Showing papers by "University of Maryland, Baltimore County published in 2022"

Aducanumab: Appropriate Use Recommendations Update

Abstract: Aducanumab (Aduhelm) is approved in the United States for the treatment of patients with mild cognitive impairment due to Alzheimer's disease or mild AD dementia. Aducanumab Appropriate Use Recommendations (AURs) have been published and have helped guide best practices for use of aducanumab. As real-world use has occurred and more information has accrued, the AURs require refinement. We update the AURs to better inform appropriate patient selection and improve shared decision-making, safety monitoring, and risk mitigation in treated patients. Based on evolving experience we emphasize the importance of detecting past medical conditions that may predispose to amyloid related imaging abnormalities (ARIA) or may increase the likelihood of ARIA complications including autoimmune or inflammatory conditions, seizures, or disorders associated with extensive white matter pathology. The apolipoprotein E ε4 (APOE4) genotype is strongly associated with ARIA and exhibits a gene dose effect. We recommend that clinicians perform APOE genotyping to better inform patient care decisions, discussions regarding risk, and clinician vigilance concerning ARIA. As most ARIA occurs during the titration period of aducanumab, we suggest performing MRI before the 5th, 7th, 9th, and 12th infusions to improve detection. Uncommonly, ARIA may be recurrent or serious; we suggest additional parameters for treatment discontinuation taking these observations into account. It is important to continue to learn from the real-world use of aducanumab and the AURs will continue to evolve as new information becomes available. This AUR update does not address efficacy, price, or insurance coverage and is provided to assist clinicians to establish best practices for use of aducanumab in the treatment of patients with mild cognitive impairment and mild Alzheimer's dementia.

Opportunistic experiments to constrain aerosol effective radiative forcing

Abstract: Aerosol-cloud interactions (ACIs) are considered to be the most uncertain driver of present-day radiative forcing due to human activities. The nonlinearity of cloud-state changes to aerosol perturbations make it challenging to attribute causality in observed relationships of aerosol radiative forcing. Using correlations to infer causality can be challenging when meteorological variability also drives both aerosol and cloud changes independently. Natural and anthropogenic aerosol perturbations from well-defined sources provide "opportunistic experiments" (also known as natural experiments) to investigate ACI in cases where causality may be more confidently inferred. These perturbations cover a wide range of locations and spatiotemporal scales, including point sources such as volcanic eruptions or industrial sources, plumes from biomass burning or forest fires, and tracks from individual ships or shipping corridors. We review the different experimental conditions and conduct a synthesis of the available satellite datasets and field campaigns to place these opportunistic experiments on a common footing, facilitating new insights and a clearer understanding of key uncertainties in aerosol radiative forcing. Cloud albedo perturbations are strongly sensitive to background meteorological conditions. Strong liquid water path increases due to aerosol perturbations are largely ruled out by averaging across experiments. Opportunistic experiments have significantly improved process-level understanding of ACI, but it remains unclear how reliably the relationships found can be scaled to the global level, thus demonstrating a need for deeper investigation in order to improve assessments of aerosol radiative forcing and climate change.

Insights from the topographic characteristics of a large global catalog of rainfall-induced landslide event inventories

Abstract: Abstract. Landslides are a key hazard in high-relief areas around the world and pose a risk to populations and infrastructure. It is important to understand where landslides are likely to occur in the landscape to inform local analyses of exposure and potential impacts. Large triggering events such as earthquakes or major rain storms often cause hundreds or thousands of landslides, and mapping the landslide populations generated by these events can provide extensive datasets of landslide locations. Previous work has explored the characteristic locations of landslides triggered by seismic shaking, but rainfall-induced landslides are likely to occur in different parts of a given landscape when compared to seismically induced failures. Here we show measurements of a range of topographic parameters associated with rainfall-induced landslides inventories, including a number of previously unpublished inventories which we also present here. We find that the average upstream angle and compound topographic index are strong predictors of landslide scar location, while the local relief and topographic position index provide a stronger sense of where landslide material may end up (and thus where hazard may be highest). By providing a large compilation of inventory data for open use by the landslide community, we suggest that this work could be useful for other regional and global landslide modeling studies and local calibration of landslide susceptibility assessment, as well as hazard mitigation studies.

