Effective Proxy Research Articles

Holocene chemostratigraphy of spring sediments in Range Creek Canyon, Utah, USA

This study builds off the paleoclimatic reconstruction created by Hart et al. that used a multiproxy study to examine the role of moisture in the exodus of the Fremont from Range Creek Canyon in the 12th century. For this research, elemental ratios, weathering indices, and pollen data from two wetland spring sediment cores were used to compare with the existing Hart et al. paleoclimatic reconstruction (Objective 1). Elemental ratios and pollen data proved to be effective proxies for precipitation fluctuation, with the ratio of Pinus to Juniperus pollen representing effective moisture and increasing with the intensity of chemical weathering. Elemental data were additionally used to identify crypto tephra in the cores to validate Range Creek Canyon’s existing chronology (Objective 2). The XRF analysis of the sediment cores constrained the chronology of environmental change in the canyon by identifying the elemental signature of the Mazama eruption (7627 ± 150 cal. year BP). The concentration of Al, Y, and Ti were 50 times higher in this layer than elsewhere in the core, indicating a sudden depositional event, such as a volcanic eruption. Based on the multiproxy data and confirmed chronology, the Fremont entered the canyon during a period of elevated precipitation lasting until 600 AD. Precipitation levels remained steady until 1200 AD, after which precipitation levels decreased, causing drought conditions that coincide with the Fremont’s departure from Range Creek Canyon.

On the hosts of neutron star mergers in the nearby Universe

ABSTRACT Recently, the characterization of binary systems of neutron stars has become central in various fields such as gravitational waves, gamma-ray bursts (GRBs), and the chemical evolution of galaxies. In this work, we explore possible observational proxies that can be used to infer some characteristics of the delay time distribution (DTD) of neutron star mergers (NSMs). We construct a sample of model galaxies that fulfils the observed galaxy stellar mass function, star formation rate versus mass relation, and the cosmic star formation rate density. The star formation history of galaxies is described with a log-normal function characterized by two parameters: the position of the maximum and the width of the distribution. We assume a theoretical DTD that mainly depends on the lower limit and the slope of the distribution of the separations of the binary neutron star systems at birth. We find that the current rate of NSMs ($\mathcal {R}=320^{+490}_{-240}$ Gpc−3 yr−1) requires that ∼0.3 per cent of neutron star progenitors lives in binary systems with the right characteristics to lead to an NSM within a Hubble time. We explore the expected relations between the rate of NSMs and the properties of the host galaxy. We find that the most effective proxy for the shape of the DTD of NSMs is the current star formation activity of the typical host. At present, the fraction of short-GRBs observed in star-forming galaxies favours DTDs with at least ${\sim}40~{{\ \rm per\ cent}}$ of mergers within 100 Myr. This conclusion will be put on a stronger basis with larger samples of short-GRBs with host association (e.g. 600 events at z ≤ 1).

Seasonal variations of siliceous microplankton fluxes and radiolarian assemblages linked to environmental conditions in Prydz Bay polynya, Eastern Antarctica

Siliceous microplankton is an effective proxy for connecting modern and past marine environments; however, radiolarians have been understudied in Prydz Bay, Eastern Antarctica. This study investigated the changes in the siliceous microbiota fluxes and radiolarian assemblages captured in a 1-year time-series sediment trap (February 2014 to February 2015, ~490 m water depth) in the polynya of Prydz Bay. The results exhibited the strong seasonality in the radiolarian assemblages and the fluxes of radiolarians, diatoms, silicoflagellates and sponge spicules, with low numbers in winter and high numbers in summer. Seasonal variations in the sea ice and plankton community were critical in these patterns. The total radiolarian flux (TRF) displayed three peaks with higher flux than the annual average TRF over the year, all of which occurred in summer. These TRF peaks were mainly driven by seasonal fluctuations of sea ice, primary productivity, grazing pressure caused by phytophagous zooplankton and resuspension of small radiolarians in the surface sediments induced by modified Circumpolar Deep Water (mCDW) intrusion onto the shelf. There were also two notable low-TRF stages, mainly related to full sea-ice coverage and high grazing pressure. Two dominant assemblages were recognized by means of Q-factor analysis. Dominant assemblage one was composed of three small-sized taxa,Antarctissasp.,Phormacantha hystrixandPlectacantha oikiskos, which could be used as a proxy for primary productivity in the Marginal Ice Zone (MIZ) in Prydz Bay. Dominant assemblage two was composed ofAntarctissa strelkoviandAntarctissa denticulata, withA. strelkovidominating. The high flux and high relative abundance ofA. strelkovimarked the extension of Ice Shelf Water (ISW) to the shelf area in Prydz Bay. These findings will provide new insights and reliable proxies for modern and paleoceanographic research in the Southern Ocean.

