Wearable Robot Design Optimization Using Closed-Form Human-Robot Dynamic Interaction Model.

Wearable robots are emerging as a viable and effective solution for assisting and enabling people who suffer from balance and mobility disorders. Virtual prototyping is a powerful tool to design robots, preventing the costly iterative physical prototyping and testing. Design of wearable robots through modelling, however, often involves computationally expensive and error-prone multi-body simulations wrapped in an optimization framework to simulate human-robot-environment interactions. This paper proposes a framework to make the human-robot link segment system statically determinate, allowing for the closed-form inverse dynamics formulation of the link-segment model to be solved directly in order to simulate human-robot dynamic interactions. The paper also uses a technique developed by the authors to estimate the walking ground reactions from reference kinematic data, avoiding the need to measure them. The proposed framework is (a) computationally efficient and (b) transparent and easy to interpret, and (c) eliminates the need for optimization, detailed musculoskeletal modelling and measuring ground reaction forces for normal walking simulations. It is used to optimise the position of hip and ankle joints and the actuator torque-velocity requirements for a seven segments of a lower-limb wearable robot that is attached to the user at the shoes and pelvis. Gait measurements were carried out on six healthy subjects, and the data were used for design optimization and validation. The new technique promises to offer a significant advance in the way in which wearable robots can be designed.

Characterization of Pharmacokinetics, Biotransformation and Elimination of Pomotrelvir Orally Administered in Healthy Male Adults Using Two [14C]-Labeled Microtracers with Separate Labeling Positions.

Pomotrelvir is an orally bioavailable, target antiviral inhibitor of the main protease (Mpro) of coronaviruses, including severe acute respiratory syndrome coronavirus 2, the etiological agent of Coronavirus Disease 2019. The pharmacokinetics, metabolism and elimination of two [14C]-labeled microtracers of 5 µCi/700 mg pomotrelvir with separate labeling positions (isotopomers), [lactam carbonyl-14C-pomotelvir] and [benzene ring-U-14C-pomotrelvir], following a single oral dose in healthy adult males was evaluated in two separate cohorts. Pomotrelvir was rapidly absorbed and eliminated primarily through metabolism and subsequently excreted via urine and feces. There were no differences in pomotrelvir pharmacokinetics between the two cohorts. The mean total radioactive dose recovered was 93.8% (n = 8) in the lactam cohort (58% in urine and 36% in feces) and 94.2% (n = 8) in the benzene cohort (75% in urine and 19% in feces), with ≥80% of [14C] recovered within 96 hours after dosing. About 5% and 3% of the intact pomotrelvir was recovered in feces and urine, respectively. Eleven major metabolites were detected and characterized using liquid chromatography-accelerator mass spectrometry and liquid chromatography tandem mass spectrometry methods, with three and six different metabolites elucidated in the samples collected from lactam and benzene cohorts, respectively, and two metabolites observed in both cohorts. The major metabolism pathway of pomotrelvir is through hydrolysis of its peptide bonds followed by phase II conjugations. These results support that the application of two radiolabeled isotopomers provided a comprehensive metabolite profiling analysis and was a successful approach in identifying the major disposition pathways of pomotrelvir that has complex routes of metabolism. SIGNIFICANCE STATEMENT: An unconventional approach using two differentially labeled [14C] microtracers, [lactam carbonyl-14C-pomotrelvir] and [benzene ring-U-14C-pomotrelvir] evaluated the mass balance of orally administered pomotrelvir in healthy adult males in two separate cohorts. The radioactive dose recovered in excreta was about 94% for both cohorts. While the two isotopomers of the radiolabeled-pomotrelvir showed no major differences in pharmacokinetics overall, they allowed for differential detection of their radiolabeled metabolites and appropriate characterization of their plasma exposure and excretion in urine and feces.

A Deep Learning Model with a Self-Attention Mechanism for Leg Joint Angle Estimation across Varied Locomotion Modes.

