The influence of organ volume sampling, lateral scatter inclusion, and the selection of objectives and constraints on the inverse treatment planning process with a commercial treatment planning system is investigated and suitable parameters are identified for an inverse treatment planning replacement of a clinical forward planning technique for prostate cancer. For the beam geometries of the forward technique, a variable set of parameters is used for the calculation of dose from pencil beams. An optimal set is identified after the evaluation of optimized plans that correspond to different sets of pencil beam parameters. This set along with a single, optimized set of objectives and constraints is used to perform inverse planning on ten randomly selected patients. The acceptability of the resulting plans is verified by comparisons to the clinical ones calculated with the forward techniques. For the particular commercial treatment planning system, the default values of the pencil beam parameters are found adequate for inverse treatment planning. For all ten patients, the optimized, single set of objectives and constraints results in plans with target coverage comparable to that of the forward plans. Furthermore inverse treatment planning reduces the overall mean rectal and bladder doses by 4.8% and 5.8% of the prescription dose respectively. The study indicates that (i) inverse treatment planning results depend implicitly on the sampling of the dose distribution, (ii) inverse treatment planning results depend on the method used by the dose calculation model to account for scatter, and (iii) for certain sites, a single set of optimization parameters can be used for all patient plans.PACS number(s): 87.53.–j, 87.90.+y From an obscure, highly specialized radiotherapeutic technique practiced in only a few specialized centers around the world, intensity modulated radiotherapy (IMRT) is developing into a mainstream radiotherapeutic technique available in most major radiotherapy centers. The IMRT technique relies on inverse treatment planning (ITP) and holds great promise for improving radiotherapy both through increased tumor control and decreased treatment morbidity. The current routine clinical use of IMRT is hindered by several difficulties, such as: complexity of equipment used for dose delivery, complexity of the ITP process, and quality assurance issues related with dose distribution calculation and dose delivery.The clinical utility of an inverse treatment plan depends on several parameters, which are usually selected through an elaborate trial‐and‐error process that may involve several iterations of optimizations, volumetric dose calculations, and plan evaluations. Thus, even though ITP automatically designs the beam apertures and modifiers that are required for the delivery of a desired dose distribution, the process may be considerably more complex than the standard forward planning, whereby a dosimetrist designs the beam apertures and selects the physical beam modifiers.In addition, the routine dosimetric quality assurance of the IMRT delivery is rather involved and time‐consuming because of: (i) the limitations of existing dosimetric verification systems; (ii) the possible need to perform quality assurance for every patient since there may be significant inter‐patient variability of intensity patterns and delivery sequences; and (iii) the uncertainty in the interpretation and in the clinical significance of differences between calculated and measured dose distributions.–The work presented in this paper focuses on the problem of parameter selection for inverse treatment planning. Such parameters account for organ volume sampling, lateral scatter inclusion as well as objectives and constraints used in the inverse treatment planning process. The density of dose‐calculation points required for analysis of treatment plans has been a subject of previous investigations and some controversy.Consider the case of a single target and a single beam port, covering generously the beam‐eye view of the target. Assume no attenuation. If a uniform dose is to be delivered to the target with no intensity modulation, a single sampling point anywhere in the target can be employed for optimization, since a uniform dose to that point guarantees a uniform dose to the target. However, if the same point is used for optimization of all beamlets across the beam port, the optimization will fail to deliver uniform dose to the target, since only few beamlets contributing dose to the particular sampling point will be activated. The rest will have zero weights, which will result in complete miss of the target.et al.Chen ––Even though for certain sites inverse planning can certainly outperform forward planning,In this paper we present an approach that identifies adequate ITP organ sampling and scatter inclusion parameters. Even though these parameters are determined for a particular commonly used treatment planning system, their magnitude should indicate reasonable values of the same parameters for other planning systems. Furthermore, without necessarily aiming to produce “the best” IMRT plan, for the particular optimization algorithm, we show that ITP with a single set of objectives and constraints is possible for a particular treatment technique for prostate cancer. In order to illustrate this possibility, for ten patients, we compare inverse treatment plans generated with a single set of optimization parameters to their forward counterparts. Our goal is not to illustrate the superiority of inverse to forward planning, but to demonstrate that the inverse plans generated with a single set of parameters are clinically acceptable since they compare favorably to forward, clinically accepted plans. The methods presented in this paper can be extended to other inverse treatment planning systems and other anatomical sites.D, normalized to the absorbed dose delivered by a 10×10cm2 open field at reference depth zref is given by f is the source‐surface distance, Ks=Ks is a radially symmetric dose spread kernel (DSK) which accounts for scatter at depth z in phantom, F=F is the beam intensity distribution, and Pint is the open (“flat”) beam fluence of primary photons at depth z. The function Pint accounts for the nonflatness of the beam and for variations of the open beam fluence with depth z in phantom.A commercial planning system  was used for the study. This system employs a pencil beam convolution model for volumetric calculation of the dose distribution on a regular 3D grid. Within this model, the absorbed dose F=F, the Helios ITP option of the CadPlan treatment planning system employs a gradient algorithm, which minimizes a square dose objective under “soft” dose and dose‐volume constraints.dp deposited to a sampling point P is given as a vector equation by Fi,j is the intensity of the beam at location , within the beam aperture and api,j, is the precalculated dose deposited to point P by a beam with intensity distribution Fi,j=δi,j. The precalculated set apij for fixed indices  is referred to as a pencil beam (i j) and Fi,j is referred to as pencil beam weight.In order to determine the optimal intensity distribution Ks, which is convolved with the primary fluence in the dose calculation process.In addition to the volume sampling rate, by supplying a single cut‐off parameter, the treatment planning system allows the user to modify the inclusion of lateral scatter in the pencil beam calculation. The cut‐off parameter limits the radial extent r of the dose‐spread kernel Ks at several depths for the particular 18 MV unit used for the planning of the cases in this study. The introduction of a cut‐off on the radial extent r of the dose spread kernel Ks results in nullifying the dose spread kernel Ks for radial distances larger than the cut‐off value.Figure Once the pencil beam parameters are specified, the user defines treatment objectives and constraints. The objectives are formulated in terms of the admissible minimum and maximum target dose levels (in Gy) and their priorities (ranging from 0 to 100). The constraints with respect to critical structures fall into two categories: (i) dose constraints that stipulate the maximum admissible dose to the structure (in Gy) along with a priority (ranging from 0 to 100) and (ii) dose‐volume constraints that stipulate the relative volume of the structure (in%) that can be exposed above a certain dose level (in Gy) along with a priority (ranging from 0 to 100).Cobj(F) to be minimized reads: wp is the priority of a constraint or an objective, Dp is a dose level of a constraint or an objective, N is the total number of dose sampling points, and the flag ξp has the value of 1 if a constraint/objective is violated and 0 if it is not. For the case of dose‐volume constraints, the objective function is identical to that given by Eq. Thus, for the case of dose constraints only, the objective (cost) function r of about 22 cm).Having specified all parameters, the user starts the optimization process with the precalculation of the pencil beams, followed by the iterative adjustment of the pencil beam weights in the process of objective‐function minimization. At its conclusion, inverse planning provides the modulated intensities of the beams as fluence matrices or maps. These optimized fluence maps are then used as inputs to a leaf motion calculator, which determines a dynamic leaf sequence for each field. These leaf sequences are then used for the calculation of deliverable fluence maps and a complete volumetric calculation of the dose distribution on a regular 3D grid see Eq.  with no Ten patients, who had recently undergone radiation treatments for the carcinoma of the prostate in our center, were randomly selected for the study. The treatment technique consisted of initial delivery of 45 Gy to planning target volume I (PTV1) in 25 daily fractions, followed by a boost of 25.2 Gy to planning target volume II (PTV2) in 14 daily fractions. PTV1 encompassed the prostate (GTV) with a uniform 1.5 cm margin, and PTV2 encompassed the GTV with a uniform 0.5 cm margin.–5% to +7% of the prescription dose.With the patient in supine position, a four‐field box technique (Plan I) with MLC‐shaped conformal beams and wedges (if necessary) was used for the initial delivery. In Plan II, a three‐field technique with one anterior (gantry angle 0°) and two posterior lateral fields (gantry angles 260° and 100°) was employed for the boost treatment of the patient in supine position. The beam energy for both plans was 18 MV. Both Plan I and Plan II were optimized manually by continuous adjustments of the MLC apertures and of the beam modifiers  until the PTV for the corresponding plan was encompassed as tightly as possible by an isodose surface at 95% of the plan prescription dose. This optimization criterion corresponds to an attempt to spare the bladder and the rectum as much as possible without violating the ICRU recommendation of target dose uniformity, given as 26×256 with a pixel size of 10×2.5 mm at the isocentre. Dynamic delivery of 250 segments per field was specified for the leaf motion calculator.The ten randomly selected patients were replanned with ITP, which employed the treatment unit, beam energy, and beam geometries used by the clinical forward planning techniques. The treatment unit is equipped with a 52‐leaf MLC with a leaf size of 10 mm at the treatment unit isocenter. The dimensions of the optimized fluence are 5 pts/cm3 to 100 pts/cm3. The radial cut‐off of the DSK was varied to cover the range from 0.16 to 2 cm. For one of the ten patients we performed ITP for several values of the above parameters while keeping the same objectives and constraints. The resulting intensities were fed into the leaf motion calculator, and the calculated deliverable fluence maps were then used for the complete volumetric calculation of dose distributions on a regular grid with a resolution of 2.5 mm.First, the sensitivity of the ITP with respect to the pencil‐beam parameters, the volume‐sampling rate of the anatomical structures, and the radial cut‐off of the DSK was evaluated. The volume sampling rates were varied to cover the range from These dose distributions were evaluated in terms of the dose statistics and the cumulative dose‐volume histograms (DVHs) of the various structures in order to determine adequate values for the volume‐sampling rate and the radial cut‐off of the DSK. The dose‐volume histograms were computed from the