Global Bond Allocation Using Duration Times Spread

The duration times the credit spread of a bond, denoted DTS, is an effective proxy for its price variance. On an aggregate level, the measure is key to specifying the covariance between bond prices as well. Using a sample of government bond market indices, the author shows that the duration and spread, both on an index level, explain the largest share of the price variance and covariance between government bond markets. The bonds in the indices are denominated in local currency and are hedged against exchange-rate risk. The findings provide new insights for managing bond risk in globally invested portfolios.

Pengujian Fraud Triangle Theory Dalam Menjelaskan Kecurangan Laporan Keuangan Menggunakan Beneish M-Score

Financial statements must be reliable and free from bias as they represent management accountability to investors. Yet, companies have many incentives to manipulate financial statements to meet investors’ performance expectations. Therefore, this study aims to examine the fraud triangle theory (pressure proxy by financial stability, opportunity proxy by nature of the industry, and rationalization proxy by total accrual to total assets) in explaining factors that cause management to commit fraud on financial statements. The population of this study is the manufacturing sector companies listed on the Indonesia Stock Exchange during the period 2018-2020. This study performs purposive sampling method to collect financial data of 102 manufacturing companies from the website of the Indonesia stock exchange (www.idx.co.id) and Refinitiv Eikon database. Based on 306 observations obtained and tested using the logistic linear regression analysis, this study found that pressure (financial stability) had no effect on financial statement fraud, while the opportunity (nature of industry) and rationalization (total accrual to total assets) had a positive effect on financial statement fraud. These findings imply that nature of industry and total accrual to total assets are effective proxy of opportunity and rationalization respectively to predict financial statement fraud measured using Beneish M-Score, particularly the financial statements of the manufacturing companies.

Population synchrony indicates functional connectivity in a threatened sedentary butterfly

Dispersal is a key influence on species’ persistence, particularly in the context of habitat fragmentation and environmental change. Previously, residual population synchrony has been demonstrated to be an effective proxy for dispersal in mobile butterflies (Powney et al. 2012). Here, we highlight the utility and limitations of population synchrony as an indicator of functional connectivity and persistence, at a range of spatial scales, in a specialist, sedentary butterfly. While at the local scale, population synchrony is likely indicative of dispersal in the pearl-bordered fritillary, Boloria euphrosyne, over larger scales, habitat is likely to influence population dynamics. Although declines in local-scale synchrony conformed to typical movement in this species, synchrony showed no significant trend with distance when studied at larger (between-site) scales. By focusing on specific site comparisons, we draw the conclusion that heterogeneity in habitat successional stage drives asynchrony between sites at larger distances and is, therefore, likely to be a more important driver of population dynamics over large distances than dispersal. Within-site assessments of synchrony highlight differences in dispersal based on habitat type, with movement shown to be most inhibited between transect sections with contrasting habitat permeability. While synchrony has implications for metapopulation stability and extinction risk, no significant difference was found in average site synchrony between sites that had gone extinct during the study period and those remaining occupied. We demonstrate that population synchrony may be used to assess local-scale movement between sedentary populations, as well as to understand barriers to dispersal and guide conservation management.

Information flow among stocks, bonds, and convertible bonds.