Dual-energy spectral CT imaging of pulmonary embolism with Mycoplasma pneumoniae pneumonia in children

Abstract: Pulmonary embolism (PE) associated with Mycoplasma pneumoniae pneumonia (MPP) in children has already attracted more attention. CT pulmonary angiography (CTPA) has been the preferred method for diagnosing PE, but it has some limitations, especially for children. Dual-energy spectral CT has been used in diagnosing PE in adults.To evaluate the application of dual-energy spectral CT in diagnosing PE in children with MPP.Eighty-three children with MPP and highly suspected PE, underwent CTPA with spectral imaging mode, 25 children were diagnosis with PE. Noise, clot-to-artery contrast-to-noise ratio, image quality and diagnosis confidence were calculated and assessed on nine monochromatic image sets (40 to 80 keV). CTPA images were observed for the presence, localization and embolic degrees of PE. Clots were divided into intra- and extra-consolidation clots. For extra-consolidation clots, iodine concentration (IC) of perfusion defects and normal lung, perfusion defects of four children before and after the treatment were measured and compared. For intra-consolidation clots, IC of consolidation areas with clots and consolidation areas without clot were measured and compared.The optimal energy level for detecting PE in children was 55 keV. 116 clots (29 extra-consolidations) were found, IC of defect regions was 0.69 ± 0.28 mg/mL (extra-consolidations) and 0.90 ± 0.23 mg/mL (intra-consolidations), both significantly lower than the 2.76 ± 0.45 mg/mL in normal lungs and 10.25 ± 1.76 mg/mL in consolidations without clots (P < 0.001). Significant difference was found in the presence or absence of perfusion defects between occlusive clots and nonocclusive clots (P < 0.001). IC of the perfusion defects significantly increased after treatment (P < 0.001).In dual-energy spectral CTPA, 55 keV images optimize PE detection for children, and MD images quantify pulmonary blood flow of PE, and may help to detect small clots and quantify embolic degrees.

Reproducibility and replicability in neuroimaging data analysis

Abstract: Purpose of review Machine learning solutions are being increasingly used in the analysis of neuroimaging (NI) data, and as a result, there is an increase in the emphasis of the reproducibility and replicability of these data-driven solutions. Although this is a very positive trend, related terminology is often not properly defined, and more importantly, (computational) reproducibility that refers to obtaining consistent results using the same data and the same code is often disregarded. Recent findings We review the findings of a recent paper on the topic along with other relevant literature, and present two examples that demonstrate the importance of accounting for reproducibility in widely used software for NI data. Summary We note that reproducibility should be a first step in all NI data analyses including those focusing on replicability, and introduce available solutions for assessing reproducibility. We add the cautionary remark that when not taken into account, lack of reproducibility can significantly bias all subsequent analysis stages.

The expansion of tree plantations across tropical biomes

Abstract: Across the tropics, recent agricultural shifts have led to a rapid expansion of tree plantations, often into intact forests and grasslands. However, this expansion is poorly characterized. Here, we report tropical tree plantation expansion between 2000 and 2012, based on classifying nearly 7 million unique patches of observed tree cover gain using optical and radar satellite imagery. The resulting map was a subsample of all tree cover gain but we coupled it with an extensive random accuracy assessment (n = 4,269 points) to provide unbiased estimates of expansion. Most predicted gain patches (69.2%) consisted of small patches of natural regrowth (31.6 ± 11.9 Mha). However, expansion of tree plantations also dominated increases in tree cover across the tropics (32.2 ± 9.4 Mha) with 92% of predicted plantation expansion occurring in biodiversity hotspots and 14% in arid biomes. We estimate that tree plantations expanded into 9.2% of accessible protected areas across the humid tropics, most frequently in southeast Asia, west Africa and Brazil. Given international tree planting commitments, it is critical to understand how future tree plantation expansion will affect remaining natural ecosystems. Changes in agricultural practices have led to the expansion of tree plantations across the tropics, but this expansion is poorly characterized. Nearly 7 million unique patches of observed tree cover gain are classified through satellite imagery to report on tropical tree plantation expansion between 2000 and 2012.

Operational Modal Analysis of a Rotating Structure Subject to Random Excitation Using a Tracking Continuously Scanning Laser Doppler Vibrometer via an Improved Demodulation Method

Abstract: A new operational modal analysis (OMA) method is developed for estimation of modal parameters (MPs) of a rotating structure (RS) subject to random excitation using a nonuniform rotating beam model, an image processing method, and an improved demodulation method. The solution to the governing equation of a nonuniform rotating beam is derived, which can be considered as the response of the beam measured by a continuously scanning laser Doppler vibrometer (CSLDV) system. A recently developed tracking CSLDV system can track and scan the RS. The image processing method determines the angular position of the RS so that the tracking CSLDV system can sweep its laser spot along a time-varying path on it. The improved demodulation method obtains undamped mode shapes (UMSs) of the RS by multiplying its measured response by sinusoids whose frequencies are its damped natural frequencies (DNFs) that are obtained from the fast Fourier transform (FFT) of the measured response. Experimental investigation of the OMA method using the tracking CSLDV system is conducted, and MPs of a rotating fan blade (RFB), including DNFs and UMSs, with different constant speeds and its instantaneous MPs with a nonconstant speed are estimated. Estimated first DNFs and UMSs of the stationary fan blade and RFB are compared with those from the lifting method that was previously developed by the authors.