volumetric dose distribution with the same dose grid for all forward and inverse plans.Having identified these values for a single patient, we then performed ITP for both Plan I and Plan II for various sets of objectives and constraints. The goal was to achieve target coverage comparable to that attained by the forward planning (FP) technique. The selected optimal dose/priority parameters are listed in Table 100 points/cm3. A volume‐sampling rate of 100 points/cm3 should be adequate for the optimization, since for this sampling rate, the distance between the sampling points is smaller than the spacing of 2.5 mm between the nodes of the grid used for the final volumetric dose calculation. For the bladder and PTV2, similar behavior of the DVHs was observed.Figure Since the dose calculation time at each iteration is directly proportional to the point density within the anatomical structures of interest, the choice of an adequate volume‐sampling rate is a compromise between the conflicting requirements for a minimal optimization time and an accurate representation of the optimization results for a given set of objectives and constraints.5 points/cm3 if one judges the differences between the DVHs for 5 points/cm3 and for 100 points/cm3 to be clinically insignificant. However, given the current clinical knowledge, such a judgment is bound to be rather subjective. Instead, based on the DVH differences revealed in Fig. 30 points/cm3 to be adequate for inverse treatment planning since, for any dose point, the volume predicted by the DVH for 30 points/cm3 differs by no more than 2% from the volume predicted by the DVH for 100 points/cm3. The 2% criterion is quite stringent, given that the volume determination accuracy in radiation therapy planning is most probably in the 5%–10% range, due to both the interobserver variabilityIn order to speed up the optimization process, one can select a volume‐sampling rate as low as 25 25 × 25 cm,8 pts/cm2), one estimates a volume‐sampling rate of about 23 pts/cm3, in general agreement with the DVH findings.It is clear from the simple example presented in the Introduction that volume‐sampling rate is correlated to the effective cross‐section size of the pencil beams employed for the optimization. For the purposes of tumor control probability estimation Niemierko and GoiteinFigure However, if the 2% criterion used in the analysis of the pencil‐beam volume‐sampling rates is applied to identify clinically identical DVHs in Fig. 30 points/cm3, the radial DSK cut‐off of 1.5 cm, and the single set of dose/priority parameters listed in Table For the ten patients used in this study, using the volume sampling rate of +7% with respect to the prescription dose.Similar observations hold true for the majority of the patients in this study. Figure The inverse plans based on a single set of objectives and constraints were also evaluated for consistency and clinical acceptability with respect to the bladder and rectal sparing. DVH and isodose analyses confirmed that adequate, clinically acceptable sparing of the bladder and the rectum was achieved for all patients.~4.8% of the prescription dose) and to the bladder by 4.1 Gy (~5.8% of the prescription dose).Figure We further investigated the forward and inverse plans for patient #6 in order to correlate the only failure of the single‐parameter ITP to outperform the forward planning in terms of bladder sparing with particular features of the anatomy and the treatment geometry. Figure It is worth noting that in addition to the dosimetric advantages offered by the plans optimized by ITP, the total time required for ITP with a single set of objectives/constraints and the default cut‐off and sampling parameters is about 15 min, in comparison to approximately 30–40 min required by experienced dosimetrists or by clinical physicists to perform the forward clinical planning. However, it also must be pointed out that, for other inverse treatment planning systems, the ITP process can be more or less time‐consuming depending on the efficiency of the optimization engine.We have presented an approach to identify optimal values of the parameters that determine the organ sampling and the scatter inclusion to be used in the process of inverse treatment planning. While a particular treatment planning system was used to investigate the sensitivity of the inverse treatment planning process with respect to these parameters, the results presented here should indicate reasonable values for analogous parameters used in other treatment planning systems. As exemplified by the treatment of scatter in this paper, shortcuts taken by the vendors may result in consistently suboptimal treatment plans irrespective of the actual dose or dose‐volume constraints employed. Thus, while certain commercial systems may not provide the user with the capability of modifying the parameters related to organ sampling and scatter inclusion, their vendors should at least provide the default values.By the example of a particular treatment planning technique, we have further demonstrated that routine inverse treatment planning based on a single set of objectives and constraints is a possibility for certain treatment sites and techniques. This finding suggests that after a proper parameter selection , inverse planning with a fixed set of parameters can serve as a useful replacement of some routine forward planning techniques.This work was partly supported by MRC Grant No. MOP 36470.


Abnormal bony morphology is a factor implicated in hip joint soft tissue damage and an increased lifetime risk of osteoarthritis. Standard 2‐dimensional radiographic measurements for diagnosis of hip deformities, such as cam deformities on the femoral neck, do not capture the full joint geometry and are not indicative of symptomatic damage.In this study, a 3‐dimensional geometric parameterisation system was developed to capture key variations in the femur and acetabulum of subjects with clinically diagnosed cam deformity. The parameterisation was performed for computed tomography scans of 20 patients . Novel quantitative measures of cam deformity were taken and used to assess differences in morphological deformities between males and females.The parametric surfaces matched the more detailed, segmented hip bone geometry with low fitting error. The quantitative severity measures captured both the size and the position of cams and distinguished between cam and control femurs. The precision of the measures was sufficient to identify differences between subjects that could not be seen with the sole use of 2‐dimensional imaging. In particular, cams were found to be more superiorly located in males than in females.As well as providing a means to distinguish between subjects more clearly, the new geometric hip parameterisation facilitates the flexible and rapid generation of a range of realistic hip geometries including cams. When combined with material property models, these stratified cam shapes can be used for further assessment of the effect of the geometric variation under impingement conditions. Repeated contact between the femoral bone and acetabular rim  can cause labral pathology and progressive delamination of cartilage.The risk of symptomatic impingement occurring is likely to depend on differences in natural soft tissue shape and quality, the activities performed by individuals, and, as investigated here, the position and shape of bone abnormalities.There is a recent shift towards conducting clinical research investigating FAI in 3D. Harris et alTo develop a geometric parameterisation method that generates subject‐specific parametric surfaces to represent morphology of proximal femurs with cams and lunate articular acetabular surfaces, capturing key variations due to cam deformity in 3D.To apply this method across a clinical data set, allowing measurements assessing impingement risk to be obtained, and assess morphological differences between male and female hips diagnosed with cam type impingement.To verify the parameterisation system using shape fitting error assessment between segmented and parametric bone surfaces and comparison of 3D measures with clinical, radiographic measures.To verify the ability of the femoral parameters to capture cam deformities by comparing with non‐cam cases.The overall objective of this work was to develop and test a novel method for generating parametric surfaces and 3D severity measures of cam deformity of the hip joint. A successful methodology was considered to be one precise enough to provide some stratification of the population of subjects with cams. The specific aims of this study were as follows:2Preoperative pelvic CT images  of 20 patients  who underwent surgery for cam type impingement were used in this study. Ethical approval (reference MEEC 11‐044) was granted by the faculty research ethics committee at the University of Leeds. Patients included in the study were able to give written, informed consent, were aged 18 years or over  and had a clinical diagnosis of cam FAI with preoperative CT scans readily available. Patients were excluded from the study if they had undergone surgery in the affected hip prior to the CT scan being taken, or in the opinion of the clinical investigator (MB), had an existing condition that would compromise their participation in the study .Bone surfaces  were segmented from the CT scans using the image processing software ScanIP  Figures A and 2A.Measurements were automatically derived from the parameters to indicate the risk of impingement on the basis of 3D hip bone geometry. For comparison, 2D clinical measurements of the same hips were taken from reconstructed radiographs, created by taking averages of CT slices in certain views. Details of this are given in Section To assess the ability of the cam parameters to distinguish between patients diagnosed with cams and those without, we also tested the femoral parameterisation process on an additional 18 control femurs . These patients had undergone CT scans because of hip pain but were not diagnosed with cam impingement. Femoral bones from these patients were segmented and processed with the same methods used for the main patient group.2.1First, the head centre was located by fitting a sphere to the nodes on the proximal side of the femoral head. In cases where there was clear external rotation visible in the axial CT view, this was corrected by performing an initial rotation of 20° about the axial axis passing through the centre of the head. This was necessary in 3 of the cam patient femurs and 1 of the control femurs, where the rotations were likely due to the subjects moving from neutral position in the scanner.All segmented femurs were then rotated to align the neck axis with the vertical image axis (in line with the superior‐inferior axis) using a rotation about the anterior‐posterior axis Figure B. This rx2 and In this new orientation, the head centre position and radius were recalculated by again fitting a sphere to the nodes on the proximal head surface. Surface nodes found in 2‐mm thick intervals of the head‐neck region perpendicular to the neck axis were then used to define slices of the proximal femur. The total number of slices, defined from the top of the head to the end of the modelled neck axis, was fixed to be equal to the head radius (rounded to the nearest mm) to ensure that the most distal slice was in a comparable position along the femoral neck for each femur. For example, for a head radius of 25 mm, 25 slices of 2 mm would be used, resulting in a height of 50 mm from the top of the head to the end of the neck. Ellipses were then fitted to the segmented bone surface in a selection of 4 of these slices. The 4 slices were selected automatically by taking a linearly spaced vector with 4 points between Parametric surfaces representing the proximal femur  were generated using the extracted parameters Figure C. A spheCam‐rad is the greatest planar distance between the head centre and the anterior half of the fitted ellipse, recorded as a percentage of the head radius. This indicates the level of offset between the head and neck in the cam region.Cam‐angle describes the position of the point on the ellipse where cam‐rad is defined . A zero angle represents an anteriorly centred cam, and greater angles indicate a more superior position.Cam‐width is the percentage of the neck circumference whose distance from the head centre is greater than 90% of the distance defined by