damping coefficient and or the natural frequency. Apart from the immediate adaptation, a subgroup showed a progressive adaptation after the first immediate change. Three functional groups were identified using support vector machine, correlations with anthropometric values suggest that muscle mass could affect the adaptation strategy used.It has been proposed that during walking and running the body has strategies to minimize the soft tissue vibrations. The concept of muscle tuning suggests that muscle activity changes in response to the input signal to modify the frequency and damping of such vibrations. Although it has been demonstrated for continuous vibrations and single impacts, the adaptations dynamics are still unclear. The purpose of this study was to determine (1) if the neuromuscular adaptation to repeated single impacts is immediate, (2) what are the adaptation mechanisms, and (3) if there are functional groups defined by different adaptation strategies. Twenty‐one subjects performed two sets of knee curl on a dynamometer with a custom‐made appliance that supported the foot and heel. The first set was for familiarization with a 90° range of movement and 400°/sec velocity. The second set had 15 repetitions with a 55° range and the same angular velocity. The subjects were not notified of the change; therefore the first impact was unexpected. A pair of electrodes and a three‐dimensional accelerometer were placed on the gastrocnemius medialis. Damping coefficient, natural frequency, and  Prolonged exposure to vibrations can have detrimental effects on the human body including reductions in motor unit firing rate and muscle contraction  and four females . Subjects gave their informed consent to participate in accordance with the University of Calgary's Conjoint Health Research Ethics Board policy on research using human subjects.The subjects performed two sets of knee flexions on a dynamometer  with a custom made appliance that supported the foot and the heel Fig. . The tesy‐axis of the accelerometer was aligned parallel to the long axis of the shank, the z‐axis normal to the skin surface, and the x‐axis normal to the z‐y plane. An additional one‐dimensional accelerometer  was placed at the most distal point of the attachment on the dynamometer to determine the phase and timing of the movement. The accelerometer data were recorded with the same DAQ‐card as the EMG and were sampled at 2400 Hz.Muscle activation of the GM was assessed by measuring electromyograms (EMG) using bipolar surface electrodes  placed on the muscle belly (according to the Seniam instructions) after cleaning with isopropyl wipes. Each electrode had a diameter of 10 mm, and the interelectrode distance was 22 mm. A ground electrode was placed on the patella. EMG amplifiers with an amplification by a factor of 1000 and a band pass filter from 10 to 500 Hz  were used to record the signal at a sampling rate of 2400 Hz. Soft tissue compartment vibrations were measured using a skin‐mounted tri‐axial accelerometer  placed 2 cm medial to the electrodes. The accelerometer was attached to the skin using double side tape and stretch adhesive bandage to improve the congruence of motion with the soft tissues. The The first set of knee flexions was for familiarization and warm up. Subjects began with their leg fully extended and flexed their knee at 400°/sec over a range of 90°. The velocity of the movement was limited by the dynamometer. The subjects were instructed to perform submaximal contractions with a self‐selected force and to apply a constant and consistent amount of force during the concentric phase through all of the repetitions (approximately 15). Recovery to full knee extension was a passive movement controlled by the isokinetic machine. The second set of knee curls consisted of 15 repetitions over a range of 55° at 400°/sec. There was a short break between (<30 sec) the sets in order to start the recording systems. The subjects were not notified of the reduction of the range of motion, therefore the first repetition ended with an unexpected event similar to an impact. After the first unexpected impact, the subjects were informed that the subsequent repetitions would be identical. Due to the similar nature of the sudden break event through all the repetitions, the word impact is used for both, the expected and the unexpected trials. Tri‐axial acceleration and muscle activity were measured during the second set of knee curls. After the testing procedure, anthropometric measurements for shank length and calf girth were conducted. The shank length was identified as the distance between the malleolus lateralis and the lateral knee joint cavity and calf girth was measured around the thickest part of the calf, approximately 1/3 from the proximal knee joint.Previous studies have shown no significant effect of gender on muscle tuning . The natural frequency of the soft tissue compartment was estimated by the highest peak value within the power spectrum (0.6 Hz resolution). To measure the decay of the power, a filter bank of 10 non‐linearly scaled wavelets was used for the wavelet transform  in the expected direction , it was 0 when there was no significant change, and it was ‐1 when there was a significant change in the opposite direction. An orthogonal vector space of dimension N = 18 was constructed whereby each variable  is represented by one axis. The values on the axes were the labels mentioned above. In this vector space a k‐means clustering was performed based on the Euclidian distances to separate the groups  dimensional vector space. However, some of the 18 variables  may respond in a correlated way to an intervention. The means of the variables that were obtained for the 21 subjects were subtracted from the measured ones and normalized by dividing them by their standard deviation. A principal component analysis (PCA) was applied to a matrix representing the normalized variables in an 18‐dimensional vector space . A significance level of 0.05 was chosen.All of the participants adapted to the vibrations and showed changes in the damping coefficient and or the natural frequency.When examining whether the adaptations were immediate, some subjects showed a different trend. They did not adapt immediately but progressively over subsequent impacts. Moreover, some of the participants showed a combination of both behaviors, they had an immediate adaptation but they continued to adapt over repeated strikes. Consequently, in the following paragraphs it will be specified if the adaptations found in the damping coefficient and in the natural frequency where immediate, progressive or a combination of both.y‐axis  were found in 18 of the 21 participants. Of these 18 participants, 17 adapted immediately to the vibration while one participant showed a progressive adaptation. Although most participants had a significant adaptation already by the second impact, there was a subgroup consisting on 11 of those 17 participants that continued to adapt over subsequent strikes, thus also showing a progressive effect. Not all of the participants had an increased damping behavior with repeated exposure, in fact five subjects had a decrease in the damping coefficient with repeated exposure , eight were immediate and five were progressive. Of these 13 participants, nine showed an increase in the damping coefficient while four showed the opposite behavior by decreasing the damping coefficient. For the axis normal to the skin (z‐axis), 17 subjects showed an adaptation, where 10 were immediate and seven were progressive. Of these 17 subjects, nine subjects increased and eight subjects decreased the damping coefficient.When examining how adaptations occurred in each axis, 13 participants demonstrated changes in the y‐axis. Of these 15 participants, 10 showed an immediate change and the rest had a progressive shift in the natural frequency. The same change was seen in 13 participants for the x‐axis, with six that had immediate and seven that had progressive changes. Finally, for the z‐axis, 15 participants showed adaptations, 13 had immediate changes, and two had progressive changes.A shift in the natural frequency was found in 15 of the 21 subjects in the The duration of the muscle activation was reduced in 18 subjects, corresponding to a reduction in the total intensity. Total intensity was calculated after the impact, consequently the active phase involving the voluntary movement and the preactivation phase were not included. Fifteen participants already had a