Measurable Quantities Research Articles

Data-driven parallel optimization method for sensor placement and state estimation based on generative adversarial principle in unobservable systems

Abstract Data-Driven State Estimation (DDSE) is characterized by low measurement requirements and high estimation accuracy, which provides the possibility of stable and efficient estimation for unobservable distribution systems with low measurement quantities. However, the lack of an efficient and flexible sensor placement method with DDSE at this stage hinders the development and application of DDSE in distribution networks. To address this issue, a data-driven parallel optimization method for sensor placement and state estimation based on the generative adversarial principle in unobservable systems is proposed in this paper. This method transforms sensor placement and state estimation into an adversarial learning model, solvable through gradient descent. The sensor placement optimization strategy generates a cost-effective placement scheme, while DDSE evaluates the sensor scheme, provides improvement suggestions, and enhances its estimation accuracy. Through adversarial training, the proposed scheme yields a significantly reduced number of sensor placement schemes compared to traditional methods, while maintaining high precision of DDSE. Simulation results on the IEEE-33 node system validate the effectiveness of the proposed approach.

The Ongoing Struggle for Agrarian Reform As an Unfinished Agenda? Lessons From Mekarsari Village

Abstract: Agrarian reform without interaction between the state and society only addresses temporary issues. The implementation of agrarian reform in Indonesia has been overly focused on achieving outputs based on easily measurable quantities, leaving social problems unaddressed. The aim of this research is to elaborate the implementation of agrarian reform, particularly in the management of assets in the Mekarsari Agrarian Reform Village. The method used is a quantitative approach using questionnaires and in-depth interviews with 50 respondents who are beneficiaries of agrarian reform. The data were then analyzed using descriptive statistics method. The results of the study indicate that the implementation of management at the planning, implementation, and monitoring and evaluation stages shows that the interaction between the responsibility of state actors and community participation is low. As a result, the implementation of agrarian reform is still one-way, limited to completing the output targets of land redistribution and granting access decided by the organizers. Without meaningful community participation, it will be difficult for the community to take control to decide on the appropriate use of resources. For this reason, the implementation of agrarian reform in Mekarsari Village still needs to be contested. Keywords: Agrarian reform, Contested, State-society interaction

Absence of measurable quantities of Candida auris and Cryptococcus spp. in the gut microbiota of Ghanaian individuals with and without HIV infection as confirmed by applying multiple real-time PCR assays.

Introduction. Fungal infections are relevant health risks for individuals with acquired immunodeficiency in the resource-limited tropics, but available surveillance data are scarce. For Candida auris and Cryptococcus spp., the evolution from environmental reservoirs to human pathogens causing life-threatening diseases is currently discussed as a public health concern in the context of climate change and limited treatment options.Gap statement. Uncovering the gastrointestinal tract as an epidemiological niche of fungi emerging from the environment into individuals for whom fungal infections are not diagnosed.Aim. To contribute to data on the local epidemiology of C. auris and Cryptococcus spp. in Western African Ghana by analysing gastrointestinal samples of Ghanaian individuals.Methodology. Four real-time PCR assays targeting C. auris and five real-time PCR assays targeting Cryptococcus spp. were applied with stool samples of 875 non-age-stratified Ghanaian HIV patients and 30 Ghanaian control individuals without known HIV infection. Also, 664 samples from Ghanaian children under 2 years of age were investigated. The true abundance of the target micro-organism was considered as unlikely in the case of one or fewer positive signals, likely in the case of two to three positive signals and highly likely in the case of four or more positive signals per sample in the real-time PCR assays.Results. The combined application of sensitive, target-specific real-time PCR assays indicates that neither C. auris, Cryptococcus neoformans complex nor Cryptococcus gattii complex were part of the gut microbiota of Ghanaian individuals with or without HIV infection.Conclusion. Despite the significant disease burden from these pathogens in immunosuppressed Ghanaian individuals, detection from gastrointestinal samples was unlikely, which should be taken into account when discussing screening strategies for these fungi of public health concern. In contrast, the detection of these fungi from such samples should not routinely be considered as commensal colonization flora.

