Measures Of Variability Research Articles

Acoustic neuromodulation with or without micro-voltage tACS reduces post-concussive symptoms

ABSTRACT Objective Persistent post-concussive symptoms (PPCS) are common and disruptive, particularly in military service members (SM), yet there are no approved therapies targeting underlying physiological processes. This study was designed to compare acoustic neuromodulation using Cereset Research™ Standard Operating Procedures (CR-SOP), with Cereset Research Cranial Electrical Stimulation (CR-CES), on PPCS. Methods SM, veterans, or dependents with PPCS (Neurobehavioral Symptom Inventory [NSI] Score ≥23) were randomized to receive 10 sessions of engineered tones linked to brainwaves (CR-SOP) or 5 sessions of CR-CES, which adds intermittent low voltage transcranial alternating current stimulation (tACS) to CR-SOP. Designed to assess non-inferiority between varied doses of CR-SOP and CR-CES, the primary outcome was a change in post-concussive symptoms on the NSI, with secondary outcomes of heart rate variability (HRV) and self-report measures of PTSD, sleep, headaches, and depression. Results Among study participants (n = 80, 21.3% female, mean age 40.2 [SD 13.2], 4.8 deployments, 3.2 TBIs), mean NSI declined from 45.6 to 29.5 after intervention (p < 0.0001), with gains sustained at 3 months (29.7). No significant between group differences for NSI (CR-SOP: baseline 43.9, post-intervention 26.0, 3-month 27.2, and CR-CES 46.4, 30.7, and 31.1, respectively), and no evidence of inferiority between the groups with respect to NSI. Similar improvements were seen on PCL-5, ISI, HIT-6, and PHQ-9, with no HRV differences between groups. Conclusion Both acoustic neuromodulation alone (CR-SOP) and a lower dose of CR-SOP, with tACS added (CR-CES), significantly improved PPCS out to 3 months. Registration ClinicalTrials.gov – NCT03649958

The association between insomnia (related symptoms) and glycaemic control: a systematic review and meta-analysis.

Insomnia characterised by difficulties in falling asleep and maintaining sleep, and early awaking, is a prevalent worldwide sleep disorder. While previous studies have suggested an association between insomnia and adverse glycaemic control, the evidence remains inconclusive. Therefore, this meta-analysis aims to explore this association. Insomnia was assessed based on defined criteria, including related symptoms such as poor sleep quality and low sleep efficiency. Glycaemic control was evaluated using indicators such as fasting plasma glucose, haemoglobin A1c, and the presence of diabetes. A literature search was performed in PubMed, Web of Science, and Scopus. The quality of the included studied was assessed using The Newcastle-Ottawa Scale. Effect sizes, including odds ratio, relative risk, mean difference, and standard mean difference, were chosen based on data type. Forest plots visually displayed pooled effect sizes and corresponding 95% confidence intervals, while the I2 test calculated heterogeneity. Meta-regression and subgroup analysis explored potential sources of heterogeneity. Leave-one-out sensitivity analysis assessed result robustness, and Begg's and Egger's tests evaluated publication bias. Ninety-one articles, comprising 84 are cross-sectional studies, (five are case-control studies, and two are cohort studies) with 2 217 521 participants, were included. Ten separate meta-analyses were conducted based on variable type (binary/continuous), study design (cross-sectional, case-control, or cohort), and measurement of exposures/outcomes. All meta-analyses indicated a positive association between insomnia (related symptoms) and adverse glycaemic control. However, three meta-analyses showed significant heterogeneity, and three lacked robustness. No publication bias was detected across any of the analyses. Insomnia is likely associated with adverse glycaemic control. As the included studies are observational, future research should prioritise diverse methodologies and robust study designs to further explore this complex relationship. insomnia, insomnia related symptoms, glycaemic control, systematic review, meta-analysis. PROSPERO CRD42024491688.