Occurrence and growth of sub-50 nm aerosol particles in the Amazonian boundary layer

Abstract: Abstract. New particle formation (NPF), referring to the nucleation of molecular clusters and their subsequent growth into the cloud condensation nuclei (CCN) size range, is a globally significant and climate-relevant source of atmospheric aerosols. Classical NPF exhibiting continuous growth from a few nanometers to the Aitken mode around 60–70 nm is widely observed in the planetary boundary layer (PBL) around the world but not in central Amazonia. Here, classical NPF events are rarely observed within the PBL, but instead, NPF begins in the upper troposphere (UT), followed by downdraft injection of sub-50 nm (CN<50) particles into the PBL and their subsequent growth. Central aspects of our understanding of these processes in the Amazon have remained enigmatic, however. Based on more than 6 years of aerosol and meteorological data from the Amazon Tall Tower Observatory (ATTO; February 2014 to September 2020), we analyzed the diurnal and seasonal patterns as well as meteorological conditions during 254 of such Amazonian growth events on 217 event days, which show a sudden occurrence of particles between 10 and 50 nm in the PBL, followed by their growth to CCN sizes. The occurrence of events was significantly higher during the wet season, with 88 % of all events from January to June, than during the dry season, with 12 % from July to December, probably due to differences in the condensation sink (CS), atmospheric aerosol load, and meteorological conditions. Across all events, a median growth rate (GR) of 5.2 nm h−1 and a median CS of 1.1 × 10−3 s−1 were observed. The growth events were more frequent during the daytime (74 %) and showed higher GR (5.9 nm h−1) compared to nighttime events (4.0 nm h−1), emphasizing the role of photochemistry and PBL evolution in particle growth. About 70 % of the events showed a negative anomaly of the equivalent potential temperature (Δθe′) – as a marker for downdrafts – and a low satellite brightness temperature (Tir) – as a marker for deep convective clouds – in good agreement with particle injection from the UT in the course of strong convective activity. About 30 % of the events, however, occurred in the absence of deep convection, partly under clear-sky conditions, and with a positive Δθe′ anomaly. Therefore, these events do not appear to be related to downdraft transport and suggest the existence of other currently unknown sources of sub-50 nm particles.

Catalyst Development for HCl Oxidation to Cl₂ in the Fluorochemical Industry

Abstract: The catalytic oxidation of gaseous HCl (containing a small amount of HF) to Cl2 is important and highly desired for chlorine recycling in the fluorochemical industry. In the present work, a series of Al-doped MgF2 (Al–MgF2) materials were synthesized via a sol–gel method, followed by calcination at different temperatures and then these synthesized Al–MgF2 materials were used as supports to prepare RuO2/Al–MgF2 catalysts by an incipient impregnation method. These developed catalysts were evaluated in the oxidation of HCl with an upper-bound HF concentration of 400 ppm, as is common in the fluorochemical industry. Specific attention was paid to investigating the effects of calcination temperature for preparing Al–MgF2 supports on the activity and stability of the resultant catalysts. It is found that at an optimal calcination temperature, Al can be incorporated into the framework of rutile structure MgF2, which can further modify the cell parameters of MgF2 close to those of RuO2, modulate the interactions between RuO2 and the support, and yet affect the chemical environment of RuO2 to enhance the catalytic activity and stability. The study on the catalytic kinetics reveals that the estimated apparent activation energy is in line with the incorporated amount of Al into the framework of MgF2 and shows an inverted volcano relationship with the calcination temperature for preparing Al–MgF2 supports. The lowest apparent activation energy of RuO2/Al–MgF2 can be achieved when the Al–MgF2 composite is calcined at 400 °C, and the resultant catalyst shows long-term stability with high activity for the oxidation of HCl containing a small amount of HF.

Review article: Global monitoring of snow water equivalent using high-frequency radar remote sensing

Abstract: Abstract. Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth's surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth's climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world's population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth's cold regions' ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements.

A comparison of metal/metal and ceramic/metal taper-trunnion modular connections in explanted total hip replacements.