Conventional trajectory planning for lower limb assistive devices usually relies on a finite-state strategy, which pre-defines fixed trajectory types for specific gait events and activities. The advancement of deep learning enables walking assistive devices to better adapt to varied terrains for diverse users by learning movement patterns from gait data. Using a self-attention mechanism, a temporal deep learning model is developed in this study to continuously generate lower limb joint angle trajectories for an ankle and knee across various activities. Additional analyses, including using Fast Fourier Transform and paired t-tests, are conducted to demonstrate the benefits of the proposed attention model architecture over the existing methods. Transfer learning has also been performed to prove the importance of data diversity. Under a 10-fold leave-one-out testing scheme, the observed attention model errors are 11.50% (±2.37%) and 9.31% (±1.56%) NRMSE for ankle and knee angle estimation, respectively, which are small in comparison to other studies. Statistical analysis using the paired t-test reveals that the proposed attention model appears superior to the baseline model in terms of reduced prediction error. The attention model also produces smoother outputs, which is crucial for safety and comfort. Transfer learning has been shown to effectively reduce model errors and noise, showing the importance of including diverse datasets. The suggested joint angle trajectory generator has the potential to seamlessly switch between different locomotion tasks, thereby mitigating the problem of detecting activity transitions encountered by the traditional finite-state strategy. This data-driven trajectory generation method can also reduce the burden on personalization, as traditional devices rely on prosthetists to experimentally tune many parameters for individuals with diverse gait patterns.

Understanding LSTM Network Behaviour of IMU-Based Locomotion Mode Recognition for Applications in Prostheses and Wearables.

Human Locomotion Mode Recognition (LMR) has the potential to be used as a control mechanism for lower-limb active prostheses. Active prostheses can assist and restore a more natural gait for amputees, but as a medical device it must minimize user risks, such as falls and trips. As such, any control system must have high accuracy and robustness, with a detailed understanding of its internal operation. Long Short-Term Memory (LSTM) machine-learning networks can perform LMR with high accuracy levels. However, the internal behavior during classification is unknown, and they struggle to generalize when presented with novel users. The target problem addressed in this paper is understanding the LSTM classification behavior for LMR. A dataset of six locomotive activities (walking, stopped, stairs and ramps) from 22 non-amputee subjects is collected, capturing both steady-state and transitions between activities in natural environments. Non-amputees are used as a substitute for amputees to provide a larger dataset. The dataset is used to analyze the internal behavior of a reduced complexity LSTM network. This analysis identifies that the model primarily classifies activity type based on data around early stance. Evaluation of generalization for unseen subjects reveals low sensitivity to hyper-parameters and over-fitting to individuals' gait traits. Investigating the differences between individual subjects showed that gait variations between users primarily occur in early stance, potentially explaining the poor generalization. Adjustment of hyper-parameters alone could not solve this, demonstrating the need for individual personalization of models. The main achievements of the paper are (i) the better understanding of LSTM for LMR, (ii) demonstration of its low sensitivity to learning hyper-parameters when evaluating novel user generalization, and (iii) demonstration of the need for personalization of ML models to achieve acceptable accuracy.

Tenofovir alafenamide versus tenofovir disoproxil fumarate, coformulated with elvitegravir, cobicistat, and emtricitabine, for initial treatment of HIV-1 infection: two randomised, double-blind, phase 3, non-inferiority trials.

