During a routine anatomical dissection in the right brachium of a 75-year-old male cadaver, a novel variation of the coracobrachialis muscle (CB) was discovered. It consisted of three parts: proximal, starting from the upper border of the scapula; medial, presenting the well-accessed CB; and distal, formed by a proximal tendinous part that arose from the coracoid process and then transitioned into a well-defined muscle body and a distal tendinous part attached to the medial epicondyle. We also present a new systematic classification of CB variations, dividing them into two simple groups. The different anatomical variations of the coracobrachialis muscle (CB) have seldom been described in the literature -3. The nIn most species, the CB has three portions: the CB longus, the CB medius, and the CB brevis. In humans, the medius and the longus fuse to form the CB; the brevis is a rarely present third head of the muscle. The musculocutaneous nerve innervates the CB .The CB serves as a guide for locating the axillary artery during a blockade of the brachial plexus . It can In this case report, we present a novel variation of the CB, and we briefly review the reported variations of the CB and divide them into two simple groups.A rare case of CB variation was observed during a routine anatomical dissection in the right brachium of a 75-year-old Caucasian male cadaver. The variant CB consisted of three parts. The first started from the superior border of the scapula over the scapular notch and had a well-presented muscular body  that continued into a slim tendon inserted into the upper third of the medial part of the medial intramuscular septum. The second part corresponded to the classical description of the CB. The most interesting aspect was the aberrant third part, consisting of well-defined proximal and distal tendinous portions and an intermediate muscle belly. The proximal tendinous portion  originated from the coracoid process together with the CB, continuing into the intermediate muscle belly , and then into the well-formed distal tendinous portion , which was attached to the medial epicondyle of the humerus .In 1867, Wood first observed that the CB had three parts: the upper part started from the coracoid process and attached to the capsule of the shoulder joint ; the middle inserted into the mid-part of the humerus and observed in humans (CB proprius or medius); the lower attached to the internal condyloid ridge, the internal intermuscular septum, or the trochlea (CB longus) . Kyou-JoDifferent variations of the CB have been reported mainly in the old anatomical literature Table .Our review of this literature and the PubMed database did not reveal a similar three-part CB muscle.Most of the terms used to describe such variants have relied on either the attachment sites of the muscle or its functional characteristics. The reported superior part of our case could be termed the scapulo-brachial muscle or CB brevis. The CB variation inserted into the medial epicondyle of the humerus is usually described as CB inferior or longus. We propose “coracoepitrochlearis muscle” as a more appropriate term for describing the proximal and distal insertions of this muscle, as presented in our case. To simplify the reported variations and terms, we suggest dividing them into two simple groups: (a) CB brevis, inserted into the proximal part of the humerus, and (b) CB longus, inserted into the distal brachium. As a result, the accessory superior part documented in our case can be accepted as CB brevis and be assigned to the first group. The lower part, the coracoepitrochlearis muscle, belongs to the second group when this classification is used. It is evident that such a grouping will simplify the variations in cases presented in the future. We do not use the term CB medius and accept this as the classically described main CB.It is widely accepted that the CB is of little importance for upper limb function . AccordiDuring embryogenesis, the intrinsic muscles of the arm differentiate from the limb bud mesenchyme of the lateral plate mesoderm. The fusion of these primary muscles generates a single muscle, which then regresses as the layers of the arm muscle differentiate. The presence of an accessory CB could be explained as resulting from a premature termination of this regression process .Although there are currently no clinical reports describing the possible complications arising from such a variant causing nerve and vascular compression because the muscle crosses over the neuro-vascular structures, it could, in principle, cause compression symptoms, as seen in other, reported muscular variations, such as the Struthers ligament, and in the presence of the chondroepitrochlearis muscle, which are well known in the surgical literature . ClinicaThe coracoepitrochlearis muscle reported here could also cause a confusion when different imaging modalities are used, and it could restrict the abduction of the arm . HoweverIn conclusion, knowledge of the variation presented extends the anatomical and clinical literature. This anatomical variant could prove clinically important during traumatic reconstruction in this region, during different esthetic surgical procedures, and for vascularized muscle transfer in the treatment of facial palsy. The potential existence of this and other anomalous muscles should also be considered in the differential diagnosis of neurovascular compression syndromes.


The transfer of patients to and from the Intensive Care Unit (ICU) is prone to medication errors. The aim of the present study is to determine whether the number of medication errors at ICU admission and discharge and the associated potential harm and costs are reduced by using the Transfer ICU and Medication reconciliation (TIM) program.This prospective 8-month observational study with a pre- and post-design will assess the effects of the TIM program compared with usual care in two Dutch hospitals. Patients will be included if they are using at least one drug before hospital admission and will stay in the ICU for at least 24 h. They are excluded if they are transferred to another hospital, admitted and discharged in the same weekend or unable to communicate in Dutch or English.In the TIM program, a clinical pharmacist reconciles patient’s medication history within 24 h after ICU admission, resulting in a “best possible” medication history and presents it to the ICU doctor. At ICU discharge the clinical pharmacist reconciles the prescribed ICU medication and the medication history with the ICU doctor, resulting in an ICU discharge medication list with medication prescription recommendations for the general ward doctor. Primary outcome measures are the proportions of patients with one or more medication transfer errors 24 h after ICU admission and 24 h after ICU discharge. Secondary outcome measures are the proportion of patients with potential adverse drug events, the severity of potential adverse drug events and the associated costs.For the primary outcome relative risks and 95% confidence intervals will be calculated.potential rather than actual adverse drug events and finally a relatively short study period.Strengths of this study are the tailor-made design of the TIM program and two participating hospitals. This study also has some limitations: A potential selection bias since this program is not performed during the weekends, collecting of Nevertheless, the findings of this study will provide valuable information on a crucial safety intervention in the ICU.NTR4159, 5 September 2013Dutch trial register:  Patients in the intensive care unit (ICU) are more likely to experience medication errors than other hospitalized patients, since the chance of errors in an ICU setting is high due to the high intensity of treatment in patients with a critical illness , 2. MediOn regular wards, many Dutch hospitals use computerized physician order entry systems with clinical decision support (CPOE/CDS). In general, these CPOE/CDS systems cannot offer supporting systems for patient monitoring required at ICUs. Therefore most ICUs in the Netherlands do not use the general CPOE/CDS system. Instead, they use a so-called Patient Data Monitoring System (PDMS). However, these systems mostly lack clinical decision support for prescribing and monitoring medication. Besides, the use of two different systems poses an additional threat to safe medication transfer to and from the ICU.Various interventions have been studied to reduce medication errors on the ICU. A systematic review by Manias et al. identified eight types of interventions: implementation of CPOE, changes in working schedules, intravenous systems, modes of education, medication reconciliation, pharmacist involvement, protocols an guidelines and support systems for clinical decision making. Only four of these interventions demonstrated reduced medication errors post-intervention, one of which was medication reconciliation at ICU admission . BesidesHowever, the effect of medication reconciliation after ICU stay is not well described in the literature. The few available studies suffer from one or more of the following limitations: (1) small sample size; (2) failure to differentiate between intentional and unintentional discrepancies and (3) lack of assessment of potential clinical impact and/or severity of discrepancies. Besides, it is not known how patient safety will be affected by a combined admission and discharge medication reconciliation program in the ICU.Transfer ICU and Medication reconciliation) program, which consists of medication reconciliation by a pharmacist at ICU admission and at ICU discharge.In the present study, we hypothesize that continuity of care will be improved and medication errors and patient harm will be reduced if medication is reconciled during both ICU transfers by a pharmacist in close collaboration with the intensive care doctors and the ICU staff. To test this hypothesis, we designed the TIM (The aim of this study is to determine the effect of the TIM program on the number of medication transfer errors (MTEs) at admission to and at discharge from the ICU. Furthermore, we will investigate the effect of the program on the number of potential adverse drug events and their severity, and finally we will estimate the cost-effectiveness of this program.A prospective 8-month observational study with a before and after design will be carried out at Haga Teaching Hospital in The Hague  and Erasmus Medical Center in Rotterdam . Both hospitals are located in the Netherlands.The study consists of three periods: first, a pre-intervention period of 14 weeks during which patients will be included who receive usual care; second, a period of 4 weeks during which the TIM intervention program will be implemented, and finally, a post intervention period of 14 weeks during which patients will be included in the TIM program  and patient’s inability to be counseled in Dutch or English.At ICU admission the ICU doctors determine pre-admission medication. In this process, they rely on the data from the previous ward (if applicable), the patient’s general practitioner, relatives or previous hospital records . Occasionally, a faxed medication list is available from the community pharmacy, but there is no standard procedure for the ICU doctor to obtain medication lists from the community pharmacy. Hence, ICU doctors do not structurally perform medication reconciliation. The admitting doctor registers pre-admission medication in the PDMS system (Haga) or HIS  (Erasmus MC) and only transcribes the medication that is to be continued during the ICU stay into the PDMS/CPOEIn Erasmus MC a dedicated ICU hospital pharmacist reviews the prescribed medication on the ICU on a daily basis during patient rounds. In Haga Teaching Hospital, twice a week, one out of a team of 4 trained ICU hospital pharmacists reviews prescribed medication and attends the patient rounds on the ICU. In both hospitals, the hospital pharmacists rely on the information about pre-admission medication available in the PDMS and do not obtain a medication list from the community pharmacy, nor do they reconcile pre-admission