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At least 19 records

Electron bunch position determination using a high frequency button beam position monitor in the AWAKE facility

The AWAKE facility uses novel proton beam-driven plasma wakefields to accelerate electron bunches over 10m of Rubidium plasma. Precise monitoring of 2 diverse beam types necessitates an electron beam position monitor (BPM) working in a frequency regime of tens of GHz. A high frequency conical button-style BPM with a working regime of up to 40 GHz has been investigated as a way to discriminate the electromagnetic fields of 19 MeV, 4 ps electron bunches propagating spatially and temporally together with a 400 GeV, 170 ps proton bunch in the AWAKE common beamline. The sensitivity of the HF BPM to the electron beam position is determined under various beam conditions, with both electrons and protons, and integration with a TRIUMF front-end is discussed.

43 PARTICLE ACCELERATORS

Machine Learning Enabled Position Detection for 6.78 MHz UAV Wireless Power Transfer System

This paper presents a novel supervised machine learning (SML) approach for accurate position detection of the receiver coil in wireless power transfer (WPT) systems using only secondary-side electrical measurements, with applications in autonomous unmanned aerial vehicle (UAV) charging. The proposed method trains a supervised learning model to map measured secondary-side voltage and current features to the receiver’s spatial position with high precision. This enables an autonomous UAV to determine its location relative to the primary coil center, the optimal position for maximizing wireless charging efficiency. The sensing method is fully integrated into a standard WPT system, utilizing the same primary and secondary coils for both power transfer and position detection, thereby eliminating additional sensing hardware. The use of a 6.78 MHz operating frequency enhances positional sensitivity, as high-frequency near-field electromagnetic fields respond strongly to small spatial variations. Experimental validation is performed on a 30 W scaled prototype featuring a 210 mm × 140 mm primary coil, a 50 mm × 80 mm receiver coil, and a 15 mm air gap. Results demonstrate reliable position estimation and a strong correlation between predicted position and optimal coil alignment. This integrated framework unifying position detection and wireless charging offers a promising foundation for future autonomous electric vertical takeoff and landing (eVTOL) systems, enabling compact, hardware-efficient, and high-accuracy charging solutions.

Colak, Kerim [New York University]

Tau PET positivity in individuals with and without cognitive impairment varies with age, amyloid-β status, APOE genotype and sex

Abstract Tau positron emission tomography (PET) imaging allows in vivo detection of tau proteinopathy in Alzheimer’s disease, which is associated with neurodegeneration and cognitive decline. Understanding how demographic, clinical and genetic factors relate to tau PET positivity will facilitate its use for clinical practice and research. Here we conducted an analysis of 42 cohorts worldwide (N = 12,048), including 7,394 cognitively unimpaired (CU) participants, 2,177 participants with mild cognitive impairment (MCI) and 2,477 participants with dementia. We found that from age 60 years to 80 years, tau PET positivity in a temporal composite region increased from 1.1% to 4.4% among CU amyloid-β (Aβ)-negative participants and from 17.4% to 22.2% among CU Aβ-positive participants. Across the same age span, tau PET positivity decreased from 68.0% to 52.9% in participants with MCI and from 91.5% to 74.6% in participants with dementia. Age, Aβ status,APOEε4 carriership and female sex were all associated with a higher prevalence of tau PET positivity across groups.APOEε4 carriership in CU individuals lowered the age at onset of both Aβ positivity and tau positivity by decades. Finally, we replicated these associations in an independent autopsy dataset (N = 5,072 from 3 cohorts).

Neurosciences & Neurology

Load assessment of a wind farm considering negative and positive yaw misalignment for wake steering