BACKGROUND: Tenofovir disoproxil fumarate can cause renal and bone toxic effects related to high plasma tenofovir concentrations. Tenofovir alafenamide is a novel tenofovir prodrug with a 90% reduction in plasma tenofovir concentrations. Tenofovir alafenamide-containing regimens can have improved renal and bone safety compared with tenofovir disoproxil fumarate-containing regimens. METHODS: In these two controlled, double-blind phase 3 studies, we recruited treatment-naive HIV-infected patients with an estimated creatinine clearance of 50 mL per min or higher from 178 outpatient centres in 16 countries. Patients were randomly assigned (1:1) to receive once-daily oral tablets containing 150 mg elvitegravir, 150 mg cobicistat, 200 mg emtricitabine, and 10 mg tenofovir alafenamide (E/C/F/tenofovir alafenamide) or 300 mg tenofovir disoproxil fumarate (E/C/F/tenofovir disoproxil fumarate) with matching placebo. Randomisation was done by a computer-generated allocation sequence (block size 4) and was stratified by HIV-1 RNA, CD4 count, and region (USA or ex-USA). Investigators, patients, study staff, and those assessing outcomes were masked to treatment group. All participants who received one dose of study drug were included in the primary intention-to-treat efficacy and safety analyses. The main outcomes were the proportion of patients with plasma HIV-1 RNA less than 50 copies per mL at week 48 as defined by the the US Food and Drug Adminstration (FDA) snapshot algorithm (pre-specified non-inferiority margin of 12%) and pre-specified renal and bone endpoints at 48 weeks. These studies are registered with ClinicalTrials.gov, numbers NCT01780506 and NCT01797445. FINDINGS: We recruited patients from Jan 22, 2013, to Nov 4, 2013 (2175 screened and 1744 randomly assigned), and gave treatment to 1733 patients (866 given E/C/F/tenofovir alafenamide and 867 given E/C/F/tenofovir disoproxil fumarate). E/C/F/tenofovir alafenamide was non-inferior to E/C/F/tenofovir disoproxil fumarate, with 800 (92%) of 866 patients in the tenofovir alafenamide group and 784 (90%) of 867 patients in the tenofovir disoproxil fumarate group having plasma HIV-1 RNA less than 50 copies per mL (adjusted difference 2·0%, 95% CI -0·7 to 4·7). Patients given E/C/F/tenofovir alafenamide had significantly smaller mean serum creatinine increases than those given E/C/F/tenofovir disoproxil fumarate (0·08 vs 0·12 mg/dL; p<0·0001), significantly less proteinuria (median % change -3 vs 20; p<0·0001), and a significantly smaller decrease in bone mineral density at spine (mean % change -1·30 vs -2·86; p<0·0001) and hip (-0·66 vs -2·95; p<0·0001) at 48 weeks. INTERPRETATION: Through 48 weeks, more than 90% of patients given E/C/F/tenofovir alafenamide or E/C/F/tenofovir disoproxil fumarate had virological success. Renal and bone effects were significantly reduced in patients given E/C/F/tenofovir alafenamide. Although these studies do not have the power to assess clinical safety events such as renal failure and fractures, our data suggest that E/C/F/tenofovir alafenamide will have a favourable long-term renal and bone safety profile. FUNDING: Gilead Sciences.

SARS-CoV-2 viral dynamics in a placebo-controlled phase 2 study of patients infected with the SARS-CoV-2 Omicron variant and treated with pomotrelvir.

Current guidelines recommend that individuals with moderate COVID-19 disease isolate for 5 days after the first appearance of symptoms or a positive SARS-CoV-2 test. It would be useful to understand the time course of infectious virus production and its correlation with virus detection using a rapid antigen test (RAT) or quantitative reverse transcriptase (qRT)-PCR. In a phase 2 study, 242 vaccinated patients with COVID-19 and at low risk for progression to severe disease initiated 5 days of treatment with pomotrelvir (PBI-0451, a SARS-CoV-2 main protease inhibitor) or placebo within 5 days after symptom onset. The primary endpoint, the proportion of subjects with SARS-CoV-2 viral titers below the limit of detection on Day 3 of treatment in the pomotrelvir versus placebo groups, was not met. No between-group differences in SARS-CoV-2 clearance or symptom resolution or alleviation were observed. Additional analyses evaluated the dynamics of SARS-CoV-2 replication in mid-turbinate nasal swabs and saliva samples using infectious virus assay (IVA), RAT, and qRT-PCR. SARS-CoV-2 cleared rapidly, with negative results first determined by IVA (TCID50 below the limit of detection), followed by the RAT (negative for SARS-CoV-2 N antigen), and qRT-PCR (RNA below the limit of detection), which suggests that delayed initiation of treatment (up to 5 days after symptom onset) may have contributed to the lack of treatment response. Symptom resolution lagged behind viral clearance assessed by IVA and RAT. These data support reliance on a negative RAT to determine when an individual is no longer producing infectious virus and may end isolation.IMPORTANCEA phase 2 double-blind, placebo-controlled study was performed evaluating pomotrelvir, a SARS-CoV-2 Mpro inhibitor, compared with placebo in 242 non-hospitalized, vaccinated, symptomatic adults with COVID-19 (Omicron). No improvement in the decrease of viral replication or relief of symptoms was observed between the two groups when treatment was initiated ≥3 days after symptom onset. These results suggest that future COVID-19 antiviral studies using a similar patient population may need to initiate treatment earlier, like influenza studies. This is the first study to prospectively evaluate SARS-CoV-2 viral dynamics and the time to viral clearance in a significant number of patients using concurrently obtained results from an infectious virus assay, a rapid antigen test (RAT), and a qRT-PCR assay over a 15-day time course. These results suggest that a negative RAT assay is a good indicator of loss of infectious virus and the ability to return to normal activities.