medication with the patient.An ICU doctor writes an ICU discharge letter, which is screened, verified and authorized by an intensivist. Combined with a nurse discharge letter, this discharge letter is sent to the admitting ward at the moment of patient transfer.In Haga Teaching Hospital, the discharge letter contains information about the registered pre-admission medication, the medication in use at discharge from the ICU and suggestions about medication use after discharge (i.e.: “Restart pre-admission medication”). In Erasmus MC, the letter contains information about medication in use at discharge and sometimes suggestions for medication use after discharge.After transfer, the doctor of the admitting ward has to transcribe medication orders from the discharge letter to the hospital CPOE/CDS. At the same time, doctors in the Haga Teaching Hospital have to stop medication registered in the CPOE/CDS that the patient is no longer required to take after ICU discharge, since the CPOE/CDS system in this hospital does not automatically stop prescribed medication when the patient is admitted to the ICU. By contrast, the CPOE/CDS system in Erasmus MC stops all medication at admission to the ICU, which urges the doctor to prescribe all medication needed after the ICU transfer.The TIM program consists of medication reconciliation at ICU admission and at ICU discharge. In both intervention hospitals, the program will be carried out by two pharmacists. The pharmacists in Erasmus MC will be supported by pharmacy students, who, after a training period of several weeks, will be able to collect the medication lists and to interview the patients or their relatives about each patient’s pre-admission medication.First, permission for reconciliation is obtained from the patients or their relatives. Next, the pharmacist compiles a best possible medication history (BPMH) as described below in the section “the gold standard medication lists”. In case of an internal transfer, the BPMH will also include the pre-admission medication transcribed or omitted at the previous ward.Next, the pharmacist transfers the BPMH to the PDMS system (Haga) or HIS (Erasmus MC) and presents the BPMH to the ICU doctor responsible for the patient. If the pharmacist notices an inexplicable discrepancy between pre-admission medication and medication prescribed on the ICU, he or she will discuss this with the ICU doctor, enabling correction of unintended omissions or other mistakes in the ICU prescriptions. Finally, the pharmacist in Haga Teaching Hospital stops the patient’s medication in the CPOE/CDS system used on the wards, which is done automatically in the HIS system of Erasmus MC when the patient is admitted to the ICU.When a patient is discharged from the ICU, the pharmacist makes a discharge medication summary. This medication summary contains an overview of medications on the patient’s BPMH combined with all the medication the patient uses in the ICU at the moment of discharge. For each drug, the ICU doctor is given a series of options of recommendations , making it easier for the ICU doctor to provide clear prescription suggestions to the doctor of the general ward. The ICU pharmacist reconciles this medication list with the ICU doctor. During this reconciliation, special attention is paid to temporarily withheld medication that should be restarted and to temporary ICU medication that should be stopped. After this reconciliation, the pharmacist amends the medication list to establish the Best Possible ICU Medication Discharge List (BPMDL-ICU) , which includes name, dosage, frequency, and route of all medication taken by a particular patient. The BPMH is created as follows: a pre-admission medication list is collected from the community pharmacy, which is combined with other available information about the patient’s medication, such as a letter from the Emergency department (if applicable), medication used in the general ward or medication lists from the operating room (OR) (if applicable). This medication list is verified by means of an interview with the patient and/or a relative, which will result in a BPMH.The gold standard is defined as the Best Possible General Ward Medication List 24 h after the ICU discharge (BPML-GW24). The BPML-GW24 includes name, dosage, frequency, and route of all medication that should ideally be prescribed within 24 h after ICU discharge. This list is based on the BPMH, on information found in the PDMS or the HIS of the ICU, on medication prescribed in the CPOE/CDS and, whenever necessary, on interviewing the ward doctor afterwards.For each included patient discharged from the ICU for at least 24 h, a pharmacist generates a BPMH and a BPML-GW-24 in order to trace medication transfer errors.The pharmacist generates a BPMH for patients newly admitted to the ICU and the Best Possible ICU Medication Discharge List (BPMDL-ICU) for patients planned to be discharged. One day past ICU discharge, a medication chart of current medication in the CPOE/CDS will be printed and a BPML-GW24 will be compiled.Figure The primary outcome measures of this study are the proportion of patients with one or more MTEs at admission to the ICU and the proportion of patients with one or more MTEs after discharge from the ICU.An MTE at admission is defined as an unintentional discrepancy between BPMH and medication prescribed within 24 h after admission to the ICU.An MTE at discharge is defined as an unintentional discrepancy between the BPML-GW24 and the medication chart of the patient within 24 h after discharge.Whether a discrepancy at admission is unintentional or not is based on information documented in the PDMS, the ICU standards of care and the ICU pharmacist’s interpretation of the situation  score due to an MTE, both at the moment of admission and at the moment of discharge. In addition, the pADEs scores and the associated costs are secondary outcome measures. A pADE score is defined as a potential and severity score for discomfort, harm and/or clinical deterioration caused by an unintentional discrepancy .Determination of the potential and severity that a patient will experience harm due to an MTE will be based on the methodology described by Nesbit et al . The samNext, our preliminary cost-effectiveness analysis will estimate the incremental costs per prevented MTE of the TIM compared to usual care, from the hospital’s perspective. Costs will comprise both the costs incurred by the reconciliation process and cost avoidance due to preventing MTEs and their pADEs.The cost avoidance of the TIM program will be determined through summation of the individual pADE judgment scores of the MTEs and multiplying it by the cost of an ADE in the pre-intervention period compared to the post-intervention period.For measuring the cost of an ADE, we will estimate the medical consumption associated with the consequences of harm, such as number of ICU days and medical specialist- and nursing staff time, by means of expert opinion and by using previous literature , 19–21. Costs incurred by the reconciliation process are restricted to labour. The number of minutes spent per patient by the pharmacist will be measured during the intervention. These minutes will be valued based on standardised costs per minute, which equal the normative income of the pharmacist (collective labour agreement) divided by the number of workable minutes per year .All costs will be based on Euro cost data. If necessary, costs will be adjusted to the year of data collection using the general price index from the Dutch Central Bureau of Statistics .We will screen hospital patient records, PDMS records, CPOE/CDS medication lists, BPMH and BPML-GW24. Collected data from these sources will be categorized into three groups: patient data, medication data and intervention program data. Data will be collected in case report forms (CRFs). All data input in the CRF will be cross-checked by two pharmacists.The following patient data are extracted from the medical records: age, gender, APACHE II , SAPS II ), reason for the ICU admission, deceased during the ICU stay, length of ICU stay, specialty of referring physician, surgical patient or non-surgical patient, ward from which the patient was referred to the ICU  and type of admission . Both APACHE II and SAPS II are general illness severity scores, APACHE is the world most widely applied severity of illness score, whereas SAPS is developed in France and validated in 12 European/North American countries. Both scores are based on the worst values recorded in the first 24 h of the ICU stay and are used in the ICU to predict outcome. They characterize disease severity and degree of organ dysfunction .The following information is collected for all medication on the BPMH and/or BPML-GW-24: name of medicine, dose form, medication group, dose and frequency.We will register for every BPMH medication whether it is (1) prescribed in the PDMS within 24 h after admission, (2) registered in the PDMS as “pre-admission medication”, (3) prescribed pre-ICU in CPOE/CDS and (4) registered as “admission medication” in the ICU discharge letter.We will register for every BPML-GW24 medication whether it is (1) prescribed in the CPOE/CDS within 24 h after the ICU discharge, (2) in use at discharge on the ICU according tot the PDMS medication chart, (3) noted on the PDMS discharge letter as “ICU medication”.All discrepancies are scored as intended or non-intended and finally the discrepancy type: omission, start, stop, different dose, substitution or incorrect prescribing will be scored.During the post-intervention phase the process of medication reconciliation is qualified as A, B or C. Quality A is defined as an optimal reconciliation based on a recent, reliable community pharmacy medication list and a reliable verification with patient and/or his representative. Quality B is defined as an intermediate reconciliation; the pharmacy record is recent and reliable and screened for obvious errors, verification with patient or relative is however not reliable. And finally quality C is defined as a sub-optimal reconciliation with either the community pharmacy medication list lacking or the patient/representative verification lacking.Other data collected on medication reconciliation are: date of reconciliation, within 24 h of the ICU stay or not, verification with patient and/or representative, time spent on verification (patient’s interview), the total reconciliation time and finally the number of medications on the BPMH and BPML-GW24.The primary outcome of this study is the proportion of patients with one or more transfer errors at admission to the ICU and at discharge from the ICU.Based on literature the expected proportion of patients with medication errors due to transfer between wards within one hospital is 62% . Based oWith an estimated mortality of 35%, in each measurement phase 205 patients should be included. Based on 1500  and 1800 (Erasmus MC) admissions a year, an estimated loss of 30% due to the ICU stay less than 24 h and another 35% loss due to weekend ICU stay, we estimate a study period of 7 weeks for Erasmus MC and 8 weeks for Haga. To be on the safe side and to measure during a robust intervention period, we will double the number of calculated weeks. Therefore a pre- and post-intervention period of 14 weeks is chosen.All data will be entered in MS Access 2007 and will be analyzed with IBM SPSS Statistics 24.t-test for continuous normally distributed variables, Mann-Whitney U-test for continuous non-normally distributed variables and chi square test for categorical variables.Patients from the intervention and control group will be compared for all baseline characteristics using For the primary outcome (MTEs) relative risks and 95% confidence intervals will be calculated. As the study has a pre- and post-design, results will be corrected for potential confounders by using multivariate logistic regression analysis.Since the usual care provided in both hospitals is not completely the same, the usual care may have impact on the primary and secondary outcomes, i.e. the number of MTE and the risk of ADEs. Therefore we will assess in