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BACKGROUND AND OBJECTIVE: To evaluate coronavirus disease 2019 (COVID-19) cases as of February 1, 2021 and the proportion of ophthalmologists in the United States older than age 60 years to provide a framework for successful vaccine distribution for the ophthalmology workforce. PATIENTS AND METHODS: The Association of American Medical Colleges ophthalmologist workforce dataset (from 2019) for each state was combined with John Hopkins University's COVID-19 tracking data to determine exposure risk for ophthalmologists, especially those older than age 60 years. RESULTS: Of the 18,915 practicing ophthalmologists in the US, 37.6% are older than age 60 years. North Dakota (48.4%), Connecticut (46.8%), and Maine (46.7%) have the highest percentages. South Dakota (9,567), Utah (7,559), and Idaho (7,411) currently have the highest COVID-19 exposure burden per ophthalmologist older than age 60 years as of February 1, 2021. CONCLUSION: Care must be taken to distribute the COVID-19 vaccine in a safe and proactive manner to ophthalmologists that face high exposure risk, both to ensure physician safety and ensure adequate care for the population they serve. [ Ophthalmic Surg Lasers Imaging Retina . 2021;52:556–559.]

Animals continuously interact with their environment through behavioral decisions, rendering the appropriate choice of movement speed and directionality an important phenotypic trait. Anthropogenic activities may alter animal behavior, including movement. A detailed understanding of movement decisions is therefore of great relevance for science and conservation alike. The study of movement decisions in relation to environmental and seasonal cues requires continuous observation of movement behavior, recently made possible by high‐resolution telemetry. We studied movement traits of 13 capercaillie (Tetrao urogallus), a mainly ground‐moving forest bird species of conservation interest, over two summer seasons in a Swedish windfarm using high‐resolution GPS tracking data (5‐min sampling interval). We filtered and removed unreliable movement steps using accelerometer data and step characteristics. We explored variation in movement speed and directionality in relation to environmental and seasonal covariates using generalized additive mixed models (GAMMs). We found evidence for clear daily and seasonal variation in speed and directionality of movement that reflected behavioral adjustments to biological and environmental seasonality. Capercaillie moved slower when more turbines were visible and faster close to turbine access roads. Movement speed and directionality were highest on open bogs, lowest on recent clear‐cuts (, We analyzed movement traits (speed and directionality) of capercaillie, a mainly ground‐dwelling forest bird, in a Swedish wind farm. We found evidence for clear daily and seasonal variation in movement traits that reflected behavioral adjustments to biological and environmental seasonality. Capercaillie movement behavior was also related to wind turbine effects, mainly turbine visibility, and habitat characteristics.

Monitoring the use of anchored fish aggregating devices (AFADs) is essential for effective fisheries management. However, detecting the use of these devices is a significant challenge for fisheries management in Indonesia. These devices are continually deployed at large scales, due to large numbers of users and high failure rates, increasing the difficulty of monitoring AFADs. To address this challenge, tracking devices were attached to 34 handline fishing vessels in Indonesia over a month period each. Given there are an estimated 10,000–50,000 unlicensed AFADs in operation, Indonesian fishing grounds provided an ideal case study location to evaluate whether we could apply spatial modeling approaches to detect AFAD usage and fish catch success. We performed a spatial cluster analysis on tracking data to identify fishing grounds and determine whether AFADs were in use. Interviews with fishers were undertaken to validate these findings. We detected 139 possible AFADs, of which 72 were positively classified as AFADs. Our approach enabled us to estimate AFAD use and sharing by vessels, predict catches, and infer AFAD lifetimes. Key implications from our study include the potential to estimate AFAD densities and deployment rates, and thus compliance with Indonesia regulations, based on vessel tracking data.

We propose the recursive inverse kinematics (RIK) algorithm to compute joint angles of a humanoid robot using skeleton tracking data. Recursive inverse kinematics calculates the angles recursively from the base body (torso) to the tree-end body (hand or foot or head) along each branch of the humanoid robot based on the multibody analysis approach. To validate the RIK algorithm, experiments with two specific human motions were conducted in an indoor environment with the Azure Kinect depth camera. The joint angles obtained from RIK with the skeleton data of human motion were compared to those from RIK with the corresponding virtual skeleton data of the RecurDyn virtual humanoid robot model. Additionally, similarity indices were defined to evaluate how similar the movements of the virtual humanoid robot from the RIK are to those of human. The obtained similarity indices showed that the posture of the virtual humanoid robot model using the RIK is close to the human posture.

Background and Aims: Modern stereotactic body radiotherapy (SBRT) techniques and systems that use online image guidance offer frameless radiotherapy of spinal tumors and the ability to control intrafraction motion during treatment. These systems allow precise alignment of the patient during the entire treatment session and react immediately to random changes in this alignment. Online tracking data provide information about intrafractional changes, and this information can be useful for designing treatment strategies even if online tracking is not being used. The present study evaluated spine motion during SBRT treatment to assess the risk of verifying patient alignment only prior to starting treatment. Methods: This study included 123 patients treated with spine SBRT. We analyzed different locations within the spine using system log files generated during treatment, which contain information about differences in the pretreatment reference spine positions by CT versus positions during SBRT treatment. The mean spine motion and intra/interfraction motion was evaluated. We defined and assessed the spine stability and spine significant shifts (SSHs) during treatment. Results: We analyzed 462 fractions. For the cervical (C) spine, the greatest shifts were in the anterior-posterior (AP) direction (2.48 mm) and in pitch rotation (1.75 deg). The thoracic (Th) spine showed the biggest shift in the AP direction (3.68 mm) and in roll rotation (1.66 deg). For the lumbar-sacral (LS) spine, the biggest shift was found for left-right (LR) translation (3.81 mm) and roll rotation (3.67 deg). No C spine case exceeded 1 mm/1 deg for interfraction variability, but 7 of 54 Th spine cases exceeded 1 mm interfraction variability for translations (maximum value, 2.5 mm in the AP direction). The interfraction variability for translations exceeded 1 mm in 2 of 24 LS spine cases (maximum value, 1.7 mm in the LR direction). Only 13% of cases had no SSHs. The mean times to SSH were 6.5±3.9 min, 8.1±5.9 min, and 8.8±7.1 min for the C, Th, and LS spine, respectively, and the mean recorded SSH values were 1.6±0.66, 1.43±0.33, and 1.46±0.47 mm/deg, respectively. Conclusion: Positional tracking during spine SBRT treatments revealed low mean translational and rotational shifts. Patient immobilization did not improve spine shifts compared with our results for the Th and LS spine without immobilization. For the most precise spine SBRT, we recommend checking the patient's position during treatment.

Background: Go Baby Go is a community program that provides modified ride-on cars to young children with disabilities. Aims: (1) To describe the real world modified ride-on car usage of young children with disabilities; (2) To compare subjectively reported modified ride-on car usage recorded by parents with objectively reported usage based on electronic tracking data. Methods: 14 young children (1–3 years old) with disabilities used a modified ride-on car for three months. Results: On average, parent-reported activity log data indicated that children used the modified ride-on car for 17.8 minutes per session (SD = 9.9) and 195.1 total minutes (SD = 234.8) over three months. Objective tracking data indicated 16.5 minutes per session (SD = 8.6) and 171.4 total minutes (SD = 206.1) over three months. No significant difference of modified ride-on car usage was found between parent-reported activity log data and objective tracking; yet, the mean absolute difference between tracking methods was 96 minutes (SD = 8.6) and suggests over- or under-reporting of families. Children used the modified ride-on car more in the first half compared to the second half of the three-month period (p Conclusions: This study may inform future research studies and local chapters of the Go Baby Go community program.