Protocols for bulk off-line fluid inclusion extraction for the analysis of δ13C-CH4 and δ13C-CO2 using a cavity ring-down spectroscopy (CRDS) analyser

Fluid inclusions are a window into deep geological fluids, providing unique access to their nature and composition. The isotopic composition of CO2 and CH4 hosted in fluid inclusions is a powerful proxy to assess the origin and transformation of deep geological fluids, giving insights into carbon sources, fluxes, and degassing in a wide variety of geodynamic settings. Over the last 5 decades, techniques have been developed to extract fluid inclusions from their host minerals and measure their bulk composition. These techniques are often challenged by analytical artifacts including high blank levels of CO2 and CH4, fluid re-speciation, gas adsorption, and diffusion. Since these processes may alter the pristine composition of gases liberated from fluid inclusions, rigorous protocols are needed in order to evaluate the isotopic integrity of the extracted volatile species. In this study, we introduce new protocols for bulk off-line fluid inclusion extraction for the analysis of δ13C-CH4 and δ13C-CO2 using a Cavity Ring-Down Spectroscopy (CRDS) analyser (Picarro G2201-i). Two mechanical fluid extraction techniques are compared: ball milling in ZrO2 jars and sample crushing in a stainless steel sealed tube under a hydraulic press. Blanks and isotopically labelled tests with the ball milling technique suggest that rotation speed, grinding stock filling degree and filling type alter the CH4 and CO2 concentrations and isotopic compositions measured by the CRDS analyser. In contrast, the crushing technique does not generate measurable quantities of blank CH4 and CO2. The protocols presented in this study allow to extract, detect, and analyse δ13C of CH4 and CO2 for concentrations above 10 and 1,000 ppm respectively. Interlaboratory experiments allowed to replicate previously measured δ13C-CH4 values in natural fluid inclusions within 1‰ with both extraction techniques. This study highlights the potential of combining simple bulk off-line fluid inclusion extraction techniques with a CRDS analyser for δ13C analysis of CO2 and CH4 without gas separation being required.

Unique seismic and eruption precursors to the 1996 and ongoing magmatic eruptions of Popocatépetl: Coupled and fluidized bed events

We describe three unique types of seismicity at Popocatépetl volcano that accompanied the initial vent-clearing eruptive activity in December 1994 through the eruption of the first two domes in 1996. We identify and describe two types of coupled events, 1) spasmodic burst coupled events, a burst of volcano tectonic (VT) events coupled with a large eruptive explosion (21 December 1994 and 5 March 1996), and 2) explosion-couplet coupled events, a pair of events with a deeper first event and whose second event correlates with a small gas emission or explosion. Explosion-couplets occurred with the onset of magmatic ash dominated eruptions and their properties are very useful for forecasting magmatic eruptions at Popocatépetl volcano. Measurable quantities including the time between the first and second phase, daily numbers of events, and the amplitude ratio between the second and first phase systematically changed as the first two domes approached the surface between March and June 1996. Interevent times decreased from many tens of seconds to a few seconds, while amplitude ratios increased from about 2 to 10 or more. Event numbers increased prior to and during initial dome extrusion. These changes were used to forecast the eruption of the first two domes. We also report on another unusual type of low frequency seismicity that accompanied emissions called fluidized bed events. Fluidized bed events occurred following the initial eruption on 21 December 1994, beginning mid-January 1995, when SO2 emissions were initially elevated, and the conduit was open. Fluidized bed events began to wane in late March through the end of May 1995 as did SO2 emissions. Consistent gas, visual and seismic observations by Centro Nacional de Prevención de Desastres (CENAPRED) enabled the direct correlation of the gas, magma, and seismic phenomena.

Fundamental representation of the amount of substance fraction of carbon dioxide in nitrogen according to the dynamic volumetric principle

Abstract The new Austrian primary standard for the amount of substance fraction of carbon dioxide in nitrogen is presented. The primary standard is working according to the dynamic volumetric principle and is a fundamental representation of the measurement quantity. The direct traceability to the basic SI units is thereby thermodynamically realized without an artefact. A complete measurement uncertainty budget is calculated and verified with a bilateral inter-laboratory comparison.

