Versar (United States)

The increasing densification of cell-free massive multiple-input multiple-output (MIMO) networks makes access point switch on/off (ASO) a key mechanism for improving energy efficiency in future wireless systems. While reinforcement learning (RL) has been explored for ASO, differences in modeling assumptions and evaluation scope leave open questions regarding robustness and scalability. In this work, ASO is investigated from an explicit energy-efficiency perspective using a RL framework based on Proximal Policy Optimization (PPO). The policy learns state-dependent AP activation under partial observability using compact per-access point (AP) large-scale fading statistics and power parameters, without requiring instantaneous small-scale channel state information or combinatorial search, enabling practical online implementation. A comprehensive evaluation is conducted under a unified and reproducible simulation framework across three cell-free deployment scenarios of increasing size that preserve AP density while incorporating realistic channel and power consumption models. Performance is assessed through both average and distribution-based metrics. Numerical results show that the PPO-based policy consistently outperforms random activation and the all-on baseline, achieving energy-efficiency improvements of up to 66% and nearly 50%, respectively, while activating a comparable number of APs. Moreover, the learned policy maintains robust performance as the network scales, reducing the likelihood of highly energy-inefficient operating regimes.

This work presents the design of a 1x4 router for transferring data packets between networks, such as LANs and WANs. Implemented in Verilog HDL, the router includes FIFO buffers, a Finite State Machine (FSM), a synchronizer, and registers. Each 8-bit packet consists of a 2-bit header for destination address and a 6-bit payload length, supporting up to 63 bytes. Synthesis was performed using Cadence Genus at a 45nm technology node. Initially, the design had 3,749 cells, which were reduced to 2,880 after optimization, improving area efficiency by lowering inverter and logic usage. Static Timing Analysis (STA) using Cadence Tempus showed positive slack values of 2.568 ns for setup and 0.224 ns for hold, confirming the design meets all timing constraints. Verification used a UVM-based environment with constrained-random tests. The design achieved 100% functional coverage, ensuring all payload sizes and routing paths were tested. The router is optimized, timing-safe, and functionally verified.

The emergence of 6G wireless networks presents new challenges, for which cell-free massive MIMO combined with machine learning (ML) offers a promising solution. A key requirement for practical deployment is the generalizability of ML models—their ability to maintain robust performance across varying propagation conditions, user distributions, and network topologies. However, achieving generalizability typically demands large, diverse training datasets and high model complexity, which can hinder practical feasibility. This study analyzes the robustness of a low-complexity deep neural network (DNN) trained for power control under a single network configuration. The model’s robustness is assessed by testing it across a wide range of unseen scenarios, including changes in the number of access points, user equipment, and propagation environments. The DNN is trained to emulate three power control schemes: max-min spectral efficiency (SE) fairness, sum SE maximization, and fractional power control. To rigorously evaluate robustness, we compare the cumulative distribution functions of performance metrics quantitatively using the Kolmogorov–Smirnov test. Results show strong robustness, particularly for the sum SE scheme, with D statistics below 0.05 and p-values above 0.001. This work provides a reproducible framework and dataset to support further research into practical ML-based power control in cell-free massive MIMO systems.

Purpose:This study describes the minimally invasive Dega osteotomy for treating residual acetabular dysplasia in ambulatory pediatric patients. The focus is on assessing the safety, feasibility, and early outcomes of this minimally invasive technique.Methods:A prospective series was conducted in a single tertiary orthopaedic center. The procedure involved an initial examination of hip joint stability using intraoperative arthrography. The surgical procedure involved a small transverse incision distal and lateral to the anterior superior iliac spine, followed by a Dega osteotomy and bone allografting. Variables such as surgical time, blood loss, incision length, and acetabular index were measured.Results:In healthy ambulatory patients, 16 osteotomies were performed on 12 patients with an average age of 32 months. The mean incision length was 2.3 cm, average blood loss was 17 mL, and mean surgical time was 21 minutes per side. Preoperative and postoperative acetabular indices averaged 40.3° and 18.6°, respectively. The mean follow-up period was 13 months. No complications were seen in this series.Conclusion:The minimally invasive Dega osteotomy technique is a safe and effective method for treating residual acetabular dysplasia in ambulatory patients. It offers advantages of minimal invasiveness, reduced surgical time, and less blood loss, with outcomes comparable to standard methods. However, further studies with larger cohorts and longer follow-up are necessary to fully establish its efficacy and safety profile.