This study examines the information flow between convertible bonds (CBs) and other investment assets, such as stocks and bonds. In particular, we employ transfer entropy (TE) as a proxy for the causal effect between the two assets considering that one of the most widely used methods, Granger causality, requires strict assumptions. When adopting TE, we find that asymmetric information flow arising between assets depends on macroeconomic phases. The stock and bond markets affected the CB market prior to and during the global financial crisis, respectively. In the post-crisis period, we find no meaningful information exchange between CBs and other investment assets concerning their return series. However, we observe a significant cause-effect relationship between CBs and stocks in the rise-fall patterns of their price series. The findings suggest that the appearance of one-directional information flow depends on macroeconomic conditions and the level of data, for example, return series or price fluctuations. Accordingly, investors could exploit this pattern predictability in their portfolio management. In addition, policymakers must closely monitor the information flow among the three markets. When any two markets exchange information in a state of strong market integration, unbalanced regulation between them could lead to market distortions and regulatory arbitrage.

Authigenic beryllium isotopes reveal fluctuations in the East Asian monsoon over the past two millennia

Reconstructing climate variability beyond human records allows reconstruction of past and prediction of future climate change. However, a lack of high-resolution paleoclimate archives and effective climate proxies has hitherto limited reconstruction of the spatiotemporal evolution of the East Asian summer monsoon (EASM). In this study, the ratio of the meteoric cosmogenic 10Be (10Bemet) to silicate-weathered 9Be in annually laminated sediments from Maar Lake Xiaolongwan (NE China) was utilized to reconstruct EASM precipitation over the past two millennia. We find two apparent humid periods during the transitions of the Dark Age Cold Period–Medieval Climate Anomaly (DACP–MCA, ∼700 CE) and MCA–Little Ice Age (MCA–LIA, ∼1250 CE). The interval of these two humid periods is consistent with previous proposition of ∼500-yr oscillations of EASM in Northeast Asia. Although there are some phase variabilities, the pattern of temporal variation from 400 to 1600 CE are synchronous with other regional climate records from the EASM region. However, the spatial pattern shows an anti-phase synchronization between the EASM and the transition zone between the EASM and the Indian summer monsoon (ISM), revealing a “dry northeastern and wet southwestern” mode during the MCA. The climate change fluctuations derived here from 10Bemet/9Be in maar lake sediments are more straightforward than Chinese cave δ18O records and global temperature anomalies, providing a unique climate proxy for detecting variations of paleo-precipitation flux in specific regions. The overall slight weakening of EASM is consistent with a long-term cooling trend, which is likely regulated by solar irradiance. The apparent decrease of EASM during the transition from MCA to LIA is interpreted as the main control of explosive volcanic eruptions. The internal fluctuations and the spatiotemporal variability of precipitation are likely associated with the integrated effect of ISM and El Niño-Southern Oscillation.

Ustekinumab Versus Anti-tumour Necrosis Factor Alpha Agents as Second-Line Biologics in Crohn's Disease

BackgroundThere are little data on positioning biologics in Crohn's disease (CD).AimsWe aimed to assess the comparative effectiveness and safety of ustekinumab vs tumour necrosis factor-alpha (anti-TNF) agents after first-line treatment with anti-TNF in CD.MethodsWe used Swedish nationwide registers to identify patients with CD, exposed to anti-TNF who initiated second-line biologic treatment with ustekinumab or second-line anti-TNF therapy. Nearest neighbour 1:1 propensity score matching (PSM) was used to balance the groups. The primary outcome was 3-year drug survival used as a proxy for effectiveness. Secondary outcomes included drug survival without hospital admission, CD-related surgery, antibiotics, hospitalization due to infection and exposure to corticosteroids.ResultsSome 312 patients remained after PSM. Drug survival at 3 years was 35% (95% CI 26–44%) in ustekinumab compared to 36% (95% CI 28–44%) in anti-TNF-treated patients (p = 0.72). No statistically significant differences were observed between the groups in 3-year survival without hospital admission (72% vs 70%, p = 0.99), surgery (87% vs 92%, p = 0.17), hospital admission due to infection (92% vs 92%, p = 0.31) or prescription of antibiotics (49% vs 50%, p = 0.56). The proportion of patients continuing second-line biologic therapy did not differ by reason for ending first-line anti-TNF (lack of response vs intolerance) or by type of first-line anti-TNF (adalimumab vs infliximab).ConclusionBased on data from Swedish routine care, no clinically relevant differences in effectiveness or safety of second-line ustekinumab vs anti-TNF treatment were observed in patients with CD with prior exposure to anti-TNF.

