Benchmarking quantized LLaMa-based models on the Brazilian Secondary School Exam

Although Large Language Models (LLMs) represent a revolution in the way we interact with computers, allowing the construction of complex questions and the ability to reason over a sequence of statements, their use is restricted due to the need for dedicated hardware for execution. In this study, we evaluate the performance of LLMs based on the 7 and 13 billion LLaMA models, subjected to a quantization process and run on home hardware. The models considered were Alpaca, Koala, and Vicuna. To evaluate the effectiveness of these models, we developed a database containing 1,006 questions from the ENEM (Brazilian National Secondary School Exam). Our analysis revealed that the best performing models achieved an accuracy of approximately 46% for the original texts of the Portuguese questions and 49% on their English translations. In addition, we evaluated the computational efficiency of the models by measuring the time required for execution. On average, the 7 and 13 billion LLMs took approximately 20 and 50 seconds, respectively, to process the queries on a machine equipped with an AMD Ryzen 5 3600x processorComment: 8 pages, 6 figures, 4 table

LGVINS:LiDAR-GPS-visual and inertial system based multi-sensor fusion for smooth and reliable UAV state estimation

With the development of Autonomous Unmanned Aerial Vehicle’s (UAV’s), Precise state estimation is a fundamental aspect of autonomous flight and plays a critical role in enabling robots specially in GPS denied environment to operate safely, reliably, and effectively across a wide range of applications and operational scenarios. In this paper, we propose a tightly-coupled multi-sensor filtering framework for robust UAV/UGV state estimation, which integrates data from an Inertial Measurement Unit (IMU), a stereo camera, GPS, and 3D range measurements from two Light Detection and Ranging (LiDAR) sensors. The proposed LGVINS system significantly improves the accuracy and robustness of state estimation in both structured and unstructured outdoor environments, such as bridge inspections, open fields, urban city and areas near buildings. It also improves positioning accuracy in scenarios with or without GPS signals. The goal is to exploit the fact that these sensor modalities have mutually exclusive strengths, the visual, inertial and the Lidar sensor techniques are implemented to compensate for the robots state estimate errors in multiple outdoor challenging environment. It effectively reduces long-term trajectory drift and ensures smooth, continuous state estimation, regardless of GPS satellite availability. We demonstrate and evaluate the LGVINS approach on public dataset as well as our own dataset collected from the proposed hardware integration on UAV, deployed on computationally-constrained systems. This demonstrates that the proposed system achieves higher accuracy and robustness in state estimation across various environments compared to currently available methods

Investigating memory prefetcher performance over parallel applications: from real to simulated

In recent years, there have been significant advances in the performance of processors, exemplified by the reduction of transistor size and the increase in the number of cores in a processor. Conversely, the memory subsystem did not advance as significantly as processors, not being able to deliver data at the required rate, and creating what is known as the memory wall [1]. An example of a technology used to mitigate the memory latency is the prefetcher, a technique that identifies access patterns from each core, creates speculative memory requests, and fetches data that can be potentially useful to the cache beforehand. In High-Performance Computing (HPC) systems, many other problems arise with parallelism. Since HPC applications are highly parallel, with many threads communicating with one another mainly through shared memory, it becomes necessary to keep data coherence in the several cache levels. Moreover, the memory interactions among different threads may also unpredictably change the data path through the memory hierarchy. When considering the memory hierarchy complexity along with prefetcher action, the behavior of the processor’s memory subsystem reaches a new level of complexity. In this work, we seek to shed light on how the prefetcher affects the processing performance of parallel HPC applications, and how accurately state-of-the-art multicore architecture simulators are simulating the execution of such applications, with and without prefetcher. We identify that an L2 cache prefetcher is more efficient in comparison with an L1 prefetcher, since avoiding excessive L3 cache accesses better contributes to performance, when comparing to accessing the L2 cache. Moreover, we show evidence that the prefetchers’ contribution to performance is limited by the memory contention that emerges when the level of parallelism increases

Understanding mobility in networks

Motivated by the growing number of mobile devices capable of connecting and exchanging messages, we propose a methodology aiming to model and analyze node mobility in networks. We note that many existing solutions in the literature rely on topological measurements calculated directly on the graph of node contacts, aiming to capture the notion of the node's importance in terms of connectivity and mobility patterns beneficial for prototyping, design, and deployment of mobile networks. However, each measure has its specificity and fails to generalize the node importance notions that ultimately change over time. Unlike previous approaches, our methodology is based on a node embedding method that models and unveils the nodes' importance in mobility and connectivity patterns while preserving their spatial and temporal characteristics. We focus on a case study based on a trace of group meetings. The results show that our methodology provides a rich representation for extracting different mobility and connectivity patterns, which can be helpful for various applications and services in mobile networks