Novel framework for assessing epidemiologic effects of influenza epidemics and pandemics.

The effects of influenza on a population are attributable to the clinical severity of illness and the number of persons infected, which can vary greatly between seasons or pandemics. To create a systematic framework for assessing the public health effects of an emerging pandemic, we reviewed data from past influenza seasons and pandemics to characterize severity and transmissibility (based on ranges of these measures in the United States) and outlined a formal assessment of the potential effects of a novel virus. The assessment was divided into 2 periods. Because early in a pandemic, measurement of severity and transmissibility is uncertain, we used a broad dichotomous scale in the initial assessment to divide the range of historic values. In the refined assessment, as more data became available, we categorized those values more precisely. By organizing and prioritizing data collection, this approach may inform an evidence-based assessment of pandemic effects and guide decision making.

Mass screening for fever in children: a comparison of 3 infrared thermal detection systems.

OBJECTIVES: Infrared thermal detection systems (ITDSs) have been used with limited success outside the United States to screen for fever during recent outbreaks of novel infectious diseases. Although ITDSs are fairly accurate in detecting fever in adults, there is little information about their utility in children. METHODS: In a pediatric emergency department, we compared temperatures of children (<18 years old) measured using 3 ITDSs (OptoTherm Thermoscreen, FLIR ThermoVision 360, and Thermofocus 0800H3) to standard, age-appropriate temperature measurements (confirmed fever defined as ≥38.0°C [oral or rectal], ≥37.0°C [axillary]). Measured temperatures were compared with parental reports of fever using descriptive, multivariate, and receiver operating characteristic analyses. RESULTS: Of 855 patients, 400 (46.8%) had parent-reported fever, and 306 (35.8%) had confirmed fever. At optimal fever thresholds, OptoTherm and FLIR had sensitivity (83.0% and 83.7%, respectively) approximately equal to parental report (83.9%) and greater than Thermofocus (76.8%), and specificity (86.3% and 85.7%) greater than parental report (70.8%) and Thermofocus (79.4%). Correlation coefficients between traditional thermometry and ITDSs were 0.78 (OptoTherm), 0.75 (FLIR), and 0.66 (Thermofocus). CONCLUSIONS: Compared with traditional thermometry, FLIR and OptoTherm were reasonably accurate in detecting fever in children and better predictors of fever than parental report. These findings suggest that ITDSs could be a useful noninvasive screening tool for fever in the pediatric age group.

A comprehensive evaluation in clinic and physiologically-based pharmacokinetic modeling and simulation to confirm lack of cytochrome P450-mediated drug-drug interaction potential for pomotrelvir.

Pomotrelvir is a new chemical entity and potent direct-acting antiviral inhibitor of the main protease of coronaviruses. Here the cytochrome P450 (CYP)-mediated drug-drug interaction (DDI) potential of pomotrelvir was evaluated for major CYP isoforms, starting with in vitro assays followed by the basic static model assessment. The identified CYP3A4-mediated potential DDIs were evaluated clinically at a supratherapeutic dose of 1050 mg twice daily (b.i.d.) of pomotrelvir, including pomotrelvir coadministration with ritonavir (strong inhibitor of CYP3A4) or midazolam (sensitive substrate of CYP3A4). Furthermore, a physiologically-based pharmacokinetic (PBPK) model was developed within the Simcyp Population-based Simulator using in vitro and in vivo information and validated with available human pharmacokinetic (PK) data. The PBPK model was simulated to assess the DDI potential for CYP isoforms that pomotrelvir has shown a weak to moderate DDI in vitro and for CYP3A4 at the therapeutic dose of 700 mg b.i.d. To support the use of pomotrelvir in women of childbearing potential, the impact of pomotrelvir on the exposure of the representative oral hormonal contraceptive drugs ethinyl estradiol and levonorgestrel was assessed using the PBPK model. The overall assessment suggested weak inhibition of pomotrelvir on CYP3A4 and minimal impact of a strong CYP3A4 inducer or inhibitor on pomotrelvir PK. Therefore, pomotrelvir is not anticipated to have clinically meaningful DDIs at the clinical dose. These comprehensive in vitro, in clinic, and in silico efforts indicate that the DDI potential of pomotrelvir is minimal, so excluding patients on concomitant medicines in clinical studies would not be required.

Deep learning with an attention mechanism for continuous biomechanical motion estimation across varied activities.

Reliable estimation of desired motion trajectories plays a crucial part in the continuous control of lower extremity assistance devices such as prostheses and orthoses. Moreover, reliable estimation methods are also required to predict hard-to-measure biomechanical quantities (e.g., joint contact moment/force) for use in sports injury science. Recognising that human locomotion is an inherently time-sequential and limb-synergetic behaviour, this study investigates models and learning algorithms for predicting the motion of a subject's leg from the motion of complementary limbs. The novel deep learning model architectures proposed are based on the Long Short-Term Memory approach with the addition of an attention mechanism. A dataset comprising Inertial Measurement Unit signals from 21 subjects traversing varied terrains was used, including stair ascent/descent, ramp ascent/descent, stopped, level-ground walking and the transitions between these conditions. Fourier Analysis is deployed to evaluate the model robustness, in addition to assessing time-based prediction errors. The experiment on three unseen test participants suggests that the branched neural network structure is preferred to tackle the multioutput problem, and the inclusion of an attention mechanism demonstrates improved performance in terms of accuracy, robustness and network size. An experimental comparison found that 57% of the model parameters were not needed after adding attention layers meanwhile the prediction error is lower than the LSTM model without attention mechanism. The attention model has errors of 9.06% and 7.64% (normalised root mean square error) for ankle and hip acceleration prediction respectively. Also, less high-frequency noise is present in the attention model predictions. We conclude that the internal structure of the proposed deep learning model is justified, principally the benefit of using an attention mechanism. Experimental results for biomechanical motion estimation are obtained, showing greater accuracy than only with LSTM. The trained attention model can be used throughout despite transitioning between terrain types. Such a model will be useful in, for example, the control of lower-limb prostheses, instead of the need to identify and switch between different trajectory generators for different walking modes.

The burning rate of energetic films of nanostructured porous silicon.

A systematic study of nanoenergetic films consisting of nanostructured porous silicon impregnated with sodium perchlorate is carried out. The explosive properties of these films are investigated as a function of thickness, porosity, and confinement. The films' burning rates are investigated using fiber-optic velocity probes, demonstrating that flame-front velocities vary between approximately 1 and 500 m s(-1) and are very sensitive to the films' structural characteristics. Analysis of the flame profile by high-speed video is also presented, suggesting that the reaction type is a deflagration rather than a detonation. A strong plume of flame is emitted from the surface, indicating the potential for this material to perform useful work either as an initiator or as a propellant. The shape of the flame front transitioned from an inverted V at thin-film thicknesses to a neat square-shaped front once the material became self-confining at 50 µm.