a secondary analysis, whether the effect of the intervention is modified by hospital site and we will present subgroup analyses per site.The aim of this study is to determine the effect of the TIM program on the proportion of patients with medication transfer errors (MTEs) at admission to and at discharge from the ICU, and on the number, severity and cost of potential adverse drug events (pADEs). Although a randomized controlled trial is generally considered to be the standard for comparing interventions, unfortunately a randomized design is not feasible for this particular investigation. Previous experience with similar projects has demonstrated that usual care is strongly influenced by an intervention program like TIM, as doctors and other healthcare providers are likely to learn from the program. Doctors will gain awareness of problems associated with transfers and may consequently change their prescribing behavior and the organization of care.To be able to compare the effects of TIM with usual care while avoiding a learning effect, we chose a before and after design. Although this is conceived to be a weaker design, we expect this study to have several strengths. First, pharmacists’ knowledge of the ICU is combined with pharmacists’ knowledge and skills regarding medication transfer and medication reconciliation. In both hospitals, dedicated ICU pharmacists participated in designing the TIM program. These ICU pharmacists have a thorough understanding of the ICU work processes, the ICU medication issues and the ICU culture. Their medication transfer and reconciliation skills have been developed in the previous years during several pilots and studies on medication transfer and reconciliation in different settings  –28. CombA second strength is that ICU doctors participated in the final design of the TIM intervention. The TIM study design was tested from an ICU-doctor perspective during a study design meeting with 4 internist-intensivists, 2 from each hospital. This led to some adaptations in the TIM program and in the outcome measures.Thirdly, the TIM intervention will be performed by ICU pharmacists, which will make the cooperation between pharmacists and the ICU doctors more effective.The fourth strength of the study is that it is performed in two different settings, a general teaching hospital and a university medical center setting, which will provide stronger results compared to a single site setting.This study has a number of limitations. First, this program is performed during workdays but not during weekends. This may lead to selection bias because quality of care can be more compromised in weekends than on weekdays due to week/weekend shifts and limited staff in weekends on the general wards. Second, the study does not include a hospital setting in which the PDMS and the CPOE/CDS system are part of the HIS. An unknown part of our MTEs can be due to transcription problems between different prescribing systems, which would not occur in hospitals which only have one prescribing system as part of the HIS. However, even if only one prescribing system is used throughout the ICU admission and discharge, the doctor of the general ward may omit restarting pre-admission medication after ICU discharge. Be that as it may, this study will not be able to answer questions about the effect of using two different prescribing systems as such. Third, although this study will be performed in two different settings, results would be even stronger and more generalizable if more hospitals were included.potential adverse drug events, assessed by a multidisciplinary panel, rather than actual adverse events. Therefore, in case of positive results on the primary outcome, future studies will be needed to study the effect on actual patient harm.Fourth, the study will measure Finally, a period of 14 weeks for the post-intervention measurement is relatively short; longer periods may be necessary in order to determine whether the results remain consistent over time.While most studies focus on the effect of medication reconciliation programs at the moment of hospital admission or discharge, this study focuses on ICU transfers and will be able to evaluate the clinical and financial impact of a comprehensive program on continuity of care. The findings of this study will provide health care professionals as well as patients, health care managers and policy makers with valuable information on a crucial safety intervention in the ICU.


The addition of short fibers has been experimentally observed to slow the stress relaxation of viscoelastic polymers, producing a change in the relaxation time constant. Our recent study attributed this effect of fibers on stress relaxation behavior to the interfacial shear stress transfer at the fiber-matrix interface. This model explained the effect of fiber addition on stress relaxation without the need to postulate structural changes at the interface. In our previous study, we developed an analytical model for the effect of fully aligned short fibers, and the model predictions were successfully compared to finite element simulations. However, in most industrial applications of short-fiber composites, fibers are not aligned, and hence it is necessary to examine the time dependence of viscoelastic polymers containing randomly oriented short fibers. In this study, we propose an analytical model to predict the stress relaxation behavior of short-fiber composites where the fibers are randomly oriented. The model predictions were compared to results obtained from Monte Carlo finite element simulations, and good agreement between the two was observed. The analytical model provides an excellent tool to accurately predict the stress relaxation behavior of randomly oriented short-fiber composites. The high modulus of short-fiber-reinforced polymers has made them useful in demanding load-bearing applications such as high-performance sporting equipment. However, because of the inherent viscoelasticity of the matrix phase, polymer composites are prone to creep  and streA stress relaxation test, where a constant strain is applied to a specimen and the decay of stress is monitored, is a straightforward way of characterizing polymer viscoelasticity. Since viscoelastic properties all result from the same molecular mechanisms, a model for stress relaxation in composites would also shed light on creep or dynamic mechanical behavior. The interaction between the fiber and matrix in a short-fiber composite is quite complex, and it has been a challenge to understand the effect of fibers on the viscoelastic properties of these materials. In particular, the effect of fibers on stress relaxation behavior is still not well-understood. Purely elastic fibers should, of course, increase the elastic component , but would not be expected to alter the time-dependent behavior of the material, which is traditionally attributed to the viscoelastic matrix. However, in many studies, researchers have found that the addition of short fibers to a polymer slows the stress-relaxation process. Kutty and Nando  investigTwo main mechanisms have been proposed in the literature to explain the change in the time constant for stress relaxation with the addition of elastic fibers. The first explanation is that since stress relaxation occurs by rearrangement of the secondary bonds in a polymer, the physical presence of fibers impedes molecular rearrangement of the polymer near the interface, resulting in a slower relaxation of the matrix. Considering the scale at which the molecular rearrangements of secondary bonds occur (angstroms), it seems unlikely that the volume of polymer close enough to a fiber surface to be affected could result in significant changes to the bulk properties of the composite. The second theory proposed in the literature focuses on chemical bonding at the fiber/matrix interface. These studies propose that when a fiber is added into a matrix, strong covalent bonds are formed at the interface. During stress relaxation, these additional covalent bonds must be overcome to allow polymer mobility and stress relaxation. Due to these additional bonds, the stress relaxation rates are expected to be slower. George et al. , and latExperimental studies agree that the presence of elastic fibers can slow the stress relaxation rate of polymers in which they are embedded. Both of the previously proposed mechanisms rely on speculation regarding the molecular interactions at the fiber-matrix interface. Furthermore, they do not provide any quantitative predictions of the changes in stress relaxation due to fiber addition.Short-fiber composite viscoelasticity has also been extensively modeled using a tensor elasticity approach to compute the stress field around elastic inclusions embedded in viscoelastic matrices ,10. UnfoIn a previous paper, we proposed a novel explanation for the effect of elastic fibers on the time-dependency of a polymer matrix composite . We deveIn our previous study, we specifically examined the effect of short fibers fully aligned with the load direction on composite stress relaxation. In that study, an analytical model was developed, studied parametrically, and then validated by finite element experiments. The analytical model showed that the time-dependence of polymer composites was influenced by two key factors. Firstly, the tensile modulus of the matrix is, of course, time-dependent. However, equally important is its time-dependent shear modulus, which results in a time-dependent shear stress transfer to the fiber. This causes the stress carried by the fiber to also decay with time, causing the overall time-dependence of the composite to be non-linear upon the addition of elastic fibers.In this study, we extend the model to account for random fiber orientation and validate it using a Monte Carlo finite element simulation. A Monte Carlo approach is one in which results are obtained and conclusions are made based on repeated random sampling. In this study, five replicates were conducted at each fiber content. For each replicate, fibers with random positions and orientations were generated to ensure that the results accurately represented a truly random system. These individual replicates were averaged to understand the effect of fiber content. Thus, for this study, the Monte Carlo approach was used to determine the effect of fiber content by conducting repeated random sampling. Since these simulations incorporate the inherent randomness of fiber positions and orientations, by adopting this approach these simulations can be considered equivalent to lab-scale experiments. We also use the model to understand critical differences in the expected viscoelastic behavior of aligned versus misaligned fiber composites.The analytical model proposed previously was based on a simple shear-lag model, originally developed by Cox . While ts. The first term represents the matrix contribution scaled by its volume fraction (t), as it must in a polymer matrix composite. The relaxation of the matrix modulus is modeled using a one-component Prony Series consisting of the instantaneous modulus (Equation (1) is a modified rule of mixtures equation for the modulus of composites containing short fibers with an aspect ratio (the length-to-diameter ratio of the fiber) of Equations (1) and (2) assume that the stress relaxation modulus decays following a Prony Series, and that the rate of relaxation is characterized by a relaxation rate constant , respectively.Because the fiber is not oriented in the loading direction, the projected length of the fiber in the loading direction is then: The volume fraction of the fibers, taking into account the total number of fibers Fx=d by Cox . Thus, can be simplified to: The contribution by the fibers is therefore reduced by a factor of The following model is derived for the stress relaxation behavior of composites consisting of a viscoelastic matrix embedded with short, elastic fibers oriented randomly in the plane. The analytical model takes into account the time-dependent shear modulus of the matrix in addition to its time-dependent elastic modulus.t, but that Note that Finite Element (FE) experiments were conducted in Abaqus/CAE  and were compared to the predictions from the analytical model to determine its accuracy. In these FE experiments, the matrix was defined as a viscoelastic material having an instantaneous modulus of 1 GPa, a long-term modulus of 0.5 GPa, a relaxation-time constant of 100 s, and a Poisson’s ratio of 0.5. The fibers were defined as having an elastic modulus of 80 GPa, a Poisson’s ratio of 0.2, a length of 260 μm, and an aspect ratio of 16. The model consisted of a two-phase system including a matrix and fibers. A rigid body was used to apply boundary conditions that corresponded to a stress relaxation experiment. A tie constraint was applied between the rigid body and the matrix surfaces. The matrix was defined as a three-dimensional deformable object while the fibers were defined as one-dimensional beam elements for computational efficiency. The interaction between the two phases was defined by defining the fibers as being embedded in the matrix with perfect bonding. High mesh densities were applied to both the matrix and the fiber: the matrix mesh consisted of a total of 2211 quadratic elements of type C3D20R while the fiber mesh consisted of 40 quadratic elements of type B32 per fiber. The experiments were conducted at various fiber contents and the number of fibers was altered in accordance with the desired fiber volume fraction. Five replicate simulations were conducted for each fiber content. For each replicate, a Python script was used to assign a random position and random orientation to each fiber. This ensured that each new experiment contained fiber placements that were random and different from previous replicates. The mesh was autogenerated on the edges of the fiber.The finite element experiment consisted of two analysis steps: An instantaneous strain was applied, followed by 400 s during which stress decay was observed. Default solver settings were used in both analysis steps. The modulus of the composite was determined using the cross-sectional area, the applied force, and displacement of the rigid body. The data was collected at 10 s intervals with a minimum increment time step of 0.004 s.The accuracy of the closed-form analytical model was evaluated through comparison to the finite element experiments conducted in Abaqus CAE. The fit between the two was compared by two methods. First, In a previous study, we conducted finite element experiments on composites with oriented fibers instead of misoriented fibers; the settings used in that study were the same as those described here . Figure As mentioned earlier, the misorientation of the fibers results in a reduction in their ability to carry stress in the loading direction. Thus, for misoriented composites, the influence of the time-dependent shear lag effectiveness factor shrinks, reducing the effect of fibers on the relaxation rate constant of the composite. The analytical model predicts that there should be a greater difference between the relaxation time constant for oriented and misoriented samples compared to the results shown in The goal of this study was to investigate the role of short fibers on stress relaxation behavior by examining the micromechanics at the fiber-matrix interface in composites with randomly oriented fibers. This novel perspective differs from previous investigations, which have focused on attributing the effect of fibers to chemical or structural changes at the interface between the fiber and the matrix. The study aimed to not only understand the role of micromechanics, but also to develop an analytical model that could be used to make predictions regarding the stress relaxation of composites with varying fiber content, orientations, and aspect ratios. Good agreement was observed between the results obtained via finite element experiments and the preditions from the analytical model. Thus, the analytical model developed in this study provides an adequate and accurate tool to predict the stress relaxation behavior of misoriented short-fiber composites with varying fiber content. It was found that the rate of stress relaxation is influenced by both the time-dependent elastic modulus of the matrix and the time-dependent shear stress transfer at the fiber-matrix interface, which stems from the time-dependent shear modulus of the matrix. However, the misorientation of fibers shrinks the contribution of the time-dependent shear stress transfer by a factor of one-third compared to the contribution of oriented fibers. The analytical model was validated using finite element experiments conducted in Abaqus CAE. Excellent agreement was observed between the analytical model and experiments at fiber volume fractions below 30%; the deviation from the analytical model beyond 30% was attributed to the inaccuracy of the shear-lag model at higher fiber volume fractions. Since the experiments followed a Monte Carlo approach with random fiber positions and orientations, its agreement with the analytical model further signifies the importance of incorporating time-dependent shear stress transfer at the fiber-matrix interface.


This paper proposes a novel joint probabilistic data association (JPDA) filter for joint target tracking and track maintenance under unknown detection probability and clutter rate. The proposed algorithm consists of two main parts: (1) the standard JPDA filter with a Poisson point process birth model for multi-object state estimation; and (2) a multi-Bernoulli filter for detection probability and clutter rate estimation. The performance of the proposed JPDA filter is evaluated through empirical tests. The results of the empirical tests show that the proposed JPDA filter has comparable performance with ideal JPDA that is assumed to have perfect knowledge of detection probability and clutter rate. Therefore, the algorithm developed is practical and could be implemented in a wide range of applications. There has been increasing attention on utilisation of small autonomous systems in military and civil applications. The issue is that the operations of these small autonomous systems are constrained by limited payload, as well as limited operation time and endurance. This has led to proliferation of lightweight, low-cost and energy efficient on-board sensors.Reliable and autonomous target tracking is a fundamental aspect of situation awareness for autonomous systems ,2,3. AppIt is known that data association in MTT is a challenging issue. With a high clutter rate, data association in MTT becomes even more challenging. One of the most popular data association approaches is the multiple hypothesis tracking (MHT) proposed in ,5. GivenJPDA is another widely used one-scan data association method. The basic assumption of JPDA is that each measurement can originate from several candidate targets in the valid gate. Therefore, JPDA never make any hard decisions on the measurement-to-target association and is a soft decision filter. The key part of JPDA is to enumerate all feasible joint events to calculate the marginal probability for the track update. Compared with the multi-scan MHT, JPDA can achieve reasonable results at lower computational burden ,11,12,13Despite its advantages, the JPDA filter, similar to most multi-target tracking algorithms, requires the knowledge of detection probability and clutter rate in implementation. These two parameters are of great importance for the JPDA filter as they determine the final estimation performance. Significant mismatches of these two key parameters could result in erroneous tracking outputs. Although the detection probability, dependent on the sensors and the scenarios, can be tested via offline experiments, it might not be cost-effective and they are typically unavailable for low-cost sensors. Furthermore, under dynamic environmental conditions or detection approaches, the clutter rate generated by the same sensor might change in a great deal: for example, in image-based target tracking, measurements are extracted from various detection algorithms , rangingMotivated by the above observations, this paper aims to propose an enhanced version of JPDA that can accommodate the unknown detection probability and clutter rate. The proposed algorithm is derived by integrating a JPDA filter with Poisson point process (PPP) birth model and a multi-Bernoulli filter. Note that the study in this paper is based on our previous work : this paThe performance of the proposed approach is evaluated through extensive numerical simulations. The simulation results demonstrate that the proposed algorithm has comparable performance with the ideal JPDA, which is assumed to have perfect knowledge of detection probability and clutter rate.The rest of the paper is organised as follows. i to refer to a target index and j to refer to a measurement index.This section addresses the system models that are used in the following sections. Throughout the paper, we use the symbol k are, respectively, defined ask, ith target at scan k, k, jth measurement received at scan k, k is governed byThe set of target states and measurements received at scan As required for JPDA, we accept the assumption that each target can generate at most one measurement and each measurement can originate from at most one target. Each target-generated measurement is independent of each other and is detected with probability a priori. When there is no prior knowledge regarding the clutter measurements, the MTT problem generally assumes that the number of clutters or false alarms is locally Poisson distributed [The clutter distribution is assumed to be unknown tributed . TherefoThe detection probability is assumed to be independent of the target state in filter design. The detailed discussion will be presented in The additional assumptions made in the paper are as follows:ith target and ith target at scan k. Then, the time evolution of In standard JPDA filtering approach, a track is defined as a sequence of measurements that originate from the same target. The original JPDA filter assumes the number of targets is known a priori at each scan and utilise a wrapper heuristic milar to , for tarne model  and the odel [PS .In this section, we first briefly review the basics of JPDA filter for the completeness and then give an intuitive analysis of the effect of the detection probability and clutter rate.jth measurement is originated from the ith target and ith target is miss detected. JPDA assumes that each single association event is independent and the posterior of each target is characterised by a mixture as [JPDA algorithm aims to calculate the marginalized association probability based on all possible joint events for data association. A joint event is an allocation of all measurements to all tracks. In JPDA, a feasible joint event is defined as one possible mapping of the measurements to the tracks such that: (1) each measurement (except for the dummy one) is assigned to at most one target; and (2) each target is uniquely assigned to a measurement. Let xture as (3)pxkiejth measurement to target i, jth measurement is associated with the ith target.Generally, propagation of the mixture distribution is computationally intractable due to the explosion of mixture terms. JPDA approximates this mixture term by a single Gaussian distribution through first moment matching method. More specifically, the state correction The hypothesis-conditioned update The posterior distribution of the joint association event ction fd . Therefoith target and ith target.Note the term Although full enumeration is intractable in real applications due to the high demand of computational power, the marginal probability proaches ,11,12,25After finding Based on Equations –7), the, the7), Finally, the posterior probability of target existence Using quations  and 4)..rkki andNote that, except for the updates of approach , for traRemark 1.Note that the utilisation of PPP birth model for target existence estimation is similar to the idea of joint integrated probabilistic data association (JIPDA) ,26. HoweTherefore, the standard JIPDA ignores the influence of the unknown targets in marginalisation. Clearly, leveraging