significant reduction in the duration by the second impact (immediate change), while three had a progressive adaptation. The reduction in duration was reflected in the EMG intensity analysis where 19 participants showed a significant decrease in EMG total intensity (post movement). Seventeen participants changed immediately while two had a progressive adaptation.The “s” index used to determine the selected number of groups showed negative values for the two groups clustering, therefore it was not used for further classification. The 3‐groups classification was selected over the 4‐groups classification as it presented a higher median value (3: 0.2417 vs. 4: 0.2415).P < 0.01) of correctly classifying 96% of individuals with the SVM.All subjects but one were assigned correctly to their group  according to the leave‐one‐out cross validation approach using a SVM .The second group, formed by six individuals, was primarily characterized by changes in the z‐axis for both damping coefficient and natural frequency. For the damping coefficient, all of the participants showed an adaptation, five of them had immediate adaptations  and the last participant had a progressive adaptation. For the natural frequency, all participants had an immediate change, and moreover, four of them kept adapting. In this second group the EMG signal reflects the behavior of the z‐axis of the natural frequency. It showed either immediate or immediate and progressive adaptations simultaneously in both variables. Five of the six individuals in the group had a non‐immediate adaptation in the The last group was made up of five participants. This group was predominantly characterized by a decrease of the damping coefficient in the y and x axes, as well as no adaptation in many of the other variables. No similarities were seen for the natural frequency variables assessed. Three of the five subjects had adaptations in the intensity and duration of the EMG signal.This study assessed the adaptations of the soft tissue vibrations over subsequent similar shocks after a first unexpected shock. We wanted to better understand which mechanisms contribute to the fast damping of the soft tissue vibrations, and how is the process over time.Our results corroborate the findings by Wakeling et al.  where paPrevious research has shown two different mechanisms used to minimize vibrations. Increases in the damping coefficient . As these individuals did not show a consistent change in the natural frequency, they were defined as “dampers”. The PCA proved this axis to have the most weight in the first principal component, thus determining the variable with the higher variance and representing the principal factor defining the groups. It was expected that this would be the axis to predominantly show adaptations as the transmission of the vibrations evoked by locomotion, from heel to the upper sections of the body, occurs along this axis. This prediction was confirmed by the percentage of significant changes being the highest in this direction and by defining the variable with the most variance determined by the PCA.The largest group was characterized by adaptations of the damping coefficient in the A second group given by the clustering analysis was predominately characterized by changes in the natural frequency. The changes in the natural frequency were inherent in multiple axes, with the z‐axis being the predominant one, and found in all subjects within the group. We defined them as “frequency shifters”. Although those changes were the governing features, some individuals in this group also showed changes in the damping coefficient (z‐axis).Nonetheless, some subjects classified in one of the previous groups presented the defining characteristics of both groups. This is an indicator that adaptations are not limited to either changes in the damping coefficient or in the natural frequency as previously reported (Boyer and Nigg y‐axis of the damping coefficient. Those individuals showed an opposite behavior to what has been reported before, they presented a decrease in the value of the damping coefficient. Although the damping coefficient decreased, the amplitude of the first oscillation for all strikes were similar and the vibrations minimized faster with repeated exposure. This phenomenon could be caused by the anisotropy of the human soft tissue packages. The individuals in this group also showed a consistent shift in the natural frequency of the z‐axis. This modulation of the muscle activity possibly caused a change in the anisotropy characteristics of some subjects leading to a more complex behavior known as beating. When there are different oscillations affecting the same system and their frequencies are close together the interaction between those various frequencies leads to an overlap, potentially canceling the waves and minimizing the vibrations. When analyzing the raw acceleration signal, the oscillations do not reproduce the characteristic damped behavior, and this is translated to a characteristic shape in the sum of the powers of the wavelets. The subjects in this group presented a second minor peak in the sum of the wavelets’ power (Fig. Furthermore, the third group identified by the cluster analysis was also characterized by the wer Fig.  causing It has been previously suggested that the muscle mass might define the type of adaptation. Boyer and Nigg  theorizeOur results differ from those reported by Boyer and Nigg  and the To date, the mechanisms to minimize vibrations in the soft tissue packages were traditionally described as an increase in the damping coefficient or a shift in the natural frequency values. The results of this study showed that some subjects use both mechanisms at the same time and suggest that other mechanisms, as the beating effect, may also affect.The capacity of some subjects to continue adapting progressively after an immediate change is another finding never before reported.The strategies utilized by the subjects characterizing various functional groups and the differences in anthropometrics between those groups represent a promising approach to find the mechanisms behind which strategy is used by every individual.The authors declare no conflicts of interest, financial or otherwise.


This paper details an investigation into the characteristic ‘plink’ sound produced by water droplets impacting a liquid surface, such as those falling from a dripping tap. Modern high-speed video and audio capture techniques have been applied to this problem for the first time. Previous literature investigating the underwater sound produced has been validated, with the key sound producing feature both above and below the water confirmed to be the entrainment of a small underwater air bubble. Recorded sound frequencies have been shown to align with the theoretical natural oscillation frequency of the entrained bubble, confirming this to be the driver of the characteristic ‘plink’ sound. For the first time these oscillations of the entrained bubble have been directly observed on video footage. An investigation into the effect of underwater reverberation showed that the airborne sound field is not simply the underwater field propagating through the water-air interface, as had previously been assumed. An alternative hypothesis is that the oscillating bubble induces oscillations of the water surface itself, giving a more efficient mechanism by which the underwater bubble drives the airborne sound field. A model for this new hypothesis produces good agreement with experimental data. This initial study focussed on the fluid mechanics of a drop’s impact, but interest soon turned to the characteristic sound it produced. Around 1920 a number of researchers applied themselves to the problem, with Mallock2 and Paget3 both citing resonance inside the air cavity as the most likely mechanism behind the sound, whilst Jones4 and Raman and Dey5 found that there appeared to be a minimum drop height below which no sound was produced. These studies also noted that the drop impact resulted in a small air bubble being trapped underwater, and in 1933 Minnaert6, considering the sounds of running water, derived a formula for the natural oscillation frequency of such a bubble, suggesting it as a possible mechanism behind the distinctive ‘plink’ with his closing comment: “It remains to investigate […] if the sounds of falling drops cannot have the same origin as the bubble sounds.” Richardson7 was the first to put this new theory to the test by investigating solid spheres entering