University School of Milwaukee

We determine the composition dependence of the below-bandgap anisotropic refractive indices and dielectric functions of β-(AlxGa1−x)2O3 for x up to 25% Al. We use Mueller matrix generalized spectroscopic ellipsometry and investigate a set of high quality single crystalline bulk (x=0%,5%,10%,15%,20%,25%) and thin film (4.6%, 9.7%, 12%, 15%, 16.3%, 21%) samples grown by the Czochralski method and by plasma-assisted molecular beam epitaxy, respectively. Bulk samples with 0.2% silicon doping are cut from ingots with (100) surface and the unintentionally doped thin films samples are grown pseudomorphically on (010) β-Ga2O3. The combination of ellipsometry data from both sample sets permits to fully determine the optical properties of the transparent alloys. We employ a quasi-orthorhombic approach which ignores the very small shear components induced by the monoclinic crystal structure. We also ignore the possibly small effects due to strain within the pseudomorphically grown epitaxial samples. We report indices and dielectric functions for polarization along lattice vectors a, b, and reciprocal lattice vector c⋆. All indices reduce with increasing incorporation of aluminum while the spectral range of transparency increases due to the increase in bandgap energy with composition. We use our results to predict Bragg reflector multilayer structures on b-plane β-(Al0.20Ga0.80)2O3, for use in polarization sensitive narrow-band optical filters in the short wavelength region.

This paper investigates robustness and convergence of iterative learning control (ILC) for mecanum-wheeled mobile robots operating under plant uncertainty and nonrepetitive disturbances. A Model-Based Corrector (MBC) ILC is introduced, which employs a fixed nominal inverse model to update the control input each iteration, thereby eliminating the need for online parameter estimation. Theoretical analysis based on the lifted-system formulation shows that convergence depends solely on the nominal model’s fidelity, ensuring stability under moderate modeling errors. The proposed method is experimentally compared with a baseline P-type ILC and an adaptive parameter-estimation ILC on a lemniscate trajectory tracking task subject to Gaussian measurement noise, a one-time disturbance, and a permanent plant change. Quantitative results demonstrate that MBC-ILC achieves the desired noise-floor accuracy (RMSE ≈ 0.02) within a few iterations, rejects nonrepetitive disturbances in a single iteration, and re-converges within six iterations following a plant change. Results show that a fixed-model corrector achieves a strong tradeoff of convergence speed, steady accuracy, and robustness at low computational cost, making it practical control architecture for robust trajectory learning in mobile robots.

Introduction: We investigated the impact of COVID-19 on physical activity (PA) in a veteran population with implanted cardiac devices by analyzing data from the devices’ embedded accelerometers. These accelerometers provide continuous, objective measurements of PA without requiring active patient participation or incurring additional costs, making them valuable for longitudinal monitoring and clinical research. Compared to pedometers, accelerometers have demonstrated superior accuracy and reliability in assessing physical activity levels. Methods: A total of 734 veterans with implanted Medtronic pacemakers or defibrillators at the Milwaukee VA Medical Center were screened for inclusion following IRB approval. Of these, 360 patients (aged 36–100 years; mean age 75.5 years) had continuous device-derived physical activity (PA) data available from 2018 through 2022. Data from 2018 and 2019 were categorized as the pre-COVID control period, while data from 2020, 2021, and 2022 were analyzed as the post-COVID study period. Results: There was a significant decline in physical activity (PA) recorded by the implanted cardiac devices between the pre-COVID and post-COVID periods (3.00 hr/day vs. 2.64 hr/day), representing a mean decrease of 0.37 hr/day (95% CI: 0.29 to 0.45; p < 0.0001). This downward trend in PA persisted even after public health restrictions were lifted. Conclusions: In a veteran population with implanted cardiac devices, physical activity significantly declined following the onset of COVID-19 and remained reduced through 2022, despite the lifting of public health restrictions. These findings highlight the lasting impact of the pandemic on functional status and underscore the value of device-based monitoring for long-term health surveillance. This has important implications for managing physical activity and health outcomes during future epidemics and pandemics.

Modern large surface naval vessels' size has significantly increased in the years, due to the need of integrating advanced sensors, platform systems, and the potential integration of directed energy systems (also called DEW). This necessitates a robust electrical power system with enhanced safety, redundancy, and modular design for fault tolerance and future upgradability. To address these challenges, the Power Corridor concept proposes a unified system for electric power distribution, conversion, isolation, and energy storage, offering improved fault tolerance, simplified layout, and reduced costs. The Power Corridor onboard integration can result in various power system topologies, from simple radial to complex zonal distributions, depending on generator, load, and interconnection arrangements. Therefore, fault analysis is crucial for evaluating specific implementations. This paper demonstrates the application of a novel methodology for assessing fault impact on different power system architectures during early design, using an all electric ship with a low voltage direct current (LVDC) Power Corridor as a case study. The work analyzes system connectivity and power shortfall under fault scenarios. The results demonstrate how it is possible to obtain significant information about the relationship between the power system topology and its fault behavior at an early stage design level, which can be useful to drive the vessel design in the later stages.