cam‐rad. Cam‐width therefore indicates the extent to which the circumference of the neck is affected by the cam. The position along the neck where the ellipses were fitted is known from the geometrical parameters.Measurements were defined to describe the size and position of the cam to isolate the region with potential to cause impingement. For each slice, the following were defined Figure D:Cam‐raThe average of these measurements from the 2 central loft slices were recorded as the overall Cam‐rad, Cam‐angle, and Cam‐width.2.2Parametric acetabular surfaces were generated by lofting through five 3D spline curves fitted to between 3 and 6 points on the segmented acetabulum Figure A, manualTwo clinically relevant angles, AV and CE angles, were extracted from the 3D spline data representing the acetabula.Five AV angles were calculated in the transverse plane as the acute angle between AP‐axis and the line between the most anterior and posterior points on the acetabular rim Figure A. The moFive CE angles were calculated in the coronal plane as the angle between the vertical line passing through the femoral head centre and the line joining the head centre and the edge of the acetabulum Figure B. The mo2.3Fitting errors were calculated in MATLAB from the triangulated surfaces as the root mean squared distance that nodes on the segmented surface in the region of interest had to move to conform to the nearest node on the parametric surface.A sphere was created in the +CAD module of ScanIP and resampled to the CT scan voxel resolution of 0.7422 × 0.7422 × 1 mm. The femoral parameterisation procedure was applied to this triangulated sphere to obtain the baseline fitting error, ie, the best fitting error that could be achieved using this method at the specified CT resolution.2.4For each of the 20 patients, 3 reconstructed radiographic views (described in the following paragraphs) were generated by using ImageJ  to rotate the CT slices where necessary and then average the slices of interest to create a simulation of a radiographic view. This process used a fixed protocol and was not subject to interuser variation. OsiriX  was used by a consultant radiologist (PR) to take 2D measurements of alpha, AV, and CE angles from these reconstructed radiographs for each patient. An additional 3 researchers  repeated the acetabular angle measurements to investigate user variation in reading angles from such radiographs, where outer bone limits can be difficult to assess.An axial view was created by averaging the transverse CT slices that included the acetabula. The AV angle was measured in this view as the angle between the line perpendicular to the line joining the posterior edges of the acetabula on both sides  and the line joining the anterior and posterior edges of the acetabulum Figure A.A coronal view was created by rotating transverse slices into the correct orientation and averaging the slices including the relevant femur. Both femurs were included in these images to verify that the vertical axis represented an inferior‐superior axis. The CE angle was measured in this view as the angle between the vertical line through femoral head centre and the line passing through the femoral head centre and the top edge of acetabulum Figure B.A cross‐table lateral view was created by rotating the femur 15° internally and by a 45° angle from the sagittal plane and averaging CT slices with a view of the medial side of the femur. This view was chosen to measure alpha angles, as it is a standard radiograph and can be readily simulated by rotating CT slices to obtain an image similar in appearance to actual radiographs. Additionally, it has been reported that alpha angles measured in this view correlated well with 3D measured asphericity.r) and linear regressions were calculated between the 3D severity measurements and the 2D measurements, and also between the 2 alpha angle measurements. Independent samples t tests were performed to test for differences in the potential impingement severity measurements between males and females . Independent samples t tests were also used to test for differences in the femoral severity parameters between the patient and control femurs . All statistics were calculated using the Statistics and Machine Learning Toolbox in MATLAB.Pearson correlation coefficients  was identified showing that the average cam‐angle was higher in male cam patients (mean 40.5°) than female cam patients (mean 16.5°)  was identified showing the average cam‐rad was higher in the cam patient group than in the control group, and this was true for both the male and female groups as well as overall , whereas cams in female subjects were more likely to be in an anterior position.Performing the femoral parameterisation process on a sample of control femurs verified its ability to differentiate between femurs diagnosed with cams and those without. Although control femurs do not have cams, the cam‐angle parameter still detects the region with smallest head‐neck offset. The lack of difference in cam‐angle between males and females in the control group suggests that the more superior location in males of this region may be a specific observation of morphological changes related to cam deformity, rather than being true in general. Since cam‐width is a measure on the basis of the value of cam‐rad, a direct comparison between control and cam groups was less useful. Cam‐width was generally higher in the control group simply because the cam‐rad values were lower.The average fitting errors between the parametric and segmented geometries were of a similar magnitude to others reported for articular surfaces of the hip approximated by sphere and conchoids4.1Recently, it has been reported that cams in female patients present in the same location as in males, but the volume and span of the cam was greater in males.The size of a cam (as measured here by cam‐rad) cannot be easily predicted from a single radiographic alpha angle. It was seen that multiple subjects with very similar alpha angles had quite different 3D severity measures. Alpha angles are dependent upon the view in which they are measured, which is evident here in the differences between the CT and cross‐table alpha angles Figure , and hasIt has been reported that AV angles are usually higher in females whilst CE angles are usually not different between males and females.The low standard deviations between users when additional researchers measured acetabular angles suggest that user variation would have minimal effect on the detected correlations. Interuser variation in alpha angles is likely to be higher, but alpha angles are in any case greatly affected by viewpoint.The automatic method of generating parametric surfaces provides the ability to represent the large variation in hip morphology4.2The parameterisation system depends on segmentation of bone from 3D images and on the assumption that hips are orientated neutrally in anatomical planes. In 3 cam femurs and 1 control femur, this was seen in the axial view to be untrue, and an additional rotation was used to align them approximately into a neutral rotation. Without this correction, the fitting errors for these cases were noticeably larger (>1 mm). Further, the neck axis was assumed to be at 40° to the superior‐inferior axis for all femurs since it was not possible to measure the femoral neck shaft angle given the field of view in the scans, and defining the neck axis for each femur presented a significant challenge because of the abnormal morphology resulting from the cam deformities. The value of 40° was therefore chosen to automate the process as it appeared in all cases to orientate the neck axis approximately vertically, as seen in Figure The segmentation of bone surfaces from CT scans followed a set protocol and user variability would be unlikely to cause more than minor differences in final parametric models. Once bone surfaces have been segmented from CT scans, the method is mostly automatic. The femoral parameterisation and severity measurements assessing the cam are obtained fully automatically through scripts. The acetabular parameterisation requires manual intervention (including some expert adjustments) to select nodes on the acetabulum to obtain an optimum fit, necessary because subject‐specific irregularities in acetabular rim shape are not well captured using standard shapes. The measured angles were calculated from nodes around the rim, which were the most straightforward to place, limiting the effect of this variation on acetabular severity measurements. Whilst the process would need further refinement and optimisation to be used as a clinical tool, particularly on the acetabular side, which has not been tested on pincer patients, it is presently capable of capturing complex hip geometry in a finite number of simple geometric parameters. Variations of both surfaces with alternative parameters can be generated automatically, and it is possible to vary each parameter separately.Fitting errors between triangulated surfaces are higher when coarse surface meshes are used because the distance from each node on a segmented surface to the nearest node on the equivalent parametric surface may be higher than the true distance between the surfaces at that point. Therefore, the mesh densities of both the parametric and segmented surfaces were iteratively increased until the fitting errors converged so that the reported fitting errors (and extracted parameters) were limited by the resolution of the original CT scans rather than the mesh density. This occurred when mesh densities were such that nodes on each surface were spaced at distances of around 0.25 to 0.3 mm.Preliminary tests found that using 4 ellipses was sufficient to capture the geometry with a similar fitting error to that found when all slices below the middle slice were included. Using more slices resulted in an uneven surface because of the reduced distance between ellipses lofted through, whilst using less than 4 ellipses leads to considerably poorer fits between the parametric and segmented surfaces. Because there is some noise (as the best possible fitting error was seen to be 0.22 mm), the measures describing cam severity are relative rather than absolute. The highest value of cam‐rad, 100.4%, should be interpreted as indicating a particularly severe cam where there is very little head‐neck offset, rather than suggesting the cam radius is literally greater than that of the head. Cam‐rad is sensitive to the position of slices used for lofting, which is why the method for choosing number of slices was standardised as equal to the head radius and linearly spaced slices were chosen automatically. Whilst a more accurate value for cam‐rad could be obtained from the full segmented surface, the described method allows all the severity measurements to be derived automatically using only the geometrical parameters describing the bone shape, and the precision was sufficient to demonstrate differences between 2 population groups.4.3This study has demonstrated that it is possible to represent segmented geometry of the acetabular cavity and proximal femur bone with a cam deformity, using a small number of parameterised curves and achieve a low overall fitting error. By adjusting the parameters, variations of the parametric surfaces can be automatically generated. The novel 3D cam severity measurements obtained from the parameterised geometry provide a systematic method of assessing impingement risk and impart more information on the shape and position of cams when compared with using only radiographic measurements, which may not give a good indication of the full extent and exact location of bony abnormalities. The potential severity, ie, risk of impingement, on the femoral side can be assessed by the cam size resulting from head‐neck offset (captured by cam‐rad) in a manner that is not dependent on a 2D view. Combining this with the position and extent of the cam (captured by cam‐angle and cam‐width), and with the acetabular severity measurements, could allow impingement to be predicted on the basis of bone shape in different scenarios, although there are other factors that play a role in its severity, such as patient activity level and vulnerability of the labrum and articular cartilage to injury. The measures developed here also allowed investigation of the differences in cams between males and females, which showed that cams in males are more likely to be superiorly located.