BACKGROUND: Recruitment to randomised clinical trials can be challenging and slow recruitment has serious consequences. This study aimed to summarise and reflect on the challenges in enrolling young children to a multidrug-resistant TB (MDR-TB) prevention trial in South Africa.METHODS: Recruitment to the Tuberculosis Child Multidrug-resistant Preventive Therapy Trial (TB-CHAMP) was tracked using an electronic recruiting platform, which was used to generate a recruiting flow diagram. Structured personnel questionnaires, meeting minutes and workshop notes were thematically analysed to elucidate barriers and solutions.RESULT: Of 3,682 (85.3%) adult rifampicin (RIF) resistant index cases with pre-screening outcomes, 1597 (43.4%) reported having no children under 5 years in the household and 562 (15.3%) were RIF-monoresistant. More than nine index cases were pre-screened for each child enrolled. Numerous barriers to recruitment were identified. Thorough recruitment planning, customised tracking data systems, a dedicated recruiting team with strong leadership, adequate resources to recruit across large geographic areas, and excellent relationships with routine TB services emerged as key factors to ensure successful recruitment.CONCLUSION: Recruitment of children into MDR-TB prevention trials can be difficult. Several MDR-TB prevention trials are underway, and lessons learnt from TB-CHAMP will be relevant to these and other TB prevention studies.

Long-term exposure to childhood abuse and occurrence of mental illness are positively correlated. Using long-term tracking data in Korea, we identified the characteristics of children and adolescents who experienced abuse and impact thereof on their psychopathology. Using the Korea Welfare Panel data, 354 teenagers in grades 4–6 of elementary school participated, were assessed at baseline, and monitored 3 years later. They were categorized into Never, Occurrence, Continuation, and Discontinuation groups according to changes in the abuse experienced. Psychopathology was evaluated using K-CBCL. Childhood abuse experience significantly affected psychopathology. At the baseline, the Continuation and Discontinuation groups had a higher severity of psychopathology than the Never group. Psychopathology at the baseline was associated with whether the patient experienced abuse that year. In the follow-up observation, the risk of psychopathology in the Occurrence and Continuation groups was higher than that in the Never group. The Discontinuation group had decreased psychopathology, which was not clinically significant in the follow-up observation (INT aRR = 2.09, 95% CI 0.61–7.13, EXT aRR = 4.23, 95% CI 1.12–16.07). Stopping abuse in late childhood reduces adolescents’ psychopathology in the long term, meaning they can recover their normal developmental trajectory according to risk groups and provide effective interventions including discontinuation of abuse.

Study question Is the emotional experience of patients during IVF different since the start of the global Covid-19 pandemic? Summary answer Tracking data since re-opening demonstrated patients lower positive challenge emotions but no significant change in harm, threat, or stress. What is known already Covid-19 caused widespread shutdown of fertility centres, including in the UK, when the HFEA mandated closure from March until May 2020. Research shows clinic closure and an uncertain future were a significant psychological burden for patients anticipating treatment. However, emotional experiences before, during and after closure have not yet been compared, which is the aim of the study. Study design, size, duration Retrospective single-centre analysis of anonymised emotional tracking data entered by 707 patients using the MediEmo smartphone app alongside their IVF cycle, from May 2017-September 2020. MediEmo includes medication timeline/ notifications, coping tools and emotional tracking. Patients rate 2 questions daily in each emotion domain (challenge, threat, harm, e.g. ‘I am feeling tense’) on a 0-3 scale and indicate coping ability (‘I am unable to cope with the stress I am experiencing’) on a binary scale. Participants/materials, setting, methods Egg donor, recipient and fertility preservation cycles were excluded. First, mood scores were analysed by 2020 month of entry to capture the emotional impact of closure. Second, “Pre-Covid” (May 2017-Feb 2020) and “After Re-opening” (May 2020–Sept 2020) emotional experiences were compared, using student t-tests. Mean and standard deviation of scores in each mood domain entered on each cycle day were calculated, centred on luteal day 0/ egg collection, from cycle day -14 to + 14. Main results and the role of chance Graphical presentation of emotional data by month clearly demonstrates the significant increase in threat, harm and stress emotions and reduced positive emotions experienced immediately prior to and during mandatory clinic closure. Of patients entering emotional data during closure in March/April 2020, 40% (14/35) stated they felt unable to cope with the stress they were currently experiencing. From May 2020 after the clinic reopened, analysis of in-cycle emotional tracking data showed there are no significant differences in harm or threat emotion levels or numbers reporting intolerable stress during IVF, compared to cycles pre-pandemic (May17-Feb 2020). Patients undertaking IVF cycles since closure are logging lower challenge scores (confident, encouraged, positive, hopeful), demonstrating less optimism, particularly in the ‘two-week wait’ phase of the cycle. The mean (s.d) of challenge scores pre-Covid was 1.50 (1.07), compared to 1.38 (1.04) after re-opening, p = 0.00085. The women who had treatment cycles post re-opening from May 2020 onwards were older (33.4(5.2) vs 32.6(4.4)), which may reflect clinical treatment prioritisation decisions. There was no significant differences in number of eggs collected (mean(s.d) Pre-Covid 12.08 (8.0) vs After re-opening 11.83 (9.4), p = 0.84) or live birth/ ongoing pregnancy rates for undelivered pregnancies (p = 0.69) between the groups. Limitations, reasons for caution Emotional data was only available for those who chose to use MediEmo, entered emotional tracking data and who gave consent for use of their clinical data in research. As such, this analysis may not fully reflect all patients’ experiences. Most of the available data were entered prior to the pandemic. Wider implications of the findings For Covid-19 safety reasons, patients currently have less in-person staff contact when undertaking IVF. The findings reassuringly suggest emotional wellbeing was not markedly different in most domains. However, daily ratings did show the emotional fall-out of clinic closures which for most threatened attainability of parenthood goals (e.g., less hope). Trial registration number Not applicable

The primary aim of this study was to determine the relationship between a team numerical advantage during structured phases of play and match event outcomes in professional Australian football. The secondary aim was to quantify how players occupy different sub-areas of the playing field in match play, while accounting for match phase and ball location. Spatiotemporal player tracking data and play-by-play event data from professional players and teams were collected from the 2019 Australian Football League season played at a single stadium. Logistic regression analysed the relationship between total players and team numerical advantage during clearances and inside 50’s. Total players and team numerical advantage were also quantified continuously throughout a match, which were separated into three match phases (offence, defence, and stoppage) and four field positions (defensive 50, defensive midfield, attacking midfield, and forward 50). Results identified an increased team numerical advantage produced a greater likelihood of gaining possession from clearances or generating a score from inside 50’s. Although, an increased number of total players inside 50 was likely associated with a concomitant decrease in the probability of scoring, irrespective of a team numerical advantage. Teams were largely outnumbered when the ball was in their forward 50 but attained a numerical advantage when the ball was in the defensive 50.