Maximizing the Minimum: The Advantages of Repeated Measures in Construction Management Education Research

ABSTRACT Many construction management (CM) courses have low enrollment numbers, making them difficult to study using independent measures research designs. However, repeated measures (RM) research designs, which have historically been underutilized in CM education research, can be used to overcome the deleterious effects of low participation by increasing the number of measurements to achieve sufficient statistical power (i.e. 1-β greater than .80). This paper is the final installment in a research series documenting an RM experiment testing the effectiveness of instructional videos on undergraduate CM students. The emphasis of this paper is on the research method – a within-subject, withdrawal-of-treatment, crossover, RM experimental design – chosen for its ability to increase the statistical power for small sample sizes. The final, actual statistical power of the study was .99. Incongruous with most research testing the pedagogical effectiveness of instructional videos, the study found no statistically significant difference between students who were given instructional videos and the control group. Researchers should consider using RM designs to amplify statistical power in studies with low anticipated participation or to avoid missing clear opportunities to improve the quality and precision of their research findings by increasing the quantity of measurements.

Þingstörf á Alþingi 1991-2015. Kyrrstaða í breyttu umhverfi

Í þessari grein er málþóf og veikt skipulag í þingstörfum á Alþingi á síðustu 24 árum skoðað í ljósi fræðikenninga um þjóðþing og um samfélagsleg áhrif netsins og breytts ytra og innra umhverfis þingsins. Í ljós kemur að þingstörfin einkennast af átökum sem eru föst í ákveðnu fari og spilla tímastjórnun og stjórn dagskrár. Megineinkenni og mælanlegar stærðir breytast lítið í þessu tilliti. Þá eru ábendingar um að gæðum lagasetningar sé ábótavant. Að stjórnarandstaðan komist í samningsaðstöðu í málum með málþófi vegna veiks skipulags þingstarfa virðist óviðeigandi lausn á annars afar mikilvægu máli. Kröfur nútímans um vönduð vinnubrögð, skilvirkni og málefnalega, hnitmiðaða og skiljanlega umræðu eru orðnar háværar.

Thermal response function method: A method for predicting the transient surface temperature of black-box objects

In engineering practice, thermal analysis of objects with unknown internal structure and/or thermophysical properties, and uncertainties in contact thermal resistances, is very challenging and even impossible using the traditional approach of direct solving the heat transfer equation. In this work, a thermal response function method (TRFM) is proposed for predicting the transient surface temperature of ‘black-box’ objects (i.e., unknown internal structure and thermophysical properties). The method relies on an introduced measurable quantity called thermal response function, which characterizes the thermal response characteristics of an object. Using the measured thermal response functions as input parameters, the transient temperature distribution on the surface of a black-box object under arbitrary external heat flux boundary condition can be predicted through linear superposition. Proof-of-concept simulations and experiments are conducted to demonstrate the feasibility and effectiveness of the TRFM method. The predicted surface temperature distribution under various external heat fluxes using TRFM agree well with the reference results. The results show that the TRFM is very promising as a solution of the challenging problem of predicting the transient surface temperature of black-box objects, with potential application for thermal imaging modeling of complex objects.

Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy

We present a study where predictive mechanistic modeling is combined with deep learning methods to predict individual patient survival probabilities under immune checkpoint inhibitor (ICI) immunotherapy. This hybrid approach enables prediction based on both measures that are calculable from mechanistic models of key mechanisms underlying ICI therapy that may not be directly measurable in the clinic and easily measurable quantities or patient characteristics that are not always readily incorporated into predictive mechanistic models. A deep learning time-to-event predictive model trained on a hybrid mechanistic + clinical data set from 93 patients achieved higher per-patient predictive accuracy based on event-time concordance, Brier score, and negative binomial log-likelihood-based criteria than when trained on only mechanistic model-derived values or only clinical data. Feature importance analysis revealed that both clinical and model-derived parameters play prominent roles in increasing prediction accuracy, further supporting the advantage of our hybrid approach.