Synthesis and applications. We show that a complex model can be used for analyzing ungulate‐pasture dynamics and sustainable management if the model is parameterized and validated for the system. Wastage levels caused by trampling and other causes should be quantified with data as they strongly affect the results and management recommendations. Summertime lichen wastage caused by reindeer is higher than expected, which suggests that seasonal pasture rotation should be used to prevent the heavy trampling of winter lichen pastures during summer. In the present situation, reindeer numbers in northernmost Finland are in most cases higher than in the management solutions given by the model.Ungulate grazing and trampling strongly affect pastures and ecosystems throughout the world. Ecological population models are used for studying these systems and determining the guidelines for sustainable and economically viable management. However, the effect of trampling and other resource wastage is either not taken into account or quantified with data in earlier models. Also, the ability of models to describe the herbivore impact on pastures is usually not validated. We used a detailed model and data to study the level of winter‐ and summertime lichen wastage by reindeer and the effects of wastage on population sizes and management. We also validated the model with respect to its ability of predicting changes in lichen biomass and compared the actual management in herding districts with model results. The modeling efficiency value (0.75) and visual comparison between the model predictions and data showed that the model was able to describe the changes in lichen pastures caused by reindeer grazing and trampling. At the current lichen biomass levels in the northernmost Finland, the lichen wastage varied from 0 to 1 times the lichen intake during winter and from 6 to 10 times the intake during summer. With a higher value for wastage, reindeer numbers and net revenues were lower in the economically optimal solutions. Higher wastage also favored the use of supplementary feeding in the optimal steady state. Actual reindeer numbers in the districts were higher than in the optimal steady‐state solutions for the model in 18 herding districts out of 20.  HerbivoEcological models are common when studying population dynamics, the outcomes of different management actions, and the optimal use of natural resources. One of the central objectives in applied ecological research is to provide objective information that ecosystem managers can use to achieve economic, conservation, and environmental goals  is removed in turn, and the calibration is performed using the rest of the data (n − 1). For model validation, the calibrated model is next used for predicting the single value that is compared with the value left out of the calibration sample. This procedure is repeated n times, and each data point is removed in turn. Thus, each data point can be used for validation and parameter estimation, and the model is calibrated for each validation computation without utilizing the data used in the validation.Model validation must be performed using data that have not been used for building the model or in parameter estimation . In parameter estimation, this assumption only affects the relative wastages between the spring, summer, and autumn seasons, but not the relation between winter wastage and total wastage outside wintertime.In our study, we estimate the parameters for lichen wastage using a model and detailed data. All other model parameters are predetermined based on existing research and data. The predetermined parameters are presented in Table In Pekkarinen et al. , the waspe1 and pe2 indicate the wastages when lichen biomass is 0 and 1,000 kg/ha, and zt is the lichen biomass in year t.Parameters pwi,1, pwi,2) and summer  that give the best fit between the model and data. The objective was given as: Parameter estimation can be performed by minimizing the loss function or maximizing the probability of observing the experimental data . We call this case constant wastage. But when wastage relative to intake is described as a linear function of the lichen biomass , we need two parameters for both winter  and summer . This we call linear wastage. For both linear and constant wastage, the maximization is subject to the model presented in Pekkarinen et al. . Parameter estimation was performed 20 times, excluding each herding district in turn and optimizing the values for lichen wastage during winter and summer. Results are shown in Figure We then estimated the parameter values for the lichen wastage equations equation  assuming3.2We first tested model validity using constant values for wastage. Visual observation Figures a and 3a 3.3The study by Pekkarinen et al.  extends 3.4Figure Figure 3.5Figure 4According to our results, when lichen biomass is below 1,000 kg/ha, the best fit between model predictions and data is found when the wastage during winter is between 0 and 0.7 times the intake rate. As our method assumes that the reduction in lichen biomass from 1995 to 2008 depends only on factors taken into account in the model, it is possible that the true wastages are somewhat smaller than those reported in our study. This would be the case if, for example, tourism would have a large enough effect on lichen biomass relative to the effect by reindeer. However, reindeer‐related processes are generally seen as the primary factors affecting the reduction in lichen biomass  increased the model fit to the data indicates that the structure and various components of the model represent the system well.Pekkarinen et al.  used theOverall the solutions for optimal management do not differ much when a constant share of wintertime wastage is changed from 0.3 used by Pekkarinen et al.  to 0.5 fWe used the validated model to compare actual reindeer numbers and lichen biomasses to optimal management solutions. We found that with the linear wastage function the optimal lichen biomasses in steady‐state solutions are lower than those found in previous optimization studies. However, it appears that these optimal lichen biomasses were still higher than in the present situation in most of the herding districts studied. Accordingly, the number of reindeer was also clearly higher in all except two herding districts. This shows that lichen biomasses may still continue to decrease in most of the districts at current reindeer levels and pasture states. This would lead to reindeer management having to increasingly rely on supplementary feeding. From the herders viewpoint this might still be the optimal solution if they receive government subsidies, prefer a higher interest rate and/or have access to low‐cost supplementary food (see Figure Mysterud  suggests5Our study uses detailed data to parameterize and validate a complex reindeer‐lichen system model. Validation can never prove a model right, but it can help show how it relates to the measured data and represents the problem entity (Brown & Kulasiri, Our study presents the first data‐based estimate of a lichen wastage parameter used in reindeer‐lichen models. Wastage by trampling can affect lichen biomass even more than lichen intake; thus, the effects of wastage are as important as other effects of herbivory. Although lichens are probably one of the food resources least tolerant of herbivore grazing and trampling (Mysterud, None declared.Antti‐Juhani Pekkarinen, Jouko Kumpula, and Olli Tahvonen conceived the ideas and designed methodology; Jouko Kumpula and Antti‐Juhani Pekkarinen collected the data; Antti‐Juhani Pekkarinen analyzed the data and led the writing of the manuscript. All authors contributed critically to the drafts and gave final approval for publication.


Zymoseptoria tritici on wheat and a quinone outside inhibitor (QoI) fungicide. For this pathogen–fungicide combination, a single treatment provided effective control under the simulated disease pressure, but only if the application timing was optimal and the dose was close to the maximum permitted. Programmes with three applications were generally not optimal as they exerted too much selection for resistance. Two‐application fungicide programmes balanced effective control with reasonable flexibility of dose and application timing, and low resistance selection, leading to long effective lives of the fungicide.Two key decisions that need to be taken about a fungicide treatment programme are (i) the number of applications that should be used per crop growing season, and (ii) the dosage that should be used in each application. There are two opposing considerations, with control efficacy improved by a higher number of applications and higher dose, and resistance management improved by a lower number of applications and lower dose. Resistance management aims to prolong the effective life of the fungicide, defined as the time between its introduction onto the market for use on the target pathogen, and the moment when effective control is lost due to a build‐up of fungicide resistance. Thus, the question is whether there are optimal combinations of dose rate and number of applications that both provide effective control and lead to a longer effective life. In this paper, it is shown how a range of spray programmes can be compared and optimal programmes selected. This is explored with  Both these considerations are of key importance to achieve durable control of the pathogen population. A general criterion to compare durability of fungicide application programmes is the effective life of the pathogen–fungicide combination. Effective life is defined as the time between the introduction of the fungicide onto the market for use on the target pathogen, and the moment when effective control is lost, under the treatment programme, due to the build‐up of fungicide resistance  the number of applications that should be used per crop growing season, and (ii) the dosage that should be used in the applications. From a resistance management perspective, a larger number of applications and/or a higher dose are expected to increase the rate of selection for fungicide resistance (van den Bosch Generic guidance by the Fungicide Resistance Action Committee (FRAC) recommends avoiding repetitive use of a single MOA, limiting the number of applications and optimizing the dose  fungicide with a single MOA and where fungicide resistance is characterized by a single mutation (or other genetic change) in the pathogen conferring a high level of resistance. This was compared with the use of the QoI fungicide mixed with a low‐risk multisite‐acting fungicide.The aim of this study was to use model simulations to find combinations of the number of applications and dosage that lead to effective disease control with a long effective life. The example used was the control of the wheat pathogen, et al. . The effects of fungicide treatments on the epidemic are simulated via their effects on pathogen life cycle components . The model simulates several successive seasons until effective control is lost.The model simulates epidemics caused by et al., The timescale is temperature sum accumulated after 1 January, to account for the temperature dependence of both crop and pathogen dynamics (Trudgil P) and to depend on leaf size . At the end of the leaf's lifespan, the leaves start to senesce leading to a decrease in the healthy area index  of the upper canopy  leaf is referred to as leaf 1. A simulation season starts when leaf 5 becomes visible, i.e. at 1147 degree‐days. Leaves are assumed to grow at a constant rate until they reach their maximum size , affecting both the transmission rate and the length of the latent period of the sensitive strain. The second fungicide considered is a low resistance risk, multisite acting protectant fungicide (hereafter referred to as ‘low‐risk’), affecting the infection efficiency of both the sensitive and the resistant strain, but not affecting the latent period (Data S1). In the simulations, resistance evolves in response to the high‐risk fungicide, but there is no resistance against the low‐risk fungicide during the period simulated. It is assumed that the low‐risk and high‐risk fungicides have independent modes of action leading to a multiplicative survival effect of the two fungicides on the transmission rate of the sensitive strain  a systemic high‐risk single‐site fungicide to which the pathogen develops resistance through a single mutation and which has both protectant and eradicant action affecting only the sensitive strain; and (ii) a mixture of the high‐risk fungicide with a nonsystemic low‐risk multisite fungicide to which the pathogen does not develop resistance over the timescale under consideration and which only has protectant action that affects both the sensitive and resistant strain. The model was parameterized using field data from studies using the high‐risk QoI fungicide pyraclostrobin and the low‐risk fungicide chlorothalonil  followed by a second spray at the full emergence of the flag leaf (‘T2’ spray). On cultivars with good host resistance, this usually provides adequate disease control under low or average disease pressure. However, in the case of more severe outbreaks, additional applications might be required at the emergence of leaf 4 (‘T0’ spray) and/or ear emergence (‘T3’ spray) . Waggoner & Berger  calculatSelection ratio, defined as the proportional increase in the frequency of the resistant strain on the top five leaves during one full growing season.et al., Fungicide effective life, defined as the number of consecutive growing seasons that the fungicide (as solo product or in mixture) is able to maintain ‘effective control’, which is defined as keeping the disease‐induced HAD loss below a predefined threshold of 5%  unless otherwise specified. Figure Figure Holding the total dose of the spray programme constant, the selection ratio increases with the number of spray applications. However, there is some overlap between the maximum and minimum selection ratios of the different number of spray treatments, so, for example, the highest selection ratios  against the selection ratio  in the first year, all spray programmes are scattered around a straight line Fig. a. The fiFigure Figure et al., For fungicide mixtures where the low‐risk:high‐risk dose ratio is kept constant, both within and between seasons, the relation between % HAD loss and the selection ratio  loss versus selection ratio in the first year.Click here for additional data file.Data S1 Summary of fungicide dynamics for a fungicide mixture.Click here for additional data file.Data S2 The pyraclostrobin and chlorothalonil dose–response curves.Click here for additional data file.