A Methodology for the Multitemporal Analysis of Land Cover Changes and Urban Expansion Using Synthetic Aperture Radar (SAR) Imagery: A Case Study of the Aburrá Valley in Colombia

The Aburrá Valley, located in the northwestern region of Colombia, has undergone significant land cover changes and urban expansion in recent decades, driven by rapid population growth and infrastructure development. This region, known for its steep topography and dense urbanization, faces considerable environmental challenges. Monitoring these transformations is essential for informed territorial planning and sustainable development. This study leverages Synthetic Aperture Radar (SAR) imagery from the Sentinel-1 mission, covering 2017–2024, to propose a methodology for the multitemporal analysis of land cover dynamics and urban expansion in the valley. The novel proposed methodology comprises several steps: first, monthly SAR images were acquired for every year under study from 2017 to 2024, ensuring the capture of surface changes. These images were properly calibrated, rescaled, and co-registered. Then, various multitemporal fusions using statistics operations were proposed to detect and find different phenomena related to land cover and urban expansion. The methodology also involved statistical fusion techniques—median, mean, and standard deviation—to capture urbanization dynamics. The kurtosis calculations highlighted areas where infrequent but significant changes occurred, such as large-scale construction projects or sudden shifts in land use, providing a statistical measure of surface variability throughout the study period. An advanced clustering technique segmented images into distinctive classes, utilizing fuzzy logic and a kernel-based method, enhancing the analysis of changes. Additionally, Pearson correlation coefficients were calculated to explore the relationships between identified land cover change classes and their spatial distribution across nine distinct geographic zones in the Aburrá Valley. The results highlight a marked increase in urbanization, particularly along the valley’s periphery, where previously vegetated areas have been replaced by built environments. Additionally, the visual inspection analysis revealed areas of high variability near river courses and industrial zones, indicating ongoing infrastructure and construction projects. These findings emphasize the rapid and often unplanned nature of urban growth in the region, posing challenges to both natural resource management and environmental conservation efforts. The study underscores the need for the continuous monitoring of land cover changes using advanced remote sensing techniques like SAR, which can overcome the limitations posed by cloud cover and rugged terrain. The conclusions drawn suggest that SAR-based multitemporal analysis is a robust tool for detecting and understanding urbanization’s spatial and temporal dynamics in regions like the Aburrá Valley, providing vital data for policymakers and planners to promote sustainable urban development and mitigate environmental degradation.

Rett Syndrome Behaviour Questionnaire: Variability of Scores and Related Factors.

Objective: Rett syndrome (RTT) is a severe neurodevelopmental disorder affecting predominantly females and associated with variants in the MECP2 gene. Recent success in clinical trials have resulted in an expanded use of the Rett Syndrome Behaviour Questionnaire (RSBQ) for clinical and research purposes. Implementation of the RSBQ as a global clinical severity scale has raised concerns about its construct validity considering its content, structure, and psychometric features. To further understand RSBQ data, we analyzed RSBQ scores available in the literature with a focus on variability and influencing factors. Methods: We identified publications reporting RSBQ total and/or subscale scores and summarized relevant study information, such as type of investigation, administration method, and descriptive data. We then analyzed means and standard deviations, calculating variance-to-mean ratios (VMR), as a measure of variability, when raw score descriptive statistics were available. Where appropriate, we compared means and VMRs by Welch t-tests. Results: Of the 14 publications identified, raw total scores from 5 observational studies and 4 clinical trials (baseline) were available. Raw subscale scores from four of the five observational studies were also available. We found a wide but comparable range of mean total scores for observational studies and clinical trials. However, VMRs were significantly higher in observational studies. Subscale scores showed either high (i.e., General Mood, Breathing Problems) or low (e.g., Hand Behaviours, Body Rocking and Expressionless Face) variability. Available data demonstrated greater variability in pediatric than adult groups and less variability when using interviews or electronic RSBQ administration compared with paper forms. Total score changes over time did not affect variability. Although certain studies offered insight into the relationship between the RSBQ and other measures, overall, data were insufficient for characterizing how RSBQ variability relates to other factors. Conclusions: Our findings on score variability support the need for more comprehensive reporting of RSBQ data, cohort characterization, and methodology; and the deployment of standardized RSBQ administration methods, such as advanced data capture systems. There is potential for use of subscales as outcome measures, subject to further psychometric validation studies, including prospective investigations testing the stability of RSBQ scores and influencing factors. Further examining the relationship between RSBQ scores and other instruments will aid in its interpretation as a clinical outcome measure.

Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study.

Modern lifestyle risk factors, like physical inactivity and poor nutrition, contribute to rising rates of obesity and chronic diseases like type 2 diabetes and heart disease. Particularly personalized interventions have been shown to be effective for long-term behavior change. Machine learning can be used to uncover insights without predefined hypotheses, revealing complex relationships and distinct population clusters. New data-driven approaches, such as the factor probabilistic distance clustering algorithm, provide opportunities to identify potentially meaningful clusters within large and complex datasets. This study aimed to identify potential clusters and relevant variables among individuals with obesity using a data-driven and hypothesis-free machine learning approach. We used cross-sectional data from individuals with abdominal obesity from The Maastricht Study. Data (2971 variables) included demographics, lifestyle, biomedical aspects, advanced phenotyping, and social factors (cohort 2010). The factor probabilistic distance clustering algorithm was applied in order to detect clusters within this high-dimensional data. To identify a subset of distinct, minimally redundant, predictive variables, we used the statistically equivalent signature algorithm. To describe the clusters, we applied measures of central tendency and variability, and we assessed the distinctiveness of the clusters through the emerged variables using the F test for continuous variables and the chi-square test for categorical variables at a confidence level of α=.001. We identified 3 distinct clusters (including 4128/9188, 44.93% of all data points) among individuals with obesity (n=4128). The most significant continuous variable for distinguishing cluster 1 (n=1458) from clusters 2 and 3 combined (n=2670) was the lower energy intake (mean 1684, SD 393 kcal/day vs mean 2358, SD 635 kcal/day; P<.001). The most significant categorical variable was occupation (P<.001). A significantly higher proportion (1236/1458, 84.77%) in cluster 1 did not work compared to clusters 2 and 3 combined (1486/2670, 55.66%; P<.001). For cluster 2 (n=1521), the most significant continuous variable was a higher energy intake (mean 2755, SD 506.2 kcal/day vs mean 1749, SD 375 kcal/day; P<.001). The most significant categorical variable was sex (P<.001). A significantly higher proportion (997/1521, 65.55%) in cluster 2 were male compared to the other 2 clusters (885/2607, 33.95%; P<.001). For cluster 3 (n=1149), the most significant continuous variable was overall higher cognitive functioning (mean 0.2349, SD 0.5702 vs mean -0.3088, SD 0.7212; P<.001), and educational level was the most significant categorical variable (P<.001). A significantly higher proportion (475/1149, 41.34%) in cluster 3 received higher vocational or university education in comparison to clusters 1 and 2 combined (729/2979, 24.47%; P<.001). This study demonstrates that a hypothesis-free and fully data-driven approach can be used to identify distinguishable participant clusters in large and complex datasets and find relevant variables that differ within populations with obesity.

The impact of digital payments on the financial vulnerability of rural households: empirical evidence from China

IntroductionPoverty eradication is the primary goal of the United Nations 2030 Agenda for Sustainable Development (SDGs). Despite China’s significant achievements in poverty alleviation, many rural households still struggle to maintain a sustainable livelihood may even slip back into poverty due to ineffective risk responses when facing risks and challenges.MethodsThis study employs data from the 2017–2019 China Household Finance Survey to theoretically and empirically examine the impact and mechanisms of digital payments on the financial vulnerability of rural households.ResultsThe study’s results indicate that digital payments significantly reduce the financial vulnerability of rural households, a finding that remains robust even after accounting for endogeneity, employing alternative variable measurement approaches, and conducting propensity score matching tests. Mechanism analysis suggest that encouraging rural households to hold commercial insurance, engage in non-farm employment and expand their family social networks are key pathways by which digital payments impact the financial vulnerability of rural households. Further heterogeneity analyses reveal that digital payment plays a more substantial role in mitigating the financial vulnerability of rural households in the western region, which have low financial assets and high health risks, compared to those in the central and eastern regions, which have high financial assets and low health risks.DiscussionTherefore, this paper suggests that the government should continue to promote the in-depth integration of digital technology and financial services, strengthen the construction of rural digital infrastructure in areas lagging behind in traditional finance, enhance the comprehensive service function of digital payments, and enrich the coping strategies of farmers to mitigate financial vulnerability, while remaining vigilant about the potential consequences of digital payment.