Transfer RNAs (tRNA) are decorated during biogenesis with a variety of modifications that modulate their stability, aminoacylation, and decoding potential during translation. The complex landscape of tRNA modification presents significant analysis challenges and to date no single approach enables the simultaneous measurement of important but disparate chemical properties of individual, mature tRNA molecules. We developed a new, integrated approach to analyze the sequence, modification, and aminoacylation state of tRNA molecules in a high throughput nanopore sequencing experiment, leveraging a chemical ligation that embeds the charged amino acid in an adapted tRNA molecule.

Diabetes Mellitus (DM) is a disease failed to control the balance of blood sugar level due to lack of insulin thereby it effect human health. In Malaysia, there are around 3.9 millions people aged 18 years old and above have diabetes according to National Health and Morbidity Survey 2019. Silicon Nanowire is a nanostructure which has ultra-high sensitivity and non-radioactive that has potential given good performances when applied on pH sensor and biosensor. Silicon nanowire pH sensor and biosensor is an electronic sensor that investigated to improve the sensitivity and accuracy for detecting DM. This project consists of two parts, which are fabrication of silicon nanowire pH sensor and simulation of silicon nanowire biosensor as preliminary study. In fabrication, silicon nanowire of pH sensor is fabricated by conventional lithography process, reaction ion etching (RIE) and metallization to achieved the width of 100 nm silicon nanowire. The pH6, pH7, pH10 and DI water as analytes to analysis the current-voltage (I-V) characteristics of silicon nanowire pH sensor. In second part, the silicon nanowire biosensor as preliminary study is done simulation by Silvaco ATLAS devices simulator. The silicon nanowire with 30 nm in height and 20 nm in width of biosensor is designed and simulated to analyze the performance in terms of sensitivity. I-V characteristics of silicon nanowire biosensor according to different concentration of negative interface charge is determined. The negative interface charge represent as the Retinol Binding Protein 4 (RBP4) which is used to diagnose DM. The I-V characteristic based on the change in current, resistance and conductance to determine sensitivity. Lastly, the sensitivity of silicon nanowire pH sensor obtained 23.9 pS/pH while the sensitivity of simulated silicon nanowire biosensor obtained 3.91 nS/e.cm2. The results shown the more negative charge of concentration analyte attached on surface silicon nanowire has been accumulated more current flow from drain terminal to source terminal. It leads to the resistance becomes highest and obtained good sensitivity. In summary, the silicon nanowire pH sensor exhibited good performance and high sensitivity in detection pH level. The simulated silicon nanowire biosensor is capable of detecting biomolecular interactions charges to obtained high sensitive and accuracy result.

Blockchain technology has presented a promising decentralized paradigm to preclude trusted thirdparties' dominancy. It is a transparent and distributed ledger initially designed for digital cryptocurrencies whilecurrently extended to serve various industries. However, Blockchain immutability presents challenges, as it can bemisused for storing illicit content, violating privacy regulations, and limiting data management flexibility. PolicyBased Chameleon Hash Function (PBCH) has transformed blockchain rewriting contents concept via permittingmodifiers to amend certain transaction since they possessed fundamental privileges satisfying certain access policy.However, PBCHF suffers from efficiency issues due to its reliance on Chameleon Hash ephemeral Trapdoor (CHET)and Attribute-Based Encryption (ABE), significantly impacting overall efficiency. We propose the Efficient PolicyBased Chameleon (EPBCHF) construction by replacing CHET with Chameleon-Hashes by Dual Long-TermTrapdoors (CHDLTT) to address these challenges. Additionally, we introduce an enhanced encryption schemeresilient against chosen-ciphertext attacks (CCA) without compromising overall efficiency. Modelling EPBCHFproves practical instantiation accompanied by rigorous security proofs. Our construction provides a fine-grainedredactable blockchain in comparison to the currently proposed solutions. The evaluated results confirm that theproposed EPBCHF is scalable and efficient due to having the ability to handle unlimited transaction volumesadditionally, data is efficiently processed without further overhead meanwhile data size consistency reflects a robustmemory management due to predicted memory size, network bandwidth and storage requirement for future growththereby, EPBCHF is proven to be reliable and scalable.

Autoimmune haemolytic anaemia (AIHA) is a complication arising from allogeneic haemopoietic stem cell transplantation (AHSCT), and it poses a significant challenge in patient management with poor outcome. We present the case of a 32-year-old Malay woman with chronic myeloid leukaemia who, after treatment failure with a tyrosine kinase inhibitor, was referred for AHSCT with HLA-matched peripheral blood stem cells donated by her younger brother. She suffered acute graft-versus-host disease and cytomegalovirus infection within three months post-transplant, followed by AIHA. She did not respond to multiple treatment modalities and had to be frequently admitted to hospital due to symptomatic anaemia which requiring frequent blood transfusion. Here, we highlight an AIHA case in post-AHSCT as a refractory disease due to resistance to standard treatment. This is a condition that requires close monitoring and care because it carries a high risk of morbidity and mortality for the patient, who unfortunately succumbed to her disease.