One of the forms of inflammatory bowel disease (IBD) that causes inflammation and ulcers in colon is ulcerative colitis (UC). This study was aimed to determine the epidemiological and clinical aspects of patients with ulcerative colitis in the west of Iran.In this cross sectional study, we evaluated 150 patients with definite diagnosis of UC who referred to a subspecialty gastroenterology clinic in Khorramabad, Iran. The study was performed from May 2014 to August 2015 by using census method. Demographic characteristics as well as patients’ clinical profiles were extracted using a checklist. Disease severity was determined by the Truelove and Witt’s classification of ulcerative colitis (UC). Data were analyzed using SPSS software, version 17 for windows .A total of 150 patients with definite diagnosis of UC were analyzed, including 84 (56 %) women and 66 (44 %) men . The mean age of patients was 33.7 ± 12.5 years with an age range of 17–98 years. The age of the majority of patients was 20–29 and most of them (56 %) were women and living in urban areas (70.7 %). The most common site of the involvement in colon was rectosigmoid . Severity of the disease was mild in 36 patients (24.1 %), moderate and severe in 74 and 40 patients (49.3 and 26.6 %), respectively. The most common clinical manifestation of the patients was dysentery (68 %) and then rectorrhagia (60 %). Only 12 of all patients (7.8 %) mentioned a positive family history of IBD in their first degree kinfolks. Ten patients (6.7 %) had a history of regular smoking and four of them (2.6 %) mentioned a history of appendectomy. Four patients (5.3 %) had a positive history of smoking by their mothers during their pregnancy.The results of this study demonstrate differences and similarities in demographic and clinical characteristics of UC in this part of Iran in comparison to other parts of the country. Inflammatory bowel disease (IBD) is known as a group of inflammatory conditions (signs and symptoms) of the colon and small intestine. Ulcerative colitis (UC) and Crohn’s disease (CD) are the most important types of IBDs. IBD causes the bowel (intestine) to be inflamed, swollen, irritated and unable to function in a healthy way. UC is a form of IBDs that leads to inflammatory and ulcerative lesions in the colon. It affects large intestine (the colon) and rectum but does not involve the small intestine; whereas CD affects both the colon and small intestine . Descriptive tests were used as appropriated.In this study, a total of 150 patients diagnosed with UC were evaluated. Out of the 150 patients examined, 84 (56 %) were women and 66 (44 %) were men . The mean age of the patients was 33.7 ± 12.5 years with an age range of 17–98 years. The age range of majority of the patients in this study was 20–29 (38.7 %). Most of them (56 %) were women and living in urban areas (70.7 %). The educational level of most of them was high school and Diploma (48 %). The frequency distribution of the demographic characteristics of the patients is shown in Table UC is a chronic disease of the colon  associated with inflammation of the lining of colon and development of tiny open sores, or ulcers, which produce mucous and pus. The combination of ulceration and inflammation can cause abdominal discomfort and also frequent emptying of the colon. The disease is the result of an abnormal response by the immune system of the body. The cells and proteins which make up the immune system, normally protect the individual from infections. However, in people with IBD, food, bacteria and other materials are mistaken for antigen by the immune system. Hence, the body sends white blood cells into the lining of the intestines and cause chronic inflammation and ulcerations. The present study was conducted to assess the clinic-epidemiological characteristics and colonoscopic findings of UC in Khorramabad city from May 2014 to August 2015. UC most commonly begins between the ages of 15 and 25. Also, another usual age of the onset is in the 6th decade of life. Females are more likely to be affected than males (Büsch et al. Ulcerative colitis is one of the important referral causes of patients to the subspecialty clinics of gastroenterology and unofficial records demonstrate increasing incidence of cases of this disease in Iranian race that may be due to changing of people´s life style and following the life style of western communities and developing of diagnostic and treatment instruments of the disease.Altogether, it seems that the epidemiologic profile and clinical characteristics of UC in our country, Iran, have a relative similarity to other places in the world, but clinical development of the disease is milder and extra intestinal manifestations are fewer; on the other hand, evaluation of all sides of the disease may have an important role to recognize real factors causing the disease and prevent from them. The high rate of frequent relapse of the disease in the patients requires more attention to their treatment and to make them pay attention to the correct and regular medicine taking. Since Khorramabad is the center of Lorestan province in which rather all patients from another parts of the province are referred to there, this city could be representative of population of the west of Iran; in addition there are some other deprived provinces such as Ilam in the west of Iran that the patients of theirs are also referred to Khorramabad to get better services. The results of this study, demonstrate differences and similarities in demographic and clinical profile of UC in this part of Iran in comparison to other parts of the country. Some other limitations of the present study were the short duration of the evaluation of the disease and few numbers of the studied patients.