Can Enterprise Digitalization Promote Green Technological Innovation? Evidence from China’s Manufacturing Sector

China’s manufacturing industry is characterized by high energy consumption and high pollution, which urgently requires resolution through green technological innovation. This study focuses on China’s A-share listed manufacturing enterprises to explore their development path for green technological innovation. The study primarily employs statistical regression analysis to uncover the causal link between digitalization and green technology innovation. The study’s conclusion indicates that the digitalization of manufacturing enterprises has significantly promoted green technological innovation. This conclusion remains robust after a series of tests, including alternative variable measurements, instrumental variable (IV) estimation, and counterfactual analysis. Mechanism analysis reveals that digitalization can enhance green technological innovation by improving human capital and innovating business models. The results of the heterogeneity analysis show that the effect of digitalization on promoting green technological innovation is more pronounced in enterprises with higher green awareness among senior executives, high green credit, non-heavy pollution industries, a higher level of existing green technological innovation, and larger enterprise scale. The government should increase support for the digital transformation of enterprises and promote green technological innovation by enhancing the green awareness of enterprise senior executives, optimizing green credit policies, formulating transformation policies for heavily polluting enterprises, implementing differentiated policies based on enterprise scale, and promoting digital transformation.

Can summary measures of magnitude and structure of trunk movement variability differentiate between people with and without chronic low back pain?

There is inconsistent evidence suggesting that people with chronic low back pain may differ in variability of repeated trunk movements compared to people without chronic low back pain. These inconsistencies may be due to low reliability and task dependence of movement variability measures, which can be addressed using multiple movement tasks and summary measures. Participants with and without chronic low back pain were recruited. Measurement sessions involved 30 repetitions of movements in the sagittal, transverse, and combined planes. Kinematics of the pelvis, thorax, and lumbar spine were estimated using inertial sensors placed on the sacrum and thorax. Magnitude of movement variability was quantified as the mean standard deviation of Euler angles for the thorax, pelvis, and lumbar spine across normalized cycles for each movement axes, resulting in 27 variables. Additionally, structure of variability was assessed using Lyapunov exponents for local dynamic stability, yielding 9 additional variables. Principal Component Analysis reduced the dimensionality of each variability measure (magnitude and structure). Stepwise logistic regression with principal component scores tested for differences between groups. In the magnitude of variability analysis, four principal components were retained. The first two principal components significantly differentiated between people with low back pain and controls, accounting for 32.5% and 14% of the total variance, respectively. In the structure of variability analysis, no principal components were found to significantly contribute to differentiating between the two groups. Summary measures of the magnitude, but not the structure, of trunk movement variability differentiated between people with and without chronic low back pain. NCT02059317, CPP: 2013.11.09bis Sud Méditerranée III, N° RCB: 2013-A01379-36.

Heart rate variability as a digital biomarker for frailty in cardiovascular patients.

Frailty is a syndrome associated with age-related impairments in multiple organ systems, of which the autonomic nervous system plays a fundamental role. Measurement of heart rate variability (HRV) is a non-invasive method to evaluate the autonomic activity and gain insights into cardiovascular health and potentially, frailty. A few small studies have explored the relationship between HRV and frailty, with promising but conflicting results. To investigate the relationship between HRV and frailty among adult patients with cardiovascular disease. A cross-sectional study was conducted using clinical data. Data were collected from an ambulatory cardiology clinic. The cohort comprised 155 patients with a mean age of 67 years (44 % female). HRV was assessed seated at rest for 2.5 min using a finger-based photoplethysmography (PPG) device. Frailty was assessed using the Clinical Frailty Scale (CFS), with a score ≥5 considered frail. Associations between HRV and frailty were examined using a Spearman correlation matrix and multivariable ordinal regression model. The LF/HF ratio (a frequency-domain measure reflecting imbalances between sympathetic and parasympathetic activity) was the primary HRV measure analyzed. The prevalence of frailty was 15 %. Among all HRV measures, the LF/HF ratio was most closely correlated with frailty (p < 0.001). In the multivariable model, each 1 standard deviation decrease in LF/HF ratio was associated with a 1.1-point increase in CFS (95 % CI 0.7-1.6, p < 0.001). The optimal ROC cutoff at which the LF/HF ratio was associated with frailty is ≤ 0.37. The LF/HF ratio is inversely correlated with the CFS and independently associated with frailty. Measurement of HRV is a promising technique to enrich existing frailty scales and assist in frailty assessments in an ambulatory cardiology clinic.