water, as these impacts also result in the entrapment of a small air bubble . Richardson found that the frequencies recorded did scale as suggested by Minnaert’s formula.The characteristic ‘plink’ produced by water droplets falling from a dripping tap is universally recognisable and has been a source of scientific curiosity for over a century. Worthington’s 1908 publication “A study of splashes”9 was the first in depth study into the sounds produced by drop impacts. Using a series of photographs Franz highlighted four key features of each impact: the initial contact; the formation of a cavity; the entrainment of an air bubble; and the recoil of the surface producing a vertical jet. Synchronised hydrophone recordings revealed the initial contact and bubble entrainment to be the key sound-generating stages, with a short pulse produced by the impact sound, followed by a delay as the crater forms, before a more significant wave packet is initiated after the bubble is entrained. Due to the low frame rate it was difficult to accurately associate physical events to the generation of the sound field.Franz’s 1959 paper “Splashes as sources of sound in liquids”10 among others, but little interest was shown in the sound-production mechanism until the late 1980s when it was suggested that the distinctive underwater sound signature of a drop impact could allow a simple hydrophone to be used to measure oceanic rainfall. This required a relationship between the size of a raindrop and the frequency of the sound it produced to be found, and led to extensive research into the underwater sound generated by individual drop impacts. Pumphrey et al.11 confirmed Franz’s earlier findings on the mechanism and key sound producing features, as well as noting that for a given drop diameter the underwater bubble only formed within a certain range of impact velocities, naming this the region of ‘regular entrainment’. Kurgan12 arrived at the same conclusions independently, whilst Medwin et al.13 looked into the effect of oblique incidences on bubble entrainment. These experimental findings were supplemented by the analytical work of Oquz and Prosperetti14, Guo and Ffowcs-Williams15 and Longuet-Higgins16.Further studies into the fluid mechanics of splashes persisted, including work by Macklin and Metaxas17 and Jacobus18 took advantage of the 26 m tall drop facility at the Naval Postgraduate School in Monterey, CA, to test drops of various sizes falling at their terminal velocities. They found that a different jet-based sound-production mechanism existed for larger drops, and linked drop diameter to frequency for these drops. Jacobus also interestingly noted a direct linear correlation between the sound energy emitted by a drop impact and the temperature difference between the drop and the main body of water.Whilst these initial studies were limited to low impact velocities and small drops, Snyder19 confirmed these findings, noting the differing underwater sound-production mechanisms of four distinct drop-size ranges. Nystuen et al.20 further investigated the sound generated by the bubble-entrainment mechanism, whilst in 1996 the same author21 found that there were some instances where the impact sound was significant due to mid-sized drops travelling too fast to create a normal cavity, but not being large enough to produce sound via the jet-based mechanism first outlined by Snyder17. Attention also focussed on the detailed characteristics of the oscillating underwater air bubble, summarised in Leighton’s book on the subject22.In 1992 Medwin23 suggests that the airborne sound is simply the underwater sound field propagating through the water-air interface, but no experimental study has been conducted to confirm this hypothesis. This study provides the first detailed investigation into the airborne sound produced by drop impacts, applying modern high-speed video and sound measurement techniques to the problem for the first time. This allows accurate causal links between the fluid dynamics of of the drop impact and the radiated sound field to be provided.As has been shown, extensive literature exists on the underwater sound produced by drop impacts. However, there appears to be a distinct gap concerning the mechanism behind the airborne sound. Leightonf, of the ‘plink’ sound produced by the drop impact, and as labelled in the figure the parameters affecting it are as follows: the drop’s equivalent spherical diameter, d, and impact velocity, U; the tank dimensions, W and L; the liquid’s depth, D, density, ρ, surface tension, σ, and dynamic viscosity, μ; and finally the speed of sound in both the air and the liquid, ca and cw. Dimensional analysis shows that the frequency’s dependence on the tank dimensions  and the speeds of sound (ca and cw) is insignificant as the former can be chosen to be much greater than the drop diameter (d), and the latter are much larger than the drop’s impact velocity (U).The scenario considered, shown schematically in Fig. et al.11 and Oquz and Prosperetti14 found that regular entrainment only occurred within a fixed range of impact velocities for a given drop size, and that no regular entrainment was observed for drop diameters smaller than 1 mm or larger than 5 mm. This indicated a need to control the drop’s diameter and impact velocity to ensure entrainment occurred regularly during experimentation.The mechanism of interest is the bubble entrainment described extensively in the literature on underwater sound production by drop impacts. Pumphrey et al.11, gives the drop’s impact velocity, U, in terms of its drop height, h, and its terminal velocity, VT.VT, depends on its drag coefficient which is non-trivial due to changes in shape caused by the interaction between the liquid and the air. To remedy this the method suggested by Beard24 was used, which combines dimensional analysis with fits to empirical data from Gunn and Kinzer25 to provide values of VT for drops with equivalent spherical diameters in the range 1.07 mm ≤ d ≤ 7 mm. The resulting values agree to within ±0.5% of the experimental values given by Gunn and Kinzer. Snyder17 validated Beard’s method, a more detailed account of which can be found in Pruppacher and Klett’s volume26.Knowledge of the drop’s impact velocity was required, and a formula giving a drop’s impact speed when falling from a given height can be derived using a simple force balance on the falling drop. This formula, shown below in the form used by Pumphrey A schematic of the experimental set-up is shown in Fig. −1).During the course of the experiments hundreds of drop impacts were recorded. They all exhibited some characteristic features which will be outlined here by studying the impact of a 4.0 mm diameter drop falling from a height of 86 mm , which then begins to recoil (frames 5 and 6); a small air bubble is then trapped under the water (frames 7 to 9) in a process referred to as bubble entrainment. The cylindrical rod visible in the lower portion of each frame had a measured diameter of 0.71 mm and was used to size the different features of the mechanism. Using this technique the maximum radius of the cavity was measured at 2.27 mm and entrainment was found to occur at a depth of 4.54 mm. The initial bubble, approximately spheroid in shape, had a major axis of 0.923 mm and a minor axis of 0.675 mm, with its final stabilised spherical diameter being 0.71 mm.A high-speed video of this drop impact was taken at 30,000 fps with the camera positioned horizontally . The cavity then forms (frames 5 to 7) before being seen to close up (frames 7 to 9), with this coinciding with the bubble entrainment seen in frames 5 to 9 of Fig. Figure d frames  and 4. TThe upper two plots in Fig. The lower plot in Fig. 27 their velocity is found to be of the order of 0.5 ms−1. As this is less than the speed of sound in air these surface disturbances cannot transmit acoustic pressure waves. The second possible sound generator is the oscillation of the water droplets thrown into the air by the recoiling surface. As water is essentially incompressible any oscillations of these droplets will be shape oscillations, rather than volume oscillations. Such compact oscillations represent a quadrupole acoustic source, and hence the water drops are extremely inefficient acoustic generators.As no further sound features occur after this bubble sound it is concluded that none of the above water flow features seen in Fig. Comparing the two signals in Fig. Frequency analysis of the two bubble signals reveals that both have the