Conductive inks are key enablers for the use of printing techniques in the fabrication of electronic systems. Focus on the understanding of aspects controlling the electrical performance of conductive ink is paramount. A comparison was made between microparticle Ag inks and an Ag nanoparticle ink. The microstructures resulting from thermal cure processes were characterized morphologically and also in terms of their effect on the resistivity of printed traces. For microparticle inks, the variability of resistivity measurements between samples as defined by coefficient of variation (CV) was greater than 0.1 when the resistivity was 10 to 50 times that of bulk Ag. When the resistivity was lower (~1.4 times that of bulk Ag) the CV of sample sets was less than 0.1. In the case of the nanoparticle ink, resistivity was found to decrease by a factor ranging from 1.2 to 1.5 after doubling the amount of layers printed prior to curing though it was expected to remain the same. Increasing the amount of layers printed also enhanced the sintering process. The creation of conductive paths in electronic systems has traditionally involved the addition and subtraction of conductive material by means of deposition, mask, and etch processing ,2. Printet al. [The thermal cure process produces microstructural changes in particle-based conductive inks , which impacts the overall electrical properties of a printed conductive trace. In the case of inks where the particle size is of the micron scale, low temperature curing (between 100 °C and 200 °C for inks designed to work in this temperature range) in which the amount of material suspending the conductive particles will decrease, resulting in particles conducting through physical contact in a process known as percolation ,10,11,12et al. ,14,15. Iet al.  and Ag [et al. ,18 nanopet al.  and manyThe allowable curing temperature range is largely dictated by the substrate choice, which is in turn dependent on the particular electronics application. For example, applications requiring flexible substrates could employ the use of a polymeric material as a substrate. The glass transition temperature of polymers in many cases will overlap with or be below the manufacturer recommended curing parameters. On the other hand, an application in which flexibility is not needed could use a rigid substrate, such as ceramic, which can withstand temperatures higher than the melting point of the printed conductor. The ability to cure the printed conductor near the melting temperature of the conductive particles allows the electrical performance of these conductors to be improved dramatically. Understanding the effect of microstructure on electrical performance is important when selecting a conductive ink for utilizing printing technologies in the production of electronic systems especially when polymeric substrates are used due to the corresponding temperature limits. In this paper, a comparison is made between micro and nanoparticle loaded conductive inks. The microstructural changes which occur as a result of thermally curing these two ink types are documented. Two printing techniques are utilized, inkjetting of nanoparticle loaded inks and direct write micro dispensing of microparticle loaded inks.® substrate  while the second was a rigid ceramic 96% alumina substrate. The ceramic substrate has the benefit of being able to withstand high temperatures, and these high temperatures substantially improve the electrical conductivity of the ink by permitting particle sintering. Conversely, the Kapton® substrate has the desirable property of being flexible, which allows conductive lines printed on this substrate to be used in conformal or flexible applications, and in general, increases the application potential. However, the drawback of Kapton® is that thermal processing is typically restricted to temperatures below the glass transition temperature of approximately 360 °C [For the characterization of microparticle inks, two substrates were used. The first substrate was a flexible DuPont Kaptony 360 °C , around For experiments involving microparticle inks, printing was performed via the direct write micro dispensing technique with an nScrypt 3D 450 system . The patterns shown in ® polyimide substrates in the pattern displayed in The second conductive ink used, DuPont CB028 , has a lower recommended curing temperature of 160 °C  and is t® substrate in the pattern depicted in et al. [A third microparticle loaded ink, Ercon E1660 , was printed via direct write micro dispense on a Kaptonn et al. . The sizρ, isR is measured resistance, A is the cross-sectional area of the printed line, and l is the length of the printed line. For each ink and substrate combination, multiple samples were printed and the resistance was measured using a Keithley Model 2000 multimeter . Cross-sectional areas of the printed lines were calculated by first measuring the line thickness with a KLA-Tencor Alpha Step IQ stylus profilometer  operating with a resolution of 20 nm. An outline representing the cross section of the printed line was generated by plotting x vs. z where the thickness was taken to be along the z-axis and the width to be along the x-axis. The cross-sectional area was approximated by calculating the area beneath the plotted curve utilizing a Riemann sum-type approachResistivity of the printed traces was calculated based on dimensional measurements of the printed patterns and the measured resistance. The equation used to calculate resistivity, In this case, ∆x is 1 μm. An example of the graphical representation of the cross section of a printed line is seen in Specimen preparation for scanning electron microscope (SEM) microanalysis of the printed lines entailed the use of a surgical scalpel to section the polymeric substrates and the use of a glass cutter to section the ceramic substrates. The samples were then subjected to Au sputtering for 30 s with a Gatan Model 682 Precision Etching Coating System  to reduce charge effects in the SEM. SEM was performed on all samples in a top down fashion using a Hitachi S-4800 Ultra-high Resolution Field Emission Scanning Electron Microscope  utilizing a 20 keV accelerating voltage.® substrate with a Dimatix 2800-Series Materials Printer . One layer (single print) was printed at 1270 DPI. In order to improve the wetting characteristics of the ink substrate interface, the Kapton® substrate was first cleaned with UV-Ozone for 10 min with a Jelight UVO Cleaner Model 342A . Sample sets of five were oven cured for 1 h at each of the following temperatures: 100 °C, 110 °C, 150 °C, 160 °C, 175 °C, 200 °C, and 250 °C. SEM microanalysis in a top down fashion was performed as described previously. Resistivity was determined based on the technique outlined previously for microparticle inks.An alternative to using microparticle-based inks in applications where the cure process is controlled by the thermal constraints of a polymeric substrate is to use a nanoparticle-based ink and take advantage of the reduced sintering temperature found in the nano regime. In order to explore this option, the 6 cm long pattern seen in ® using the same ink cured at 160 °C was calculated to be 480 nΩ•m +/−74 nΩ•m. The resistivity of the DuPont CB028 ink samples printed on Kapton® and cured at 160 °C was calculated to be 239 nΩ•m +/−57 nΩ•m. The Ercon E1660 samples in the air dried condition had a resistivity of 405 nΩ•m +/−45 nΩ•m while samples of the same ink cured at 138 °C for 1h had a resistivity of 103 nΩ•m +/−14 nΩ•m. The three inks printed on Kapton® were roughly an order of magnitude less conductive than the patterns printed on ceramic due to the ability of the ceramic substrate to withstand the higher curing temperature. The DuPont ink cured at 160 °C is roughly two times more conductive than the Ferro ink cured at the same temperature. Utilizing the Ferro 3309F processed at this temperature is not the manufacturer intended application as the Ferro 3309F ink was optimized for 850 °C. The air drying of the E1660 samples produced a resistivity on par with the 3309F cured at 160 °C while the Ercon E1660 cured at 138 °C produced the most conductive trace for the inks printed on Kapton®. This significantly better performance is potentially due to the average particle size being the largest among the inks tested. The implication made here is that percolation theory should also be characterized in terms of particle size in addition to the amount of binder material separating the conductive particles. However, the larger particle size restricts the minimum feature size that can be printed.Using the resistance and dimensional measurements of the printed lines, resistivity for the inks was calculated and the graphical results are seen in Based on the comparison of the measured results to the bulk resistivity of Ag, a conclusion can be drawn that the Ferro 3309F printed on ceramic has created a conductive path with a conductivity approaching bulk Ag (67% of bulk Ag) due to the higher temperatures involved in the curing process. A conclusion can also be drawn that as the Ferro is intended for LTCC processing which will create a microstructure favorable to conductivity—in this case, grains.et al. [Microstructural characterization reveals differences in the governing factors controlling conductivity, namely conduction through physical contact between particles vs. conduction in a grainy film. In the case of both DuPont CB028 and Ercon E1660, the microstructure is that of individual particles conducting as a result of the particles physically touching one another as seen in et al.  which shet al. ,27. The et al. ® did not result in the creation of a film and therefore the resistivity is higher due to the dependence of resistivity on the amount of physical contact between the Ag particles. The difference between the two main factors controlling resistivity (contact area vs. grain size) is graphically represented in The impact of grain size and porosity on the resistivity of a printed conductive trace has been characterized in literature ,29. The ® substrates. The graphical results of the corresponding resistivity (ρ) measurements for each curing temperature are also seen in The microstructural evolution, which occurs with an increase in processing temperature, is illustrated in Analyzing the variability in resistance measurements of the nanoparticle loaded ink does not reveal as clear of a relationship between method of conduction and variability as the results of the microparticle loaded inks did. One reason for this may be the non-homogenous nature of the inkjet printing process. When comparing the microstructure of the edge of the printed line with the center of the printed line, a difference between the degree of sintering is observed as seen in To further explore the effect of particle contact area on the resulting microstructure, printing the pattern in multiple times was explored. Printing the same pattern with two or more layers—essentially printing the pattern multiple times on itself—results in a decrease in resistivity though expectation is that resistivity should be the same between one and multiple layers as the ratio of area over length should normalize the measurements. All samples were printed at the same time and then thermally cured at the same time for the given cure temperature. Analyzing the microstructural differences between lines printed in one and multiple layers may explain the drop in resistivity. Comparing the microstructures  of linesThe fact the necking process is more evolved at the same processing temperature is consistent with the notion of the dense packing model controlling the amount of sintering and also follows observations made on the edge of the printed lines in the previous experiment. Also seen in Comparing the microstructure of the fully sintered film to that of the Ferro 3309F ink cured at 850 °C reveals limitations of utilizing nanoparticle ink. Despite being fully sintered at 250 °C, there is no grain growth occurring at this processing temperature. Increasing the cure time to 24 h did not result in grain coarsening as is illustrated in Analysis of the data from all the experiments performed in this study reveals two trends. The first trend was observed from examining the variability of the resistivity of the printed samples. As the microstructure becomes more conductive, there is less variability. In the case of microparticle loaded inks, conduction through percolation yields a more variable situation than conduction through grainy film. The trend of a decrease in variability as the resistivity lowers is also observable in the processing of printed lines composed of nanoparticle loaded ink though not as pronounced as the trend observed in the microparticle loaded ink experiments. The second observable trend is a decrease in resistivity in inkjet printed lines when the pattern is printed two or more times prior to the application of the thermal curing process. When deciding which ink type to use, the electrical performance is only one parameter to consider along with the recommended curing temperature. From the graph in The microstructures, which arise as a result of the thermal processing of Ag particle loaded inks, play a role in the overall electrical performance of printed conductive traces. The key enabler for the most conductive microstructure observed in the experiments performed in this paper was high temperature processing  of the printed traces. The thermal processing in this temperature regime can only be withstood by rigid ceramic substrates. The dominant characteristic of this microstructure are grains of 5 μm in diameter.An observable trend in the decrease in sample set variability with an increase in conductivity exists in the processing of microparticle loaded conductors that corresponds with a microstructural change incurred by the thermal processing of printed traces. The trend is not as clear when examining the resistivity of lines created from the inkjet printing of nanoparticle loaded ink due to the lack of homogeneity of the microstructure at the edge of the printed lines.Despite the fact lines created via inkjet printing of Ag nanoparticle loaded ink have the ability to attain a more conductive microstructure due to the ability of the nanoparticles to undergo sintering at low temperatures, lines created with Ag microparticle based inks (particles on the order of 5 μm) will have a similar resistivity. In the case of nanoparticle loaded inks, once a sintered film is attained, temperatures on the order of 460 °C would be required to obtain a coarse grain structure.A profound nuance of inkjet printed traces is that the number of layers printed before curing results in a decrease in the measured resistivity of the conductive trace. The reduction in resistivity may be due to the densification of the packing of the nanoparticles resulting from the additional of layers. The densification results in a higher contact area between the individual particles which will enhance conduction through percolation when sintering has not occurred. The sintering process is enhanced by increasing the amount of layers printed which may also be due to more contact between the Ag nanoparticles which would enhance the diffusion mechanisms driving the sintering process.