the PPP birth model is beneficial and more realistic in initialisation and calculating the marginal association probability.This subsection analyses the effect of detection probability and clutter rate on the performance of JPDA filter provided that they are given in advance.The effect of the detection probability quations  and 7)  PD on thFrom Equation , one canConsequently, significant mismatch of either detection probability In this section, we will propose a novel JPDA filter to adjust the unknown detection probability and clutter rate by leveraging the multi-Bernoulli filter.k, the posterior PDF of the multi-target state is characterised as a multi-Bernoulli RFS. More specifically, each target is modelled as a single Bernoulli RFS, which is fully described by the existence probability (1)Prediction step. If the posterior multi-target density at time (2)Update step. If the predicted multi-target density at time k is characterised as a multi-Bernoulli RFS as The recently proposed multi-Bernoulli filter ,27,28,29The advantage of the multi-Bernoulli filter is that it utilises the mathematically sound RFS theory and thus directly avoids the data association process in multi-target tracking, leading to computational efficiency. However, the target identity or the target label cannot be maintained during the filtering recursion. This means that the multi-Bernoulli filter cannot be used to support the target label management. Therefore, if the label information is required for practice, the application of multi-Bernoulli filter is limited. Fortunately, as our aim is to estimate the clutter rate as well as the detection probability using the multi-Bernoulli filter, there is no need to manage the clutter identity.To apply the multi-Bernoulli filter to estimate the clutter rate, we consider each false alarm as a target with its own transition model, birth model and death model . This coIn reality, the detection probability is related to the target state. This fact makes the system state propagation/prediction of the augmented system intractable. To address this problem, we further assume that the detection probability is independent of the target state, i.e.,Note that the target detection probability used in JPDA is typically piecewise constant and thus the independence assumption is reasonable in filter design. Furthermore, the validation presented in the following section reveals that the proposed algorithm works well in the presence of time-varying detection probability.In general, the clutter dynamics is highly dependent on the sensors. If we have some prior information regarding the sensors, we can utilise such information to build the clutter dynamics model. Otherwise, general models can be leveraged, e.g., Gaussian distribution and random walk. Similarly, if there is no prior information, a typical choice of the detection probability model is the well-known beta distribution ∼Betaα,β . The betBy substituting the augmented state space into the original multi-Bernoulli filter, we can readily estimate the number of clutters at one scan k, we utilise the original JPDA with PPP birth model as the main tracker to provide the multi-target state estimation. The required detection probability and clutter rate is obtained from an one-step multi-Bernoulli filter. As discussed earlier, by incorporating the PPP model into JPDA, the posterior of JPDA estimation can be modelled as the multi-Bernoulli RFS and thus the estimated output of the JPDA is feedback to the multi-Bernoulli filter for its initialisation at every time instant. The advantage of the proposed parallel filtering scheme is that one can fully exploit the strengths of both approaches: using the JPDA for track management and obtaining fast estimation of detection probability as well as clutter rate by the multi-Bernoulli filter.The proposed JPDA is shown in Remark 2.The computational complexity of the proposed estimation algorithm comes from two main parts: JPDA and multi-Bernoulli filter. Although the original marginalisation in JPDA is a #P-complete problem, leading to the fact that the computational time increases exponentially with respect to the number of targets, the approximation by Gibbs-sampling is a polynomial-time algorithm, as detailed in . AdditioIn this section, the effectiveness of the proposed JPDA filtering algorithm is investigated through numerical simulations in a cluttered environment. Our experiments explore a scenario, involving 10 manoeuvring targets with different birth time. The ground truth of the considered scenario is depicted in T the sampling period, and The state vector contains planar position and velocity. We use the well-known constant velocity (CV) model for target prediction. The CV model is defined asIt is assumed that we use a radar for multiple targets tracking. The target-generated nonlinear range and bearing measurements are modelled byThe clutter is assumed to be uniformly distributed in the surveillance region with its number being Poisson with X and Y be the position estimation set and true target position set, respectively. The cardinality of these two sets are m and n, respectively. Then, for n. p determines the sensitivity of c determines the relative weighting of the penalties allocated to cardinality and localization errors. In all simulations, these two parameters are set as The optimal sub-pattern assignment (OSPA) distance metric  is consifined as ,(26)dpcFor the purpose of comparison, we also perform the ideal JPDA filter with perfect knowledge of detection probability and clutter rate, the following four non-ideal JPDA filters: (1) ideal The results of OSPA distance and cardinality estimation obtained by 200 Monte-Carlo runs are shown in This paper developed an enhanced version of JPDA by incorporating with the multi-Bernoulli filter to accommodate the unknown detection probability and clutter rate. By utilising the PPP birth in JPDA filter, the multi-target estimation output can be characterised as a multi-Bernoulli RFS. This enables the application of the multi-Bernoulli filter in a feedback loop to estimate the unknown detection probability and clutter rate. Simulation results confirm that the proposed algorithm exhibits the advantages of the original JPDA filter and can correct the biased estimations induced by the unknown detection probability and clutter. Under the condition where detection probability and clutter rate are difficult to be obtained, the proposed JPDA filter can be a practical solution, providing performance comparable to the ideal JPDA filter.


The aim of this study is to examine how well different informative priors model age-at-death in Bayesian statistics, which will shed light on how the skeleton ages, particularly at the sacroiliac joint. Data from four samples were compared for their performance as informative priors for auricular surface age-at-death estimation: (1) American population from US Census data; (2) county data from the US Census data; (3) a local cemetery; and (4) a skeletal collection. The skeletal collection and cemetery are located within the county that was sampled. A Gompertz model was applied to compare survivorship across the four samples. Transition analysis parameters, coupled with the generated Gompertz parameters, were input into Bayes' theorem to generate highest posterior density ranges from posterior density functions. Transition analysis describes the age at which an individual transitions from one age phase to another. The result is age ranges that should describe the chronological age of 90% of the individuals who fall in a particular phase. Cumulative binomial tests indicate the method performed lower than 90% at capturing chronological age as assigned to a biological phase, despite wide age ranges at older ages. The samples performed similarly overall, despite small differences in survivorship. Collectively, these results show that as we age, the senescence pattern becomes more variable. More local samples performed better at describing the aging process than more general samples, which implies practitioners need to consider sample selection when using the literature to diagnose and work with patients with sacroiliac joint pain. Knowledge about how these indicators change as we age can inform practitioners of joint changes that affect older adults, which in turn apprises application of age-at-death estimation methods. In particular, the sacroiliac joint is a source of pain for adults as they age due to the development of ankylosing spondylitis and changes to the cartilage that cushions the joint. As one ages, the sacroiliac joint transitions to become rougher and more irregular It is of interest in this research to look at different representative levels of prior samples to ascertain which is the most appropriate for selection in Bayesian analyses of age-at-death. The potential pools of age-at-death structure data can be found in skeletal collections, cemeteries, county records, and country records, to name a few. Here, I examine the age-at-death demographics from an American skeletal collection developed mostly from willing, local donors, a cemetery local to the skeletal collection, the county in which the collection and cemetery reside, and the country in which the collection, cemetery, and, county are located. The auricular surface indicators were recorded from individuals in the skeletal collection. Thus, the forensic approach, wherein a subset of the target sample is used as an informative prior, will be called upon in this analysis.This paper takes a biodemographic approach to investigating age and age-related changes in the skeleton. While this paper focuses on skeletal indicators of senescence, these data inform us of the aging processes humans undergo, which provides insight into longevity. The age-at-death distribution of several samples are examined and tested for differences that might impact age-at-death information derived from the skeleton, which impacts our understanding of biological and chronological age. Based on the literature, I hypothesize there will be small differences in the age-at-death distributions of the four samples. The performance of each sample will be measured by the calculated accuracy of auricular surface to capture chronological age from biological age, which supports the aim of this article.2.The age-at-death distribution of four American male samples was modeled. The US Census dataset provided information for two of the samples: (1) the age-at-death of all adult (age 18 and older) American males who died between 1999 and 2013 ; and (2) the age-at-death of adult Knox County, Tennessee American males who died between 1999 and 2013 . All causes of death regardless of whether an autopsy was performed, were considered. No restrictions were placed upon the data obtained from the US Census other than gender and Knox County residency.The third sample  is an age-at-death distribution from a local cemetery that represents Knox County residents. The cemetery was not restricted to a particular type of resident , which should provide a relatively unbiased sample of Knox county residents as each resident has an equal probability of being buried in the cemetery. These data were obtained from “Find a Grave”, an online research dataset, which allows for use of cemetery data for “scholarly historical research.” These results are applicable to historical and contemporary Americans. The date of death, date of birth, and name of the interred individuals were obtained from headstones and are accessible online. The data were screened for duplicate entries and names assessed for gender. Names were assigned probable genders based on the knowledge of gender-name association for the region. Individuals with gender neutral names were eliminated. Only males age 18 and over were included.The final sample  is comprised of individuals from the William M. Bass Donated Skeletal Collection (Donated Collection), housed at the University of Tennessee, Knoxville. The Anthropological Research Facility that is associated with the Donated Collection was started in 1980 by Dr. William Bass and represents local, regional, and