same dominant frequency at 8.66 kHz. For well over a hundred drop impacts the dominant frequency of the bubble sound above and below the water was found to agree to roughly within the resolution (400 Hz) of the discrete-time Fourier transform (DFT) used. This again suggests that the underlying mechanism driving each sound system is the same.One way to mathematically demonstrate the similarity of two signals is through use of statistical correlation analysis. Figure If the entrained bubble is in fact responsible for the ‘plink’ sound then suppressing the bubble should suppress the sound. This was achieved in two different ways: firstly by using the sizing rod, and secondly by introducing a surfactant. Figure A similar result was achieved using the second method, with washing-up liquid used as the surfactant. A video of the resulting drop impact is available as Supplementary Video 6 derived the following formula for the natural oscillation frequency of a submerged gas bubble by using energy arguments:f is the natural frequency, a is the bubble radius, γ is the ratio of specific heats for the gas inside the bubble, Po is the static pressure on the exterior surface of the bubble, and ρ is the density of the liquid. Using the sizing rod as depicted in Fig. In his 1933 paper Minnaert28 developed correction factors that may be applied to Minnaert’s formula for non-spherical bubbles and those close to a flat surface, both of which act to increase the natural frequency predicted by Minnaert and so would reduce the errors observed here. Accurate modification of the predicted frequency in this case is not possible due to the complex initial shape of the entrained bubble and the curved nature of the water surface at the bottom of the cavity  along the z axis is given by Blackstock29 to beρa is the air density, ca is the speed of sound in air, uo is the velocity of the ‘piston’, and k is the wavenumber. In our case the piston velocity, uo, can be estimated using the velocity perturbation arising from the pulsating bubble. By using an image source as shown in Fig. r is the distance from the bubble, ω is the radian frequency, t is the time, cw is the speed of sound in water, d is the distance from the bubble’s centre to the water surface, and A is a constant. From this pressure perturbation the velocity perturbation can be found using the momentum equation, and for The portion of the water surface closest to the bubble will be excited most strongly, and in this case that is the bottom of the cavity as indicated by the red arrows in the figure. Because the cavity depth is small compared to the acoustic wavelength, the sound radiated from this segment of the surface can be modelled as a piston, of radius d from the bubble, isTherefore the magnitude of the velocity perturbation at the water surface, a distance Substituting this into Equation r = R, the distance of the hydrophone from the bubble. For the microphone the pressure field is given by Equation z = zo, the distance of the microphone from the impact site. The ratio of the above and below water sound fields can thus be calculated to beTo compare the above and below water sound fields the ratio of the microphone and hydrophone pressures must be found. For the hydrophone the pressure field is given by Equation R ~ zo. Observations during the experiment show that the radius of the bottom of the cavity is approximately three times the distance of the surface from the bubble, and so ro ~ 3d, or During these experiments the distances of the microphone and hydrophone from the impact site were approximately equal, so The impact of a drop of liquid falling on a free surface creates a very rich sequence of dynamics that involves: the initial impact, capillary waves on the surface, a cavity due to the inertia of the drop, a recoil of the cavity due to surface tension, an entrapped air bubble, the recoiling surface forming a jet that disintegrates into a liquid drop above the air surface. This investigation has used modern high-speed video techniques for the first time, synchronised with microphone recordings in air and hydrophone in water to demonstrate that the oscillation of an entrapped air bubble is the key driver for both the underwater sound and the characteristic airborne ‘plink’. All the other features are effectively silent. However, the airborne sound is not simply the underwater sound field propagating through the water surface, as had been previously thought. In order for the ‘plink’ to be significant, the oscillating bubble needs to be in close proximity beneath the air cavity created by the inertia of the drop impact. The bubble then drives the bottom of the cavity like a piston in a baffle. The predictions based on this model are found to agree well with all the experimental data collected.Supplementary InformationSupplementary Video S1Supplementary Video S2Supplementary Video S3Supplementary Video S4Supplementary Video S5Supplementary Video S6


VMAT) and a double‐shell‐bolus full‐head device (DSBFD) designed for patient immobilization and better skin coverage. A VMAT plan was generated using an Eclipse treatment‐planning system for a prescribed dose of 60 Gy in 30 fractions. The treatment plan was analyzed to determine the conformity index (CI), the homogeneity index (HI), the target‐coverage, and the dose to the organs‐at‐risk (OARs). Skin‐doses were measured using optically stimulated luminescence (OSL) dosimeters. Clinical follow‐up was performed by the radiation oncologist during and after the course of radiotherapy. With regard to planning target volume (PTV) coverage, the V95 was 99%. The measured and calculated dose to the skin was in the range 100–108% of the prescribed dose. The mean brain‐PTV dose was 711 cGy. The CI and HI were 1.09 and 1.08, respectively. The mean positioning accuracy for the patient over the course of treatment was within 2 mm. The measured accumulated skin dose and planning dose was agreed within 2%. Clinical examination of the patient 6 months after radiotherapy showed good response to the treatment and a 90% reduction in scarring. The DSBFD technique combined with RapidArc treatment was useful in terms of the target dose distribution and coverage. Daily patient alignment was found very precise, reproducible and less time‐consuming.Malignancies with a superficial involvement of the scalp/skull present technical challenges for radiation‐treatment‐planning, such as achieving skin coverage with the prescribed dose and with the desirable conformity, homogeneity, and lower brain dose. We report a radiotherapy treatment technique for a patient diagnosed with diffuse basosquamous cell carcinoma of the scalp and adjacent skull‐bone. This study presents the plan's quality parameters, patient's dosimetry, and patient's outcome. The patient was treated using volume‐modulated‐arc therapy ( PTVplanning target volumeCTVclinical target volumeCIconformity indexHIhomogeneity indexDSBdouble‐shell‐bolusCBCTcone beam computed tomographyCTcomputed tomographyVMATvolume‐modulated arc therapyIMRTintensity‐modulated radiation therapyTPStreatment planning systemOARorgan‐at‐riskV95(%)the PTV volume receiving 95% of the prescribed doseD95(%)the dose (%) received by the 95% volume of the PTVOSLDoptically stimulated luminescence dosimetersAAAanalytical anisotropic algorithmHThelical tomotherapy1Radiotherapy is the only treatment option for basosquamous cell carcinoma of the scalp when surgery is not recommended, such as in cases of large lesions that involve the skull and brain, or owing to cosmetic and reconstructive issues, or when the patient is unwilling to undergo surgery. These extensive scalp lesions present a challenge for radiation therapy because of the convex shape of the target and its proximity to critical structures.Traditionally, electron‐beam techniques have been used for total scalp irradiation.In comparison to static and arcing electron techniques, intensity‐modulated radiation therapy (IMRT) has shownA double‐shell‐bolus full‐head device (DSBFD) was designed for patient‐immobilization and better coverage of the CTV especially skin. Here, we report a linac‐based radiotherapy treatment technique, VMAT, combined with the DSBFD for a patient diagnosed with diffuse basosquamous cell carcinoma of the scalp and adjacent skull bone. It is worth mentioning to report that the DSBFD device is consistently reproducible, precise, and take short time in every day placement compared to conventional bolus.Furthermore, the skin dose must be verified with a