The building of mathematical and computer models of cities has a long history. The core elements are models of flows  and the dynamics of structural evolution. In this article, we develop a stochastic model of urban structure to formally account for uncertainty arising from less predictable events. Standard practice has been to calibrate the spatial interaction models independently and to explore the dynamics through simulation. We present two significant results that will be transformative for both elements. First, we represent the structural variables through a single potential function and develop stochastic differential equations to model the evolution. Second, we show that the parameters of the spatial interaction model can be estimated from the structure alone, independently of flow data, using the Bayesian inferential framework. The posterior distribution is doubly intractable and poses significant computational challenges that we overcome using Markov chain Monte Carlo methods. We demonstrate our methodology with a case study on the London, UK, retail system. The key features of cities and regions are activities at locations, flows between locations and the structure that facilitates these activities . It is wRandom utility models, such as the multinomial logit model , provideIt turns out that the flows between locations concern a vast number of individuals and are well represented by statistical averaging procedures . It alsoWe note, however, that there is an urgent need to provide an improved modelling capability that captures the stochastic nature and uncertainty associated with the evolution of urban structure. The key shortcoming of the Harris and Wilson model is that it is deterministic and converges to one of multiple equilibria as determined by the initial conditions. In reality, the behaviour provided by the Harris and Wilson model would be accompanied by fluctuations arising from less predictable events. We instead introduce mathematically well-posed systems of stochastic differential equations (SDEs) to address this shortcoming, and provide an associated Bayesian inference methodology for parameter estimation and model calibration.To this end, we take a novel approach and construct a probability distribution to represent the uncertainty in equilibrium structures for urban and regional systems. The probability distribution is a Boltzmann–Gibbs measure that is the invariant distribution of a related SDE model , and is 2.M destination zones where consumer-led activities take place, for example shopping. Similarly, there are N origin zones from where consumers create demands for each of the destination zones. We define urban structure as the vector of sizes In this section, we construct a probability distribution for urban and regional systems. We work in the setting of the Harris and Wilson model  and use (a)j and origin zone i is denoted Tij. We illustrate a component of an urban or regional system in N origin zones areM destination zones areα,β>0 are scaling parameters and each cij≥0 represents the cost or inconvenience of carrying out an activity at zone j from i.The flow between destination zone 1ϵ>0 is the responsiveness parameter and κ>0 is the cost per unit floor size. The assumption that zones aim to maximize their size until an equilibrium is reached is justified by including the cost of capital in the running costs. A natural generalization of the Harris and Wilson model is the following SDE with multiplicative noise that we interpret in the Stratonovich2 sense:M-dimensional Brownian motion B and volatility parameter σ>0. A heuristic interpretation of the SDE is that, over a short time δt, the net capacity term ‘Dj−κWj’ in , denoted ρ, evolves in time according to the Fokker–Planck equation  with a suitable scaling of β determined by a preliminary study, as done in , and hold β=0.5 fixed. For the regime with high noise, the approximate draws are obtained by running a Markov chain of length 10 000 using HMC combined with parallel tempering for five different temperature levels [Vθ(x) obtained from numerical optimization as there is little variation between samples. The results are in figures α and lower values of β create a sparse structure in that all activity takes place in very few zones. Conversely, lower values of α and higher values of β lead to a more dense structure.Next, we draw the latent variables from the prior distribution e levels . For theλ=0.1 so that the relative noise for a zone of size 1/M7 is 3%. Although an improved specification of observation noise from a preliminary study would lead to more accurate inferences, the arguments and methodology we are presenting would remain the same. We run Markov chains of length 20 000. For the high-noise regime, we use the pseudo-marginal MCMC methodology in appendix C. Our importance sampling estimates comprised 10 particles and 50 equally spaced inverse temperatures. For the low-noise regime, we were unable to obtain precise importance sampling estimates due to the concentration of measure, so used the MCMC methodology in appendix C with the saddle point approximation in ; however, increasing M means that the z(θ) estimates are more challenging to obtain owing to the curse of dimensionality. It is of interest to develop more tractable methods, for example optimization based, so that inference can be performed for international models on a practical time scale. We have presented an aggregate model that can be refined to better represent domain-specific characteristics as discussed in [Our work has led to specific areas for further research. We are actively investigating the deployment of our methodology to large-scale urban systems, for which there are substantial computational challenges to overcome. The cost of a potential or gradient evaluation is ussed in . It remaussed in .


This technical report describes the creation of a gastroschisis model for a newborn. This is a simple, low-cost task trainer that provides the opportunity for Neonatology providers, including fellows, residents, nurse practitioners, physician assistants, and nurses, to practice the management of a baby with gastroschisis after birth and prior to surgery. Included is a suggested checklist with which the model can be employed. The details can be modified to suit different learning objectives. Gastroschisis is a congenital defect that occurs in 1:5000 live births .Neonates with gastroschisis are typically placed in a plastic bag or wrap. If a bag is used, the baby’s body is placed in the bag (legs first) up to the area just above the nipple line. The hands are left outside of the bag and then the string is pulled gently Figure .The baby is placed with the right side down to decrease the risk of compromise to the vascular supply of the gut.In order to provide better care for a newborn with gastroschisis, we built an original task trainer. Our simulator is inexpensive to make, simple to assemble, and has a realistic appearance and feel. It is superior to other models due to its ease of assembly and readily available components .We use this simulation-based model in our yearly boot camp which is a condensed course for critical neonatal intensive care unit (NICU) procedures, and during monthly simulation sessions that run throughout the year. Training can also be conducted in a just-in-time  method bWe used a low-technology manikin  but this model can be applied to most resuscitation trainers. To the right of the umbilicus, we carved a hole of 4 cm x 4 cm with a scalpel blade in order to insert the simulated intestines Figure . This prThe simulated intestines: We used edible snack stick collagen casing . For bowel contents, we used two cans of soft dog food. Dog food was chosen because the texture and color closely resembled the viable intestine. We tried gelatine but the color and texture were inadequate. We crushed the dog food in a food processor and used a 16-inch cake decorating piping bag with a tip diameter of 10 mm Figure . The cruThe distal end of the 275-cm length segment of the sausage casing was knotted. We chose this length to simulate the length of the bowel of a full term baby, but less could be used to simulate a smaller gastroschisis. The dog food was transferred to the piping bag, the sausage casing was attached to the tip of the piping bag, and the contents were squeezed into the casing. From time to time, we stopped pipetting and pushed the contents further in by squeezing the casing with our hands. The casing was filled loosely so it could still be easily manipulated and the proximal end was tied in a knot Figure .Assembly of the simulator: To create bowel loops, we took a 40-cm wooden spoon, coiled the filled casing around the spoon handle in loops of about 50 cm in length (25 cm on each side of the spoon), then threaded a 50-cm inch string instead of the spoon and tied it to create a "bouquet" of loops .D. Recognize and treat bowel that has vascular compromise .E. Complete a scenario using the critical action checklist (below) that demonstrates the trainees' ability to evaluate a complex situation, design a treatment plan., and demonstrate it on a model.Critical action checklist for Gastroschisis handling:1. Ensure adequate supplies are gathered2. Delegate tasks to team members3. Place baby in the steri-drape 50 x 50 plastic bag 4. Attach pulse oximeter to the right hand5. Suction and intubate the baby by avoiding positive pressure ventilation if respiratory failure is included in the scenario.6. Secure endotracheal tube7. Insert oropharyngeal replogle tube8. Dry the upper part of the body9. Attach a temperature probe if a prolonged stay in the delivery room is anticipated10. Place baby with the right side down11. Place an intravenous (IV) on baby’s upper arm12. Transfer baby to the NICU13. Upon admission to the NICU, check the baby’s vital signs and hydration status. Start the baby on IV fluids per unit protocol14. Attach the replogle to low continuous suction15. Check vital signs q15 minutes, replace any losses from the orogastric (OG) tube with electrolyte containing solutions as is customary to local practice16. Consider administration of normal saline boluses in addition to maintenance fluids to keep normal vital signs and urine outputWe have used this model more than 10 times for training scenarios and at national meetings. Our neonatal fellows, nurse practitioners, and physician assistants report better understanding and confidence in handling a baby with gastroschisis after practicing on the task trainer. Participants in the training scenarios commented: "The gastroschisis model was very good. It had a very life-like feel, just like a real bowel."  "It improved my confidence in handling this condition in the delivery room and the immediate pre-operative period." "Having been called to both real and simulation-based gastroschisis, it felt just like a real bowel."  "Using the model helped with positioning, and I knew just what to do and how to handle the bowel in a real situation." The scenarios can be varied depending on the experience level and learning objectives for the particular group. The complexity can be increased by adding complications that have occurred in clinical cases, such as a strangulation of the blood supply, hypotension from inadequate fluid administration, or hypothermia.Positive pressure ventilation (PPV) is to be avoided when resuscitating a baby with an abdominal wall defect in order to prevent air from trapping in the intestines that could make the abdominal wall closure more difficult. This learning point can be added to the most routine scenario and can be brought up in the debrief. The scenario can be further modified to include silo placement which would include interprofessional training of surgical residents.By employing this gastroschisis model, we are able to teach trainees to perform the actual procedures in a safe environment where team-based performance and communication skills can also be developed. This model for gastroschisis has the look and feel of a real intestine. This makes the experience more life-like or real. The simulation can be conducted in-situ or in a remote area from the delivery room and the NICU. This could allow assessment of the actual clinical environment for safety threats and increase the transfer of learning. The atmosphere is not meant to be threatening and care must be taken to establish ground rules for a positive learning environment. The debrief after the scenario is run by the trainees along with the trained faculty who act as facilitators. This guided group discussion helps diminish the tension and complete the learning objectives.This report contains detailed instructions and images that will help medical providers create their own models of a gastroschisis task trainer that is easy to assemble, inexpensive, reusable, and realistic. Using this model will improve the familiarity and performance of trainees who care for newborns with gastroschisis.