Wake steering strategies are employed to increase the overall power production of wind farms by deflecting wakes of upstream turbines away from downstream ones. The gain in net power comes at the expense of increased fatigue loads experienced by downstream turbines. In this work we investigate performance and fatigue loading characteristics of a small farm consisting of five aligned International Energy Agency Wind Technology Collaboration Programme 15 MW wind turbines. A parametric study is performed where, for every wind direction from −20 to 20°, the yaw misalignment angle varies from −25 to 25°. This setup allows us to investigate asymmetries and identify optimal conditions for a given wind direction. In general, we find that positive yaw configurations are preferred and that yaw configurations that result in attractive power differences when compared to a baseline no-yaw scenario (25 %) come with significant increase in fatigue loading (we use the standard deviation and damage-equivalent load (DEL) of the blade-root, low-speed shaft, and tower-base moments as proxies for fatigue load). We find that for any given positive wind inflow angle, yaw angles between −2.5 and 15° yield power differences of 10 %–20 % over a no-yaw baseline, and positive yaw is preferred because of lower fatigue loading. For any given negative wind inflow angles, positive yaw also results in lower magnitudes of standard deviation and DEL for the channels investigated. A small power loss of up to 2 % is observed for some positive yaw angles under negative wind directions (as compared to symmetric negative yaw and positive wind cases), but improvements in terms of loads exceed 25 % and may be enough to justify a positive yaw configuration under negative winds as well. We show that such behavior can be explained by partial waking and the direction of the rotation of the rotor.

17 WIND ENERGY

A317_Fast and Thermal Neutron Spectrum Dosimetry Measurements in the Advanced Test Reactor large-B and small-I Positions Following the Sixth Core Internals Change-out

The Advanced Test Reactor (ATR) has a wide variety of irradiation positions that have had experiments that were developed by users from around the world. Most experiment irradiations rely on thoroughly benchmarked numerical models. However, some irradiation positions in ATR are not as well- characterized and are complicated by spectral perturbations from control cylinder orientation. The “small I” and “large-B” irradiation positions are located nearby control cylinders and suffer from these flux perturbations from control cylinder orientations that change during an irradiation cycle to maintain the desired core power distribution. Models predicted that these types of position would exhibit both spectral shifts and amplitude changes in neutron flux, but few measurements have been conducted to benchmark these predictions. Recently, requalification testing was performed to confirm the operational readiness of the ATR following the completion of the Core Internals Change-out (CIC). These tests provided a unique opportunity to validate the analytical methods used to simulate the ATR because nearly all components in the reactor were in a clean as-built state, significantly reducing modelling uncertainties. One subset of the testing included characterization of the fast and thermal neutron flux in the “small-I” and “large-B” positions using silver, cobalt, and nickel neutron dosimetry. In contrast to typical irradiation cycles, the control cylinders were held in position during the post-CIC nuclear testing. The specific activity of these dosimeter wires was measured following two low-power tests with different control cylinder positions.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN

Concurrent Inter-Model Spread of Boreal Winter Westerly Jet Meridional Positions Between the Northern and Southern Hemispheres in CMIP6 Models

Here, this study investigates the inter-model spread of climatological extratropical westerly jets in boreal winter, using the historical simulation of 52 Coupled Model Intercomparison Project phase 6 (CMIP6) models from 1851 to 2014. The results show that there is a substantial spread in the latitude of the upper-tropospheric westerly jet across models, characterised by large inter-model standard deviations to both the poleward and equatorward sides of the jet axis, although the multi-model ensemble mean (MME) performs well in simulating meridional position of westerly jets. Furthermore, we detect the consistency of inter-model jet position spread between the Northern and Southern Hemispheres, based on the inter-model empirical orthogonal function (EOF) decomposition and correlation of regional-averaged zonal winds. Specifically, the models that simulate the westerly jets poleward/equatorward relative to the MME position in one hemisphere also tend to simulate the jets poleward/equatorward in the other hemisphere. Accordingly, we define a global jet spread index to depict the concurrence of jet shift in the two hemispheres. The results of inter-model regression analyses based on this index indicate that the models positioning the jets poleward than the MME tend to simulate a wider Hadley Cell, a poleward-shifted Ferrel Cell in the Southern Hemisphere, enhanced precipitation in the subtropics and suppressed precipitation in the tropics, and warmer sea surface temperatures in the subtropics and mid-latitudes. The present results suggest that improving the simulation of jet positions in climate models requires a comprehensive consideration of thermal states in the tropics and subtropics/mid latitudes.