Abstract TMP51: Association between genetic variation and acute stroke characteristics

Introduction: Strokes lead to acute deficits with wide-ranging severity. Genetic variation may explain some of these inter-subject differences. The current report examined the relationship that candidate genetic variants have with acute injury and acute behavioral deficits. We hypothesized that variants known to be associated with poorer stroke recovery would also be associated with more a severe acute presentation. Methods: Infarcts were outlined on clinical scans acquired during acute stroke admission as part of the STRONG (“Stroke, sTress, RehabilitatiON, and Genetics”) study and resampled to MNI152 brain standard space. Multivariable linear regression modeling was used to examine association with genetic measures known to be related to stroke outcome: 3 single nucleotide polymorphisms (SNPs): BDNF (rs6265), ACE (rs4291), and FAAH (rs324420), plus ApoE e4 and ApoE e2; a dopamine polygene score was also explored. Acute injury (infarct volume) and acute deficits (NIHSS score, grip strength, and acute stress disorder inventory (ASDI)) were each examined as the dependent measure in separate models that used age, gender, and ancestry as covariates. To understand where in the brain these relationships occurred, voxel lesion symptom mapping (VLSM) was used to test for associations between acute injury and each genetic measure. Results: In 448 subjects (age 63.4±14.4 yr (mean±SD), 43.1% females), lesion volume ranged from 0.46 to 535.13 cc and involved cortical grey matter in 63% of patients. Larger lesion volume was associated with presence of the ACE SNP (β=8.77, p=0.03); lower NIHSS score, with ApoE e4 (β=-1.69, p=0.04); greater grip strength, with ApoE e2 SNPs (β=6.78, p=0.03); and higher ASDI, with the ACE SNP (β=0.56, p=0.05). VLSM revealed that acute injury to the postcentral gyrus was significantly more likely in the presence of the ACE SNP (z=-3.5), and that acute injury to the calcarine fissure was significantly more likely in the presence of the BDNF SNP (z=-2.53). Conclusions: Genetic variants known to be associated with differences in stroke recovery are also related to acute stroke deficits and injury. In particular, a common variant in the gene for ACE was associated with differences in lesion volume and location, findings that may suggest a personalized medicine approach to acute therapy. Measures of genetic variability may be useful to understand inter-subject differences in acute injury and symptom severity, and may have therapeutic implications.

Geomorphodiversity and anthropization indices for Italian urban areas

Urban geomorphology analyzes modifications of morphology and topography induced by human activity in cities, urban and peri–urban areas. Urban expansion modifies ecosystems, but global actions for sustainability focus on the biosphere, overlooking the role of abiotic components, embedded in and supported by the geosphere and its ecosystem services.We propose the joint study of indicators of land surface variability and of anthropic modifications. We consider geomorphodiversity, as a discrete measure of richness and variability of abiotic components, and a new index describing the degree of human impact inferred from land cover classes. We suggest that a joint study of the two indicators helps quantifying and understanding the effect of specific land cover changes on areas with different values of geomorphodiversity and the relationships between abiotic parameters and the human presence in urban areas.Public datasets permits study geomorphology simultaneously at the national scale, and the local scale, within individual urban areas. We show that (1) urban development in Italy was fostered in lowlands, alluvial plains or hills, and urban areas with large values of geomorphodiversity host larger numbers of natural areas; (2) different definitions of urban boundaries are essential to investigate different aspects of human impact on the landscape; (3) synthetic scenarios of land use change, corresponding to different values of anthropization, are useful to study the effect on geomorphodiversity.Quantitative geomorphodiversity and anthropization index contain complementary information, and their joint study is an additional tool to plan city development and conservation of natural areas in a broad sense.

