Recent measurements of inertial particles in isotropic turbulence (Hammond & Meng, J. Fluid Mech., vol. 921, 2021, A16) revealed surprising extreme clustering of particles at near-contact separations $(r)$, whereby the radial distribution function, $g(r)$, grows from $O(10)$ to $O(10^3)$ with a $(r/a)^{-6}$ scaling (where $a$ is the particle radius), and a surprising upturn of the mean inward particle-pair relative velocity (MIRV). Hydrodynamic interactions (HIs) were proposed to explain the extreme clustering, but despite predicting the correct scaling $(r/a)^{-6}$, the HI theory underpredicted $g(r)$ by at least two orders of magnitude (Bragg et al., J. Fluid Mech., vol. 933, 2022, A31). To further understand the extreme clustering phenomenon and the relevance of HI, we characterize $g(r)$ and particle-pair kinematics for Stokes numbers $0.07 \leq St \leq 3.68$ in a homogeneous isotropic turbulence chamber using three-dimensional (3-D) particle tracking resolved to near–contact. A drift–diffusion equation governing $g(r)$ is presented to investigate the kinematic mechanisms of particle pairs. Measurements in all 24 conditions show that when $r/a\lessapprox 20$, extreme clustering consistently occurs, scaling as $g(r) \sim (r/a)^{-k}$ with $4.5 \leq k \leq 7.6$, which increases with $St$. Here $g(r)$ varies with $St$, particle size, density and polydispersity in ways that HI cannot explain. The extreme clustering region features an inward drift contributed by particle-pair turbophoresis and an inward radial relative acceleration. The latter indicates an interparticle attractive force at these separations that HI also cannot explain. The MIRV turns upward when approaching the extreme clustering region, opposite to direct numerical simulation predictions. These observations further support our previous assessment that extreme clustering arises from particle–particle interactions, but HI is not the main mechanism.

Background: Assessment of patients for temporal lobe epilepsy (TLE) surgery requires multimodality input, including EEG to ensure optimal surgical planning. Often EEG demonstrates abnormal foci not detected on clinical MRI. 7T MRI provides improved resolution and we investigated its utility to detect potential abnormalities associated with EEG. Methods: Images were acquired on 7T MRI scanner (N=13) in oatients with TLE. Evaluation of 7T imaging for focal abnormalities was performed. Correlation of 7T MRI findings with EEG of focal slowing or interictal epileptic spikes (IEDs) and seizures was performed. Results: Assessment of 7T MRI demonstrated concordance with TLE in 8/13 cases. Three cases exhibited abnormal 7T MRI abnormalities not detected by 1.5 T MRI. Eleven out of 13 cases had EEG findings without anatomic correlates on MRI, with IEDs localizing to contralateral temporal, frontal, and parieto-occipital lobes. 7T images did not reveal focal anatomical abnormalities to account for the EEG findings in these patients. Conclusions: To our knowledge, this is the first study to investigate the role of 7T MRI in relation to EEG abnormalities. 7T RI findings show concordance with clinical data. 7T MRI did not reveal anatomical findings to account for EEG abnormalities, suggesting that such changes may be functional rather than anatomical.

Expanding recent observations by Hammond & Meng (J. Fluid Mech., vol. 921, 2021, A16), we present a range of detailed experimental data of the radial distribution function (r.d.f.) of inertial particles in isotropic turbulence for different Stokes number, $St$, showing that the r.d.f. grows explosively with decreasing separation r, exhibiting $r^{-6}$ scaling as the collision radius is approached, regardless of $St$ or particle radius $a$. To understand such explosive clustering, we correct a number of errors in the theory by Yavuz et al. (Phys. Rev. Lett., vol. 120, 2018, 244504) based on hydrodynamic interactions between pairs of small, weakly inertial particles. A comparison between the corrected theory and the experiment shows that the theory by Yavuz et al. underpredicts the r.d.f. by orders of magnitude. To explain this discrepancy, we explore several alternative mechanisms for this discrepancy that were not included in the theory and show that none of them are likely the explanation. This suggests new, yet-to-be-identified physical mechanisms are at play, requiring further investigation and new theories.