reliable dosimeter even if 100% skin coverage is predicted by the treatment planning system (TPS). In addition, the patient's daily positioning accuracy during treatment is very important because of the tight margin created by the inclusion of skin in the planning target volume (PTV) and the close proximity of the PTV to the brain.V95, D95), and doses to the organs‐at‐risk (OARs). In addition, we provide the patient's dosimetry results, including daily and accumulated skin dose measurements with optically stimulated luminescence dosimeters (OSLDs), and discuss in detail the impact of the DSB device on target coverage and patient positioning. Finally, we report on the radiation oncologist's observations of the patient during and after radiotherapy and on the patient's outcome according to the results of the post‐treatment MRI.We present the applied VMAT‐based radiotherapy method and the design and manufacture of a head immobilization device, DSBFD, used to achieve 100% dose coverage at the skin and reduce dose to the OAR especially mean dose of the brain. Furthermore, we achieved good planning quality parameters, including the conformity index (CI), homogeneity index (HI), PTV coverage ]. Palpation of the lesion revealed that it was immobile, adherent to bone, had averted margins and granulation, and bled easily when touched. A complete head and neck examination showed no other ulcers or lesions. No neck lymph nodes were palpable. A punch biopsy showed ulcerative, moderately differentiated, keratinizing basosquamous cell carcinoma. CT of the head and neck performed prior to treatment showed focal skin thickening and ulceration of the left higher scalp region with an underlying aggressive bony lesion of the parietal bone that was consistent with the patient's squamous cell carcinoma. The metastatic workup was negative. The lesion was inoperable owing to its large size and its adherence to bone, and a complete excision with wide negative margins was not achievable in this location. As a result, the patient was scheduled for external‐beam radiotherapy with 60 Gy, to be delivered in 30 fractionations. The patient tolerated the treatment well and showed no signs of severe toxicity.A 53‐year‐old woman presented in our department with a typical history of an old burn on her head that occurred at the age of 5 and was followed by skin grafting at that time. At the time of the examination, the patient had a nonhealing ulcer at the graft site that had lasted for 1 yr and was gradually increasing in size. Physical examination showed a large ulcer that was approximately 15 × 10 cm2.BMarjolin's ulcer is a term used to describe a rare type of squamous cell carcinoma occurring at sites of chronic burn or scars. The malignant transformation is usually slow, with an average latency time of approximately 30 years. The tumor may initially present as an ulceration that fails to heal, and nodules may develop as the lesion progresses. Other clinical signs include rolled or averted wound margins, excessive tissue granulation, rapid increase in size, and bleeding to the touch. Squamous cell carcinomas occurring at sites of chronic burn or scars are typically aggressive and associated with a poor prognosis. Surgery remains the main treatment for Marjolin's ulcer, and wide surgical excisions with margins of up to 2–4 cm are commonly suggested. Because of their relatively poor vascularity due to extensive fibrosis, these cancers show poor response to systemic chemotherapy and radiotherapy.2.CThe main objective of the immobilization device for the patient's head was to achieve 100% skin coverage and ensure an accurate and reproducible daily setup. Another aim of this design was to treat the patient in the prone position, owing to the location of the lesion. The device comprised unique anterior and posterior shells designed to cover the patient's head and secure the 1‐cm‐thick bolus flush against the target area. The design and fabrication process of the shells are described below.2.C.1The patient was placed in the supine position on a comfortable headrest that was selected to fit her head and neck as shown in Fig. Next, the patient was aligned in the treatment position using anatomical landmarks, such as the tragus, septum, brows, and superior sternal notch. Anterior scout images were acquired using a CT scanner to confirm the position. The midline was marked to guide the therapist during the shell construction process and ensure the patient's alignment was maintained.A three‐point shell was placed in a hot water bath until translucent. Subsequently, the shell was patted dry and stretched over the patient's face. A good molding over the entire face was ensured and special care was given to the forehead, nose, chin, and cheeks. Bolus was sandwiched between the shells at the forehead area.After the mask was set, it was removed from the patient.The mask was cut to include the entire face area to the level of the ears.This shell was used for the immobilization of the face when the patient was in the prone position. The mask covered the face from the forehead to the chin and extended laterally to the level of the ears Fig. .The pat2.C.2The anterior shell was placed on the prone headrest. The patient was then placed in a prone position with her arms by her sides. A mattress and an ankle rest placed under her ankles were used for comfort. The posterior shell is shown in Fig. A posterior scout image was obtained to verify the patient's alignment.The anterior mask was fixed to the prone headrest (a glue gun was used).A three‐point shell was placed in a hot water bath until translucent. The shell was then patted dry and stretched over the patient's posterior head and neck area. A good molding of the shell over the neck and skull area was ensured.When the posterior shell was set and completely dried, the bolus was added. The thickness and area of the bolus were determined by the radiation oncologist and verified by the medical physicist. During application, a better attachment to the shell was achieved by removing the skin of the bolus and placing its sticky side facing the shell. We ensured that there were no gaps or overlap resulting from the irregular shape of the area to be covered.A thermoplastic sheet was placed in a hot water bath. Next, the sheet was positioned over the bolus and attached to the posterior shell (the bolus was permanently sandwiched between the shells). As advised by the medical physicist and the radiation oncologist, the therapist performed a CT scan of the patient in the treatment position  under the standard brain imaging protocol (120 kVp and 120 mAs). Images were reconstructed with a voxel size of 1 × 1 × 2 mm2.EThe delineation of the CTV and the PTV was performed by the radiation oncologist using the Eclipse TPS . For the CTV‐to‐PTV expansion, a 3 mm margin was applied. The OARs, including the eyes, lenses, optic nerves, optic chiasm, and brain‐PTV, were delineated by the medical physicist and reviewed by radiation oncologists.3. A high‐skin dose within the PTV was among the highest priorities. The objective was to achieve more than 100% of the prescribed dose at the skin and reduce the dose to the OAR. The RapidArc treatment was delivered using two arcs (clockwise and counterclockwise) from a 6 MV beam with a single isocenter, 350° gantry rotation, collimator angles of 15° and 345° and a maximum dose rate of 600 MU/min.The CT images and OAR contours are shown in Fig. 2.FV95, D95, the mean brain dose and doses to the OARs . Dose fall of characteristic beyond the PTV extending into normal tissue was evaluated from the DVH curve of the Brain‐PTV structure. For the dose fall off trend, the parameters including D5% and D20% for the Brain‐PTV structure were closely looked by the RO during the plan approval.The approved treatment plan was evaluated according to standard planning quality parameters, including the CI, HI, dose‐volume histograms (DVHs), the mean dose to the skin in the PTV, 2.F.1VPTV is the treatment volume of the identified isodose, VTV is the volume of the PTV, and TVPV is the volume of the PTV inside the identified isodose.The CI of the treatment plan was defined using the following equation2.F.2D98%, D50%, and D2% are the doses received by 98%, 50%, and 2% of the PTV volume, respectively.The HI was defined using the following formula:2.G2. The CBCT exposure parameters were 80 kVp, 25 mA, and 8 ms. The setup error was determined by the anatomical displacement between the kV or CBCT images and the reference planning CT images and was expressed as translational couch shifts in three directions.For superficial and complex targets, the use of CBCT and kV imaging were highly recommended to ensure patient alignment. During treatment, an on‐board imaging (OBI) system was used to align the patient for the delivery of each radiotherapy fraction. The OBI 2.HIn vivo dosimetry for radiotherapy patients is necessary to verify that the dose delivered to the patient corresponds to the prescribed dose calculated by the TPS. The use of OSLDs is highly recommended for skin dose measurements at superficial lesions of the scalp or adjacent regions of the skull. We used a commercially available OSLD system  that consisted of a small microStar® reader and InLight® nanoDot™ dosimeters (Al2O3:C), for more detail on OSLD read Mail et al.As the disease was most severe and intense at the skin of the patient, skin dose monitoring was very important. 