Abstract: Corrosion and wear are commonly found at the taper-trunnion connection of modular total hip arthroplasty (THA) explanted devices. While metal/metal (M/M) modular taper-trunnion connections exhibit more wear/corrosion than ceramic/metal (C/M) modular taper-trunnion connections, damage is present in both, regardless of material. This study used a combination of assessment techniques including clinical data, visual scoring assessment, optical imaging, profilometry, and x-ray photoelectron microscopy (XPS), to investigate wear mechanisms and damage features at the modular taper-trunnion connection of 10 M/M and 8 C/M explanted THAs. No correlation was found between any demographic variable and corrosion wear and assessment scores. All assessment techniques demonstrated that the stem trunnions had more damage than head tapers for both explant groups and agreed that C/M explants had less corrosion and wear compared to M/M explants. However, visual assessment scores differed between assessment techniques when evaluating the tapers and trunnions within the two groups. Profilometry showed an increase (p <.05) in surface roughness for stem trunnions compared to head tapers for both explant groups. X-ray photoelectron spectroscopy performed on deposits from two M/M explants found chromium and molybdenum carbides beneath the surface while chromium sulfate and aged bone mineral were found on the surface suggesting that the debris is a result of corrosion rather than wear. These results indicate that taper-trunnion damage is more prevalent for M/M explants, but C/M explants are still susceptible to damage. More comprehensive analysis of damage is necessary to better understand the origins of taper-trunnion damage.

Inferring iron-oxide species content in atmospheric mineral dust from DSCOVR EPIC observations

Abstract: Abstract. The iron-oxide content of dust in the atmosphere and most notably its apportionment between hematite (α-Fe2O3) and goethite (α-FeOOH) are key determinants in quantifying dust's light absorption, its top of atmosphere ultraviolet (UV) radiances used for dust monitoring, and ultimately shortwave dust direct radiative effects (DREs). Hematite and goethite column mass concentrations and iron-oxide mass fractions of total dust mass concentration were retrieved from the Deep Space Climate Observatory (DSCOVR) Earth Polychromatic Imaging Camera (EPIC) measurements in the ultraviolet–visible (UV–Vis) channels. The retrievals were performed for dust-identified aerosol plumes over land using aerosol optical depth (AOD) and the spectral imaginary refractive index provided by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm over six continental regions (North America, North Africa, West Asia, Central Asia, East Asia, and Australia). The dust particles are represented as an internal mixture of non-absorbing host and absorbing hematite and goethite. We use the Maxwell Garnett effective medium approximation with carefully selected complex refractive indices of hematite and goethite that produce mass fractions of iron-oxide species consistent with in situ values found in the literature to derive the hematite and goethite volumetric/mass concentrations from MAIAC EPIC products. We compared the retrieved hematite and goethite concentrations with in situ dust aerosol mineralogical content measurements, as well as with published data. Our data display variations within the published range of hematite, goethite, and iron-oxide mass fractions for pure-mineral-dust cases. A specific analysis is presented for 15 sites over the main dust-source regions. Sites in the central Sahara, Sahel, and Middle East exhibit a greater temporal variability of iron oxides relative to other sites. The Niger site (13.52∘ N, 2.63∘ E) is dominated by goethite over the Harmattan season with a median of ∼ 2 weight percentage (wt %) of iron oxide. The Saudi Arabia site (27.49∘ N, 41.98∘ E) over the Middle East also exhibited a surge of goethite content with the beginning of the shamal season. The Sahel dust is richer in iron oxide than Saharan and northern China dust except in summer. The Bodélé Depression area shows a distinctively lower iron-oxide concentration (∼ 1 wt %) throughout the year. Finally, we show that EPIC data allow the constraining of the hematite refractive index. Specifically, we select 5 out of 13 different hematite refractive indices that are widely variable in published laboratory studies by constraining the iron-oxide mass ratio to the known measured values. The provided climatology of hematite and goethite mass fractions across the main dust regions of Earth will be useful for dust shortwave DRE studies and climate modeling.