A device is described for use in confirming the energy constancy of clinical electron beams. A wedge shaped absorber is placed over an ionization chamber leading to an energy dependent response. A measurement under the energy filter is divided by a measurement in air to correct for the inherent energy dependence of the chamber. A nearly linear response is demonstrated.PACS number(s): 87.52.–g, 87.53.–j, 87.66.–a The report of AAPM TG40 Ref.  includesE¯0, its mean incident energy. E¯0 is definedE¯0 is constant.A clinical electron beam's penetrative ability is described by dmax and the second depth is selected to be near the reference d50. The ratio of these measurements is compared to a reference ratio. There are three drawbacks to this technique: (1) The measurement apparatus must be customized for each individual treatment unit, i.e., the needed arrangement of phantom pieces can be different for two beams, each having the same nominal energy if their dmax or d50 values differ; (2) the process is arduous in that the apparatus must be reconfigured prior to each exposure; (3) the measurement result does not lend itself to direct interpretation, i.e., a discrepancy in ionization ratio does not point directly to a corresponding error in beam energy.A common technique is to compare the ionization measured at two depths in the phantom. The first depth is selected to be near MoyerAn electron beam's PDD curve is characterized by a region of more or less uniform dose followed by a rapid falloff, especially in the range of 4 to 15 MeV.If a linear, cylindrical chamber is irradiated under a slab absorber of thickness greater than the electron range, it registers only a small signal. If the absorber is longitudinally shifted so that part of the chamber is exposed, then the chamber generates a partial signal. Since the fractional volume irradiated is equal to the fractional length exposed, the chamber signal will be roughly proportional to the distance along the chamber by which the absorber is shifted.If the chamber is covered by a wedge‐shaped absorber, then each location along the chamber is shielded to a different radiological depth. However, the situation is analogous to that of the shifted slab as shown in Fig. The absolute transmission of the wedge is offset by the absolute position of the wedge along the chamber. Shifts of the wedge along the chamber add or subtract the chamber signal as shifts of a slab would add or subtract the signal. The sensitivity of the wedge in discriminating energy is increased as the slope of the wedge is increased.10×5−3 CT/BNC,10.0−cm sensitive length) was selected as the detector. All measurements were made in air with the supplied acrylic buildup cap (12′ ′ outer diameter) and without backscatter.For validation, a cylindrical CT ionization chamber (RADCAL Model [tan−1(111)=5.2°]. Small uncertainties in the slope of the wedge are not critical when a single wedge is to be used in a constancy measurement. The wedge was wider than the diameter of the ionization chamber.Cerrobend was selected as the absorber material because it is readily available. The wedge was cast in a mold constructed of three pieces of expanded polystyrene. The length of the base was 11 cm, long enough to cover the length of the chamber. The thickness of the heel was 1 cm, which yields a wedge angle of approximately 5% The objective of validation was to demonstrate, through measurement, that a wedge‐shaped absorber can be used to detect the mean incident energy of a clinical electron beam and can thus be used to verify the constancy of that energy over time.During these measurements, the toe of the wedge was approximately aligned to one end of the chamber and the wedge was not moved between measurements. The absolute ionization measured under the wedge depends on the absolute position of the wedge with respect to the chamber. Since the wedge was not precisely placed with respect to the chamber, the absolute ionization measured at specific energies is not meaningful and is thus not tabulated. When used to verify energy constancy as part of a quality assurance program, a wedge must be locked with alignment pins into a fixed and reproducible position.15×15 cm cone was used to create an electron field larger than the ionization chamber. The base of the wedge was oriented perpendicular to the central axis of the beam at an SSD of 100 cm. The ionization chamber was located immediately behind the absorbing wedge. Expanded polystyrene was used to support the wedge and chamber and radiation was delivered with the accelerator gantry in a lateral position. For each available energy, ionization was measured with and without the wedge in place.The result, which is of interest, is the change of the signal generated in the ionization chamber as beam energy is changed. Measurements were made using the electron energies available on a VARIAN Clinac 18. A E¯0, a 2 mm shift in d50 would result from an energy change of 0.466 MeV. Given the measured energy sensitivity, a 0.466‐MeV energy change would result (2.9%/MeV×0.466 MeV) in a 1.35% change in ionization ratio. This change would be readily discernible with a good quality electrometer.These net transmission values resulting from these measurements are shown in Fig. E¯0.Use of a wedge‐shaped absorber with a linear ionization chamber was shown to be a feasible alternative to the common method of verifying energy constancy of a clinical electron beam. This alternative method offers three advantages: (1) The measurement procedure need not be customized for each specific treatment unit; (2) only two measurement configurations (wedge in and wedge out) are required to check a cluster of energies; (3) the measurement result is a simple ionization ratio that can be directly interpreted in terms of the constancy of


The Padé approximation is a useful method for creating new inequalities and improving certain inequalities. In this paper we use the Padé approximant to give the refinements of some remarkable inequalities involving inverse trigonometric functions, it is shown that the new inequalities presented in this paper are more refined than that obtained in earlier papers. The inequalityThe inverse trigonometric version of the Wilker inequality was considered in  and 2],,2], as fx.The Shafer-Fink double inequality for the arctangent function asserts thatet al. in ).It is the aim of this paper to give the refinements of the aforesaid inverse trigonometric inequalities using the Padé approximant method.i.e.,Suppose that we are given a power series i.e.,For a given function m and n, that is, the coefficients One can prove that the Padé approximant of a function In fact, with the help of the Taylor series,For example, we consider the Taylor seriesx for the order Then the Padé approximant of arcsinFrom the above equation, we findThereforex and arctanx which will be used in subsequent sections. In Table In order to prove the main results in Section For everyone hasWe consider the functionx yieldsDifferentiating Evidently, equality . The proFor everyone hasWe introduce a function Its derivativeequality . Lemma 2For any positive real numberx, one hasWe define a function ψ is strictly decreasing on Then we haveLetx givesDifferentiating ϕ is strictly increasing on We have The inequality  is proveIn this section we will formulate and prove the refinements of the aforesaid inverse trigonometric inequalities.For everythe following inequality holds:whereWe remark that if the above inequality is true for By using Lemmas Additionally,equality . The proequality  is complBy making use of the Taylor expansion, we haveWe note thatThe Taylor’s approximation prompts to consider another method for proving the inequality asserted in Theorem LetThen forwe have the following inequality:The first inequality can be rewritten asSince Thus we need to prove the following inequality:Therefore, we obtainThe last inequality can be rewritten asSince Hence we need to prove the following inequality:Now, fromIn conclusion, the inequality  follows Finally, we deal with the improved version of the Shafer-Fink inequality .Using the well-known trigonometric identityy  in  gives3.The left-hand side inequality of  can be rLet us consider the function Its derivatives areUsing the formulaThenNote thatTherefore Using similar arguments, we haveality of  is proveIn order to prove the right-hand side inequality of , we obseIt is easy to find that the right-hand side inequality of  is equivDefine a function t givesDifferentiating The function Also, we haveSince Using the same arguments, we haveality of  is proveIt is easy to observe thatThus, the left-hand side inequality of  is stronAlso, we haveHence we conclude thatality of  is stronality of  when \dox and arctanx. And then we use the Padé approximation to improve some remarkable inequalities involving inverse trigonometric functions, we show that the new inequalities presented in this paper are more refined than that obtained in earlier papers. It is worth to mention that the Padé approximation method has also been applied to dealing with the refinements of certain inequalities for trigonometric functions and hyperbolic functions in our recent papers x and arc


TBX1 is the only one that has been found to be mutated in some patients with a phenotype that is very similar to that of patients with the full deletion, suggesting that TBX1 haploinsufficiency is a major contributor to the syndromes phenotype. Multi- and single-gene mouse models have provided a considerable amount of information about the consequences of decreased and increased dosage of the genomic region (and in particular of the Tbx1 gene) on mouse embryonic development. Modified alleles of Tbx1, as well as conditional ablation strategies have been utilized to map in vivo the tissues and developmental stages most sensitive to gene dosage. These experiments have revealed substantially different sensitivity to gene dosage in different tissues and at different times, underlying the importance of the developmental context within which gene dosage reduction occurs.The 22q11.2 deletion/DiGeorge syndrome is a relatively common “genomic” disorder that results from heterozygous deletion of a 3-Mbp segment of chromosome 22. Of the more than 30 genes deleted in this syndrome,