33.A3.A.1D1%) values of 6240 cGy (104%). The V95 was 99% and the PTV mean dose was 6075 cGy. These dosimetric parameters show that the dose distribution within the PTV was very uniform, homogenous, and conformal. The mean skin dose measured within the PTV was 6239 cGy. From the brain‐PTV curve  criteria. The mean doses to the brain and brain‐PTV were 1217 and 711 cGy, respectively. The other dosimetric parameters of the brain, 3.BDuring the kV and CBCT imaging, the shifts and patient contours were monitored for any significant changes. The overall alignment accuracy Fig.  for the 3.C± 51 cGy (106% of the prescribed dose). The accumulated dose measured with OSLD‐C after 30 fractions was 6158 ± 101 cGy (102.5% of the prescribed dose), which shows the closest agreement (2%) with the dose of 6239 cGy calculated by the treatment plan at the location of OSLD‐C. The results of in vivo dosimetry for radiotherapy patients, especially for the delivered skin dose, must correspond to the prescribed dose calculated by the TPS. Typically, calculations and measurements of the skin/surface doses are always difficult and complicated; however, the calculated and measured doses obtained in this study were in close agreement.The OSLD‐A reading obtained after each fractionation is plotted versus the number of fractions in Fig. 3.DAn MRI of the head and neck performed at 8 weeks post‐radiotherapy showed evidence of scarring and loss of subcutaneous tissue in the left front parietal region. Upon clinical examination, the patient's response to the radiation treatment was shown to be excellent, approximately 20% of the initial scarring. The scaring comparison can be seen from Fig. 4The main goal of this study was to provide a uniform dose (with the desired skin coverage) to the target  while maintaining the dose delivered to the normal tissues as low as possible  were ignored because of its low magnitude compared to the prescribed therapeutic dose. The patient outcome, including lesion resolution and disease control, was reasonably good. The difference between the lesion/tumor size before and after radiotherapy can be observed from the pre‐ and post‐radiotherapy images in Fig. 5The use of the DSB device was determined to significantly aid with the coverage of a complicated (concave) shape and a superficial target (skin lesion). Our objective of 100% coverage of the skin was successfully achieved. Furthermore, the implementation of the DSB improved dose homogeneity and conformity in the PTV and showed reduction in mean dose to the brain compared to the published data.The dose measurements at the skin lesion with OSLDs, including daily and total accumulated doses, were useful for determining dose accuracy and the level of agreement with the planned dose. Also, it gives a strong clue regarding the patient alignment throughout the treatment duration in the form of dose accuracy at the skin. The daily dose measurements at the skin lesion were achieved 100% of the prescribed dose throughout the treatment. The agreement between the measured dose and the planning dose was within 2%.6This study was reviewed and approved by the Research Ethics Boards  of the King Abdullah International Medical Research Center (KAIMRC), Ministry of National Guard Health Affairs, Saudi Arabia. Consent of participant in this study was obtained from the patient.Available on request.The authors declare that they have no competing interests.No funding has been used or requested.


Frustrations, monetary losses, lost time, high fuel consumption and CO The unplanned development of urban centers often is associated with severe socio-economic problems. Such uncontrolled urban growth typically causes significant stress on city structures due to the unexpected demand of various resources and services. One of the most affected sectors is the urban transport systems, in which inefficiencies may lead to many negative consequences. Among them are the increase in greenhouse gas emissions and many hours stuck in traffic congestions, thus resulting in health issues and monetary losses. For instance, the congestion cost in the United States, the United Kingdom and Germany were almost $461 billion in 2017 [One approach to prevent these problems is the development of an Intelligent Transport System (ITS). An ITS uses communication, processing and sensing technologies to improve the urban traffic and consequently the flow of vehicles in the urban road. Moreover, an ITS does not only aim to provide traffic management services  but also security management services and infotainment applications to drivers, passengers and pedestrians ,3,4,5,6.ITS services and applications have intrinsic characteristics regarding the way they process, store and disseminate a vast amount of data generated in ITS ,8,9. Thelow latency–some ITS data have strict time constraints, such as data for re-route systems; predominant wireless access–modern ITS systems heavily rely on wireless communications; wide geographical distribution–ITS has sensors geographically spread. However, the scope of the data gathered is restricted to the location of the sensors that generated such data; real-time interaction–re-routing systems have real-time requirements; mobility–an ITS is used to optimize the mobility of vehicles in the city. Although, the ITS may also leverage mobility to perform data delivery activities to various stakeholders; scalability–an ITS needs to be scalable, due to the high number of vehicles and sensors; and extensibility–if the city grows, the ITS infrastructure also needs to grow to support the expanded region. These characteristics enable Fog Computing to offer an ideal platform for highly dynamic and heterogeneous ITS environment [The main benefits to designing an ITS with Fog paradigm are : low latironment .Generally, route suggestion services rely on data from specific regions, as traffic conditions, which may be irrelevant to other regions of a city. In this scenario, such service may exchange a large amount of data from heterogeneous data sources ,12 to moCloudlet which have processing and communication capabilities  and are geographically distributed to be closer to the access networks [A, possesses a more powerful resource, however the longer distance to retrieve data and the presence users beyond congested connections due to the use of the Internet often limit the real-time services and increase the network cost, especially considering a high dynamic vehicular network topology. Fog paradigm and Cloudlets environment are shown in B, where the resources are closer to the end devices permitting a faster response time and a local service decision. Finally, users and sensors devices  are represented in C.In this scenario, a route management service that takes advantage of the features of the Fog computing paradigm is extremely desirable in ITS. This happens because the Fog computing paradigm moves its resources (storage and processing) to the edge of the network, thus bringing the available resources as close as possible to end-users without the assistance of the Internet . The Fognetworks . Since CIn the literature, several studies address the problem of route management in urban centers ,24,25,26Fast Offset Xpath Service, which is based on the Fog computing paradigm. FOXS uses the Cloudlets to monitor the traffic conditions and to calculate the vehicle route. In this way, FOXS allows that the computational power resides closer to where it is most required, thus dividing the system load and increasing the overall scalability of the system and holding the capability to collect, process