Conceptual Inconsistencies in Variable Definitions and Measurement Items within ISP Non-/compliance Research: A systematic literature review

Conceptual Inconsistencies in Variable Definitions and Measurement Items within ISP Non-/compliance Research: A systematic literature review

Variable Range Measure: a new range measure for super-efficiency model based on DDF in presence of nonpositive data

Variable Range Measure: a new range measure for super-efficiency model based on DDF in presence of nonpositive data

Regularity and existence for semilinear mixed local-nonlocal equations with variable singularities and measure data

Regularity and existence for semilinear mixed local-nonlocal equations with variable singularities and measure data

Greater Influence of Density on the Electrical Properties of an Organic Semiconductor Glass Compared to Molecular Orientation.

Physical vapor deposition is widely used in the fabrication of organic light-emitting diodes and has the potential to adjust the density and orientation through substrate temperature control, which may lead to enhanced electrical performance. However, it is unclear whether this enhanced property is because of the horizontal molecular orientation or the increased density. The effects of the density and orientation on the electrical properties of a potential electron transport material, (3-dibenzo[c,h]acridin-7-yl)phenyl)diphenylphosphine oxide (TPPO-dibenzacridine), were investigated. According to the gyration tensor analysis, TPPO-dibenzacridine resembled an oblate ellipsoid. Furthermore, these films exhibited the highest density when prepared at a substrate temperature of 87.5% of the glass transition temperature with an increase in density of approximately 1.5%. Variable angle spectroscopic ellipsometry measurements confirmed that the transition dipole moment direction of the dibenzacridine moiety, which is involved in the electrical properties, remained isotropic at this temperature. Although horizontal orientations are known to optimize their π-π overlap and improve the electrical properties, the lowest driving voltage was observed under these conditions, which led to the conclusion that the enhanced electrical properties of TPPO-dibenzacridine are greatly influenced by the increased density rather than by the molecular orientation.

Diffusive convective elliptic problem in variable exponent space and measure data

Diffusive convective elliptic problem in variable exponent space and measure data

Test–Retest Reliability and Concurrent Validity of Photoplethysmography Finger Sensor to Collect Measures of Heart Rate Variability

The purpose of the current study was to determine the test–retest reliability and concurrent validity of a photoplethysmography (PPG) finger sensor when collecting heart rate variability (HRV) metrics in reference to electrocardiography (ECG) and heart rate monitor (HRM) devices. Five minutes of R-R interval data were collected from 45 participants (23 females; age: 23.13 ± 4.45 yrs; body mass index: 25.39 ± 4.13 kg/m2) in the supine and seated positions in testing sessions 48 h apart. Moderate-to-excellent test–retest reliability of the HRV data collected from the PPG sensor was identified (ICC2,1 = 0.60–0.93). Additionally, similar standard errors of the mean, coefficient of variation, and minimal detectable change metrics were observed across all devices. Statistically significant (p &lt; 0.05) differences were identified in the HRV data between the PPG sensor and ECG and HRM devices; however, these differences were interpreted as trivial-to-small (g = 0.00–0.59). Further, the PPG sensor tended to only overestimate HRV metrics by &lt;0.5 ms and near perfect relationships (r = 0.91–1.00) and very large-to-near perfect agreement (CCC = 0.81–1.00) were identified between collection methods. The PPG sensor demonstrated adequate test–retest reliability and concurrent validity in both the supine and seated resting positions.

Association of extreme heat events with sleep and cardiovascular health: a scoping review