54 ENVIRONMENTAL SCIENCES

Thermal processing to modulate surface chemistry and bulk charge distribution in nickel-rich layered lithium positive electrodes

The broader application of nickel-rich layered oxides as positive electrode materials for lithium-ion batteries has been hindered by their high manufacturing cost and inferior cycling stability. Thermal processing, which is integral to electrode materials manufacturing and fundamental in materials science, has not been fully utilized to design advanced positive electrode materials. Herein, we demonstrate the capability of using quenching heat treatment to regulate Li distribution and modulate electronic structure near particle surface. The resulting materials exhibit less parasitic reactions with the electrolyte and an improved charge distribution homogeneity in secondary particles, leading to more stable cycling performance at high voltages (4.5 V vs Li/Li + ). Our synchrotron X-ray analyses reveal the underlying interplay between surface structure and bulk charge distribution in positive electrode materials particles. While strategies used to stabilize positive electrode materials through compositional control, surface modification, and electrolyte engineering have become mature, thermal processing can be advantageous to further improve positive electrode materials manufacturing.

36 MATERIALS SCIENCE

Prototype acoustic positioning system for the Pacific Ocean Neutrino Experiment

We present the design and initial performance characterization of the prototype acoustic positioning system intended for the Pacific Ocean Neutrino Experiment. It comprises novel piezo-acoustic receivers with dedicated filtering- and amplification electronics installed in P-ONE instruments and is complemented by a commercial system comprised of cabled and autonomous acoustic pingers for sub-sea installation manufactured by Sonardyne Ltd. We performed an in-depth characterization of the acoustic receiver electronics and their acoustic sensitivity when integrated into P-ONE pressure housings. These show absolute sensitivities of up to -125 dB re V2/μPa2 in a frequency range of 10–40 kHz. We furthermore conducted a positioning measurement campaign in the ocean by deploying three autonomous acoustic pingers on the seafloor, as well as a cabled acoustic interrogator and a P-ONE prototype module deployed from a ship. Using a simple peak-finding detection algorithm, we observe high accuracy in the tracking of relative ranging times at approximately 230–280 μs at distances of up to 1600 m, which is sufficient for positioning detectors in a cubic-kilometer detector and which can be further improved with more involved detection algorithms. The tracking accuracy is further confirmed by independent ranging of the Sonardyne system and closely follows the ship's drift in the wind measured by GPS. The absolute positioning shows the same tracking accuracy with its absolute precision only limited by the large uncertainties of the deployed pinger positions on the seafloor.

Data analysis

Supervised Learning-Based Spatial Position Estimation with Vertical Displacement for Hovering UAV Wireless Power Transfer

This study presents a supervised learning-based spatial position estimation approach for wireless power transfer (WPT) systems supporting hovering unmanned aerial vehicle (UAV) charging. Unlike stationary charging scenarios, hovering UAVs introduce continuous lateral misalignment and vertical displacement, leading to variations in magnetic coupling and reduced power transfer efficiency. To address this challenge, the proposed method estimates the relative spatial position of the receiver coil using only electrical measurements obtained at the secondary side. A supervised learning model is trained to map output voltage and current features to spatial coordinates, enabling position awareness without requiring external sensors, vision systems, or communication links. The sensing functionality is inherently integrated into the WPT system, allowing simultaneous power transfer and localization through the same magnetic interface. Experimental validation is conducted on a laboratory-scale prototype under varying lateral offsets and air-gap conditions. In addition, spline-based interpolation is employed to increase spatial data density for training. The results demonstrate that the proposed framework can capture spatial variations associated with both lateral and vertical displacement, providing reliable position estimation under hovering conditions. This work establishes a hardware-efficient, sensorless solution for UAV wireless charging and serves as a baseline for advanced data-driven position estimation methods in dynamic WPT systems.

Asa, Erdem [ORNL] (ORCID:0000000190884812)

Predicting ptychography probe positions using single-shot phase retrieval neural network

Ptychography is a powerful imaging technique that is used in a variety of fields, including materials science, biology, and nanotechnology. However, the accuracy of the reconstructed ptychography image is highly dependent on the accuracy of the recorded probe positions which often contain errors. These errors are typically corrected jointly with phase retrieval through numerical optimization approaches. When the error accumulates along the scan path or when the error magnitude is large, these approaches may not converge with satisfactory result. We propose a fundamentally new approach for ptychography probe position prediction for data with large position errors, where a neural network is used to make single-shot phase retrieval on individual diffraction patterns, yielding the object image at each scan point. The pairwise offsets among these images are then found using a robust image registration method, and the results are combined to yield the complete scan path by constructing and solving a linear equation. We show that our method can achieve good position prediction accuracy for data with large and accumulating errors on the order of 10 2 pixels, a magnitude that often makes optimization-based algorithms fail to converge. For ptychography instruments without sophisticated position control equipment such as interferometers, our method is of significant practical potential.