Susceptibility to infection such as SARS-CoV-2 may be influenced by host genotype. TwinsUK volunteers (n = 3261) completing the C-19 COVID-19 symptom tracker app allowed classical twin studies of COVID-19 symptoms, including predicted COVID-19, a symptom-based algorithm to predict true infection, derived from app users tested for SARS-CoV-2. We found heritability of 49% (32−64%) for delirium; 34% (20−47%) for diarrhea; 31% (8−52%) for fatigue; 19% (0−38%) for anosmia; 46% (31−60%) for skipped meals and 31% (11−48%) for predicted COVID-19. Heritability estimates were not affected by cohabiting or by social deprivation. The results suggest the importance of host genetics in the risk of clinical manifestations of COVID-19 and provide grounds for planning genome-wide association studies to establish specific genes involved in viral infectivity and the host immune response.

TwinsUK is the largest cohort of community-dwelling adult twins in the UK. The registry comprises over 14,000 volunteer twins (14,838 including mixed, single and triplets); it is predominantly female (82%) and middle-aged (mean age 59). In addition, over 1800 parents and siblings of twins are registered volunteers. During the last 27 years, TwinsUK has collected numerous questionnaire responses, physical/cognitive measures and biological measures on over 8500 subjects. Data were collected alongside four comprehensive phenotyping clinical visits to the Department of Twin Research and Genetic Epidemiology, King’s College London. Such collection methods have resulted in very detailed longitudinal clinical, biochemical, behavioral, dietary and socioeconomic cohort characterization; it provides a multidisciplinary platform for the study of complex disease during the adult life course, including the process of healthy aging. The major strength of TwinsUK is the availability of several ‘omic’ technologies for a range of sample types from participants, which includes genomewide scans of single-nucleotide variants, next-generation sequencing, metabolomic profiles, microbiomics, exome sequencing, epigenetic markers, gene expression arrays, RNA sequencing and telomere length measures. TwinsUK facilitates and actively encourages sharing the ‘TwinsUK’ resource with the scientific community — interested researchers may request data via the TwinsUK website (http://twinsuk.ac.uk/resources-for-researchers/access-our-data/) for their own use or future collaboration with the study team. In addition, further cohort data collection is planned via the Wellcome Open Research gateway (https://wellcomeopenresearch.org/gateways). The current article presents an up-to-date report on the application of technological advances, new study procedures in the cohort and future direction of TwinsUK.

As image analysis expands into clinical and basic applications it is important that users be aware of opportunities and limitations. A common image analysis workflow involves the digitization of stained tissue sections into a red-green-blue (RGB) colour model for quantitative interpretation. Upstream of the digital image, quality and variability can be degraded at each step (tissue handling, fixation, sectioning, staining, image acquisition). Digital image analysis presents additional steps where variables can affect data quality. Image analysis platforms are not uniform. Aside from interface preferences, some introduce unintended variability due to their processing architecture that may not be obvious to the end-user. One important component of this is colour space representation: hue-saturation-intensity (HSI) vs. colour deconvolution (CD). A potential weakness of analyses within the HSI colour space is the mis-identification of darkly stained pixels, particularly when more than one stain is present. We were interested to discover whether HSI or CD provided greater fidelity in a typical immunoperoxidase/hematoxylin dataset.

Fifty-nine samples were processed using HSI- and CD-based analyses. Processed image pairs were compared with the original sample to determine which processed image provided a more accurate representation. CD proved superior to HSI in 94.9% of the analyzed image pairs. Where the option exists, CD-based image analysis is strongly recommended.