BackgroundExtreme heat events (EHEs), driven by anthropogenic climate change, exacerbate the risk of cardiovascular disease (CVD), although the underlying mechanisms are unclear. A possible mechanism leading to heat-related CVD is disturbances in sleep health, which can increase the risk of hypertension, and is associated with ideal cardiovascular health. Thus, our objective was to systematically review the peer-reviewed literature that describes the relationship between EHEs, sleep health, and cardiovascular measures and outcomes and narratively describe methodologies, evidence, and gaps in this area in order to develop a future research agenda linking sleep health, EHEs, and CVD.MethodsA comprehensive literature search was performed in the following databases from inception–June 2023: Ovid MEDLINE, Ovid Embase, CINAHL, Web of Science, and the Cochrane Library. Studies retrieved were then screened for eligibility against predefined inclusion/exclusion criteria. Then studies were described qualitatively in relation to study design, findings, and the evidence linking the relationship between sleep health, EHEs, and CVD.ResultsOf the 2035 records screened, only three studies met the inclusion criteria. In these three studies, EHE was measured as absolute temperatures (greater than 30 °C) or relative temperatures (i.e., 90th percentile daily maximum temperature within the region). Cardiovascular (CV) measures described included blood pressure (BP), heart rate (HR), and HR variability (no CVD outcomes were described), and objective and subjective measurements of sleep health outcomes included sleep duration, calmness, ease of falling asleep, ease of awakening, freshness after awakening, and sleep satisfaction. Two studies were controlled trials, and one was a cohort study. During EHEs, individuals slept for shorter periods of time and less efficiently, with greater degrees of HR variability in two of the three studies lasting at most 1–2 days; BP (both systolic and diastolic) significantly decreased during EHEs in two of the studies. No formal assessment of a mediating relationship between EHE exposure, sleep outcomes, and CV measures was undertaken.ConclusionsFew studies examine the link between CVD, sleep, and extreme heat as a possible mechanism of elevated CVD risk during EHEs, despite a strong physiological rationale. Our findings highlight an important gap in the literature that should be closely examined as EHEs become more frequent and their harmful impacts of health increase.

Enhancement of Spin Wave Transmission Through Antiferromagnet in Pt/NiO/CoFeB Heterostructure

A significant enhancement of the spin current transmission through the antiferromagnetic insulating material NiO in Pt/NiO/CoFeB heterostructures was observed in this work. The ultrafast spin currents excited by laser pulses were injected into the Pt layers after passing through the NiO layers, and then transient charge currents were generated via the inverse spin Hall effect (ISHE), leading to a terahertz (THz) emission from the structure. The emitted THz signals were measured using electro-optic sampling with a ZnTe crystal. Thin NiO layers remarkably enhanced the THz signal amplitude, suggesting high spin transfer efficiency in NiO, and lighting a direction to ameliorate the spintronic THz emitter. The variable temperature measurements showed the amplitude had a maximum near the Néel temperature (TN) of the NiO layer with a specific thickness. The results of phase difference suggested that the coherent evanescent spin wave-mediated transmission had a contribution below the TN of the NiO layer, while the thermal magnon-mediated transmission existed at all temperatures. Our results not only achieve an enhancement in the spintronic THz source but also provide a THz spectroscopic method to investigate the dynamics of the ultrafast spintronic phenomenon.

Triply Ordered 6H Halide Perovskites: A Family of Triangular Lattice Antiferromagnets.

Three new hexagonal perovskites with Cs3M+M2+RhCl9 (M+ = Na+, Ag+; M2+ = Mn2+, Fe2+) stoichiometry have been synthesized from solution precipitation reactions. These air-stable compounds crystallize as triply cation-ordered variants of the 6H perovskite structure. This structure contains octahedra that share a common face to form M2+RhCl94- dimers that are arranged on a two-dimensional triangular network. M+ cations reside in octahedral holes located between dimer layers and connect M2+RhCl94- dimers through corner-sharing linkages. The cation sites in the corner-sharing layers are fully occupied by Na+/Ag+, except for Cs3AgMnRhCl9, where a small amount of Ag+/Mn2+ antisite disorder is observed. The M2+RhCl94- dimers adopt an ordered configuration that lowers the symmetry from P63/mmc to P63mc. Optical absorption in the near ultraviolet (UV) and visible regions is dominated by Rh d-to-d transitions and metal-to-metal charge transfer transitions. Variable temperature magnetic susceptibility measurements show no sign of long-range magnetic order down to 2 K. Curie-Weiss fits reveal relatively weak antiferromagnetic interactions between M2+ ions, with Weiss constants that range from -2.3 to -5.4 K. The strength of the antiferromagnetic interactions between M2+ ions increases as the covalency of the M2+-Cl bond increases. The ordering of three different cations in the 6H perovskite structure diminishes magnetic coupling between layers, leading to a new family of two-dimensional triangular lattice antiferromagnets.