global donations. Local donors mostly comprise the collection Senescence changes of the auricular surface were captured through visually inspecting the morphology and classifying the stage of the indicator into one of the 8 phases in the Lovejoy et al. method h(t) is the death rate adjusted by 18 years (the minimum age of this sample), α is the mortality parameter and β the senescence parameter. These parameters represent the values used for the informative prior in Bayesian analysis. A single plot was generated with the survivorship curve for each of the four samples to compare the survivorship distribution.A Gompertz survivorship model was ran on the ages of the individuals in all four samples, which estimates the mortality and senescence parameters: In order to compare the performance of each sample to estimate chronological age from biological age indicators, the accuracy of each method must be ascertained. To do this, the transition analysis parameters that provide the age at which an individual transitions from phase to phase in the auricular surface method for this sample were obtained from Hens and Godde Pr(j|ac) is the probability of an individual who dies at age a would be in the thj stage of skeletal morphology (phase) c. PDF are used to generate highest posterior densities and highest posterior density ranges (HPDR), which correspond to coverage, or a provided age range. In other words, 90% coverage is utilized here, which means the age ranges provide 90% coverage of the individuals who scored a particular phase. Thus, for phase 2, 90% of the individuals who scored a phase 2 should have an age-at-death that falls in the HPDR for phase 2. Cumulative binomial tests examined the knowledge of whether the coverage provided from the HPDR will meet the specified coverage. A small hold out sample of individuals from the Donated Collection, that were not utilized to construct the HPDRs, were assessed with cumulative binomial tests using age-at-death and assigned phase. This ascertained whether the 90% HPDR coverage held true in a separate sample.To calculate age ranges associated with each auricular surface phase, the transition analysis parameters  are combined with the aforementioned Gompertz parameters , which represent the informative prior's age-at-death distribution, in Bayes Theorem. Probability density functions (PDF) are integrated into Bayes theorem: The Bayesian approach of this analysis stems from the known prior age-at-death information from each of the four samples. The protocol for generating the age ranges follows the work of Konigsberg and colleagues 3.The mortality and senescence parameters are listed in The HPDRs  showed t4.The age-at-death distribution of a skeletal collection, cemetery, county, and country survivorships plotted somewhat similarly as regards to overall shape of the curves, but age differed among the skeletal and cemetery samples vs. the county and country samples. Moreover, there were key shape differences, in particular, at older ages. Despite these differences, the prior samples provided age ranges that were roughly similar, but the skeletal collection (forensic method) generated the best age estimates. Thus, the hypothesis that small differences will be reported that will not greatly impact performance was supported. However, all four prior samples' coverage underperformed, indicating biological age of the sacroiliac joint does not translate linearly to chronological age.It is not surprising there were large age ranges in advanced phases and the performance of the age ranges was lower than probability; many scholars report unease with using the method Even though a different population may be needed to more accurately model auricular surfaces in American males, the level of representation of a sample appears to be important. Upon examination of The trends in the fit of the informative priors support Godde and Hens The broad age ranges associated with the sacroiliac aging method indicate that as we transition through the auricular surface phases, aging becomes more variable. Thus, there is a lot of diversity in age-related changes at the sacroiliac joint. This may be due to the normal degeneration of tissue, which is a less reliable process than growth and development progression. Biomechanical forces may also be driving this, although it is less clear how as the sacroiliac joint functions as a stabilizer and load dissipater for the lower extremities from the weight of the trunk These results directly impact practitioners working with aged populations. It is important to understand the increasing variability in presentation of biological age, which translates to greater diversity in how older adults respond to and present age-related changes in the sacroiliac joint. This may also explain some of the difficulty in making diagnoses of specific sacroiliac joint conditions during life These findings can be applied to reconstructing the biological impact of lifeways of historic Americans and identifying individuals in forensic contexts. Only through knowledge of modern Americans with documentation of demographics in life can we learn how to interpret the osteobiography of historic Americans. Modeling age in historic Americans should follow the recommendation of this paper to find a more localized population  or to utilize the forensic approach. Moreover, time is an important component; Godde and Hens


DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete.In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported to other methylation, DNA and RNA analysis tools.The developed software tool achieves execution times one order of magnitude shorter than the existing tools, while yielding equal sensitivity for short reads and even better sensitivity for long reads.The online version of this article (doi:10.1186/s12859-017-1574-3) contains supplementary material, which is available to authorized users. The introduction of NGS (Next Generation Sequencing) technologies has made possible the sequencing of genomic DNA in a short time (days), producing billions of short DNA samples (commonly denoted as reads). The typical read length produced by current NGS sequencers ranges from 50 to 400 nucleotides (nts), though new sequencers yielding reads of several thousand nts are already in the market . Also, tA particular topic of DNA analysis is DNA methylation. By aligning and comparing (mapping) bisulfite-treated reads to the genomic DNA sequence, it is possible to determine the methylation of each pair-base. Several methylation tools have been developed over recent years –6), but In this paper, we propose a new strategy for methylation analysis that greatly reduces the required execution time of the mapping tools while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported not only to other methylation analysis tools, but also to DNA and RNA analysis tools. It consists of two independent techniques: first, we use a bidirectional implementation of the BWT that tries to map each read onto the reference genome simultaneously starting from both read ends (and proceeding to the center of the read), instead of mapping each read from one end to the opposite one.Unlike other implementations of bidirectional BWT , 11, it The Burrows-Wheeler Transform (BWT) is a compression procedure originally designed for data (text) compression , 13. Latsegment. The mapping procedure is as follows: the last nucleotide of the read is searched in the reference genome. Next, the sequence of the last two nts of the read is searched on the reference genome, then the sequence of the last three nts, and so on. In each search, a new nucleotide from the end of the read is added to the sequence to be found. This procedure is repeated, until an EID is reached. At that point, a segment of the read will be aligned to one or more locations of the reference genome. Also, it is possible to use the BWT to perform the alignment in the opposite direction [Nevertheless, the BWT is used to perform a unidirectional backward search in all cases. The BWT starts from one end of the read, trying to align as many nucleotides (nts) of the read as possible to a sequence of the reference genome, until an EID is found. Figure irection  by constirection  for the Unlike other implementations of bidirectional BWT , 11 our HPG-Methyl [The BWT implementation and use described in the previous section can be used in any alignment process. In order to prove its potential, we have integrated this version of the BWT in the parallel pipeline of a software tool designed for methylation analysis, termed G-Methyl .Like most of current software tools , 14, HPGn segments denoted as seeds (8 segments in the figure), and independently aligning each seed of the read against the reference genome by using the BWT. This stage is called seeding. Each of the seeds can be aligned everywhere, but the alignment of two or more seeds at short distances can reveal candidate areas for read alignment. Thus, the next stage of the pipeline consists of selecting those areas in the reference genome (with lengths similar to the read length) where two or more seeds have been aligned. These areas are called Candidate Alignment Locations (CALs), since the potential alignment of the whole read in these areas need to be carefully analyzed. The next pipeline stage consist of using another more accurate algorithm  to align the read against each of the CALs. However, it must be noted that the alignment of the read against the CAL means a huge reduction in the computational cost, compared to the alignment of the read against the whole genome.Figure In order to take full advantage of the BWT implementation described in the previous section, we have changed the HPG-Methyl pipeline, denoting this new pipeline as HPG-Methyl2. HPG-Methyl2 merges several stages into a single but more flexible stage, based on the BWT. The new stage provides considerably fewer candidate regions of the genome where each considered read can be mapped, although these regions are much more effective. As a result, the use of the SWA in the pipeline is greatly reduced, and it is used to map much shorter read segments.n seed pairs (forward and backward seeds) that cover most of the read, and they can be merged and filtered to generate new CALs. In effect, we consider that a new CAL is formed by either any seed whose length is greater than a given threshold, or by any group of seeds (two or more) whose alignment is found within a distance lower than the read length (including the length of the seeds). Figure Figure The next stage in the pipeline is the SW stage, where the SWA is used to study the alignments of the read in the CALs yielded by this stage, as in the HPG-Methyl software . HoweverHPG-Methyl2. For comparison purposes, we have also evaluated two additional tools: HPG-Methyl and Bismark. These tools were selected because they yielded the best performance at the time HPG-Methyl was evaluated [http://grch37.ensembl.org/Homo_sapiens/Info/Index)), while the latter ones have been obtained from the European Nucleotide Archive (http://www.ebi.ac.uk/ena/data/view/SRR309230 and SRR837425). All the datasets contain fixed read lengths, and we have considered datasets of different reads lengths, from 75 to 3200 nts. All the synthetic datasets contain four million reads. The performance evaluation has been carried out on the same computer platform used to evaluate the HPG-Methyl tool [http://ark.intel.com/products/63697) with 48 Gbytes of RAM. Nevertheless, the average use of memory shown by all the considered tools did not exceed 17 Gbytes of RAM. We have used the default parameter settings in the execution of the Bismark tool, other than the number of parallel execution threads. The Hpg-Methyl tools is the only tool where the optimum parameter settings are not automatically computed based on each read length, and therefore these parameters should be explicitely used in the command line according to the length of the reads in the dataset, as described in the README.TXT file . The HPG-Methyl2 tool automatically computes the optimum parameter settings for each read length, so it only needs the number of parallel threads to be used in the execution. An example execution command for each of the considered tools can be found in the “Additional file In this section, we present a comparative performance evaluation of the BWT implementation and deployment described in the previous section. We have denoted this implementation as valuated . We haveTable Table Homo sapiens. The length of the reads in each file is 75 and 100 nts, respectively. Table Also, we have tested the considered tools with real datasets  containing 16.6 million bisulfite reads coming from Finally, Table The performance evaluation results show that the new software tool achieves execution times one order of magnitude shorter for long reads, while yielding equal or better sensitivity. The strategy employed in this software can be exported not only to other methylation analysis tools, but also to DNA and RNA analysis tools. As a future work to be done, we plan to apply the same strategy of BWT deployment to other existing software tools with a similar parallel pipeline, such as the HPG Aligner , 18.Project name: HPG-Methyl2Project home page:https://github.com/grev-uv/hpg-methylOperating System: The software has been tested on Ubuntu LinuxProgramming language: CLicense: GPL v2