Characterization and Control of Carbon Nanotube Doping

Carbon nanotube FETs show great promise for beyond-Si and monolithic 3D electronics, however there are still fundamental questions to explore. In particular, controlled N- and P- doping is a fundamental process module which can be used to engineer semiconductor resistance in un-gated regions such as the contact or extension, as well as optimize band-to-band tunneling leakage [1-4]. To-date both N- and P- doping has been demonstrated for CNT, but the optimal strategies for doping control and carrier density quantification have not been determined. In this work, we present a study of N- and P- doping using solid-state dopants and doping control strategy using a dielectric barrier of tunable thickness. A TCAD evaluation reveals the tradeoffs between carrier density and mobility for increasing dielectric barrier thickness, and reveals the critical role of dielectric constant in optimizing performance of spacer doping [5]. Multiple characterization approaches under evaluation help to correlate doping strength to experimentally measurable quantities with insight into the doping mechanisms. Finally, we will summarize potential approaches for improving doping control and quantification, and progress towards integration of the doping in highly-scaled high-performance carbon nanotube FETs [6].[1] Z. Zhang, et al., “Complementary carbon nanotube metal-oxide-semiconductor field-effect transistors with localized solid-state extension doping,” Nature Electronics, 2023.[2] Q. Lin, et al., “Band-to-band Tunneling Leakage Current Characterization and Projection in Carbon Nanotube Transistors,” ACS Nano, 2023.[3] G. Zeevi, et al., “PN Junction and band to band tunneling in carbon nanotube transistors at room temperature,” Nanotechnology, 2021.[4] L. Liyanage, et al., “VLSI-compatible carbon nanotube doping technique with low work-function metal oxides,” Nano Letters, 2014.[5] C. Gilardi et al., “Barrier Booster for Remote Extension Doping and its DTCO for 1D & 2D FETs”, IEDM 2023[6] S.Li, et al., “High-performance and low parasitic capacitance CNT MOSFET: 1.2 mA/μm at VDS of 0.75 V by self-aligned doping in sub-20 nm spacer,” IEDM 2023.

Towards Rational Design of Battery Formation Protocols: From Electrochemical Modeling to Factory Deployment

In battery manufacturing, the formation process is both paramount and problematic. It is paramount since all batteries undergo formation charging and aging steps to build a resilient solid electrolyte interphase (SEI) and to screen for defects. It is problematic because the formation process is expensive to operate, remains a major source of factory energy demand, requires larger factory footprints, and takes an order of magnitude longer than nearly every other manufacturing step. Despite the centrality of the formation process in battery manufacturing, steps taken to optimizing formation protocols remain ad-hoc in the absence of design principles and physical models.We highlight recent progress in developing a principled understanding of the SEI formation process applied towards industrial battery formation process (i.e. in the context of a full cell). We review a reduced-order electrochemical model of the formation process that captures first cycle charge dynamics and subsequent cycling and aging degradation behavior [1]. The model predicts measurable quantities such as first cycle efficiency (FCE) and irreversible thickness growth under multiple formation protocols. We discuss opportunities to integrate the electrochemical formation model with differential voltage analysis (DVA) to visualize the connection between first cycle charge dynamics from the perspective of shifting electrode stoichiometries [2] and comment on applications towards physics-informed battery lifetime prediction [3]. We finally share recent data elucidating the effect of formation temperature, pressure, and protocol on cycle life.

Creative-aesthetic product design and tools

Providing a product with characteristics of beauty and creative innovation is one of the aims of any contemporary industry to meet the needs of customers and satisfy their aesthetic and functional requirements. To study the production process and the realisation of creative products with aesthetically pleasing attributes, we created an environment that allows the construction of simple textured polygons (triangles, squares, rhombuses and pentagons) through a software application. To overcome traditional ways of assessing creative products, a Birkhoff aesthetic measure, Euclidean distance and entropy measure have been developed and applied to a sample of smart products, manufactured in the implemented environment, to analyse their aesthetic, creative and order–complexity–chaos features, respectively. The results provided us with measurable quantities of the required qualities for the sample and for each distinct product, combining the metrics to visualise the creative products in 2D and 3D spaces. Further mathematical methods, such as the point process and density probability map applied on the same sample, allowed us to move from a statistical space to probabilistic landscapes, with enhanced forecasting capability on creative features for all future products. Industrial applications are expected in the production and evaluation of products from a creative point of view.

Archaeological Studies and Statistical Analysis of Sasanian Coins (Drachm) from Tis Village in Southeast of Iran

In 2002 AD, a hoard comprising of 183 coins was discovered by workers during the construction of a road near a village within the environs of Tis near Chabahar in Southeastern Iran. From this cache of 183 coins, 157 are currently preserved in the Museum of Zahedan and are used in this study. To date, no research has been conducted on any of the coins, which are arranged in albums with only a small number displaying details of their various properties. Initial research involved identifying the coins, identifying and recording their exact location, and developing a typology. This study identifies the precise location as determined via analysis of the king, the mint, and the date and in consideration and comparison of the listing of the coins by Stephen Albums, in which the qualitative measurement of the quantity of coins and quantitative measurement of coin’s mints have been studied. Studies show that the coins are attributed to the Sasanian period, Peroz I and are classified into four groups of typological type, and in 15 different mints, including Mazda Artaxerxes, Estakhri, and Darabgerd. Using the relative frequency graph, the highest quantity of coins, according to typology, is attributed to the second type at 35.02 % and the lowest attributed to the first and third types jointly at 11.46 % of the total. The highest quantity of coins is attributed to the mint of Estakhr at 13.37 % and the lowest to the mint of Gorgan at 0.64 % of the total. Due to an absence of determinable typological features, 10.88 % of the coins could not be attributed to any type. In addition, 26.74 % of the coins could not be attributed to any specific mints.