Study question Is the emotional experience different in FET and stimulated IUI cycles compared to IVF cycles? Summary answer Emotional tracking data demonstrated cautious optimism and lower harm emotions in IUI, but FET cycles are associated with higher harm emotions than fresh IVF. What is known already It is sometimes claimed on clinic websites and by advocates for elective freeze all that FET cycles are inherently less stressful. However, little research evaluates the emotional difference between fresh and frozen cycles and the assumed emotional ease of FET may reflect clinician interpretation/bias rather than patient’s lived experiences. Many undertaking FET will have experienced disappointment in a fresh cycle and with increasing cycles comes increased cost. IUI treatment is perceived as less physically and emotionally intense, but studies have shown increased depression levels after a failed IUI cycle and high drop-out. Study design, size, duration Retrospective single-centre analysis of anonymised emotional tracking data entered by 707 patients using MediEmo app alongside IVF, 104 during stimulated IUI and 65 during medicated FET from May 2017-September 2020. MediEmo includes medication timeline/ notifications, coping tools and emotional tracking. Patients rate 2 questions daily in each emotion domain (challenge, threat, harm, e.g. ‘I am feeling tense’) on a 0-3 scale and indicate coping ability (‘I am unable to cope with the stress I’m experiencing’). Participants/materials, setting, methods Egg donor, recipient and fertility preservation cycles were excluded. Mean and standard deviation of scores in each mood domain entered per cycle day were calculated, centred on luteal day 0/ egg collection, from cycle day +/-14. Between group analysis performed using one-way analysis of variance (ANOVA) is presented here. Time series analysis, graphical presentation of emotions by cycle day and analysis of cycles resulting in live birth or return for further treatment will be presented. Main results and the role of chance Analysis of emotional tracking data demonstrated patients experience higher levels of positive challenge emotions (confident/encouraged/hopeful/positive) during FET and IUI cycles than fresh IVF: mean(s.d) score FET 1.64(1.1), IUI 1.74(0.89), IVF 1.48(1.06) (ANOVA p Threat emotions (worried/nervous/anxious/tense) are significantly lower in FET compared to IVF and IUI cycles: FET mean 0.67(0.91), IUI 0.97(0.90), IVF 0.87(0.91), (ANOVA p However, the harm emotions (sad/discouraged/disappointed) experienced by patients are significantly higher in FET, mean 0.62(0.89) compared to IVF 0.50(0.81), which are higher than IUI cycles, 0.36(0.68), (ANOVA p As this is retrospective observational data, there are differences between groups in addition to treatment modality, e.g. mean patient ages in the FET and IUI groups were older than those entering data during IVF; FET 34.2(4.09), IUI 33.9(5.2), IVF 32.6(4.47). However, age was not correlated with levels of challenge emotions, suggesting assumptions that patient emotions, e.g. hopefulness, are closely linked to objective prognosis may be flawed. Limitations, reasons for caution Emotional data was only available for those who chose to use MediEmo, entered emotional tracking data and who gave consent for use of data in research. As such, this analysis may not fully reflect all patients’ experiences. However, these limitations apply to all groups and should not prevent useful comparison. Wider implications of the findings Patients have less contact with clinic staff during FET or IUI than fresh IVF cycles. Fertility staff need to ensure availability of support during all treatment cycles and be empathic, particularly for those embarking on FET, who may still be coming to terms with a failed fresh transfer cycle. Trial registration number Not applicable

Background The interest in intra-cardiac blood flow analysis is rapidly growing, and it has encouraged the development of different non-invasive imaging techniques. Among these, Vector Flow Mapping (VFM), combing Color-Doppler imaging and speckle tracking data, seems to be a promising approach, feasible in adult and children population. Aim of the review The aim of this review is to give a historical perspective on the development of VFM method and a summary of the current algorithms and parameters potentially evaluable. Then, we will present the current state-of-the-art of VFM with an overview of clinical studies and applications of this technique.

In this work, we aim to construct a new behavior analysis method by using machine learning. We used two cameras to capture three-dimensional (3D) tracking data of zebrafish, which were analyzed using fuzzy adaptive resonance theory (FuzzyART), a type of machine learning algorithm, to identify specific behavioral features. The method was tested based on an experiment in which electric shocks were delivered to zebrafish and zebrafish swimming was tracked in 3D simultaneously to find electric shock-associated behaviors. By processing the obtained data with FuzzyART, we discovered that distinguishing behaviors were statistically linked to the electric shock based on the machine learning algorithm. Moreover, our system could accept user-supplied data for detection and quantitative analysis of the behavior features, such as the behavior features defined by the 3D tracking analysis above. This system could be applied to discover new distinct behavior features in mutant zebrafish and used for drug administration screening and cognitive ability tests of zebrafish in the future.

Purpose In this study we calculate composite dose delivered to the prostate by using the Calypso tracking ‐data‐ stream acquired during patient treatment in our clinic. We evaluate the composite distributions under multiple simulated Calypso tolerance level schemes and then recommend a tolerance level. Materials and methods Seven Calypso‐localized prostate cancer patients treated in our clinic were selected for retrospective analysis. Two different IMRT treatment plans, with prostate PTV margins of 5 and 3 mm respectively, were computed for each patient. A delivered composite dose distribution was computed from Calypso tracking data for each plan. Additionally, we explored the dosimetric implications for “worst case” scenarios by assuming that the prostate position was located at one of the eight extreme corners of a 3 or 5 mm “box.” To characterize plan quality under each of the studied scenarios, we recorded the maximum, mean, and minimum doses and volumetric coverage for prostate, PTV, bladder, and rectum. Results and discussions Calculated composite dose distributions were very similar to the original plan for all patients. The difference in maximum, mean, and minimum doses as well as volumetric coverage for the prostate, PTV, bladder, and rectum were all

Epidemics are regularly associated with reports of superspreading: single individuals infecting many others. How do we determine if such events are due to people inherently being biological superspreaders or simply due to random chance? We present an analytically solvable model for airborne diseases which reveal the spreading statistics of epidemics in socio-spatial heterogeneous spaces and provide a baseline to which data may be compared. In contrast to classical SIR models, we explicitly model social events where airborne pathogen transmission allows a single individual to infect many simultaneously, a key feature that generates distinctive output statistics. We find that diseases that have a short duration of high infectiousness can give extreme statistics such as 20% infecting more than 80%, depending on the socio-spatial heterogeneity. Quantifying this by a distribution over sizes of social gatherings, tracking data of social proximity for university students suggest that this can be a approximated by a power law. Finally, we study mitigation efforts applied to our model. We find that the effect of banning large gatherings works equally well for diseases with any duration of infectiousness, but depends strongly on socio-spatial heterogeneity.

Background Secure patient portals are widely available, and patients use them to view their electronic health records, including their clinical notes. We conducted experiments asking them to cogenerate notes with their clinicians, an intervention called OurNotes. Objective This study aims to assess patient and provider experiences and attitudes after 12 months of a pilot intervention. Methods Before scheduled primary care visits, patients were asked to submit a word-constrained, unstructured interval history and an agenda for what they would like to discuss at the visit. Using site-specific methods, their providers were invited to incorporate the submissions into notes documenting the visits. Sites served urban, suburban, and rural patients in primary care practices in 4 academic health centers in Boston (Massachusetts), Lebanon (New Hampshire), Denver (Colorado), and Seattle (Washington). Each practice offered electronic access to visit notes (open notes) to its patients for several years. A mixed methods evaluation used tracking data and electronic survey responses from patients and clinicians. Participants were 174 providers and 1962 patients who submitted at least 1 previsit form. We asked providers about the usefulness of the submissions, effects on workflow, and ideas for the future. We asked patients about difficulties and benefits of providing the requested information and ideas for future improvements. Results Forms were submitted before 9.15% (5365/58,652) eligible visits, and 43.7% (76/174) providers and 26.76% (525/1962) patients responded to the postintervention evaluation surveys; 74 providers and 321 patients remembered receiving and completing the forms and answered the survey questions. Most clinicians thought interim patient histories (69/74, 93%) and patient agendas (72/74, 97%) as good ideas, 70% (52/74) usually or always incorporated them into visit notes, 54% (40/74) reported no change in visit length, and 35% (26/74) thought they saved time. Their most common suggestions related to improving notifications when patient forms were received, making it easier to find the form and insert it into the note, and educating patients about how best to prepare their submissions. Patient respondents were generally well educated, most found the history (259/321, 80.7%) and agenda (286/321, 89.1%) questions not difficult to answer; more than 92.2% (296/321) thought sending answers before the visit a good idea; 68.8% (221/321) thought the questions helped them prepare for the visit. Common suggestions by patients included learning to write better answers and wanting to know that their submissions were read by their clinicians. At the end of the pilot, all participating providers chose to continue the OurNotes previsit form, and sites considered expanding the intervention to more clinicians and adapting it for telemedicine visits. Conclusions OurNotes interests patients, and providers experience it as a positive intervention. Participation by patients, care partners, clinicians, and electronic health record experts will facilitate further development.