Objectives: People living with HIV (PLWH) are more likely to report sleep difficulties and cognitive deficits. While cognitive impairment associated with sleep problems have been found in healthy and medical populations, less is known about the effects of poor sleep health (SH) on cognition among PLWH. This study examined differences in cognitive performance among participants classified based upon their HIV status and reported SH. Methods: One hundred sixteen (N=116) adults recruited from the Greater Los Angeles community were administered a comprehensive cognitive test battery and completed a questionnaire about SH. Participants were classified into the following HIV/SH groups: [HIV+/good sleep health (SH+; n=34); HIV−/SH+ (n=32); HIV−/poor sleep health (SH−; n=18) and HIV+/SH− (n=32)]. Results: For both HIV+ and HIV− individuals, poor SH was associated with lower cognitive performance, with the domains of learning and memory driving the overall relationship. The HIV+/SH− group had poorer scores in domains of learning and memory compared to the SH+ groups. Additionally, the HIV−/SH− group demonstrated poorer learning compared to the HIV−/SH+ group. Conclusions: Our findings suggest that sleep problems within medical populations are relevant to cognitive functioning, highlighting the clinical and scientific importance of monitoring sleep health and cognition to help identify individuals at greatest risk of poor health outcomes. Longitudinal investigations using both objective and subjective measures of sleep are needed to determine the robustness of the current findings and the enduring effects of poor SH in the context of chronic disease. (JINS, 2018, 24, 1038–1046)

We describe a model for framework silicates in which the SiO4 (and AlO4) tetrahedra are treated as perfectly rigid and freely jointed. From this model we are able to identify low-energy modes of distortion of the structure, which we call Rigid unit modes. These modes can act as soft modes to allow easy distortions at phase transition. We discuss three forces that will operate at a phase transition in conjunction with the candidate soft modes to determine which of the rigid unit modes will actually precipitate a phase transition, and illustrate these ideas by detailed discussions of the phase transitions in quartz, leucite and cristobalite. The model can also be used to estimate the transition temperature, and the theory highlights an important role for the stiffness of the tetrahedra.

We apply the Rigid Unit Mode model, which was initially developed for crystalline silicates, to the study of the flexibility of silica glass. Using a density-of-states approach we show that silica glass has the same flexibility against infinitesimal displacements of crystalline phases. Molecular dynamics simulations also show that parts of the silica structure are able to undergo large spontaneous changes through reorientations of the SiO4 tetrahedra with no energy cost.

Twin researchers face the challenge of accurately determining the zygosity of twins for research. As part of the annual questionnaire between 1999 and 2006, 8,307 twins from the TwinsUK registry were asked to complete five questions (independently from their co-twin) to ascertain their self-perceived zygosity during childhood on up to five separate occasions. This questionnaire is known as the ‘peas in the pod’ questionnaire (PPQ), but there is little evidence of its validation. Answers were scored and classified as monozygotic (MZ), dizygotic (DZ), or unknown zygosity (UZ) and were compared with 4,484 twins with genotyping data who had not been selected for zygosity. Of these, 3,859 individuals (46.5% of those who had a zygosity from PPQ) had zygosity classified by both the PPQ and genotyping. Of the 708 individual twins whose answers meant that they were consistently classed as MZ in the PPQ, 683 (96.5%) were MZ within the genotype data. Of the 945 individual twins consistently classed as DZ within questionnaire, 936 (99.0%) were DZ in the genotype data. Where both twins scored MZ consistently across multiple questionnaires, 99.6% were MZ on genotyping, 99.7% were DZ on genotyping if both twins consistently scored DZ. However, for the initial questionnaire, 88.6% of those scoring as MZ were genotypically MZ and 98.7% DZ. For twin pairs where both scored UZ, 94.7% were DZ. Using the PPQ on a single occasion provided a definitive classification of whether the twin was MZ or DZ with an overall accuracy of 86.9%, increasing to 97.9% when there was a consistent classification of zygosity across multiple questionnaires. This study has shown that the PPQ questionnaire is an excellent proxy indicator of zygosity in the absence of genotyping information.