A simple method to estimate flow restriction for dual ventilation of dissimilar patients: The BathRC model.

BACKGROUND: With large numbers of COVID-19 patients requiring mechanical ventilation and ventilators possibly being in short supply, in extremis two patients may have to share one ventilator. Careful matching of patient ventilation requirements is necessary. However, good matching is difficult to achieve as lung characteristics can have a wide range and may vary over time. Adding flow restriction to the flow path between ventilator and patient gives the opportunity to control the airway pressure and hence flow and volume individually for each patient. This study aimed to create and validate a simple model for calculating required flow restriction. METHODS AND FINDINGS: We created a simple linear resistance-compliance model, termed the BathRC model, of the ventilator tubing system and lung allowing direct calculation of the relationships between pressures, volumes, and required flow restriction. Experimental measurements were made for parameter determination and validation using a clinical ventilator connected to two test lungs. For validation, differing amounts of restriction were introduced into the ventilator circuit. The BathRC model was able to predict tidal lung volumes with a mean error of 4% (min:1.2%, max:9.3%). CONCLUSION: We present a simple model validated model that can be used to estimate required flow restriction for dual patient ventilation. The BathRC model is freely available; this tool is provided to demonstrate that flow restriction can be readily estimated. Models and data are available at DOI 10.15125/BATH-00816.

Evaluation of the sub-surface morphology and composition of gunshot residue using focussed ion beam analysis.

Recent work in the forensic analysis of Gunshot residues (GSR) has suggested that the sub-surface or internal composition and morphology of these residues be explored. A particular area of interest is in heavy metal free, or non-toxic ammunition, which are becoming more frequently encountered in the marketplace. As the formulation of the primer compound changes the conditions of the firearm discharge, there is the possibility that different primer formulations may result in the formation of different GSR particles with distinct internal morphologies and compositions. To that end, the internal morphology and composition of GSR particles may provide additional information that could be useful in the investigation of firearms crime. This research investigated the internal morphology of GSR originating from a variety of different ammunition products. Both traditional three-component primed ammunition, and a selection of heavy metal free and non-toxic alternatives were considered. Particles were identified using SEM-EDS, before being cross-sectioned using a focussed ion beam (FIB) instrument. The FIB-sectioned particles were then re-acquired and mapped using SEM-EDS, to assess both internal morphology and composition. Particles observed in this study presented distinct morphological and compositional features at the sub-particle level that may provide an indication of the primer formulation from which they originated. That said, further investigation of a variety of samples should be undertaken to verify the consistency of these features, or any deviations that may be observed based on primer type. However, these results indicate that there may be promise in obtaining additional detail from sub-particle morphology and composition.

School dismissal as a pandemic influenza response: When, where and for how long?

We used individual-based computer simulation models at community, regional and national levels to evaluate the likely impact of coordinated pre-emptive school dismissal policies during an influenza pandemic. Such policies involve three key decisions: when, over what geographical scale, and how long to keep schools closed. Our evaluation includes uncertainty and sensitivity analyses, as well as model output uncertainties arising from variability in serial intervals and presumed modifications of social contacts during school dismissal periods. During the period before vaccines become widely available, school dismissals are particularly effective in delaying the epidemic peak, typically by 4-6 days for each additional week of dismissal. Assuming the surveillance is able to correctly and promptly diagnose at least 5-10% of symptomatic individuals within the jurisdiction, dismissals at the city or county level yield the greatest reduction in disease incidence for a given dismissal duration for all but the most severe pandemic scenarios considered here. Broader (multi-county) dismissals should be considered for the most severe and fast-spreading (1918-like) pandemics, in which multi-month closures may be necessary to delay the epidemic peak sufficiently to allow for vaccines to be implemented.

Computing low-dimensional representations of speech from socio-auditory structures for phonetic analyses.