A new synthetic correlation electron cyclotron emission diagnostic for validating nonlinear gyrokinetic simulations of electron temperature turbulence.

To validate nonlinear gyrokinetic simulations of electron temperature turbulence, the experimental correlation electron cyclotron emission (CECE) measurements are to be compared using a synthetic CECE diagnostic, which generates modeled CECE measurement quantities by implementing realistic measurement parameters (e.g., spatial and wavenumber resolutions, radial location, etc.) to nonlinear gyrokinetic simulations. In this work, we calculate the radial and vertical spatial and wavenumber transfer functions, which are defined by the electron cyclotron emission emissivity radial profile and vertical probing antenna pattern, respectively. These transfer functions are applied to nonlinear gyrokinetic simulations of electron temperature turbulence using the continuum gyrokinetic code. A simultaneous comparison of the experimental electron temperature turbulence power spectrum and root-mean-square (RMS) level, as well as the radial correlation length with the new synthetic CECE diagnostic at a core location ρ ∼ 0.75 in an L-mode DIII-D tokamak plasma, is presented. The preliminary result shows that the synthetic CECE output underestimates the RMS level by ∼42% and overestimates the radial correlation length by ∼40%.

Tracking Control for $(x,u)$-Flat Systems by Quasi-Static Feedback of Classical States

It is well known that for flat systems the tracking control problem can be solved by utilizing a linearizing quasi-static feedback of generalized states. If measurements (or estimates) of a so-called generalized Brunovský state are available, a linear, decoupled and asymptotically stable tracking error dynamics can be achieved. However, from a practical point of view, it is often desirable to achieve the same tracking error dynamics by feedback of a classical state instead of a generalized one. This is due to the fact that the components of a classical state typically correspond to measurable physical quantities, whereas a generalized Brunovský state often contains higher order time derivatives of the (fictitious) flat output which are not directly accessible by measurements. In this paper, a systematic solution for the tracking control problem based on quasi-static feedback and measurements of classical states only is derived for the subclass of $(x,u)$-flat systems.

Pengaruh Media Audio Visual Terhadap Hasil Belajar IPA Eksperimen Kelas VII MTs Qotrun Nada Depok

The aim of the research is to determine the effect of implementing Audio Visual Learning Media on science learning outcomes by conducting experiments on class VIII students at MTs Qotrun Nada Depok. The research model used is an experimental method with analysis of the mean difference between two samples. The sample used was 40 students from classes VII.1 and VII.2 as the experimental class and 40 students from classes VII.3 and VII.4 as the control class. Research data to test the hypothesis comes from test scores on Measurement Materials and quantities. The instruments used are validity and reliability. The results of the research are the results of learning science using Audio Visual Learning Media (experimental class), with an average score of 72.30 with a median of 70.59; mode 68.42; variance 177.07; and standard deviation 13.31. It can be concluded that students' science learning outcomes provide good results. The science learning outcomes of students who did not use Audio Visual Learning Media (control class) obtained an average score of 50.85 with a median of 43.75; mode 47.17; variant 190.85; and standard deviation 13.81. This shows that students' science learning outcomes provide quite good results. So it can be concluded that there is an influence of Audio Visual Learning Media on science learning outcomes. From the research results, it was found that tcount = 7.13 was higher than ttable = 1.996 at a significance level of 5%, so H0 was rejected and H1 was accepted. This means that there is a significant difference between students' science learning outcomes taught with Audio Visual Learning Media. Keywords: ,

An accelerated inexact Newton regularization scheme with a learned feature-selection rule for non-linear inverse problems