Purpose Patient decision aids (PtDAs) have been reported to have a positive influence on patients making a health care decision in trials. Nevertheless, post-trial implementation is poor. The aim of this study is to explore patient, clinician, and organizational success factors for implementing a PtDA designed for breast cancer patients, facing a decision on their radiation treatment. Methods We performed a process evaluation within a multi-center pre- and post-implementation trial. The PtDA was incorporated as much as possible in the logistics of 13 participating centers. Tracking data were collected on PtDA use. Process characteristics were recorded by both clinicians and patients. A logistic regression method was applied to investigate which process characteristics were significantly related to the probability that patients logged in to the PtDA. Results 189 patients received the PtDA of whom140 (77%) used the PtDA. If patients received the link via the surgery department they were more likely to use the PtDA (OR 9.77 (1.28–74.51)), compared to patients that received the link via the radiation oncology department. If the report of the multidisciplinary team stated that radiation treatment “had to be discussed with the patient”, patients were more likely to use the PtDA (OR 2.29 (1.12–4.71)). Educational level was not related to the probability of PtDA use. Conclusions We accomplished a high level of PtDA use. Patients were more likely to use the PtDA if they received the link via the surgery department and if “to be discussed with the patient” was written in the multidisciplinary team report.

Incontinence patients suffering from neurogenic bladder dysfunction lack information about the filling level of their urinary bladder. A real-time prediction of the filling level of their bladder could support them managing their daily routines. In this study, we developed a system that predicts the bladder filling level based on user-tracked fluid intake. The system collects and analyzes the data to predict the current filling level of the bladder. Displayed in an app, users can optimize their micturition frequency receiving an alert when a critical level is reached. In the same way users can compare the predicted- and their target filling level.

Aiming at the problem of local optimization caused by too high pheromone concentration of ant colony algorithm, an improved ant colony algorithm based on chaos perturbation is proposed to improve the processing speed of target tracking data association. According to the characteristics of the multi-objective data association problem, the problem is transformed into a combinatorial optimization problem, and an adaptive chaos mechanism is introduced to establish a data association model. Experiments show the feasibility and effectiveness of the improved ant colony algorithm, which improves the operation speed while ensuring accuracy, reduces the blindness of ant colony search, improves the search efficiency of the algorithm, and avoids the ant colony algorithm falling into the local optimal.

Rationale and Objectives Quantify changes in total and by-subspecialty radiology workload due to deferring nonurgent services during the initial COVID-19 pandemic, and describe operational strategies implemented due to shifts in priority. Materials and Methods This retrospective, Institutional Review Board-exempt, study was performed between February 3, 2020 and April 19, 2020 at a large academic medical center. During March 9–15 (intervention period), nonurgent outpatient service deferments began. Five-week periods pre- (baseline) and postintervention (COVID) were defined. Primary outcomes were radiology volume (reports per day) overall and in 11 subspecialty divisions. Linear regression assessed relationship between baseline vs. COVID volumes stratified by division. Secondary outcomes included changes in relative value units (RVUs), inpatient and outpatient volumes. Results There were 62,791 baseline reports vs. 23,369 during COVID; a 60% overall precipitous volume decrease (p < 0.001). Mean volume decrease pre- and during-COVID was significant (p < 0.001) amongst all individual divisions. Mean volume decrease differed amongst divisions: Interventional Radiology experienced least disruption (29% volume decrease), 7 divisions experienced 40%–60% decreases, and Musculoskeletal, Breast, and Cardiovascular imaging experienced >75% volume decrease. Total RVUs decreased 60% (71,186 baseline; 28,476 COVID). Both outpatient and inpatient report volumes decreased; 72% (41,115 baseline; 11,326 COVID) and 43% (12,626 baseline vs. 6,845 COVID), respectively. In labor pool tracking data, 21.8% (162/744) total radiology employees were reassigned to other hospital duties during the intervention period. Conclusion Precipitous radiology workload reductions impacted subspecialty divisions with marked variation. Data-driven operational decisions during COVID-19 assisted workflow and staffing assignment changes. Ongoing adjustments will be needed as healthcare systems transition operations to a “new normal.”

BackgroundMalaria incidence has plateaued in Sub-Saharan Africa despite Seasonal Malaria Chemoprevention’s introduction. Community health workers use a door-to-door delivery strategy to treat children with SMC drugs, but for SMC to be as effective as in clinical trials, coverage must be high over successive seasons.MethodsWe developed and used a microplanning model that ‘utilizes raster to estimate population size, generates optimal households visit itinerary, and quantifies SMC coverage based on CHWs’ time investment for treatment and walking. CHWs’ performance under current SMC deployment mode was assessed using CHWs’ tracking data and compared to microplanning in villages with varying demographics and geographies.ResultsEstimates showed that microplanning significantly reduces CHWs’ walking distance by 25%, increases the number of visited households by 36% (p < 0.001) and increases SMC coverage by 21% from 37.3% under current SMC deployment mode up to 58.3% under microplanning (p < 0.001). Optimal visit itinerary alone increased SMC coverage up to 100% in small villages whereas in larger or hard-to-reach villages, filling the gap additionally needed an optimization of the CHW ratio.ConclusionWe estimate that for a pair of CHWs, the daily optimal number of visited children (assuming 8.5mn of treatment duration per child) and walking distance should not exceed 45 and 5km respectively. Our work contributes to extend SMC coverage by 21-63% and may have broader applicability for other community health programs.