Dissolved organic matter in the northwestern Pacific marginal seas: Insight into the distribution of its optical properties

Dissolved organic carbon (DOC) and the optical properties of dissolved organic matter (chromophoric- and fluorescent dissolved organic matter; CDOM and FDOM) were measured to determine the distributions and drivers of DOM in the northwestern Pacific marginal seas, including the East China Sea, the Yellow Sea, and the East/Japan Sea, in August 2020. In this study, the concentrations of DOC and CDOM/FDOM in surface water showed good correlations with salinity, indicating a predominant contribution from the Changjiang River. However, significantly high concentrations of DOC and FDOM were also observed in the central Yellow Sea region, which seems to be produced mainly from the continental shelf-water and enriched over the water residence time of the Yellow Sea, while the lowest concentrations of DOC and CDOM/FDOM were found in high-salinity waters near the southern sea of Korea. In addition, the East/Japan Sea showed relatively low DOC concentrations and high FDOM values. To distinguish the physical mixing and biogeochemical processes of DOM, we estimated the water mass fractions using an optimum multi-parameter analysis with hydrological and DOM parameters of the major water masses in this region. Our results showed that five primary external drivers of DOM distribution were intrusions of (1) the Changjiang diluted water and (2) the Kuroshio Current water in the surface water, the mixing of (3) the Yellow Sea bottom cold water and (4) the Kuroshio sub-surface water in the bottom layer, and (5) upwelling of the East/Japan Sea water. We conclude that the distribution of DOM is significantly influenced by the mixing of multiple water masses, and the optical signature of DOM can be an effective proxy for tracing the origins and characteristics of DOM in this region.

Evolutionary contingency in lingulid brachiopods across mass extinctions

Morphology usually serves as an effective proxy for functional ecology,1,2,3,4,5 and evaluating morphological, anatomical, and ecological changes permits a deeper understanding of the nature of diversification and macroevolution.5,6,7,8,9,10,11,12 Lingulid (order Lingulida) brachiopods are both diverse and abundant during the early Palaeozoic but decrease in diversity over time, with only a few genera of linguloids and discinoids present in modern marine ecosystems, resulting in them frequently being referred to as "living fossils."13,14,15 The dynamics that drove this decline remain uncertain, and it has not been determined if there is an associated decline in morphological and ecological diversity. Here, we apply geometric morphometrics to reconstruct global morphospace occupation for lingulid brachiopods through the Phanerozoic, with results showing that maximum morphospace occupation was reached by the Early Ordovician. At this time of peak diversity, linguloids with a sub-rectangular shell shape already possessed several evolutionary features, such as the rearrangement of mantle canals and reduction of the pseudointerarea, common to all modern infaunal forms. The end Ordovician mass extinction has a differential effect on linguloids, disproportionally wiping out those forms with a rounded shell shape, while forms with sub-rectangular shells survived both the end Ordovician and the Permian-Triassic mass extinctions, leaving a fauna predominantly composed of infaunal forms. For discinoids, both morphospace occupation and epibenthic life strategies remain consistent through the Phanerozoic. Morphospace occupation over time, when considered using anatomical and ecological analyses, suggests that the limited morphological and ecological diversity of modern lingulid brachiopods reflects evolutionary contingency rather than deterministic processes.