Low-dimensional representations of speech data, such as formant values extracted by linear predictive coding analysis or spectral moments computed from whole spectra viewed as probability distributions, have been instrumental in both phonetic and phonological analyses over the last few decades. In this paper, we present a framework for computing low-dimensional representations of speech data based on two assumptions: that speech data represented in high-dimensional data spaces lie on shapes called manifolds that can be used to map speech data to low-dimensional coordinate spaces, and that manifolds underlying speech data are generated from a combination of language-specific lexical, phonological, and phonetic information as well as culture-specific socio-indexical information that is expressed by talkers of a given speech community. We demonstrate the basic mechanics of the framework by carrying out an analysis of children's productions of sibilant fricatives relative to those of adults in their speech community using the phoneigen package - a publicly available implementation of the framework. We focus the demonstration on enumerating the steps for constructing manifolds from data and then using them to map the data to a low-dimensional space, explicating how manifold structure affects the learned low-dimensional representations, and comparing the use of these representations against standard acoustic features in a phonetic analysis. We conclude with a discussion of the framework's underlying assumptions, its broader modeling potential, and its position relative to recent advances in the field of representation learning.

Analysis of elemental and isotopic variation in glass frictionators from 0.22 rimfire primers.

The majority of 0.22 calibre rimfire ammunition available in Australia, and overseas, tends to use glass powder rather than antimony sulfide frictionator in the primer. This glass can be the nucleus of a GSR particle, with other primer components condensing around and onto the glass structure. As the composition of glass frictionator remains largely unaltered during ammunition discharge [1] there is the possibility that frictionator composition could be used in GSR examinations to either correlate or discriminate between samples, thereby providing valuable information to an investigation. In this study, the composition of glass frictionator from a wide variety of ammunition was analysed by time-of-flight - secondary ion mass spectrometry (ToF-SIMS), sensitive high-resolution ion microprobe (SHRIMP) and scanning electron microscopy - energy dispersive X-ray spectrometry (SEM-EDS). Refractive index (RI) was measured using glass refractive index measurement (GRIM). Across the population of ammunition studied, it was found that the elemental and isotopic composition of frictionator varied. ToF-SIMS was able to discriminate 94.1% of brands in a pairwise comparison and SEM-EDS achieved a pairwise discrimination power of 79.4%. If SHRIMP was combined with the other two techniques, 95.6% of brands could be discriminated. Refractive index measurements supported the elemental data showing that there appeared, in most cases, to be only one population of glass within a cartridge. The results suggest that there is scope for frictionator analysis to contribute valuable, new capability to forensic GSR examinations.

Repeat testing of low-level HIV-1 RNA: assay performance and implementation in clinical trials.

OBJECTIVE: Assess the performance of HIV-1 RNA repeat testing of stored samples in cases of low-level viremia during clinical trials. DESIGN: Prospective and retrospective analysis of randomized clinical trial samples and reference standards. METHODS: To evaluate assay variability of the Cobas AmpliPrep/Cobas TaqMan HIV-1 Test, v2.0, three separate sources of samples were utilized: the World Health Organization (WHO) HIV reference standard (assayed using 50 independent measurements at six viral loads <200 copies/ml), retrospective analysis of four to six aliquots of plasma samples from four clinical trial participants, and prospective repeat testing of 120 samples from participants in randomized trials with low-level viremia. RESULTS: The TaqMan assay on the WHO HIV-1 RNA standards at viral loads <200 copies/ml performed within the expected variability according to assay specifications. However, standards with low viral loads of 36 and 18 copies/ml reported values of ≥ 50 copies/ml in 66 and 18% of tests, respectively. In participants treated with antiretrovirals who had unexpected viremia of 50-200 copies/ml after achieving <50 copies/ml, retesting of multiple aliquots of stored plasma found <50 copies/ml in nearly all cases upon retesting (14/15; 93%). Repeat testing was prospectively implemented in four clinical trials for all samples with virologic rebound of 50-200 copies/ml (n = 120 samples from 92 participants) from which 42% (50/120) had a retest result of less than 50 copies/ml and 58% (70/120) retested ≥ 50 copies/ml. CONCLUSION: The TaqMan HIV-1 RNA assay shows variability around 50 copies/ml that affects clinical trial results and may impact clinical practice. In participants with a history of viral load suppression, unexpected low-level viremia may be because of assay variability rather than low drug adherence or true virologic failure. Retesting a stored aliquot of the same sample may differentiate between assay variability and virologic failure as the source of viremia. This retesting strategy could save time, money, and anxiety for patients and their providers, as well as decrease follow-up clinic visits without increasing the risk of virologic failure and resistance development.