47 OTHER INSTRUMENTATION

Optimizing collimator positions using bayesian optimization in the Fermilab MI-8 transfer line

Collimators are used to minimize losses and to remove particles that would otherwise get lost downstream and irradiate the machine. Finding the optimal jaw positions is time consuming and with the upstream beam properties changing, the collimation settings would need to be readjusted each time. Therefore, a method to optimize collimator positions and to operate them at full capacity in a short time is required for loss control downstream. A study of collimator positions was conducted and a machine learning (ML) model was developed to predict optimal collimator positions. Bayesian Optimization (BO) was used to calculate new jaw positions from the ML model. The results of BO and usage of ML for better performance of the collimation system are presented in this paper.

Babacan, Betiay [Fermilab]

Pseudomonas aeruginosa Adhesion and Biofilm Formation on Poly(l-lysine)-Tethered Hydrogels: Synergistic Effect of Substrate Stiffness and Positive Charge Density

Infections associated with antibacterial-resistant Pseudomonas aeruginosa (P. aeruginosa) are the major cause of morbidity and mortality of patients, presenting one of the greatest therapeutic challenges for treatment of community-acquired and nosocomial infections. To develop antimicrobial hydrogel coatings to control the adhesion and subsequent biofilm formation of P. aeruginosa, we have used photo-cross-linked poly(ethylene glycol) diacrylate (PEGDA) hydrogels with varied cross-linking densities and covalently grafted poly(l-lysine) (PLL) at different weight compositions (ϕ PLL ). Both surface stiffness and positive charge density of the hydrogels were efficiently tuned over a broad range to investigate their effects on two main strains of P. aeruginosa, PA01 and PA14. We found that both number and viability of attached cells were positively correlated with the hydrogel stiffness, leading to thicker and larger coverage of cell colonies at 72 h postseeding on the stiffer substrates. The dependence of both PA01 and PA14 strains on ϕ PLL , however, was nonmonotonic. Positive charges from dissociated amine groups in the grafted PLL chains significantly promoted initial adhesion and proliferation of both strains at low ϕ PLL and developed into the thickest biofilms on the stiffest hydrogels grafted with ϕ PLL of 1–2%. Nevertheless, on the softest hydrogels grafted with PLL at high ϕ PLL of 7–10%, the bacteria no longer attached or survived. These results not only improved our fundamental understanding of bacteria-material interactions but also provided a series of PLL-grafted PEGDA hydrogels with controlled stiffness and positive charge density as ideal surface coating materials to prevent bacterial infections.

bacteria

Improved laser-plasma accelerator stability via high-bandwidth longitudinal focal position stabilization of a 100 TW-class laser system

Laser-plasma accelerators (LPAs) offer an attractive alternative to conventional accelerators for the development of compact electron sources and next-generation light sources. Due to orders-of-magnitude larger accelerating gradients, LPAs enable the acceleration of high-brightness electron beams to ultrarelativistic energies in millimeter- to centimeter-scale distances. However, LPA stability is limited by shot-to-shot fluctuations of the driving laser system. Specifically, fluctuations in the final-focus longitudinal position result in correlated instability in LPA electron beam qualities, including total beam charge, average beam energy, and energy spread. We demonstrate active stabilization of the longitudinal focal position for a 100 TW-class laser system. This repetition-rate scalable stabilization system leverages noninvasive wave front monitoring of a copropagating, unamplified kHz pulse train to guide corrective adjustments to the focal position of a 1 Hz amplified drive laser via an upstream telescope on millisecond timescales. In this demonstration, the approach limits standard deviation fluctuations of the amplified drive beam’s longitudinal focal position to ±0.22⁢ mm (representing at least a 53% reduction), achieved with a correction bandwidth that reaches the Nyquist frequency limit. Consequently, we observe marked improvements in both long-term and shot-to-shot LPA stability in terms of charge and spectrum.