Se presenta una guía de los pulsos de ecolocalización de 42 especies de murciélagos registrados en ocho estaciones ubicadas cercanas al río Vilcanota‑Urubamba, región Cusco. Los objetivos incluyeron la optimización en la obtención de grabaciones acústicas limpias específicas para cada especie y el desarrollo de una biblioteca acústica en Perú. Se presenta el túnel de vuelo como una técnica mas eficaz que la caja de vuelo, al permitir el vuelo sostenido en una sola dirección y la captura de pulsos de buena calidad. No se identificaron relaciones taxonómicas definidas basadas en los pulsos de ecolocalización. La variación de la forma de los pulsos de ecolocalización fueron explicadas por las variables Frecuencia pico y ancho de banda según el PCA. El Clúster formó cuatro grupos acústicos sin alguna relación clara entre características taxonómicas, evolutivas o ecológicas. Alimentar bibliotecas acústicas como “Mashu Peru”, será crucial para poder describir de manera mas precisa los pulsos de ecolocalización de cada especie, comprender mejor la plasticidad de la bioacústica y su sensibilidad ante factores metodológicos, ambientales y geográficos, resultado de esto queda un precedente para futuras investigaciones y colaborando con estrategias de conservación de los murciélagos.

Background/Objectives: Improvements in diabetic retinopathy (DR) screening could boost early detection rates and contribute to better patient outcomes. The availability of primary care-based DR screening could address this issue, although operational challenges remain. This study represents a preliminary evaluation of the feasibility and operational performance of a retinal screening system suitable for integration into a primary care setting. Methods: This was a multi-center, data collection study for a non-mydriatic retinal camera system, conducted in 4 iterative development phases; phase 4 simulated a clinical workflow. Study endpoints evaluated image quality (gradability) and operational characterization in phase 4 (time to complete image capture). Participants were required to be at least 22 years of age, and separate participant pools were recruited throughout study phases. In each phase, multiple images per eye were collected, and graded independently by sponsor-employed and external graders. Results: The study included 212 participants. In phases 1-3 (n=192), evaluation of the first image captured per eye for all participants (k=383) by non-sponsor graders showed 93.7% of images (359/383) as gradable; in phase 4 (n=20; k=55), there were 81.8% (45/55) gradable images. Regarding operational results, 90.1% of first-attempts trigger times were less than 30 seconds; by the third attempt, 96.7% were less than 30 seconds, Conclusions: These are encouraging preliminary results in terms of performance and usability for the retinal camera system in this study, which may have potential application in primary care clinics.

The central question for this paper is how to improve the production process by closing the gap between industrial designers and software engineers of television(TV)-based User Interfaces (UI) in an industrial environment. Software engineers are highly interested whether one UI design can be converted into several fully functional UIs for TV products with different screen properties. The aim of the software engineers is to apply automatic layout and scaling in order to speed up and improve the production process. However, the question is whether a UI design lends itself for such automatic layout and scaling. This is investigated by analysing a prototype UI design done by industrial designers. In a first requirements study, industrial designers had created meta-annotations on top of their UI design in order to disclose their design rationale for discussions with software engineers. In a second study, five (out of ten) industrial designers assessed the potential of four different meta-annotation approaches. The question was which annotation method industrial designers would prefer and whether it could satisfy the technical requirements of the software engineering process. One main result is that the industrial designers preferred the method they were already familiar with, which therefore seems to be the most effective one although the main objective of automatic layout and scaling could still not be achieved.