Central to the One Health approach and any disease eradication program is the question of whether a pathogen has a non-human reservoir. Despite well-established conceptual frameworks that define a reservoir of infection, empirical characterization of reservoirs often remains controversial, challenging and sometimes misleading. What is essentially missing are applicable requirements that standardize the use of the term ‘reservoir of infection’ across multiple disciplines. We propose an empirical framework, considering maintenance and feasible transmission of a pathogen, to standardize the acceptance of a disease reservoir across multiple disciplines. We demonstrate the intended use of these requirements by applying them to different diseases that are known to infect both humans and animals. The most applicable and accepted way to investigate and define a reservoir emphasizes the annotation of a target group , which directly or indirectly connect epidemiologically to the target  a high-genetic similarity of the pathogen found in the reservoir system, (ii) a high degree of functional similarity (infectivity and viability), and (iii) a longitudinal approach that considers the factor of time . In bacteria, investigations can be further complicated by plasmids that can be exchanged and mutated over time.53 A high amount of phylogenetic relatedness of pathogens isolated from the non-target and target populations does not provide sufficient evidence for the involvement of a pathogen and its ability to infect both groups. Importantly, DNA-based analyses only provide information on the functional potential of a pathogen and must not reflect the gene-expression within a host.54 For example, the bacterium Treponema paraluiscuniculi (which causes syphilis in rabbits), is over 99% identical on the basis of the whole genome to the human pathogen T. pallidum (which causes human treponematosis), but does not infect humans.55 As phylogenetic information fails to reflect the downstream effects of mutations, proof that a pathogen can proliferate in the potential reservoir is required.56 Information on the transcriptome and proteome of bacteria or the phenotype of viruses are necessary to see the effect of mutations on pathogen viability.57 There are different ways to test for the functional ability of a pathogen in different species. Owing to the ethical concerns, cell and tissue assays have been increasingly used in therapeutic research instead of animal models.8 Although these assays are limited in their conclusiveness, they can provide important insight into the molecular mechanisms involved. For example, the failure to infect primary tissue culture from rhesus macaques with human immunodeficiency virus 1 (HIV-1) demonstrates that non-human primates were unlikely to act as a maintenance population  and vast quantities of available data have not led to concrete applicable criteria when examining the capacity of a pathogen to be maintained in a population. Recognizing both the ethical limitations in regards to animal testing of time . Owing tpulation .58 In so1 However, only longitudinal studies with adequate sampling regimes (multiple sampling) to test for antibodies against a pathogen can provide information on the timing or frequency of infection, both of which are important for reservoir studies.59 Furthermore, cross-reactivity and erroneous assays can lead to false-positive results. For more diffuse reservoir systems, including multi-species compositions where the diversity of host susceptibility  protects against widespread infection (dilution effect),60 a longer time frame must be applied. This guarantees a more accurate understanding of the maintenance within a population .When examining pathogen maintenance, a longitudinal approach is required to consider the dynamics of a potential reservoir system, including the influence of genetic variation in any given population. Defining a population that was infected at a single time point as a maintenance population for a pathogen is based on assumptions and is therefore speculative. Sero-prevalence surveys are an attractive way to detect the presence of pathogens in a population, as it indicates that an immunocompetent subject was in contact with the pathogen.4 otherwise the non-target population remains a maintenance population with the potential to be a reservoir. Therefore, the determination of a feasible and somewhat permanent transmission route between the non-target and target populations is key to identifying a reservoir system , they may act as part of the non-target community.61 Four basic requirements need to be met to make a compelling argument for the existence of a feasible transmission route: (i) spatial (direct or indirect) and temporal connectivity between the reservoir system and the target population, (ii) pathogen involvement in this feasible transmission route, (iii) proof of viability of the pathogen during the proposed transmission route and (iv) a longitudinal approach that requires the isolation of a pathogen multiple times in a given transmission route . If the amount of viable and therefore infectious organisms is below the infectious dose, the particular transmission route is unfeasible. Without a feasible transmission route between target and non-target populations, no functional reservoir exists. Furthermore, to include all parts of a reservoir population, long-term investigations must focus on the transmission between the non-target and target groups as well as feasible transmission within the non-target community.61 Unconnected maintenance host populations may become a future reservoir through temporal shifts of the ecosystem.To prove the feasibility of a transmission route, direct or indirect spatial connectivity as well as temporal overlap between the non-target and target populations must be present. Connectivity measurements depend on the type of transmission route; for example, direct contact transmission requires overlapping territory. Computational tools can help determine the necessary overlap in a population by modeling the transmission across an affected population.201 Despite sufficient planning, the cause and effect of intervention studies are often difficult to determine64 and the removal of a pathogen from a particular ecosystem may cause unanticipated effects. A negative outcome does not necessary indicate the lack of a reservoir or transmission route.65 Instead, it can show that the intervention may have been incomplete or that the complexity of a reservoir is not entirely understood.Biological systems are dynamic and can change over time . Single 66 Furthermore, the artificial environment in a laboratory, which is often used to study the susceptibility of a species, differs substantially from a natural setting.67 The use of laboratory animals or cell- and tissue-based assays can be advantageous when studying pathogenicity, but it cannot solely contribute to the understanding of the epidemiology of a pathogen, which is largely impacted by variables such as genetic diversity, co-infection, cross-protective immunity and spatial connectivity. As a consequence, any epidemiological model requires additional information on the geographic range and the ecological landscape.68 This includes population densities and functional profiles of species that are involved in the reservoir system.69 The importance of sample size in field studies and animal experiments cannot be stressed enough as it greatly affects the efficacy of analysis, especially in reservoirs with low-frequency crossover events.Pathogens must be studied in the context of natural ecosystems. The complexity of reservoir systems increases as multiple non-target populations interact as an ecological entity, which is influenced by factors such as competition, co-existence or predation.Neither laboratory experiments, nor intervention studies, nor epidemiological models alone can provide a full understanding of a natural reservoir of infection. Only the combination of methods that are based on established and validated species-specific assays and technically sound field investigations can provide confidence that the pathogen is maintained in a non-target population and that a feasible transmission route exists. This, however, requires the political will and financial support to conduct long-term One Health studies to explore diseases in their natural context.Borrelia burgdorferi) fulfill all of the requirements proposed in this study, whereas some well-known diseases, such as Ebola, need further research until a reservoir system can be accepted (The term ‘disease reservoir’ should be used carefully and only if there is convincing evidence demonstrating the maintenance and a feasible transmission route of a particular pathogen . We propaccepted . For the


The performance of the Global Navigation Satellite System (GNSS) compass is related to the quality of carrier phase measurement. How to process the carrier phase error properly is important to improve the GNSS compass accuracy. In this work, we propose a dual frequency carrier phase error difference checking algorithm for the GNSS compass. The algorithm aims at eliminating large carrier phase error in dual frequency double differenced carrier phase measurement according to the error difference between two frequencies. The advantage of the proposed algorithm is that it does not need additional environment information and has a good performance on multiple large errors compared with previous research. The core of the proposed algorithm is removing the geographical distance from the dual frequency carrier phase measurement, then the carrier phase error is separated and detectable. We generate the Double Differenced Geometry-Free (DDGF) measurement according to the characteristic that the different frequency carrier phase measurements contain the same geometrical distance. Then, we propose the DDGF detection to detect the large carrier phase error difference between two frequencies. The theoretical performance of the proposed DDGF detection is analyzed. An open sky test, a manmade multipath test and an urban vehicle test were carried out to evaluate the performance of the proposed algorithm. The result shows that the proposed DDGF detection is able to detect large error in dual frequency carrier phase measurement by checking the error difference between two frequencies. After the DDGF detection, the accuracy of the baseline vector is improved in the GNSS compass. The Global Navigation Satellite System (GNSS) compass is an attitude indicator based on the theory of carrier phase relative positioning . It is aAnother key technique of the GNSS compass besides integer ambiguity resolution is how to improve its accuracy. It is proven that the GNSS compass accuracy is related to the carrier phase measurement quality for a certain baseline length . Most