Seasonal and diurnal variability of a water body's effects on the urban microclimate in a coastal city in Italy

Investigating diurnal and seasonal variations in a multi-domain approach still needs to be exploited for people's wellbeing in urban coastal areas. This study, therefore, presents an innovative method to assess the effects of urban water bodies accounting for hyperlocal climate conditions, continuously mapped via mobile/wearable environmental monitoring. This was performed via wearable sensing during winter and summer, analyzing eight urban canyons with different morphologies and anthropogenic activities. The water body's effect was assessed by comparing air temperature along these canyons, while heat stress was evaluated through Physiological Equivalent Temperature (PET). In winter, the sea effect was not explicitly identified. Conversely, the cooling effect was evident in summer. Despite statistically significant correlations between air temperature and distance from the sea, no association between air temperature and sky view factor (SVF) was detected. Additionally, particulate matter (PM) concentration analysis did not allow identifying specific anthropogenic actions and cannot behave as an effective proxy. However, different temperature trends in winter and summer may represent a clear and cheap-to-detect outcome of the anthropogenic complexity in every urban canyon, which includes varied urban features and local overheating forcing. This highlights the importance of hyperlocal microclimate monitoring accounting for these strategic differences to be detected, during heat waves for instance.

What Are the Most Effective Proxies in Identifying Storm‐Surge Deposits in Paleotempestology? A Quantitative Evaluation From the Sand‐Limited, Peat‐Dominated Environment of the Florida Coastal Everglades

AbstractAlthough many studies have attempted to reconstruct millennial‐scale hurricane patterns using various proxy‐based methods, it is still unclear what the most effective proxies are to identify storm surge deposits in different environmental settings. This study quantitatively compares the application of grain‐size, loss‐on‐ignition, stable isotopes, X‐ray fluorescence, and palynological proxies in paleotempestology from an organic‐rich environment in the Florida Everglades. The nonparametric tests indicate that only 9 among the 27 parameters (mean diameter, %water, %organic, %carbonate, Ca, Sr, Ca/Ti, Cl/Br, and marine microfossils) exhibited significant differences between storm‐surge and in situ deposits. The principal component analysis shows that five marine indicators (Sr, Ca, Ca/Ti, %Carbonate, and Marine microfossils) have the closest association with the allochthonous samples, while Cl/Br and Mz are the most sensitive proxies in low‐ and high‐energy environments, respectively. Moreover, organic geochemical proxies (e.g., δ13C and δ15N of bulk sedimentary organic matter) are ineffective for identifying storm‐surge deposits in organic‐rich mangrove environments.

Out of One, Many: Using Language Models to Simulate Human Samples

AbstractWe propose and explore the possibility that language models can be studied as effective proxies for specific human subpopulations in social science research. Practical and research applications of artificial intelligence tools have sometimes been limited by problematic biases (such as racism or sexism), which are often treated as uniform properties of the models. We show that the “algorithmic bias” within one such tool—the GPT-3 language model—is instead both fine-grained and demographically correlated, meaning that proper conditioning will cause it to accurately emulate response distributions from a wide variety of human subgroups. We term this propertyalgorithmic fidelityand explore its extent in GPT-3. We create “silicon samples” by conditioning the model on thousands of sociodemographic backstories from real human participants in multiple large surveys conducted in the United States. We then compare the silicon and human samples to demonstrate that the information contained in GPT-3 goes far beyond surface similarity. It is nuanced, multifaceted, and reflects the complex interplay between ideas, attitudes, and sociocultural context that characterize human attitudes. We suggest that language models with sufficient algorithmic fidelity thus constitute a novel and powerful tool to advance understanding of humans and society across a variety of disciplines.