With computational inverse problems, it is desirable to develop an efficient inversion algorithm to find a solution from measurement data through a mathematical model connecting the unknown solution and measurable quantity based on the first principles. However, most of mathematical models represent only a few aspects of the physical quantity of interest, and some of them are even incomplete in the sense that one measurement corresponds to many solutions satisfying the forward model. In this paper, in light of the recently developed iNETT method in (2023 Inverse Problems 39 055002), we propose a novel iterative regularization method for efficiently solving non-linear ill-posed inverse problems with potentially non-injective forward mappings and (locally) non-stable inversion mappings. Our approach integrates the inexact Newton iteration, the non-stationary iterated Tikhonov regularization, the two-point gradient acceleration method, and the structure-free feature-selection rule. The main difficulty in the regularization technique is how to design an appropriate regularization penalty, capturing the key feature of the unknown solution. To overcome this difficulty, we replace the traditional regularization penalty with a deep neural network, which is structure-free and can identify the correct solution in a huge null space. A comprehensive convergence analysis of the proposed algorithm is performed under standard assumptions of regularization theory. Numerical experiments with comparisons with other state-of-the-art methods for two model problems are presented to show the efficiency of the proposed approach.

Optimal Sensor Placement with Minimal Predicted Posterior Variance

The performance of each monitoring system critically depends on the sensor layout and typical optimization criteria are based on the accessibility to the structure on site, experience with similar structures, and an optimal signal-to-noise ratio. More advanced criteria aim to optimize the feature extraction process, and this paper aims to develop a sensor placement strategy for optimal damage diagnosis. The approach is based on Bayesian updating and the optimization goal is to find a sensor layout that is the most sensitive to small changes in the examined system parameters. It is shown that such layouts manifest themselves through a minimum variance in the posterior distribution. Using Kalman filters, the posterior variance can be “predicted” based on the measurement error and numerical models, so no data from and no simulations in the damaged state are required. By employing a polynomial chaos expansion (PCE)-based Kalman filter, the method becomes applicable for structures with many measurement channels, multiple examined system parameters, and for a large number of sensor combinations. Gaussian distributions are assumed for both system inputs and outputs. For proof of concept, the sensor placement is optimized on a numerical cantilever beam, demonstrating that the method can efficiently find the optimal sensor layout. Moreover, arbitrary measurement quantities (inclinations, vibrations, etc.) or damage-sensitive features (statistical values, modal parameters, etc.) can be used as observations, and multiple system parameters can be considered at the same time. Among other factors, an optimal sensor layout leads to large measurement responses, a small measurement error, and more advanced statistical quantities that will be elaborated on in detail.

Aqueous and Plasma Levels of Phosphorylated Tau 181 in Individuals with Normal Cognition.

Plasma and cerebrospinal fluid (CSF) levels of p-tau181 have been associated with Alzheimer's disease (AD). The retina and vitreous have shown measurable quantities of phosphorylated tau 181 (p-tau181). The aqueous humor, which can be collected during cataract surgery, may have measurable concentrations of p-tau181. To determine whether p-tau181 is detectable in the aqueous humor and if so, whether it is associated with other measures that might be consistent with AD such as higher plasma p-tau181 concentration and lower Montreal Cognitive Assessment (MoCA-BLIND version 7.1) score. Aqueous humor samples, blood samples, and MoCA-BLIND scores were collected from patients who did not carry a clinical diagnosis of cognitive impairment at the time of cataract surgery. Aqueous p-tau181 concentrations and plasma p-tau181 concentrations were then measured using ultra-sensitive single-molecule assay ELISA technology. A rank-transformed mixed-effects multivariate regression model was used to determine associations between aqueous concentrations, plasma concentrations, and MoCA-BLIND scores. 16 eyes of 16 participants were enrolled with an average age of 71.6. Average MoCA-BLIND score was 20.6/22, average aqueous p-tau181 concentration was 6.4 pg/mL, and average plasma p-tau181 concentration was 3.1 pg/mL. Higher plasma p-tau181 was significantly associated with higher aqueous p-tau181 (p = 0.02). Aqueous p-tau181 and plasma p-tau181 were negatively associated with MoCA-BLIND scores (p = 0.005 and p = 0.001 respectively) in these patients. Aqueous p-tau181 is positively correlated with plasma p-tau181 and is negatively correlated with MoCA-BLIND scores. Further study in individuals with mild cognitive impairment or AD characterized by cerebrospinal fluid and volumetric MRI metrics may yield further insights.