Effect of carbon nanotube alignment on nanocomposite sensing performance

Abstract The objective of this study is to derive a numerical model of carbon nanotube (CNT)-based thin films that accurately reflect their electrical and electromechanical performance as observed through experimental tests. Although nanocomposites based on CNTs dispersed in polymer matrices have been studied extensively, their nanocomposite properties vary depending on CNT orientations. This study aimed to explain how differences in nanocomposite behavior could be revealed by numerical models considering different CNT alignment conditions. First, a percolation-based thin film model was generated by randomly dispersing CNT elements in a predefined two-dimensional domain. The degree of CNT alignment in the film was controlled by limiting the CNT elements’ maximum angle they make with respect to the film’s longitudinal axis. Then, numerical simulations on CNT-based film models were conducted. Second, multi-walled carbon nanotube (MWCNT)-epoxy films were prepared via drop casting. Alternating current was applied to the MWCNT-epoxy mixture before curing to prepare films with different degrees of CNT alignment. The electrical and electromechanical properties of these specimens were characterized, and the results were compared with simulations. Good agreement between experiments and simulations was observed

X-Factoring: Why the Texas Supreme Court Should Revisit Its Examination of Paid or Incurred Medical Expenses

Abstract forthcoming

ACN-Sim: An Open-Source Simulator for Data-Driven Electric Vehicle Charging Research

ACN-Sim is a data-driven, open-source simulation environment designed to accelerate research in the field of smart electric vehicle (EV) charging. It fills the need in this community for a widely available, realistic simulation environment in which researchers can evaluate algorithms and test assumptions. ACN-Sim provides a modular, extensible architecture, which models the complexity of real charging systems, including battery charging behavior and unbalanced three-phase infrastructure. It also integrates with a broader ecosystem of research tools. These include ACN-Data, an open dataset of EV charging sessions, which provides realistic simulation scenarios and ACN-Live, a framework for field-testing charging algorithms. It also integrates with grid simulators like MATPOWER, PandaPower and OpenDSS, and OpenAI Gym for training reinforcement learning agents.Comment: 9 pages, 8 figures. [v2] Update timezone issue with Fig. 8 where x-axis and background load was shifted by 3 hour

Development and Validation of eRADAR: A Tool Using EHR Data to Detect Unrecognized Dementia.

ObjectivesEarly recognition of dementia would allow patients and their families to receive care earlier in the disease process, potentially improving care management and patient outcomes, yet nearly half of patients with dementia are undiagnosed. Our aim was to develop and validate an electronic health record (EHR)-based tool to help detect patients with unrecognized dementia (EHR Risk of Alzheimer's and Dementia Assessment Rule [eRADAR]).DesignRetrospective cohort study.SettingKaiser Permanente Washington (KPWA), an integrated healthcare delivery system.ParticipantsA total of 16 665 visits among 4330 participants in the Adult Changes in Thought (ACT) study, who undergo a comprehensive process to detect and diagnose dementia every 2 years and have linked KPWA EHR data, divided into development (70%) and validation (30%) samples.MeasurementsEHR predictors included demographics, medical diagnoses, vital signs, healthcare utilization, and medications within the previous 2 years. Unrecognized dementia was defined as detection in ACT before documentation in the KPWA EHR (ie, lack of dementia or memory loss diagnosis codes or dementia medication fills).ResultsOverall, 1015 ACT visits resulted in a diagnosis of incident dementia, of which 498 (49%) were unrecognized in the KPWA EHR. The final 31-predictor model included markers of dementia-related symptoms (eg, psychosis diagnoses, antidepressant fills), healthcare utilization pattern (eg, emergency department visits), and dementia risk factors (eg, cerebrovascular disease, diabetes). Discrimination was good in the development (C statistic = .78; 95% confidence interval [CI] = .76-.81) and validation (C statistic = .81; 95% CI = .78-.84) samples, and calibration was good based on plots of predicted vs observed risk. If patients with scores in the top 5% were flagged for additional evaluation, we estimate that 1 in 6 would have dementia.ConclusionThe eRADAR tool uses existing EHR data to detect patients with good accuracy who may have unrecognized dementia. J Am Geriatr Soc 68:103-111, 2019

N=2 SUSY and the Hexipentisteriruncicantitruncated 7-Simplex

We study algorithms for recursively creating arbitrary N-extended `supermultiplets' given minimal matrix representations of off-shell, N = 1 supermultiplet matrices. We observe connections between the color vertex problems in graph theory and the different supermultiplet sets locations in the permutahedron by using the concepts of truncation and chromatic number. The concept of `hopping operators' is introduced, constructed, and then used to partition the 8! vertices of the permutahedron. We explicitly partition these into 5,040 octets constrained in locations on the permutahedron by a magic number rule. Boolean factors in this recursive construction are shown to obey a doubly even binary flip rule. Although these hopping operators do not generally constitute normal subgroups of the permutation group, we find that `ab-normal cosets' exist where the same left- and right-hoppers appear as unordered sets. Finally, using computer simulations, we investigate the types of faces on higher-order permutahedron which may give rise to lower-order supermultiplets.Comment: 35 pages, 12 figure

Thermal and magnetic properties of a low-temperature antiferromagnet Ce4_4Pt12_{12}Sn25_{25}

We report specific heat ($C$) and magnetization ($M$) of single crystalline Ce$_4$Pt$_{12}$Sn$_{25}$ at temperature down to $\sim$50mK and in fields up to 3T. $C/T$ exhibits a sharp anomaly at 180mK, with a large $\Delta C/T\sim$30J/molK$^2$-Ce, which, together with the corresponding cusp-like magnetization anomaly, indicates an antiferromagnetic (AFM) ground state with a N\'eel temperature $T_N$=180mK. Numerical calculations based on a Heisenberg model reproduce both zero-field $C$ and $M$ data, thus placing Ce$_4$Pt$_{12}$Sn$_{25}$ in the weak exchange coupling $J<J_c$ limit of the Doniach diagram, with a very small Kondo scale $T_K\ll T_N$. Magnetic field suppresses the AFM state at $H^*\approx$0.7T, much more effectively than expected from the Heisenberg model, indicating additional effects possibly due to frustration or residual Kondo screening.Comment: 8 pages, 7 figures, accepted for publication in Phys. Rev.