Higher Sensitivity of NIRv,Rad in Detecting Net Primary Productivity of C4 Than that of C3: Evidence from Ground Measurements of Wheat and Maize

Accurate quantification of net primary productivity (NPP) is key to estimating vegetation productivity and studying the global carbon cycle. However, C3 and C4 plants vary in their living environments and potential productivity due to their different photosynthetic pathways. This study thus explored the potential of the near-infrared radiance of vegetation (NIRv,Rad) to track hourly and daily changes in C3 and C4 plants and investigate whether their photosynthetic pathways affect the relationship between NPP and NIRv,Rad. Statistics including long-term spectral data, the growth environment, and physiological indicators were collected using an automatic spectral monitoring system. The vegetation index NIRv,Rad was extracted from the collected spectral data and NPP was calculated using the collected net photosynthetic rate and leaf area index. The results showed that NIRv,Rad can effectively respond to NPP changes in C3 and C4 plants on hourly and daily scales. The NPP–NIRv,Rad relationship on the hourly scale was superior, with R2 values for winter wheat and summer maize of 0.81 and 0.70, respectively. Furthermore, when the accumulation of NPP was equal, the NIRv,Rad of summer maize showed larger changes, indicating that it was more sensitive to NPP change for this species than for winter wheat. Overall, the study demonstrated that NIRv,Rad can serve as an effective proxy indicator of NPP. In addition, this study provides a theoretical basis and scientific guidance for the construction of new simple models and realizing efficient agriculture, as well as a new method for rapid and accurate quantification of the NPP of C3 and C4 plants at geospatial scales in future research.

Mapping areas prone to piping using random forest with key explanatory variables

In previous studies, areas prone to soil piping were mapped on the catchment scale by integrating data-mining algorithms and geographical databases. However, this left the question of which input data layers are most influential on soil pipe distribution in semiarid regions, and how they can be exploited for accurate predictions of areas prone to piping. Here, a random forest (RF) procedure was applied to classify areas prone to piping using input data layers selected based on knowledge gained through previous theoretical modeling and empirical measurements. The input data layers were: potential incoming solar radiation; distance from the closest streambank; streambank slope gradient; topographic wetness index; flow accumulation; and vegetation cover as a proxy for the shading effect. An extensive dataset of field measurements (N = 774) was used to train and validate the RF classification procedure. Our results indicated that: (i) RF—based on carefully selected influential input data layers—can be used to map areas prone to soil piping at the catchment scale with high accuracy; (ii) the effect of potential solar radiation and—to a lesser extent—tree shading is noteworthy for soil cracking and subsequent piping development; and (iii) soil pipes were found at short distances (<30 m) from steep bank slopes due to the effect of tension cracks in the streambanks. These observations, over a wide region, further establish the effect of soil cracking, and drying and wetting processes, on soil pipe development in semiarid regions. Future studies applying piping susceptibility mapping at the catchment scale may benefit from using these input layers.

Geographically weighted regression (GWR) and Prediction-area (P-A) plot to generate enhanced geochemical signatures for mineral exploration targeting

The geochemical exploration provides an effective and direct spatial evidence for identifying undiscovered deposits. Geochemical data are spatial data with many attributes, such as closure effect, collinearity, multivariate, spatial correlation and heterogeneity. The data processing method considering the attributes of geochemical data is very important for accurately identification of the undiscovered deposits. In this paper, a data-driven mineral exploration targeting method was proposed, first log-ratio transformation was performed to eliminate the closure effect, and then central standardization was applied to avoid collinearity. Then, the geographically weighted regression (GWR) was carried out with rock-forming oxides and immobile elements as dependent variables and ore-forming elements as independent variables, which considering the spatial attributes of geochemical data, and the residuals were regarded as the geochemical evidences. Afterwards, associated elements for mineralization were selected and the P-A plot was used to evaluate the relative importance of ore-forming elements (residual errors) and associated elements to indicate the locations of the deposits of the type sought, and finally an enhanced data-driven multi-element geochemical signature was generated for mineral exploration targeting. The geochemical anomalies extraction effect was significantly enhanced compared with traditional method. The method considering the multi-attribute characteristics of geochemical data provided an effective geochemical proxy for mineral exploration targeting, which was of great significance for improving the geochemical exploration theory and prospecting practice.