The effects of Reynolds number ($R_{\unicode[STIX]{x1D706}}$) and Stokes number ($St$) on particle-pair relative velocity (RV) are investigated systematically using a recently developed planar four-frame particle tracking technique in a novel homogeneous and isotropic turbulence chamber. We compare the measured results with direct numerical simulation (DNS), verifying whether the conclusions of the DNS for simplified conditions and limited $R_{\unicode[STIX]{x1D706}}$ are still valid in reality. Two experiments are performed: varying $R_{\unicode[STIX]{x1D706}}$ between 246 and 357 at six $St$ values, and varying $St$ between 0.02 and 4.63 at five $R_{\unicode[STIX]{x1D706}}$ values. The measured mean inward particle-pair RV $\langle w_{r}^{-}\rangle$ as a function of separation distance $r$ is compared with the DNS under closely matched conditions. At all experimental conditions, an excellent agreement is achieved, except when the particle separation distance $r\lesssim 10\unicode[STIX]{x1D702}$ ($\unicode[STIX]{x1D702}$ is the Kolmogorov length scale), where the experimental $\langle w_{r}^{-}\rangle$ is consistently higher, possibly due to particle polydispersity and finite laser thickness in the experiments (Dou et al., arXiv:1712.07506, 2017). At any fixed $St,\langle w_{r}^{-}\rangle$ is essentially independent of $R_{\unicode[STIX]{x1D706}}$, echoing the DNS finding of Ireland et al. (J. Fluid Mech., vol. 796, 2016, pp. 617–658). At any fixed $R_{\unicode[STIX]{x1D706}}$, $\langle w_{r}^{-}\rangle$ increases with $St$ at small $r$, showing dominance of the path-history effect in the dissipation range when $St\gtrsim O(1)$, but decreases with $St$ at large $r$, indicating dominance of inertial filtering. We further compare the $\langle w_{r}^{-}\rangle$ and RV variance $\langle w_{r}^{2}\rangle$ from experiments with DNS and theoretical predictions by Pan & Padoan (J. Fluid Mech., vol. 661, 2010, pp. 73–107). For $St\lesssim 1$, experimental $\langle w_{r}^{-}\rangle$ and $\langle w_{r}^{2}\rangle$ match these values well at $r\gtrsim 10\unicode[STIX]{x1D702}$, but they are higher than both DNS and theory at $r\lesssim 10\unicode[STIX]{x1D702}$. For $St\gtrsim 1$, $\langle w_{r}^{-}\rangle$ from all three match well, except for $r\lesssim 10\unicode[STIX]{x1D702}$, for which experimental values are higher, while $\langle w_{r}^{2}\rangle$ from experiment and DNS are much higher than theoretical predictions. We discuss potential causes of these discrepancies. What this study shows is the first experimental validation of $R_{\unicode[STIX]{x1D706}}$ and $St$ effect on inertial particle-pair $\langle w_{r}^{-}\rangle$ in homogeneous and isotropic turbulence.

Objectives: We describe a new evidence-based method for screening and evaluating emerging medical technologies. Washington State agencies, under legislative direction, have granted authority to its agency Medical Directors and policy leaders to make coverage decisions on medical technologies using a “dossier” process. The dossier process is employed when technology advocates or manufacturers request Washington State healthcare purchasers to pay for new and emerging technologies. This offers the advocate an opportunity to submit scientific evidence and information classically associated with a more formal health technology assessment.

Methods: The submitted information is independently reviewed and summarized for Washington State's public healthcare purchasers allowing a more standardized coverage decision for all public purchasers in Washington State.

Results: This process has allowed Washington State to make twelve evidence-based coverage decisions at a fraction of the cost of classic technology assessment. To date, of twelve reviews over 6 years, one health technology was approved for coverage, ten were not covered and one did not require a coverage decision.

Conclusions: This evidence-based dossier process has yielded high-value coverage decisions of new and emerging medical technologies for public healthcare purchasers in Washington State.

While in the design of aircraft hydraulic equipment and landing gear, the final choice of materials used is obviously influenced by a large number of factors including space, wear corrosion resistance, fatigue and, the achievement of minimum weight at an economic cost is usually a primary consideration, the acceptable premium for each kg of weight saved varying from under £5 to over £200 depending on the aircraft type.

The range of materials available to the equipment designer is wide and it is therefore desirable to formulate some guide lines to assist the designer in making the most appropriate material selection for the type of equipment being considered.