ofThe influence of the multipath is usually more severe than carrier phase noise. Currently, multipath can be mitigated using three processing strategies : (1) theThere is another type of error detection method based on Detection, Identification and Adaptation (DIA) theory. The representative method, namely Receiver Autonomous Integrity Monitoring (RAIM), is often used in civil aviation Single Point Positioning (SPP) ,24. As fThe GNSS satellite broadcasts signals in multiple frequencies. Some well-known carrier phase combinations can be generated by combining different carrier phase measurement, such as Wide Lane (WL), Narrow Lane (NL), Ionosphere Free (IF) and Geometry Free (GF) ,34. The In this paper, we propose a dual frequency carrier phase error difference checking algorithm for the GNSS compass. The algorithm is focused on detecting large carrier phase error, which cannot be eliminated by the differencing technique. By subtracting the geographical distances in the dual frequency DD carrier phase, we can obtain the Double-Differenced Geometry-Free (DDGF) measurement. As the correlated errors are nearly zero in the short baseline GNSS compass model, the DDGF measurement only contains multipath and carrier phase noise. We estimate the theoretical magnitude of the multipath and the carrier phase noise. Then, the theoretical threshold is formed. Whether the DDGF carrier phase has large multipath or carrier phase noise is detected according to the theoretical threshold. The carrier phase measurement that does not pass the DDGF detection will be eliminated by weighted estimation.The rest of this paper is organized as follows: in GNSS carrier phase relative positioning needs two receivers, respectively named “base” and “rover”. The carrier phase measurement observed by the two receivers at a certain epoch can be written as :(1)ϕb,kThe Single-Differenced (SD) measurement model can be obtained by subtracting the base receiver’s measurements from the rover receiver’s measurements, namely Equations (1) and (2).Then, choosing the e length . In GNSSA method ,37 to reOnce the integer ambiguity is resolved, the DD carrier phase becomes a highly precise measurement including geographical distance, carrier phase noise and multipath. Geographical distance is the useful information to calculate the baseline vector. Multipath and carrier phase noise are the useless components that will influence the accuracy of the baseline vector. Therefore, processing the carrier phase noise and multipath are the key to improving the positioning accuracy further.From Equation (6), it is clear that after the integer ambiguity is resolved, the DD carrier phase measurement contains the geographical distance, multipath and carrier phase noise in the GNSS compass model. Dual frequency DD carrier phase measurement has exactly the same geographical distance. We define the double-differenced geometry free (DDGF) measurement by subtracting the geographical distances in the dual frequency DD carrier phase:From Equation (8), it is clear that DDGF measurement is supposed to be zero and only contains carrier phase error. The residual error is actually the error difference between two frequencies. Based on that characteristic, we design the DDGF detection by comparing the DDGF measurement and its theoretical estimation. The theoretical magnitude of carrier phase and multipath can be estimated according to the receiver’s parameters. The thermal noise for an arctangent PLL is computed as follows ,19:(9)σThe Allan deviation oscillator phase noise of the third-order loop is :(10)σA3The motion-based phase noise includes vibration-induced oscillator phase noise, dynamic stress error and reference oscillator acceleration stress error. The multipath and motion-based carrier phase noise is relatively hard to model. It depends on the motion of the receiver and the environment. In this work, we use the empirical value 2° . Accordieviation . TherefoIf there is no large multipath or carrier phase noise, the magnitude of For GNSS relative positioning, different carrier phase measurement can be given different weighting values according to the real environment, namely the weighted estimation . The meaFrom The final product of GNSS carrier phase relative positioning is the baseline vector. The definition of the baseline vector is:The baseline vector is calculated by the DD carrier phase measurement. The relationship between the baseline vector and the DD carrier phase measurement is nonlinear. We expand the DD carrier phase using the Taylor series expansion method and reserve the first-order terms:atellite , and thej to #1, then the satellite #1 is the reference satellite. Then, the DD carrier phase vector can be written as:q is the total number of the available satellites.There are several DD carrier phase measurements of different satellites and different frequencies. We combine them as a vector. We exchange the place of the reference satellite #In a similar way, the LOS of different satellites and different frequencies can be expressed as:Then, the vector form of Equation (15) for different satellites and different frequencies can be written as:In consideration of the weighting for different carrier phase measurement, Equation (18) can be rewritten as:As the PLL thermal noise is the main error source of the carrier phase error, in the case here, there is no large carrier phase noise or multipath . In thatThe transportation matrix Then, the DD carrier phase carrier phase measurement covariance matrix According to the error theory , the optFinally, the weighted baseline vector can be calculated as Equation (27):After the baseline vector is known, the attitude can be calculated through a well-known and widely-used formula ,38.In The DDGF measurement is linear with either of the dual frequency DD carrier phase according to the first line of Equation (7). Assuming only one of the two frequencies has error, Equation (7) can be treated as the linear equation with one variable. In that case, the DDGF measurement increases as the carrier phase error grows. As shown in However, both frequencies may have large carrier phase error. Sometimes, the error in different frequencies may be the same. In that case, the difference of the dual frequency errors is close to zero. It makes the DDGF measurement below the theoretical threshold, but there may be large errors in both frequencies. Consequently, undetected error remains.We change the color in We calculate the ratio of the DDGF detection success area out of the possible dual frequency error pairs. The result of B1-B3 is 85.30%. However, this result is based on the error being evenly distributed. Usually, the carrier phase error is not evenly distributed, as it can hardly reach one cycle. According to the previous work, the GNSS measurement error can be approximately treated as a zero mean with a Gaussian distribution ,10. HencIn order to demonstrate the proposed algorithm and evaluate its performance, a series of experiments were carried out in Beijing, China, including the open sky test, manmade multipath test and urban vehicle test.In this work, we choose B1 and B3 of BDS for the open sky test because the satellite type is various in BDS, including the Medium Earth Orbit (MEO), GEosynchronous Orbit (GEO) and Inclined GeoSynchronous Orbits (IGSO) satellites. The characteristic of all types of GNSS satellites can be analyzed. Two YWELL DY-GABR042P00D antennas and a RACOBIT OEM-B41 BDS dual frequency receiver were used. The receiver (a) and the antenna (b) are shown in The data were collected at 0.1 Hz, with a five-degree cut-off elevation angle, from UTC time 08:02 to the next day 19:58, for a total of 12,930 epochs logged. From As for the IGSO and MEO satellites, the DDGF detecting results are similarly. Different from the GEO satellite, the DDGF measurement is nearly zero mean and varies greatly. It may be larger than the theoretical threshold in the case that the elevation angle is very low.The manmade multipath test is analyzed to evaluate the performance of DDGF detection in severe multipath environments. The same baseline, experiment devices and frequencies are used in the manmade multipath test compared to the open sky test. Hence, the mean value of the previous 36-h open sky test result can be used as the reference. A reflector was set to the east side of the rover antenna. The multipath environment is shown in The data were collected at 1 Hz, with a five degree cut-off elevation angle, from UTC time 23:01 to the next day 05:00 for a total of 21,580 epochs logged. The results of the DDGF detection are shown in The urban vehicle test was carried out to demonstrate the dynamic performance of the proposed algorithm. This time, GPS L1 and L2 are chosen in consideration that the satellite distribution of GPS is more suitable for blocking from all directions. Two HARXON HX-CS3601A survey antennas and NovAtel-OEM628 dual frequency receivers were used. The location of two antennas is shown in As the true baseline vector is unable to be obtained in a dynamic situation, we use the baseline length to evaluate the performance because the baseline length is unchanged no matter how the vehicle moves. Before driving, the baseline length is measured from the 10-hour static open sky average value.The driving was in Haidian District, Beijing, China. The driving route is shown in Data were collected at 1 Hz, with a five degree cut-off elevation angle, between 11:15 and 11:50, UTC time, for a total of 2592 epochs logged. In this work, we propose a dual frequency carrier phase error difference checking algorithm for the GNSS compass. The algorithm aims at eliminating large carrier phase noise and multipath error in DD carrier phase measurement. We utilize the characteristic that the different frequency carrier phase measurements contain the same geometrical distance and form the DDGF measurement. The DDGF detection is designed according to the theoretical estimation of the carrier phase error. The theoretical performance of the proposed DDGF detection is analyzed. The result shows that the detecting success ratio of all of the GNSS constellation dual frequency pairs is about three quarters in the condition that the error is zero mean Gaussian distributed.We analyze the characteristic of the DDGF measurement in different types of satellites from the open sky test. The DDGF measurement of GEO satellites is stable, but not zero mean. As for IGSO and MEO, it is nearly zero mean, but varies greatly and may be larger than the theoretical threshold in the case that the satellite elevation angle is very low. Some large errors of the baseline vector can be mitigated after the DDGF detection.The manmade multipath test is analyzed to evaluate the performance of DDGF detection in a severe multipath environment. As the location of the reflector is known, the satellites that may be suffering from the multipath severely are known. The DDGF detection result matches the anticipation. The DDGF measurement of the influenced GEO satellite is above the theoretical threshold during the whole test. The DDGF measurement of the influenced MEO satellite is much larger than the theoretical threshold when its elevation is low. As the elevation angle increases, the DDGF measurement is back to normal. After the DDGF detection, the baseline vector error is about a half of the result before DDGF detection compared with the long-term open sky reference baseline vector.The urban vehicle test was carried out to evaluate the dynamic performance of the proposed algorithm. We analyze the baseline length because the baseline length is unchanged no matter how the vehicle moves. The 10-h static open sky average value is treated as the reference. The results indicate that the proposed algorithm improves both the mean value and the standard deviation performance in the urban vehicle test.Based on these results, the proposed DDGF detection has the ability to detect large error in dual frequency carrier phase measurement without the help of prior environment information. After the DDGF detection, the accuracy of the baseline vector is improved in the GNSS compass.