200-year ice core bromine reconstruction at Dome C (Antarctica): observational and modelling results

Abstract. Bromine enrichment (Brenr) has been proposed as an ice core proxy for past sea-ice reconstruction. Understanding the processes that influence bromine preservation in the ice is crucial to achieve a reliable interpretation of ice core signals and to potentially relate them to past sea-ice variability. Here, we present a 210 years bromine record that sheds light on the main processes controlling bromine preservation in the snow and ice at Dome C, East Antarctic plateau. Using observations alongside a modelling approach, we demonstrate that the bromine signal is preserved at Dome C and it is not affected by the strong variations in ultraviolet radiation reaching the Antarctic plateau due to the stratospheric ozone hole. Based on this, we investigate whether the Dome C Brenr record can be used as an effective tracer of past Antarctic sea ice. Due to the limited time window covered by satellite measurements and the low sea-ice variability observed during the last 30 years in East Antarctica, we cannot fully validate Brenr as an effective proxy for past sea-ice reconstructions at Dome C.

Age-Associated Changes on Gait Smoothness in the Third and the Fourth Age

Although gait disorders represent a highly prevalent condition in older adults, the alterations associated with physiologic aging are often not easily differentiable from those originated by concurrent neurologic or orthopedic conditions. Thus, the detailed quantitative assessment of gait patterns represents a crucial issue. In this context, the study of trunk accelerations may represent an effective proxy of locomotion skills in terms of symmetry. This can be carried out by calculating the Harmonic Ratio (HR), a parameter obtained through the processing of trunk accelerations in the frequency domain. In this study, trunk accelerations during level walking of 449 healthy older adults (of age &gt; 65) who were stratified into three groups (Group 1: 65–74 years, n = 175; Group 2: 75–85 years, n = 227; Group 3: &gt;85 years, n = 47) were acquired by means of a miniaturized Inertial Measurement Unit located in the low back and processed to obtain spatio-temporal parameters of gait and HR, in antero-posterior (AP), medio-lateral (ML) and vertical (V) directions. The results show that Group 3 exhibited a 16% reduction in gait speed and a 10% reduction in stride length when compared with Group 1 (p &lt; 0.001 in both cases). Regarding the cadence, Group 3 was characterized by a 5% reduction with respect to Groups 1 and 2 (p &lt; 0.001 in both cases). The analysis of HR revealed a general trend of linear decrease with age in the three groups. In particular, Group 3 was characterized by HR values significantly lower (−17%) than those of Group 1 in all three directions and significantly lower than Group 2 in ML and V directions (−10%). Taken together, such results suggest that HR may represent a valid measure to quantitatively characterize the progressive deterioration of locomotor abilities associated with aging, which seems to occur until the late stages of life.

U.S. National VS30 Models and Maps Informed by Remote Sensing and Machine Learning

Abstract The shear-wave velocity time averaged over the upper 30 m (VS30) is widely used as a proxy for site effects, forms the basis of seismic site class, and underpins site-amplification factors in empirical ground-motion models. Many earthquake simulations, therefore, require VS30. This presents a challenge at regional scale, given the infeasibility of subsurface testing over vast areas. Although various models for predicting VS30 have thus been proposed, the most popular U.S. national, or “background,” model is a regression equation based on just one variable. Given the growth of community data sets, satellite remote sensing, and algorithmic learning, more advanced and accurate solutions may be possible. Toward that end, we develop national VS30 models and maps using field data from over 7000 sites and machine learning (ML), wherein up to 17 geospatial parameters are used to predict subsurface conditions (i.e., VS30). Of the two models developed, that using geologic data performs marginally better, yet such data are not always available. Both models significantly outperform existing solutions in unbiased testing and are used to create new VS30 maps at ∼220 m resolution. These maps are updated in the vicinity of field measurements using regression kriging and cover the 50 U.S. states and Puerto Rico. Ultimately, and like any model, performance cannot be known where data is sparse. In this regard, alternative maps that use other models are proposed for steep slopes. More broadly, this study demonstrates the utility of ML for inferring below-ground conditions from geospatial data, a technique that could be applied to other data and objectives.