and store large volumes of data. For that, FOXS uses the network infrastructure Road side Units (RSUs) as a Cloudlet entity, which is deployed in the city to manage the traffic of vehicles. For its operation, a mechanism that gathers all necessary data from vehicles and road sensors was developed. Such mechanism optimizes the delivery rate and reduces the number of messages in the system. Then with the data collected by the corresponding Fog entities, the level of congestion of the roads is estimated. Finally, according to the conditions of the roads, the corresponding Fog entities calculates a new route as a suggestion.Given the aforementioned limitations, this article proposes a traffic service to control congestion, named FOXS–This article was based on our previous work . It shouIn addition, we extend the previous experiments proposed in Reference . Other rThe remainder of this article is structured as follows. This section presents related works that address the problem of route management, that is, traffic congestion management of vehicles in urban centers. In the last few years, such a problem has been explored by several works ,26,28,29There are several works ,31,32 th2 emissions and fuel consumption of vehicles. To this end, real-time data about vehicular traffic conditions, such as position, speed and direction are gathered by a centralized system through vehicle-to-infrastructure (V2I) communication. Four steps are periodically executed in the traffic care system: (a) Data collection and representation, which describes the network using a directed graph, in which the weights are the average travel time; (b) Congestion prediction is the service that periodically checks all road segments to detect signs of congestion; (c) Selection of Vehicles to Be Rerouted selects candidate vehicles near the congested roads; and (d) Choose alternative routes for each previously selected vehicle. The authors employ three strategies for calculating new routes: (i) Dynamic Shortest Path, which calculates the route with the lowest travel time; (ii) Random k Shortest Paths, which selects the k lowest travel time path routes and assign, at random, one of them to the vehicle; and (iii) Entropy Balanced k Shortest Paths, which is an enhancement of Random k Shortest Paths, in which it is considered the impact of the selected road on the future density of the road. However, these strategies have the following drawbacks: (i) congestion in other places due to the suggestion of routes to the same area; (ii) long routes can be selected to reduce the traffic of vehicles in another area; and (iii) the use a central server requires a substantial computational resource and network communication, so the use of a central server is not salable.The system proposed in Reference  is respoK-NN (k-nearest neighbors) according to the average speed and the density of the path. As output, it informs the road classification based on the traffic condition . Finally, CHIMERA uses the K-Shortest Path-based algorithm for the route choice. However, different from this article, these solutions [The work described in References ,25 propoolutions ,25 did nMeneguette et al.  proposedDoolan et al.  proposedYounes et al. ,35,36 prWang et al.  proposedJeong et al.  proposedThis section presents a traffic management service for route suggestion: FOXS, Fast Offset Xpath Service. FOXS is based on the Fog computing paradigm, which allows distributing the computer and communication resources among ITS components using the various computational entities, as presented The FOX is composed of two main components, Vehicles and Cloudlets. Vehicles have communication capabilities and embedded sensors  that are responsible for collecting data about road conditions as well as receive/request new routes. Cloudlets are implemented as RSU and the Cloudlet set forms the Fog computing environment see , Label AIt is important to point out that the spatial context-aware characteristics allow that each Cloudlet to be independent of each other. To increase the flexibility and environment communication penetration, the Cloudlet can be equipped with various communication technologies  and multiple antennas , Label CIn order to perform Data Gathering, we need to deploy the RSU infrastructure, that is, the Cloudlets. After the deployment process, the Cloudlet gathers road/vehicle data.For this implementation, we use a set of RSU with Cloudlet capability spread homogeneously in the environment to achieve full coverage of the entire map see . Each ClCloudlets are distributed accordingly to their coverage by applying the Hexagonal Binning  algoritFor the service to work correctly, the components of the traffic management system, such as Cloudlets and vehicles, send control data periodically (beacons) informing about the roads traffic conditions in their region and other types of data that FOXS uses. The acquisition of this data is executed in a distributed way using the communication capability of the Cloudlets. Cloudlets send beacons informing its position, the route interval for that region and the list of roads congested inside its region. Vehicles use such information to find nearby Cloudlets to send traffic information and request a new route. The data sent are the vehicle speed, position, time spent to move on each road and its current route. These data are sent periodically through beacons to the closest Cloudlet. Once the Cloudlet receives data about a specific region, it uses with the proposal of acquiring knowledge to execute the traffic service. The data exchanged considering the proposed cloud-based architecture and the DSRC/WAVE communication protocol is illustrated in  In order to improve the communication between vehicles and RSU, a mechanism for message scheduling was developed to increase the packet delivery rate in the architecture using a DSRC/WAVE communication standard. The mechanism (presented in Algorithm 1) has the objective of scheduling the time of sending the packets to the 802.11p MAC layer to avoid the resynchronization problem . The meIn this phase, the system processes the collected information from the previous step. Once the map is all covered by Cloudlets, each Cloudlet has the responsibility of collecting and processing only road data within its coverage. Thereby, limiting the data gathering/processing to a smaller region, reducing the cost of communication and making a processing load balance between Cloudlets in the system.However, as described in Reference , the sizV is the set of intersections within range of the AoK (representing the vertices) and E is the set of roads connecting the intersections (representing the edges). The weight of each road G where: i is the relation of the maximum allowed speed in the road inversely proportional to the speed at which vehicles travel on the road. Therefore, if the vehicle speed is close to the maximum speed allowed on the road, the weight of the road is lower; j is the road occupancy that is inferred through vehicle’s positions sent by vehicle beacons.Each Cloudlet periodically updates the weight of each route based on information gathered by vehicles inside its coverage. A  multi-weight directed graph The periodic road weight updating is done in the following way. The Cloudlet makes averages of the data sent by vehicles that pass in a specific road for a time interval. Next, is used the Exponential Moving Average (EMA) to obtain the new road weight. The EMA is used to smooth out a large oscillation in the road weight that may occur toward recurrent events such as a vehicle parking or stopped for a short period of time. Thus, implying in an abrupt increase of the road weight implying on the road choice in the routing process.i is used by the routing algorithm  present in the Highway Capacity Manual (HCM) [The road weight  section ) and theal (HCM) . The HCMNote that each Cloudlet only classifies and updates the weight of the roads in its coverage area. To update roads on its AoK outside its coverage, Cloudlets share the road knowledge between them using publish/subscribe paradigm . SubscriAfter, all these update processes, the Cloudlets disseminates in beacon messages the list of congested roads inside of its AoK. Thus, FOXS takes action in order to avoid the formation of congestion.In this phase, each Cloudlet performs the detection and control of congestion by calculating alternative routes to the vehicles. Thus, decreasing the load on the congested roads. Each vehicle, periodically, checks if it will pass