Methods for eliciting, annotating, and analyzing databases for child speech development.

Methods from automatic speech recognition (ASR), such as segmentation and forced alignment, have facilitated the rapid annotation and analysis of very large adult speech databases and databases of caregiver-infant interaction, enabling advances in speech science that were unimaginable just a few decades ago. This paper centers on two main problems that must be addressed in order to have analogous resources for developing and exploiting databases of young children's speech. The first problem is to understand and appreciate the differences between adult and child speech that cause ASR models developed for adult speech to fail when applied to child speech. These differences include the fact that children's vocal tracts are smaller than those of adult males and also changing rapidly in size and shape over the course of development, leading to between-talker variability across age groups that dwarfs the between-talker differences between adult men and women. Moreover, children do not achieve fully adult-like speech motor control until they are young adults, and their vocabularies and phonological proficiency are developing as well, leading to considerably more within-talker variability as well as more between-talker variability. The second problem then is to determine what annotation schemas and analysis techniques can most usefully capture relevant aspects of this variability. Indeed, standard acoustic characterizations applied to child speech reveal that adult-centered annotation schemas fail to capture phenomena such as the emergence of covert contrasts in children's developing phonological systems, while also revealing children's nonuniform progression toward community speech norms as they acquire the phonological systems of their native languages. Both problems point to the need for more basic research into the growth and development of the articulatory system (as well as of the lexicon and phonological system) that is oriented explicitly toward the construction of age-appropriate computational models.

Brief Report: Randomized, Double-Blind Comparison of Tenofovir Alafenamide (TAF) vs Tenofovir Disoproxil Fumarate (TDF), Each Coformulated With Elvitegravir, Cobicistat, and Emtricitabine (E/C/F) for Initial HIV-1 Treatment: Week 144 Results.

In 2 double-blind phase 3 trials, 1733 antiretroviral-naive adults were randomized to tenofovir alafenamide (TAF) or tenofovir disoproxil fumarate (TDF), each coformulated with elvitegravir/cobicistat/emtricitabine (E/C/F). At 144 weeks, TAF was superior to TDF in virologic efficacy, with 84.2% vs 80.0% having HIV-1 RNA <50 copies/mL (difference 4.2%; 95% confidence interval: 0.6% to 7.8%). TAF had less impact than TDF on bone mineral density and renal biomarkers. No participants on TAF had renal-related discontinuations vs 12 on TDF (P < 0.001), with no cases of proximal tubulopathy for TAF vs 4 for TDF. There were greater increases in lipids with TAF vs TDF, with no difference in the total cholesterol to high-density lipoprotein ratio. For initial HIV therapy, E/C/F/TAF is superior to E/C/F/TDF in efficacy and bone and renal safety.

The war on severe acute respiratory syndrome: United States Forces Korea's campaign plan.

A mysterious new respiratory illness known as severe acute respiratory syndrome (SARS) has become the most perplexing infectious disease to emerge in the 21st century. From March to May 2003, it competed daily with the war in Iraq as the most sensational media event of the moment. U.S. personnel serving in the Republic of Korea represented the largest U.S. military population at risk for SARS. With tensions growing between Pyongyang and Washington, the United States/Republic of Korea alliance could not afford to be rendered combat ineffective by SARS. To remain mission ready, the U.S. Forces Korea (USFK) commander declared a "War on SARS" and directed his medical staff to develop a plan to prevent a SARS outbreak among USFK personnel. This article outlines the USFK campaign plan for the SARS epidemic and documents lessons learned for future outbreaks of highly infectious diseases.