Beam control

Position-Enhanced Gradient Attack (PEGA) on Medical Language Models

Federated Learning (FL) enables collaborative training of language models on sensitive clinical notes without sharing the data. However, this paradigm is vulnerable to gradient inversion attacks that can reconstruct private data from shared gradients. We find that state-of-the-art attacks are less effective in the medical domain, failing to overcome the unique challenges posed by its specialized vocabulary and unstructured format. To address this, we introduce the Position-Enhanced Gradient Attack (PEGA), a novel attack that makes gradients position-aware by optimizing token and position embeddings simultaneously. PEGA employs two key innovations: a periodic sorting of positional embeddings to resolve token order ambiguity and a late-stage embedding replacement strategy to correct hard-to-recover critical tokens. To evaluate the leakage of sensitive data more directly, we also propose the Unified PHI-Recall (UPHI), a new metric measuring the recovery of Protected Health Information. Experiments on the MIMIC-III dataset show that PEGA significantly outperforms leading attacks like TAG and LAMP, particularly in its ability to reconstruct identifiable patient information, exposing a more severe and nuanced privacy risk in federated medical NLP.

Xu, Nuo [University of Minnesota]

The impact of kidney function on Alzheimer’s disease blood biomarkers: implications for predicting amyloid-β positivity

Impaired kidney function has a potential confounding effect on blood biomarker levels, including biomarkers for Alzheimer’s disease (AD). Given the imminent use of certain blood biomarkers in the routine diagnostic work-up of patients with suspected AD, knowledge on the potential impact of comorbidities on the utility of blood biomarkers is important. We aimed to evaluate the association between kidney function, assessed through estimated glomerular filtration rate (eGFR) calculated from plasma creatinine and AD blood biomarkers, as well as their influence over predicting Aβ-positivity. We included 242 participants from the Translational Biomarkers in Aging and Dementia (TRIAD) cohort, comprising cognitively unimpaired individuals (CU; n = 124), mild cognitive impairment (MCI; n = 58), AD dementia (n = 34), and non-AD dementia (n = 26) patients all characterized by [ 18 F] AZD-4694. Plasma samples were analyzed for Aβ42, Aβ40, glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), tau phosphorylated at threonine 181 (p-tau181), 217 (p-tau217), 231 (p-tau231) and N-terminal containing tau fragments (NTA-tau) using Simoa technology. Kidney function was assessed by eGFR in mL/min/1.73 m 2 , based on plasma creatinine levels, age, and sex. Participants were also stratified according to their eGFR-indexed stages of chronic kidney disease (CKD). We evaluated the association between eGFR and blood biomarker levels with linear models and assessed whether eGFR provided added predictive value to determine Aβ-positivity with logistic regression models. Biomarker concentrations were highest in individuals with CKD stage 3, followed by stages 2 and 1, but differences were only significant for NfL, Aβ42, and Aβ40 (not Aβ42/Aβ40). All investigated biomarkers showed significant associations with eGFR except plasma NTA-tau, with stronger relationships observed for Aβ40 and NfL. However, after adjusting for either age, sex or Aβ-PET SUVr, the association with eGFR was no longer significant for all biomarkers except Aβ40, Aβ42, NfL, and GFAP. When evaluating whether accounting for kidney function could lead to improved prediction of Aβ-positivity, we observed no improvements in model fit (Akaike Information Criterion, AIC) or in discriminative performance (AUC) by adding eGFR to a base model including each plasma biomarker, age, and sex. While covariates like age and sex improved model fit, eGFR contributed minimally, and there were no significant differences in clinical discrimination based on AUC values. We found that kidney function seems to be associated with AD blood biomarker concentrations. However, these associations did not remain significant after adjusting for age and sex, except for Aβ40, Aβ42, NfL, and GFAP. While covariates such as age and sex improved prediction of Aβ-positivity, including eGFR in the models did not lead to improved prediction for any biomarker. Our findings indicate that renal function, within the normal to mild impairment range, does not seem to have a clinically relevant impact when using highly accurate blood biomarkers, such as p-tau217, in a biomarker-supported diagnosis.