Background: The current COVID-19 pandemic has raised a major challenge to healthcare systems Deployment of telehealth solutions can help maintaining continuity of care while limiting pts' and healthcare workers’ exposure with the virus In this context, Gustave Roussy Cancer Institute has implemented a pts reported outcome platform (CAPRI-COVID) to improve monitoring and effective management of COVID-19 positive pts with cancer Methods: CAPRI-COVID consists in a mobile application (CAPRI App) and a telephone platform with a dedicated call number, the entire procedure being managed by four NNs After an initial assessment by the NNs, remote monitoring of 6 COVID-related symptoms were collected daily, either by the patient via the CAPRI App or by NNs during a phone call In case of worsening or emerging symptoms, an automated alert was sent to the platform;NN assessed the clinical condition and could ask for a medical advice if necessary The monitoring period was 14 days (with at least 2 days with complete regression of symptoms) Each intervention performed by NNs was tracked on the platform, as well as pts-reported data This analysis presents the data collected via the platform from March 23 to May 4 2020 Results: Overall, 116 COVID-positive pts have completed the monitoring period (median age: 58 5 years, 21-90;56 9% female) 54 3% were monitored after hospitalization for COVID-19, 37 1% after RT-PCR screening (symptomatic pts) and 8 6% for systematic screening prior to surgery There were no deaths or admissions to intensive care unit 7 8% of pts were hospitalized (excluding scheduled hospitalization) NNs conducted an average of 9 9 calls per patient Of 53 events requiring a medical opinion, 50 9% resulted in a visit to the emergency room 41 4% of pts downloaded the CAPRI App, and completed the tracking data on average 1 1 times per day Conclusions: CAPRI-COVID enabled to keep the majority of pts at home, and helped to ensure secure pts’ pathways during this epidemic NNs play an essential role in addition with the use of CAPRI App which helped limiting phone calls and focusing on the management of complex pts Ongoing analyses are exploring actions of NNs and pts’ experience Legal entity responsible for the study: Gustave Roussy Funding: Has not received any funding Disclosure: O Mir: Honoraria (self), Travel/Accommodation/Expenses: Amgen;Honoraria (self), Honoraria (institution): AstraZeneca;Honoraria (self), Research grant/Funding (institution): Bayer;Honoraria (institution), Advisory/Consultancy, Research grant/Funding (institution): Blueprint Medicines;Honoraria (self): Bristol-Myers Squibb;Honoraria (self), Speaker Bureau/Expert testimony, Research grant/Funding (institution): Eli Lilly;Honoraria (self), Honoraria (institution), Advisory/Consultancy, Shareholder/Stockholder/Stock options: Ipsen;Honoraria (self): Lundbeck;Honoraria (self): MSD;Honoraria (self), Honoraria (institution): Novartis;Honoraria (self), Honoraria (institution), Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Pfizer;Honoraria (self), Honoraria (institution), Speaker Bureau/Expert testimony, Travel/Accommodation/Expenses: Roche;Honoraria (self), Speaker Bureau/Expert testimony: Servier;Honoraria (self): Vifor Pharma;Shareholder/Stockholder/Stock options: Amplitude Surgical;Honoraria (self), Shareholder/Stockholder/Stock options: Transgene;Honoraria (institution): PharmaMar F Scotte: Honoraria (self): CIO Roche;Honoraria (self): MSD;Honoraria (self): Pierre fabre Oncology;Honoraria (self): Leo Pharma;Honoraria (self): BMS;Honoraria (self): Pfizer;Honoraria (self): Mundi Pharma;Honoraria (self): Mylan All other authors have declared no conflicts of interest

Municipalities around the globe are increasingly adopting and integrating sustainability goals into their service functions. As with many public programs, local sustainability initiatives benefit from regular and systematic assessment aimed at determining the extent to which efforts are achieving their performance goals. However, there currently is little understanding of how local governments are collecting and tracking data on their sustainability-related performance and to what extent they integrate its lessons into their sustainability management practice. This study helps fill this gap by investigating U.S. local governments’ sustainability performance management systems and provides empirical evidence on some of their key institutional and system characteristics. Our findings indicate that a significant number of U.S. local governments are engaged in sustainability performance assessment, but they vary in their ability to establish appropriate indicators as well as supporting mechanisms, indicating significant room for improvement in local sustainability performance management.

Background Self-regulation for weight loss requires regular self-monitoring of weight, but the frequency of weight tracking commonly declines over time. Objective This study aimed to investigate whether it is a decline in weight loss or a drop in motivation to lose weight (using physical activity tracking as a proxy) that may be prompting a stop in weight monitoring. Methods We analyzed weight and physical activity data from 1605 Withings Health Mate app users, who had set a weight loss goal and stopped tracking their weight for at least six weeks after a minimum of 16 weeks of continuous tracking. Mixed effects models compared weight change, average daily steps, and physical activity tracking frequency between a 4-week period of continuous tracking and a 4-week period preceding the stop in weight tracking. Additional mixed effects models investigated subsequent changes in physical activity data during 4 weeks of the 6-week long stop in weight tracking. Results People lost weight during continuous tracking (mean −0.47 kg, SD 1.73) but gained weight preceding the stop in weight tracking (mean 0.25 kg, SD 1.62; difference 0.71 kg; 95% CI 0.60 to 0.81). Average daily steps (beta=−220 daily steps per time period; 95% CI −320 to −120) and physical activity tracking frequency (beta=−3.4 days per time period; 95% CI −3.8 to −3.1) significantly declined from the continuous tracking to the pre-stop period. From pre-stop to post-stop, physical activity tracking frequency further decreased (beta=−6.6 days per time period; 95% CI −7.12 to −6.16), whereas daily step count on the day’s activity was measured increased (beta=110 daily steps per time period; 95% CI 50 to 170). Conclusions In the weeks before people stop tracking their weight, their physical activity and physical activity monitoring frequency decline. At the same time, weight increases, suggesting that declining motivation for weight control and difficulties with making use of negative weight feedback might explain why people stop tracking their weight. The increase in daily steps but decrease in physical activity tracking frequency post-stop might result from selective measurement of more active days.

This study integrates the daily intercity migration data with the classic Susceptible-Exposed-Infected-Removed (SEIR) model to construct a new model suitable for describing the dynamics of epidemic spreading of Coronavirus Disease 2019 (COVID-19) in China. Daily intercity migration data for 367 cities in China are collected from Baidu Migration, a mobile-app based human migration tracking data system. Historical data of infected, recovered and death cases from official source are used for model fitting. The set of model parameters obtained from best data fitting using a constrained nonlinear optimisation procedure is used for estimation of the dynamics of epidemic spreading in the coming months. Our results show that the number of infections in most cities in China will peak between mid February to early March 2020, with about 0.8%, less than 0.1% and less than 0.01% of the population eventually infected in Wuhan, Hubei Province and the rest of China, respectively. Moreover, for most cities outside and within Hubei Province (except Wuhan), the total number of infected individuals is expected to be less than 300 and 4000, respectively. Funding Statement: This work was supported by National Science Foundation of China Project 61703355, Guangdong Youth University Innovative Talents Project 2016KQNCX223, and City University of Hong Kong under Special Fund 9380114. Declaration of Interests: None.

We analyze the effect of social distancing related to COVID-19 on domestic violence incidents in the U S using novel daily mobile device tracking data, the tim

Seaborne trade continues to grow and is an important component of the global economy. Threats from shipping to marine ecosystems include oil spills and other water pollution, air pollution, anchor scouring, biological invasions, container loss, chronic noise, and collisions between ships and large whales. Shipping and its associated threats can be influenced by a suite of regulations and economic events. The dynamic nature of ship traffic can be characterized using ship tracking data from automatic identification system (AIS) technology. These data enhance our ability to analyze the ecological threats from commercial shipping as a component of spatially explicit risk assessments. We explore ship traffic variability using a case study in waters off California. AIS data from 2008 to 2015 were used to evaluate the role of vessel emission regulations and economic events on vessel routes and speeds. We document vessels navigating around emission control areas (ECAs) or reducing speed when traveling through them. Large freight vessels decreased speeds from 2008 to 2015 by about 3–6 knots in many areas, with lowered speeds observed in areas of both heavy and sparse vessel use. The timing and location of the speed reductions appear to be most influenced by state and international clean fuel standards, which required the use of more costly fuels. Therefore, the speed reductions may have provided a more cost-effective means of travel. We also found temporary speed increases off southern California when vessels used longer routes to avoid traveling through an ECA. We conclude that the establishment of ECAs had a profound influence on vessel routes and speeds, likely due to the higher costs of clean fuels. Proposals have come before the International Maritime Organization (IMO) to establish clean fuel requirements in various locations around the world to reduce air-borne emissions from vessels. Our research suggests such proposals, or other events that may affect marine fuel prices, can have key impacts on vessel behavior. Consequently, it is important to consider this variability when designing strategies to minimize threats from shipping to vulnerable biophysical systems.