Enhanced enzyme reuse through the bioconjugation of L-asparaginase and silica-based supported ionic liquid-like phase materials

L-asparaginase (ASNase) is an amidohydrolase that can be used as a biopharmaceutical, as an agent for acrylamide reduction, and as an active molecule for L-asparagine detection. However, its free form displays some limitations, such as the enzyme’s single use and low stability. Hence, immobilization is one of the most effective tools for enzyme recovery and reuse. Silica is a promising material due to its low-cost, biological compatibility, and tunable physicochemical characteristics if properly functionalized. Ionic liquids (ILs) are designer compounds that allow the tailoring of their physicochemical properties for a given task. If properly designed, bioconjugates combine the features of the selected ILs with those of the support used, enabling the simple recovery and reuse of the enzyme. In this work, silica-based supported ionic liquid-like phase (SSILLP) materials with quaternary ammoniums and chloride as the counterion were studied as novel supports for ASNase immobilization since it has been reported that ammonium ILs have beneficial effects on enzyme stability. SSILLP materials were characterized by elemental analysis and zeta potential. The immobilization process was studied and the pH effect, enzyme/support ratio, and contact time were optimized regarding the ASNase enzymatic activity. ASNase–SSILLP bioconjugates were characterized by ATR-FTIR. The bioconjugates displayed promising potential since [Si][N3444]Cl, [Si][N3666]Cl, and [Si][N3888]Cl recovered more than 92% of the initial ASNase activity under the optimized immobilization conditions (pH 8, 6 × 10−3 mg of ASNase per mg of SSILLP material, and 60 min). The ASNase–SSILLP bioconjugates showed more enhanced enzyme reuse than reported for other materials and immobilization methods, allowing five cycles of reaction while keeping more than 75% of the initial immobilized ASNase activity. According to molecular docking studies, the main interactions established between ASNase and SSILLP materials correspond to hydrophobic interactions. Overall, it is here demonstrated that SSILLP materials are efficient supports for ASNase, paving the way for their use in the pharmaceutical and food industries.publishe

Coronaviruses Detected in Brazilian Wild Birds Reveal Close Evolutionary Relationships with Beta- and Deltacoronaviruses Isolated From Mammals

This study showed that the most of the coronaviruses (CoVs) detected in Brazilian wild birds clustered with the mouse hepatitis virus A59 strain, belonging to the BetaCoV group. Furthermore, CoV detected in two different bird species, Amazona vinacea and Brotogeris tirica, clustered with a CoV isolated from Sparrow (SpaCoV HKU17) belonging to a monophyletic group related with the CoVs isolated from swines (PorCoV HKU15), both belonging to the DeltaCoV genus, previously unreported in South America. Considering the risk of inter-species host switching and further adaptation to new hosts, detection in bird species of CoVs closely related to mammal CoVs should warn for the potential emergence of new threatening viruses.Fundação de Amparo à Pesquisa do Estado de São Paulo (Grants 2013/03922-6 and 2011/50919-5

Teleostei fishes of the North Coast of Brazil

The North Coast of Brazil is a biogeographical area of the Exclusive Economic Zone of Brazil that share environmental features with region under influence of the Plume of the rio Amazon and Orinoco. Despite the relevance of the region's fish fauna, in biogeo-graphic, ecologic, and commercial terms, this area is poorly known. This study presents the most complete and updated list of the bony fish fauna from the North Coast of Brazil, aiming to minimize our knowledge gap on such region's biodiversity. The main sources of infor-mation were records from zoological collections, inventories obtained during the surveys of the Research and Conservation National Center of Northern Marine Biodiversity and collec-tions from the authors. A total of 787 species of the Teleostei were recorded off the North Coast of Brazil and adjacent waters, representing 156 families and 45 orders. Most (531) of these species are coastal, 256 inhabit deeper water, and 31 pelagic (oceanic) species are com-mon to both the internal and external continental shelf, of which 54 represent new records. Given the progressive intensification of fisheries and increasing incentives for the exploita-tion of the local gas and oil reserves, a more adequate inventory of the marine fish fauna of the North Coast of Brazil is fundamentally important for the management of the region's aquatic biodiversity