through a congestion road. For that, the vehicles receive a beacon message sent by the Cloudlet with a list of congested roads. This list only contains roads belonging to the Cloudlet’s AoK.Hence, at each route interval, the vehicle checks if its route passes through a congested road. The service delivery mechanism is illustrated in A) until the last road in its current route that is within the AoK of the Cloudlet (point B).Therefore, the Cloudlet computes a new route for the requesting vehicle in the scope of its AoK, that is, only using roads within the blue circle. Thus, the rerouting process does not change the part of the route outside of the AoK in purple (standard route). As we can see in G of AoK with its congestion characteristics (in Algorithm 2 as G) and the variable K describing the maximum number of alternative routes that must be calculated.As we can see in the Algorithm 2, the routing process begins when the RSU receives a new route request from vehicles with their information  . With this, the graph K alternative shortest paths as possible routes the vehicle can take . A route from this set is probabilistically selected based on the sum of the weights (w) of its roads by applying the Boltzmann probability distribution [The route weight is calculated as the sum of the weights of all the roads contained in the path. Thus, the routes with lower weight are the most requested, possibly moving the congestion from one point to another. Aiming to avoid this problem, the service computes a set ribution   to make a probabilistic choice of a route, thus preventing the algorithm to choose the same route multiple times. Thus, using the set of J = set of vehicles on the scenarioj  definedj for temperature T, according to Equation (The Equation :(2)KTj=∑i of vehicle j with the parameter of temperature T, according to Equation (The Equation :(3)PTj(rWhen The Equation :(4)E(Rj)v . If this condition is not satisfied, the new alternative route is concatenated to the remaining of the original route that lies outside the AoK of the Cloudlet that made the routing of v . After, the system sends a message to the vehicle with the new route.Once the route is selected, the system checks whether the last edge of the calculated alternative route is the destination of vehicle route size factor, which determines how much longer (in percent) the new route may be in comparison with the current route. If this route size factor does not satisfy, the vehicle maintains the current route. In this way, the system can limit the maximum size of the route, thus avoiding the increase of other traffic problems as the COWhen the requesting vehicle receives this new route, its navigation system verifies the satisfaction of the variable BASE.This section shows the methodology used, the obtained results and scenario modeled to validate FOXS regarding traffic efficiency and network cost. The performance of FOXS was validated by comparing it with CHIMERA , PAN 1 ahttp://www.omnetpp.org. For the simulation of traffic and mobility of vehicles, we employed the SUMO 0.25.0 simulator (Simulation of Urban MObility) [http://www.hbefa.net—Handbook Emission Factors for Road Transport) integrated into SUMO was used.The simulations were conducted using the network simulator OMNeT++ 5 Obility) , an openObility)  that impWe used realistic scenarios from an urban region of two big cities that suffer from traffic jam problems, Ottawa-Canada and Cologne-Germany. Such scenarios were chosen to evaluate the services in environments with different characteristics. The Ottawa scenario has a simpler structure with symmetrical streets and a smaller flow of vehicles compared to the Cologne scenario. The Cologne scenario was chosen to stress the system due to its more complex structure with fewer alternative routes and a considerably higher vehicle density. Furthermore, the network parameters for all simulations was set to 18 Mbit/s at the MAC layer and the transmission power to on model . Table 3Traffic Efficiency evaluation, we consider the following metrics:Traveled time: the average travel time from the starting point to the destination of all vehicles;Stopped time: the average time spent stuck in traffic jams for all vehicles;Average speed: the average speed of all vehicles;Traveled distance: the average distance that all vehicles traveled;Fuel consumption: the average fuel consumption of all vehicles to traverse the whole route;CO the average COPlanning time index (PTI): measures the reliability of the ratio of the 95% travel time to the ideal flow on the same path .Route size Histogram: the histogram of the number of routes by its size grouped into intervals of 500 m.Cumulative Distribution Function(CDF) of the routes size: the CDF of routes size.PTI by route size: PTI of a group of routes with similar sizes in 500 m interval.PTI Utility metric: the percentage of influence of the PTI by route size in the PTI result.All evaluated solutions follow the same operation flow ;Collisions per packets sent: the percentage of collided packet per all packet sent;Network delay: the average time to spread messages to all vehicles (in milliseconds);Application delay: the average time for the application to receive the new route when requested, with the service response time and retransmission time when necessary (in milliseconds);New route accepted: the average of new route accepted per vehicle in simulation;Cloudlet routes computed: the average of routes computed per Cloudlet;Cloudlet computation heat-map: representing the amount of routing executed by regions.To verify the behavior of the solutions according to the route size, we present the metrics: Route size Histogram with its CDF and PTI by route size presenting the route size distribution and the relation between the PTI and the route size range. The PTI Utility metric shows the route size influence on the quality of the result in a specific scenario. The http://www.openstreetmap.org/, by possessing an area of 8 kmOttawa scenario  represenBASE related percentage of all metrics for the implemented solutions concerning traffic efficiency. The solutions PAN1, PAN3, CHIMERA and, FOXS reduced the stopped time  has better results than PAN3 (5.1%). This happens because PAN3 calculates three alternatives routes and choose one at random. Thus, the second and third bests routes may have different sizes compared to the best route due to the geography of the city map. This not happens in FOXS, because the alternative route is chosen in a probability way reducing the chance of choosing a wrong route and the use of the route size factor. Similar behavior can be observed when we look at the travel time presented in BASE.ped time a in 16.1BASE (2.39%), because it always chooses the shortest route to destination besides the other solutions that calculate the new route based on the road condition. Considering FOXS, alternative routes, on average, are not 0.39% longer than the original ones. These results can be explained by the fact that FOXS employs a parameter that controls how much longer alternative routes can be. Analyzing the traveled distance d, only tThe quality of the congestion control of the solutions evaluated using the PTI is presented in Analyzing the network metrics, in ffic see . Figure Despite the higher volume of network messages generated by FOXS, as described above, FOXS handle the urban traffic better distributing the vehicles across the map avoiding the creation of new traffic jam. Consequently, the number of network collisions (0.9%) is lower among the solutions see b. HoweveIn Cologne scenario is a sub-part of a TAPAS Cologne scenario  present that incBASE solution. In this scenario, all the solutions evaluated had a similar behavior compared to the Ottawa scenario. However, the main difference between them was reduced, due to a greater vehicle density in the Cologne scenario  and the PAN1 and FOXS had the lowest route increase with 1.35% and 1.53% respectively d. Note tped time a was redped time b was incBASE  Data Gathering, where all data are collected, (ii) Data Processing, where the gathered data is transformed in relevant information to the service and (iii) Service Delivery, where the route suggestion is computed and forwarded to users. Several experiments in two different urban scenarios were executed in order to show the efficiency of the proposed traffic service. These experiments showed the reduction of the drawbacks generated by the traffic congestion in the stopped time (reduction of 70%), the CO