Simple Summary ADHD-like (attention deficit hyperactivity disorder) behavior in dogs may be expressed as impulsivity, inattentiveness, or aggression, compromising both dog and owner quality of life. Its treatment in a clinical setting requires behavioral modification and sometimes a medical treatment is added. There is a lack of objective tools for assessment and diagnosis of the problem, and behavioral experts mostly rely on owner reports. To address this gap, in this paper we use a self-developed computational tool which automatically analyzes movement of a dog from video footage collected during behavioral consultation. Based on a computational analysis of behavioral consultations of 12 dogs medically treated due to ADHD-like behavior and of a control group of 12 dogs with no reported behavioral problems, we identify three dimensions of characteristic movement patterns of dogs with ADHD-like behaviors, which are detectable during consultation. These include (i) high speed of movement, (ii) large coverage of room space, and (iii) frequent re-orientation in room space. These patterns can form the basis for computational methods for objective assessment of dogs with ADHD-like behavior that could help for diagnosis and clinical treatment of the disorder. Abstract Computational approaches were called for to address the challenges of more objective behavior assessment which would be less reliant on owner reports. This study aims to use computational analysis for investigating a hypothesis that dogs with ADHD-like (attention deficit hyperactivity disorder) behavior exhibit characteristic movement patterns directly observable during veterinary consultation. Behavioral consultations of 12 dogs medically treated due to ADHD-like behavior were recorded, as well as of a control group of 12 dogs with no reported behavioral problems. Computational analysis with a self-developed tool based on computer vision and machine learning was performed, analyzing 12 movement parameters that can be extracted from automatic dog tracking data. Significant differences in seven movement parameters were found, which led to the identification of three dimensions of movement patterns which may be instrumental for more objective assessment of ADHD-like behavior by clinicians, while being directly observable during consultation. These include (i) high speed, (ii) large coverage of space, and (iii) constant re-orientation in space. Computational tools used on video data collected during consultation have the potential to support quantifiable assessment of ADHD-like behavior informed by the identified dimensions.

Long-term follow-up is needed to evaluate the impact of short-term cancer research programs on the career trajectories of medical and graduate students. Participation in these programs may be crucial in fostering the next generation of cancer research scientists. This report presents the career outcomes and research productivity of 77 medical and public health students with 25 years of tracking data following their participation in a summer cancer research training program at the University of Alabama at Birmingham (UAB) in 1990-1998. Of 64 summer trainees with contact information, complete survey responses were received from 55 (86.0%) individuals. Over half reported clinical care of cancer patients and 18.2% stated that they were engaged in cancer research. Literature searches confirmed that 23.4% (18/77) of trainees have published cancer research papers. Future studies should explore the optimal timing of short-term post-baccalaureate academic cancer training experiences to identify participant characteristics and institutional factors that influence career choices and determine research productivity.

To acquire 3-D tracking data on juvenile salmonids, Juvenile Salmon Acoustic Telemetry System (JSATS) cabled hydrophone arrays were deployed in the forebays of two dams on the Snake River and at a mid-reach reservoir between the dams. The depth distributions of fish were estimated by statistical analyses performed on large 3-D tracking data sets from ~33,500 individual acoustic tagged yearling and subyearling Chinook salmon and juvenile steelhead at the two dams in 2012 and subyearling Chinook salmon at the two dams and the mid-reach reservoir in 2013. This research investigated the correlation between vertical migration behavior and passage routes. The depth distributions of fish within the forebays of the dams were significantly different from fish passing the mid-reach reservoir. Fish residing deeper in the forebay tended to pass the dam using deeper powerhouse routes. This difference in depth distributions indicated that the depth distribution of fish at the mid-reach reservoir was not related to behaviors of fish passing through certain routes of the adjacent dams. For fish that were detected deeper than 17.5 m in the forebays, the probability of powerhouse passage (i.e., turbine) increased significantly. Another important finding was the variation in depth distributions during dam passage associated with the diel period, especially the crepuscular periods.

Wildlife crossings are designed to mitigate barrier effects of transportation infrastructure on wildlife movement. Most efforts in evaluating crossing efficiency focus on counting animal use. However, crossings placed at suboptimal locations may alter animals' natural movement pattern and decrease population fitness, which cannot be reflected solely by counts of animal use. The long-distance migration of Tibetan antelope (Pantholops hodgsonii) is directly affected by the Qinghai-Tibet Railway (QTR). Using the Wubei wildlife underpass along the QTR, we evaluated how underpass placement affects migration routes and decreases movement efficiency. We calculated the net-squared displacement of each animal to identify migration segments (wintering, calving, and migrating) based on Argos tracking data. We used two corridor modeling methods to identify optimal routes that theoretically require less energy to travel between seasonal habitats. We calculated the distance from actual migration routes recorded by Argos to the modelled optimal routes. We found that antelopes stray farther away from the optimal routes as they approach Wubei, indicating that animals have to deviate from their optimal migration pathway to access the railway underpass. On average, antelopes prolong their migration distance by 86.19 km (SEM = 17.29 km) in order to access the underpass. Our study suggests crossing location can affect animal migrations even if structures facilitate animal crossing. To better conserve long-distance migrations, long-term studies using tracking data which evaluate optimal migration routes are needed. We suggest considering the location and structural characteristics in designing and improving wildlife crossings, which do not only facilitate utilization, but also optimize animal movement processes such as migration.

Despite growing adoption of consumer wearables, the potential for sleep metrics from these devices to contribute to sleep-related biomedical research remains largely uncharacterized. Here we analyze sleep tracking data, along with questionnaire responses and multi-modal phenotypic data, generated from 482 normal volunteers. First, we provide a detailed comparison of wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived sleep duration. We also analyzed our multi-modal phenotypic data and showed that wearable-derived TST and SE are associated with various cardiovascular disease risk markers, whereas self-reported measures were not. Using whole-genome sequencing data, we estimated leukocyte telomere length and showed that volunteers with insufficient sleep also exhibit premature telomere attrition. Our study highlights the potential for sleep metrics generated by consumer wearables to provide novel insights into data generated from population cohort studies.

A smart bracelet accumulates exercise data like calories, step counts, and the length of exercise, etc. It is very convenient for a regular exerciser to follow up his exercise status or find out if he is exercising more than last month. The increasing data can serve as an incentive for consistent exercise. However, there isn’t much study in the extant literature if sports related devices can increase the behaviors of regular exercise. Based on the data smart bracelet collected, this study examined whether using a smart bracelet increases the users’ exercise behaviors and enhances their physical conditions. The study found that by using a smart bracelet, regular exercisers maintain their regular exercise pattern and non-regular exercisers enhanced their exercise performance.

There have been efforts around the globe to track individuals of many marine species and assess their movements and distribution, with the putative goal of supporting their conservation and management. Determining whether, and how, tracking data have been successfully applied to address real-world conservation issues is, however, difficult. Here, we compile a broad range of case studies from diverse marine taxa to show how tracking data have helped inform conservation policy and management, including reductions in fisheries bycatch and vessel strikes, and the design and administration of marine protected areas and important habitats. Using these examples, we highlight pathways through which the past and future investment in collecting animal tracking data might be better used to achieve tangible conservation benefits.