60 APPLIED LIFE SCIENCES

Discovery of genes that positively affect biomass and stress associated traits in poplar

Woody biomass serves as a renewable resource for various industries, including pulp and paper production, construction, biofuels, and electricity generation. However, the molecular mechanisms behind biomass traits are poorly understood, which significantly curtails the speed and efficiency of their improvement. We used activation tagging to discover genes that can positively affect tree biomass-associated traits. We generated and screened under greenhouse conditions a population of 2,700 independent activation tagging lines. A total of 761 lines, which had significantly and positively affected at least one biomass-associated trait, were discovered. The tag was positioned in the genome for forty lines which were affected in multiple traits and activation of proximal genes validated for a subset. For two lines we fully recapitulated the phenotype of the original lines through overexpression. Moreover, the overexpression led to more pronounced and additional improvements, not observed in the original lines. Importantly, the overexpression of a Fasciclin-like gene (PtaFLA10) and a Patatin-like gene (PtaPAT) was found to substantially improve biomass, with a 40% increase in dry-stem weight, and enhance drought tolerance, respectively. Additionally, PtaPAT overexpression increased cellulose content, which is crucial for biofuel production. Our work shows that the activation tagging approach applied even on a non-genome saturation scale in a poplar tree can be successfully used for the discovery of genes positively modify biomass productivity. Such dominant forward genetics approaches can aid in biotechnological manipulation of woody biomass traits and help unravel the functions and mechanisms of individual genes, gene families, and regulatory modules.

Plant Sciences

Correcting Turbulence-induced Errors in Fiber Positioning for the Dark Energy Spectroscopic Instrument

Highly multiplexed, robotic, fiber-fed spectroscopic surveys are observing tens of millions of stars and galaxies. For many systems, accurate positioning relies on imaging the fibers in the focal plane and feeding that information back to the robotic positioners to correct their positions. Inhomogeneities and turbulence in the air between the focal plane and the imaging camera can affect the measured positions of fibers, limiting the accuracy with which fibers can be placed on targets. For the Dark Energy Spectroscopic Instrument, we dramatically reduced the effect of turbulence on measurements of positioner locations in the focal plane by taking advantage of stationary positioners and the correlation function of the turbulence. We were able to reduce positioning errors from 7.3 to 3.5 μm, speeding the survey by 1.6% under typical conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND

Position-specific kinetic isotope effects for nitrous oxide: a new expansion of the Rayleigh model

Nitrous oxide (N 2 O) is a potent greenhouse gas and the most significant anthropogenic ozone-depleting substance currently being emitted. A major source of anthropogenic N 2 O emissions is the microbial conversion of fixed nitrogen species from fertilizers in agricultural soils. Thus, understanding the enzymatic mechanisms by which microbes produce N 2 O has environmental significance. Measurement of the 15 N/ 14 N isotope ratios of N 2 O produced by purified enzymes or axenic microbial cultures is a promising technique for studying N 2 O biosynthesis. Typically, N 2 O-producing enzymes combine nitrogen atoms from two identical substrate molecules (NO or NH 2 OH). Position-specific isotope analysis of the central (N α ) and outer (N β ) nitrogen atoms in N 2 O enables the determination of the individual kinetic isotope effects (KIEs) for N α and N β , providing mechanistic insight into the incorporation of each nitrogen atom. Previously, position-specific KIEs (and fractionation factors) were quantified using the Rayleigh distillation equation, i.e., via linear regression of δ 15 N α or δ 15 N β against [–f In f / (1 – f)], where f is the fraction of substrate remaining in a closed system. This approach, however, is inaccurate for N α and N β because it does not account for fractionation at N α affecting the isotopic composition of substrate available for incorporation into the β position (and vice versa). Therefore, we developed a new expansion of the Rayleigh model that includes specific terms for fractionation at the individual N 2 O nitrogen atoms. By applying this Expanded Rayleigh model to a variety of simulated N 2 O synthesis reactions with different combinations of normal, inverse, and/or no KIEs at N α and N β , we demonstrate that our new model is both accurate and robust. We also applied this new model to two previously published datasets describing N 2 O production from NH 2 OH oxidation in a methanotroph culture (Methylosinus trichosporium) and N 2 O production from NO by a purified Histoplasma capsulatum (fungal) P450 NOR, demonstrating that the Expanded Rayleigh model is a useful tool in calculating position-specific fractionation for N 2 O synthesis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH