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Mediolateral balance control during walking is a challenging task in post-stroke hemiparetic individuals. To detect and treat dynamic balance disorders, it is important to assess balance using reliable methods. The Berg Balance Scale (BBS), Dynamic Gait Index (DGI), margin-of-stability (MoS), and peak-to-peak range of angular-momentum (H) are some of the most commonly used measures to assess dynamic balance and fall risk in clinical and laboratory settings. However, it is not clear if these measures lead to similar conclusions. Thus, the purpose of this study was to assess dynamic balance in post-stroke hemiparetic individuals using BBS, DGI, MoS and the range of H and determine if these measure are correlated. BBS and DGI were collected from 19 individuals post-stroke. Additionally, kinematic and kinetic data were collected while the same individuals walked at their self-selected speed. MoS and the range of H were calculated in the mediolateral direction for each participant. Correlation analyses revealed moderate associations between all measures. Overall, a higher range of angular-momentum was associated with a higher MoS, wider step width and lower BBS and DGI scores, indicating poor balance control. Further, only the MoS from the paretic foot placement, but not the nonparetic foot, correlated with the other balance measures. Although moderate correlations existed between all the balance measures, these findings do not necessarily advocate the use of a single measure as each test may assess different constructs of dynamic balance. These findings have important implications for the use and interpretation of dynamic balance assessments.

Current methods of balance assessment in the clinical environment are often subjective, time-consuming and lack clinical relevance for non-ambulatory older adults. The objective of this study was to develop a novel method of balance assessment that utilizes data collected using the Microsoft Kinect 2 to create a Berg Balance Scale score, which is completely determined by statistical methods rather than by human evaluators. 74 older adults, both healthy and balance impaired, were recruited for this trial. All participants completed the Berg Balance Scale (BBS) which was scored independently by trained physical therapists. Participants then completed the items of the “Modified Berg Balance Scale” in front of the Microsoft Kinect camera. Kinematic data collected during this measurement was used to train a feed-forward neural network that was used to assign a Berg Balance Scale score. The neural network model estimated the clinician-assigned BBS score to within a median of 0.93 points for the participants in our sample population (range: 0.02–5.69). Using low-cost depth sensing camera technology and a clinical protocol that takes less than 5 min to complete in both ambulatory and non-ambulatory older adults, the method outlined in this manuscript can accurately predict a participant’s BBS score and thereby identify whether they are deemed a high fall risk or not. If implemented correctly, this could enable fall prevention services to be deployed in a timely fashion using low-cost, accessible technology, resulting in improved safety of older adults.

There are strong indications that many consumers are switching towards more socially and environmentally responsible products and services, reflecting a shift in consumer values indicated in several countries. However, little is known about the motives that drive some toward, or deter others from, higher levels of ethical concern and action in their purchasing decisions. Following a qualitative investigation using ZMET and focus group discussions, a questionnaire was developed and administered to a representative sample of consumers; nearly 1,000 usable questionnaires were collected. The degree of awareness, concern and action regarding 16 ethical issues was quantified, using a measure developed from the Stages of Change concept within the Transtheoretical model. Motivations for ethical behaviour, in relation to each individual's most salient ethical issue, were investigated using initially 22 motive statements within the framework of the Decisional Balance Scale (DBS). The findings suggest that the DBS and Stages model have an explanatory value within the ethical decision-making context, and that the motives identified do reflect the Decisional Balance Constructs. Indeed the study suggests that respondents' motivational attitudes are a function of their stage of ethical awareness, concern and action. Therefore, the Decisional Balance Scale may well prove useful for designing appropriate interventions and communications to facilitate movement towards more ethical decision-making. These findings yield strategic insight for communicating messages to ethical consumers and for better understanding their purchasing decisions.

Living systems break detailed balance at small scales, consuming energy and producing entropy in the environment to perform molecular and cellular functions. However, it remains unclear how broken detailed balance manifests at macroscopic scales and how such dynamics support higher-order biological functions. Here we present a framework to quantify broken detailed balance by measuring entropy production in macroscopic systems. We apply our method to the human brain, an organ whose immense metabolic consumption drives a diverse range of cognitive functions. Using whole-brain imaging data, we demonstrate that the brain nearly obeys detailed balance when at rest, but strongly breaks detailed balance when performing physically and cognitively demanding tasks. Using a dynamic Ising model, we show that these large-scale violations of detailed balance can emerge from fine-scale asymmetries in the interactions between elements, a known feature of neural systems. Together, these results suggest that violations of detailed balance are vital for cognition and provide a general tool for quantifying entropy production in macroscopic systems.

Traditionally metacommunity studies have quantified the relative importance of dispersal and environmental processes on observed β-diversity. Separating β-diversity into its replacement and nestedness components and linking such patterns to metacommunity drivers can provide richer insights into biodiversity organization across spatial scales. It is often very difficult to measure actual dispersal rates in the field and to define the boundaries of natural metacommunities. To overcome those limitations, we revisited an experimental metacommunity dataset to test the independent and interacting effects of environmental heterogeneity and dispersal on each component of β-diversity. We show that the balance between the replacement and nestedness components of β-diversity resulting from eutrophication changes completely depending on dispersal rates. Nutrient enrichment negatively affected local zooplankton diversity and generated a pattern of β-diversity derived from nestedness in unconnected, environmentally heterogeneous landscapes. Increasing dispersal erased the pattern of nestedness, whereas the replacement component gained importance. In environmentally homogeneous metacommunities, dispersal limitation created community dissimilarity via species replacement whereas the nestedness component remained low and unchanged across dispersal levels. Our study provides novel insights into how environmental heterogeneity and dispersal interact and shape metacommunity structure.

Hydrogen embrittlement of high-strength steel is an obstacle for using these steels in sustainable energy production. Hydrogen embrittlement involves hydrogen-defect interactions at multiple-length scales. However, the challenge of measuring the precise location of hydrogen atoms limits our understanding. Thermal desorption spectroscopy can identify hydrogen retention or trapping, but data cannot be easily linked to the relative contributions of different microstructural features. We used cryo-transfer atom probe tomography to observe hydrogen at specific microstructural features in steels. Direct observation of hydrogen at carbon-rich dislocations and grain boundaries provides validation for embrittlement models. Hydrogen observed at an incoherent interface between niobium carbides and the surrounding steel provides direct evidence that these incoherent boundaries can act as trapping sites. This information is vital for designing embrittlement-resistant steels.

The constituent particles of matter can arrange themselves in various ways, giving rise to emergent phenomena that can be surprisingly rich and often cannot be understood by studying only the individual constituents. Discovering and understanding the emergence of such phenomena in quantum materials—especially those in which multiple degrees of freedom or energy scales are delicately balanced—is of fundamental interest to condensed-matter research 1 , 2 . Here we report on the surprising observation of emergent ferroelectricity in graphene-based moiré heterostructures. Ferroelectric materials show electrically switchable electric dipoles, which are usually formed by spatial separation between the average centres of positive and negative charge within the unit cell. On this basis, it is difficult to imagine graphene—a material composed of only carbon atoms—exhibiting ferroelectricity 3 . However, in this work we realize switchable ferroelectricity in Bernal-stacked bilayer graphene sandwiched between two hexagonal boron nitride layers. By introducing a moiré superlattice potential (via aligning bilayer graphene with the top and/or bottom boron nitride crystals), we observe prominent and robust hysteretic behaviour of the graphene resistance with an externally applied out-of-plane displacement field. Our systematic transport measurements reveal a rich and striking response as a function of displacement field and electron filling, and beyond the framework of conventional ferroelectrics. We further directly probe the ferroelectric polarization through a non-local monolayer graphene sensor. Our results suggest an unconventional, odd-parity electronic ordering in the bilayer graphene/boron nitride moiré system. This emergent moiré ferroelectricity may enable ultrafast, programmable and atomically thin carbon-based memory devices. Electronic ferroelectricity is observed in a graphene-based moiré heterostructure, which is explained using a spontaneous interlayer charge-transfer model driven by layer-specific on-site Coulomb repulsion.

Torque sensors such as the torsion balance enabled the first determination of the gravitational constant by Henri Cavendish1 and the discovery of Coulomb’s law. Torque sensors are also widely used in studying small-scale magnetism2,3, the Casimir effect4 and other applications5. Great effort has been made to improve the torque detection sensitivity by nanofabrication and cryogenic cooling. Until now, the most sensitive torque sensor has achieved a remarkable sensitivity of 2.9 × 10−24 N m Hz−1/2 at millikelvin temperatures in a dilution refrigerator6. Here, we show a torque sensor reaching sensitivity of (4.2 ± 1.2) × 10−27 N m Hz−1/2 at room temperature. It is created by an optically levitated nanoparticle in vacuum. Our system does not require complex nanofabrication. Moreover, we drive a nanoparticle to rotate at a record high speed beyond 5 GHz (300 billion r.p.m.). Our calculations show that this system will be able to detect the long sought after vacuum friction7–10 near a surface under realistic conditions. The optically levitated nanorotor will also have applications in studying nanoscale magnetism2,3 and the quantum geometric phase11.A torque sensitivity of (4.2 ± 1.2) × 10−27 N m Hz−1/2 is achieved at room temperature. This sensitivity would be enough to measure vacuum friction.

Schizophrenia is one of the most common, burdensome, and costly psychiatric disorders in adults worldwide. Antipsychotic drugs are its treatment of choice, but there is controversy about which agent should be used. We aimed to compare and rank antipsychotics by quantifying information from randomised controlled trials. We did a network meta-analysis of placebo-controlled and head-to-head randomised controlled trials and compared 32 antipsychotics. We searched Embase, MEDLINE, PsycINFO, PubMed, BIOSIS, Cochrane Central Register of Controlled Trials (CENTRAL), WHO International Clinical Trials Registry Platform, and ClinicalTrials.gov from database inception to Jan 8, 2019. Two authors independently selected studies and extracted data. We included randomised controlled trials in adults with acute symptoms of schizophrenia or related disorders. We excluded studies in patients with treatment resistance, first episode, predominant negative or depressive symptoms, concomitant medical illnesses, and relapse-prevention studies. Our primary outcome was change in overall symptoms measured with standardised rating scales. We also extracted data for eight efficacy and eight safety outcomes. Differences in the findings of the studies were explored in metaregressions and sensitivity analyses. Effect size measures were standardised mean differences, mean differences, or risk ratios with 95% credible intervals (CrIs). Confidence in the evidence was assessed using CINeMA (Confidence in Network Meta-Analysis). The study protocol is registered with PROSPERO, number CRD42014014919. We identified 54 417 citations and included 402 studies with data for 53 463 participants. Effect size estimates suggested all antipsychotics reduced overall symptoms more than placebo (although not statistically significant for six drugs), with standardised mean differences ranging from −0·89 (95% CrI −1·08 to −0·71) for clozapine to −0·03 (−0·59 to 0·52) for levomepromazine (40 815 participants). Standardised mean differences compared with placebo for reduction of positive symptoms (31 179 participants) varied from −0·69 (95% CrI −0·86 to −0·52) for amisulpride to −0·17 (−0·31 to −0·04) for brexpiprazole, for negative symptoms (32 015 participants) from −0·62 (−0·84 to −0·39; clozapine) to −0·10 (−0·45 to 0·25; flupentixol), for depressive symptoms (19 683 participants) from −0·90 (−1·36 to −0·44; sulpiride) to 0·04 (−0·39 to 0·47; flupentixol). Risk ratios compared with placebo for all-cause discontinuation (42 672 participants) ranged from 0·52 (0·12 to 0·95; clopenthixol) to 1·15 (0·36 to 1·47; pimozide), for sedation (30 770 participants) from 0·92 (0·17 to 2·03; pimozide) to 10·20 (4·72 to 29·41; zuclopenthixol), for use of antiparkinson medication (24 911 participants) from 0·46 (0·19 to 0·88; clozapine) to 6·14 (4·81 to 6·55; pimozide). Mean differences compared to placebo for weight gain (28 317 participants) ranged from −0·16 kg (−0·73 to 0·40; ziprasidone) to 3·21 kg (2·10 to 4·31; zotepine), for prolactin elevation (21 569 participants) from −77·05 ng/mL (−120·23 to −33·54; clozapine) to 48·51 ng/mL (43·52 to 53·51; paliperidone) and for QTc prolongation (15 467 participants) from −2·21 ms (−4·54 to 0·15; lurasidone) to 23·90 ms (20·56 to 27·33; sertindole). Conclusions for the primary outcome did not substantially change after adjusting for possible effect moderators or in sensitivity analyses (eg, when excluding placebo-controlled studies). The confidence in evidence was often low or very low. There are some efficacy differences between antipsychotics, but most of them are gradual rather than discrete. Differences in side-effects are more marked. These findings will aid clinicians in balancing risks versus benefits of those drugs available in their countries. They should consider the importance of each outcome, the patients' medical problems, and preferences. German Ministry of Education and Research and National Institute for Health Research

Magnetic fields in plasmas can rapidly rearrange themselves in a process known as magnetic reconnection, which releases energy and accelerates particles. Torbert et al. used the Magnetospheric Multiscale (MMS) mission to probe a reconnection event in Earth's magnetotail—the region of plasma downstream from the planet as it moves through the solar wind. MMS has previously studied reconnection in the upstream magnetopause, but a different orbit was used to study the magnetotail, where the symmetry of the process is different. The authors measured plasma properties on scales of the electron dynamics, leading to insights that will apply in other regions where magnetic reconnection occurs. Science , this issue p. 1391 Magnetic reconnection in Earth’s magnetotail is observed on electron dynamics scales. Magnetic reconnection is an energy conversion process that occurs in many astrophysical contexts including Earth’s magnetosphere, where the process can be investigated in situ by spacecraft. On 11 July 2017, the four Magnetospheric Multiscale spacecraft encountered a reconnection site in Earth’s magnetotail, where reconnection involves symmetric inflow conditions. The electron-scale plasma measurements revealed (i) super-Alfvénic electron jets reaching 15,000 kilometers per second; (ii) electron meandering motion and acceleration by the electric field, producing multiple crescent-shaped structures in the velocity distributions; and (iii) the spatial dimensions of the electron diffusion region with an aspect ratio of 0.1 to 0.2, consistent with fast reconnection. The well-structured multiple layers of electron populations indicate that the dominant electron dynamics are mostly laminar, despite the presence of turbulence near the reconnection site.