Groups of animals coordinate remarkable, coherent, movement patterns during periods of collective motion. Such movement patterns include the toroidal mills seen in fish shoals, highly aligned parallel motion like that of flocks of migrating birds, and the swarming of insects. Since the 1970’s a wide range of collective motion models have been studied that prescribe rules of interaction between individuals, and that are capable of generating emergent patterns that are visually similar to those seen in real animal group. This does not necessarily mean that real animals apply exactly the same interactions as those prescribed in models. In more recent work, researchers have sought to infer the rules of interaction of real animals directly from tracking data, by using a number of techniques, including averaging methods. In one of the simplest formulations, the averaging methods determine the mean changes in the components of the velocity of an individual over time as a function of the relative coordinates of group mates. The averaging methods can also be used to estimate other closely related quantities including the mean relative direction of motion of group mates as a function of their relative coordinates. Since these methods for extracting interaction rules and related quantities from trajectory data are relatively new, the accuracy of these methods has had limited inspection. In this paper, we examine the ability of an averaging method to reveal prescribed rules of interaction from data generated by two individual based models for collective motion. Our work suggests that an averaging method can capture the qualitative features of underlying interactions from trajectory data alone, including repulsion and attraction effects evident in changes in speed and direction of motion, and the presence of a blind zone. However, our work also illustrates that the output from a simple averaging method can be affected by emergent group level patterns of movement, and the sizes of the regions over which repulsion and attraction effects are apparent can be distorted depending on how individuals combine interactions with multiple group mates.

Life expectancy of the elderly is a significant problem in China, and it changes not only the health care, but also the pension. This study used tracking data from the Chinese Urban and Rural Elderly Population Survey to calculate the age-specific Active Life Expectancy (ALE) of the Chinese elderly population aged 60 years and over. For analysis, this population was divided into different sub-populations according to gender, census register and region. The main conclusions of our study are as follows: 1) The quality of life for elderly males may be greater than that for elderly females; 2) There were significant differences in Active Life Expectancy (ALE) and Inactive Life Expectancy (ILE) between urban and rural elderly; 3) The differences in ALE between the eastern, central and western regions of China were not significant; and 4) The increased remaining life expectancy of the elderly was mainly attributed to the extended ALE in the lower age group and the expanded ILE in the higher age group. This study expands the knowledge of Chinese elderly’s life expectancy in different health status.

Breast ultrasonography (US) presents an alternative to mammography in young asymptomatic individuals and a complementary examination in screening of women with dense breasts. Handheld US is the standard-of-care, yet when used in whole-breast examination, no effort has been devoted to monitoring breast coverage and missed regions, which is the purpose of this study. We introduce a computer-aided system assisting radiologists and US technologists in covering the whole breast with minimum alteration to the standard workflow. The proposed system comprises a standard US device, proprietary electromagnetic 3D tracking technology and software that combines US visual and tracking data to estimate a probe trajectory, total time spent in different breast segments, and a map of missed regions. A case study, which involved four radiologists (two junior and two senior) performing whole-breast ultrasound in 75 asymptomatic patients, was conducted to test the importance and relevance of the system. The mean process time per breast was $$74\pm 22\,{\mathrm {s}}$$ , with no statistically significant difference between the left and the right sides, and slightly longer examination time of junior radiologists. The process time density shows that central parts of the breast have better coverage compared to the periphery. Within the central part, missed regions of minimum detectable size of $$0.09\,{\mathrm {cm}}^2$$ occur in $$8\%$$ of examinations, and non-negligible $$1\,{\mathrm {cm}}^2$$ regions occur in $$3\%$$ of cases. The results of the case study indicate that missed regions are present in handheld whole-breast US, which renders the proposed system for tracking the probe position during examination a valuable tool for monitoring coverage.

Recent research in language and vision has developed models for predicting and disambiguating verbs from images. Here, we ask whether the predictions made by such models correspond to human intuitions about visual verbs. We show that the image regions a verb prediction model identifies as salient for a given verb correlate with the regions fixated by human observers performing a verb classification task.

Currently, nearly 70% of the reentries of intact orbital objects are uncontrolled, corresponding to about 50% of the returning mass, i.e. approximately 100 metric tons per year. In 2015, 79% of the mass was concentrated in 40 upper stages and the remaining 21% mostly in about ten large spacecraft. The average mass of the sizable objects was around 2 metric tons. Predicting the reentry time and location of an uncontrolled object remains a very tricky task, being affected by various sources of inevitable uncertainty. In spite of decades of efforts, mean relative errors of 20-30% often occur. This means that even predictions issued 3 hours before reentry may be affected by an along-track uncertainty of 40,000 km (corresponding to one full orbital path), possibly halved during the last hour if further tracking data are available. This kind of information is not much useful and manageable for civil protection applications, often resulting in confusion and misunderstandings regarding its precise meaning and relevance. Therefore, specific approaches and procedures have been developed to provide understandable and unambiguous information useful for civil protection planning and applications, as shown in practice for recent reentry prediction campaigns of significant satellites (UARS, ROSAT, Phobos-Grunt, GOCE, Progress-M 27M).

Data extraction is one of the most time-consuming tasks in performing a systematic review. Extraction is often onto some sort of form. Sharing completed forms can be used to check quality and accuracy of extraction or for re-cycling data to other researchers for updating. However, validating each piece of extracted data is time-consuming and linking to source problematic. In this methodology paper, we summarize three methods for reporting the location of data in original full-text reports, comparing their advantages and disadvantages.

Behavioural responses of lemon sharks Negaprion brevirostris to a fin-mounted tag package (CEFAS G6A tri-axial accelerometer with epoxied Sonotronics PT4 acoustic transmitter) were measured in a controlled captive environment (n = 10, total length, LT range 80-140 cm) and in free-ranging sharks upon release (n = 7, LT range 100-160 cm). No changes were detected in behaviour (i.e. swimming speed, tailbeat frequency, time spent resting and frequency of chafing) between control and tagged captive shark trials, suggesting that the tag package itself does not alter behaviour. In the free-ranging trials, an initial period of elevated swimming activity was found in all individuals (represented by overall dynamic body acceleration). Negaprion brevirostris, however, appeared to recover quickly, returning to a steady swimming state between 2 and 35 min after release. Post-release tracking found that all sharks swim immediately for the shoreline and remain within 100 m of shore for prolonged periods. Hence, although N. brevirostris are capable of quick adaptation to stressors and demonstrate rapid recovery in terms of activity, tracking data suggest that they may modify their spatial use patterns post release. This research is important in separating deviation in behaviour due to environmental stressors from artefacts caused by experimental techniques.

It is necessary to develop a mechanism to estimate and analyze cumulative radiation risks from multiple CT exams in various clinical scenarios in children.To identify major contributors to high cumulative CT dose estimates using actual dose-length product values collected for 5 years in children.Between August 2006 and July 2011 we reviewed 26,937 CT exams in 13,803 children. Among them, we included 931 children (median age 3.5 years, age range 0 days-15 years; M:F = 533:398) who had 5,339 CT exams. Each child underwent at least three CT scans and had accessible radiation dose reports. Dose-length product values were automatically extracted from DICOM files and we used recently updated conversion factors for age, gender, anatomical region and tube voltage to estimate CT radiation dose. We tracked the calculated CT dose estimates to obtain a 5-year cumulative value for each child. The study population was divided into three groups according to the cumulative CT dose estimates: high, ≥30 mSv; moderate, 10-30 mSv; and low,10 mSv. We reviewed clinical data and CT protocols to identify major contributors to high and moderate cumulative CT dose estimates.Median cumulative CT dose estimate was 5.4 mSv (range 0.5-71.1 mSv), and median number of CT scans was 4 (range 3-36). High cumulative CT dose estimates were most common in children with malignant tumors (57.9%, 11/19). High frequency of CT scans was attributed to high cumulative CT dose estimates in children with ventriculoperitoneal shunt (35 in 1 child) and malignant tumors (range 18-49). Moreover, high-dose CT protocols, such as multiphase abdomen CT (median 4.7 mSv) contributed to high cumulative CT dose estimates even in children with a low number of CT scans.Disease group, number of CT scans, and high-dose CT protocols are major contributors to higher cumulative CT dose estimates in children.