Intrinsic Ferromagnetism of Two-Dimensional (2D) MnO₂ Revisited: A Many-Body Quantum Monte Carlo and DFT+<i>U</i> Study

Abstract: Monolayer MnO$_2$ is one of the few predicted two-dimensional (2D) ferromagnets that has been experimentally synthesized and is commercially available. The Mermin-Wagner theorem states that magnetic order in a 2D material cannot persist unless magnetic anisotropy (MA) is present and perpendicular to the plane, which permits a finite critical temperature. Previous computational studies have predicted the magnetic ordering and Curie temperature of 2D MnO$_2$ with DFT+U (Density Funtional Theory + Hubbard U correction), with the results having a strong dependence on the Hubbard U parameter. Diffusion Monte Carlo (DMC) is a correlated electronic structure method that has had demonstrated success for the electronic and magnetic properties of a variety of 2D and bulk systems since it has a weaker dependence on the starting Hubbard parameter and density functional. In this study, we used DMC and DFT+U to calculate the magnetic properties of monolayer MnO$_2$. We found that the ferromagnetic ordering is more favorable than antiferromagnetic and determined a statistical bound on the magnetic exchange parameter ($J$). In addition, we performed spin-orbit MA energy calculations using DFT+U and using our DMC and DFT+U parameters along with the analytical model of Torelli and Olsen, we estimated an upper bound of 28.8 K for the critical temperature of MnO$_2$. These QMC results intend to serve as an accurate theoretical benchmark, necessary for the realization and development of future 2D magnetic devices. These results also demonstrate the need for accurate methodologies to predict magnetic properties of correlated 2D materials.

On the impact of canopy model complexity on simulated carbon, water, and solar-induced chlorophyll fluorescence fluxes

Abstract: Abstract. Lack of direct carbon, water, and energy flux observations at global scales makes it difficult to calibrate land surface models (LSMs). The increasing number of remote-sensing-based products provide an alternative way to verify or constrain land models given their global coverage and satisfactory spatial and temporal resolutions. However, these products and LSMs often differ in their assumptions and model setups, for example, the canopy model complexity. The disagreements hamper the fusion of global-scale datasets with LSMs. To evaluate how much the canopy complexity affects predicted canopy fluxes, we simulated and compared the carbon, water, and solar-induced chlorophyll fluorescence (SIF) fluxes using five different canopy complexity setups from a one-layered canopy to a multi-layered canopy with leaf angular distributions. We modeled the canopy fluxes using the recently developed land model by the Climate Modeling Alliance, CliMA Land. Our model results suggested that (1) when using the same model inputs, model-predicted carbon, water, and SIF fluxes were all higher for simpler canopy setups; (2) when accounting for vertical photosynthetic capacity heterogeneity, differences between canopy complexity levels increased compared to the scenario of a uniform canopy; and (3) SIF fluxes modeled with different canopy complexity levels changed with sun-sensor geometry. Given the different modeled canopy fluxes with different canopy complexities, we recommend (1) not misusing parameters inverted with different canopy complexities or assumptions to avoid biases in model outputs and (2) using a complex canopy model with angular distribution and a hyperspectral radiation transfer scheme when linking land processes to remotely sensed spectra.

Applications of Artificial Intelligence in 18 F-Sodium Fluoride Positron Emission Tomography/Computed Tomography:: Current State and Future Directions

Abstract: This review discusses the current state of artificial intelligence (AI) in 18F-NaF-PET/CT imaging and the potential applications to come in diagnosis, prognostication, and improvement of care in patients with bone diseases, with emphasis on the role of AI algorithms in CT bone segmentation, relying on their prevalence in medical imaging and utility in the extraction of spatial information in combined PET/CT studies.

A framework for battery internal temperature and state-of-charge estimation based on fractional-order thermoelectric model

Abstract: In recent years, the rapid development of electric vehicles has raised a wave of innovation in lithium-ion batteries. The safety operation of lithium-ion batteries is one of the major bottlenecks restraining the development of the energy storage market. The temperature especially the internal temperature can significantly affect the performance and safety of the battery; therefore, this paper presented a novel framework for joint estimation of the internal temperature and state-of-charge of the battery based on a fractional-order thermoelectric model. Due to the nonlinearity, coupling, and time-varying parameters of lithium-ion batteries, a fractional-order thermoelectric model which is suitable for a wide temperature range is first established to simulate the battery’s thermodynamic and electrical properties. The parameters of the model are identified by the electrochemical impedance spectroscopy experiments and particle swarm optimization method at six different temperatures, and then the relationship between parameters and temperature is obtained. Finally, the framework for joint estimation of both the cell internal temperature and the state-of-charge is presented based on the model-based state observer. The experimental results under different operation conditions indicated that, compared with the traditional off-line prediction method, the model-based online estimation method not only shows stronger robustness under different initial conditions but also has better accuracy. Specifically, the absolute mean error of the estimation of state-of-charge and internal temperature based on the proposed method is about 0.5% and 0.3°C respectively, which is about half of that based on the off-line prediction method.