Background Bar code- or radio frequency identification (RFID)-based medical instrument management systems have gradually been introduced in the field of surgical medicine for the individual management and identification of instruments. We hypothesized that individual management of instruments using RFID tags can provide previously unavailable information, particularly the precise service life of an instrument. Such information can be used to prevent medical accidents caused by surgical instrument failure. This study aimed to predict the precise service life of instruments by analyzing the data available in instrument management systems. Methods We evaluated the repair history of instruments and the usage count until failure and then analyzed the data by the following three methods: the distribution of the instrument usage count was determined, an instrument failure probability model was generated through logistic regression analysis, and survival analysis was performed to predict instrument failure. Results The usage count followed a normal distribution. Analysis showed that instruments were not used uniformly during surgery. In addition, the Kaplan–Meier curves plotted for five types of instruments showed significant differences in the cumulative survival rate of different instruments. Conclusions The usage history of instruments obtained with RFID tags or bar codes can be used to predict the probability of instrument failure. This prediction is significant for determining the service life of an instrument. Implementation of the developed model in instrument management systems can help prevent accidents due to instrument failure. Knowledge of the instrument service life will also help in developing a purchase plan for instruments to minimize wastage.

We examined whether older individuals with mild cognitive impairment (MCI) differed from healthy controls (HC) and persons with dementia (AD) in objective and perceived behavioral competence as well as in emotional well-being. We used a merged sample of 257 older adults aged 59 to 91 years (M = 72.9; SD = 6.4) stemming from Israel and Germany. Objective behavioral competence (assessed based on global positioning system (GPS)-based tracking data and a structured questionnaire) of MCI individuals was mostly similar to the HC group. Regarding perceived behavioral competence and emotional well-being, MCI individuals were more similar to the AD group and below the HC group’s mean levels. Findings suggest that a differentiated view of MCI individual’s competence and emotional well-being is in place.

Purpose To present a detailed optimization process of automated radiation dose tracking data in standard CT chest examination for multi detector computed tomography (MDCT). Tasks resulting from such a goal are related with correct processing of collected data, deep analysis and interpretation of the data, identification of incorrect clinical practice and to compare the results with another radiology department practice. Materials and methods A single retrospective study was conducted involving regular enrolled patients for routine CT chest examination in Acibadem City Clinic Tokuda Hospital. All MDCT exams were performed on a 64-detector row computed tomography (LightSpeed VCT, GEHC) without any iterative reconstructions. The tube voltage (kV), slice thickness (mm), rotation time (s/rot) and table speed (mm/s) were periodically altered parameters according to radiation dose reduction without compromising the quality of the image. In the course of the study a web-based dose management software was used (DoseWatch, GEHC) which allows all MDCT chest examinations to be properly tracked and radiation doses to be collected. Results After the step by step optimization the CTDIvol and DLP were decreased to 9,20 mGy and 373,77 mGy.cm respectively while maintaining good diagnostic image quality. In comparison with Acibadem City Clinic Cancer Centre (Optima CT660, SS40 ASIR, GEHC) these values are slightly higher which is explained by the fact that in Optima CT660 an iterative reconstruction algorithm was systematically used (CTDIvol6,43 mGy and DLP 265,2 mGy·cm). Conclusions The CT chest radiation dose was reduced with 56% (CTDIvol) and 63% (DLP) with preserving the diagnostic image quality. A significant CT chest dose reduction was achieved even without using any iterative reconstruction algorithm.

Purpose To study the impact of daily rotations and translations of the prostate on dosimetric coverage during radiation therapy (RT). Methods and Materials Real-time tracking data for 26 patients were obtained during RT. Intensity modulated radiation therapy plans meeting RTOG 0126 dosimetric criteria were created with 0-, 2-, 3-, and 5-mm planning target volume (PTV) margins. Daily translations and rotations were used to reconstruct prostate delivered dose from the planned dose. D95 and V79 were computed from the delivered dose to evaluate target coverage and the adequacy of PTV margins. Prostate equivalent rotation is a new metric introduced in this study to quantify prostate rotations by accounting for prostate shape and length of rotational lever arm. Results Large variations in prostate delivered dose were seen among patients. Adequate target coverage was met in 39%, 65%, and 84% of the patients for plans with 2-, 3-, and 5-mm PTV margins, respectively. Although no correlations between prostate delivered dose and daily rotations were seen, the data showed a clear correlation with prostate equivalent rotation. Conclusions Prostate rotations during RT could cause significant underdosing even if daily translations were managed. These rotations should be managed with rotational tolerances based on prostate equivalent rotations.

Purpose To evaluate the setup, interfraction, and intrafraction organ motion error distributions and simulate intrafraction intervention strategies for prostate radiotherapy. Methods and Materials A total of 17 patients underwent treatment setup and were monitored using the Calypso system during radiotherapy. On average, the prostate tracking measurements were performed for 8 min/fraction for 28 fractions for each patient. For both patient couch shift data and intrafraction organ motion data, the systematic and random errors were obtained from the patient population. The planning target volume margins were calculated using the van Herk formula. Two intervention strategies were simulated using the tracking data: the deviation threshold and period. The related planning target volume margins, time costs, and prostate position “fluctuation” were presented. Results The required treatment margin for the left–right, superoinferior, and anteroposterior axes was 8.4, 10.8, and 14.7 mm for skin mark-only setup and 1.3, 2.3, and 2.8 mm using the on-line setup correction, respectively. Prostate motion significantly correlated among the superoinferior and anteroposterior directions. Of the 17 patients, 14 had prostate motion within 5 mm of the initial setup position for ≥91.6% of the total tracking time. The treatment margin decreased to 1.1, 1.8, and 2.3 mm with a 3-mm threshold correction and to 0.5, 1.0, and 1.5 mm with an every-2-min correction in the left–right, superoinferior, and anteroposterior directions, respectively. The periodic corrections significantly increase the treatment time and increased the number of instances when the setup correction was made during transient excursions. Conclusions The residual systematic and random error due to intrafraction prostate motion is small after on-line setup correction. Threshold-based and time-based intervention strategies both reduced the planning target volume margins. The time-based strategies increased the treatment time and the in-fraction position fluctuation.

Aims To track smokers' responses to the increasing price of cigarettes after a tax increase, and assess socio-demographic differences in responses. Design The Cancer Institute NSW's Tobacco Tracking Survey (CITTS) is a continuous tracking telephone survey. Weekly data were collected between May and September 2010. Settings New South Wales, Australia. Participants A total of 834 smokers and 163 recent quitters (quit in last 12 months). Measurements Responses to the price increase included smoking-related changes (tried to quit, cut down) and product-related changes (changed to lower priced brands, started using loose tobacco, bought in bulk). Recent quitters were asked how much the increasing price of cigarettes influenced them to quit. Findings Overall, 47.5% of smokers made smoking-related changes and 11.4% made product-related changes without making smoking-related changes. Multinomial logistic regressions showed that younger smokers (versus older) were more likely to make product-related changes and smoking-related changes in comparison to no changes. Low- or moderate-income smokers (versus high-income) were more likely to make smoking-related changes compared to no changes. Highly addicted smokers (versus low addicted) were more likely to make product-related changes and less likely to make smoking-related changes. The proportion of smokers making only product-related changes decreased with time, while smoking-related changes increased. Recent quitters who quit after the tax increase (versus before) were more likely to report that price influenced them. Conclusions The effect of increasing cigarette prices on smoking does not appear to be mitigated by using cheaper cigarette products or sources. These results support the use of higher cigarette prices to encourage smoking cessation.