Examining Lower Latency Routing with Overlay Networks

In today's rapidly expanding digital landscape, where access to timely online content is paramount to users, the underlying network infrastructure and latency performance significantly influence the user experience. We present an empirical study of the current Internet's connectivity and the achievable latencies to propose better routing paths if available. Understanding the severity of the non-optimal internet topology with RIPE Atlas stats, we conduct practical experiments to demonstrate that local traffic from the San Diego area to the University of California, San Diego reaches up to Los Angeles before serving responses. We examine the traceroutes and build an experimental overlay network to constrain the San Diego traffic within the city to get better round-trip time latencies

Oral Myiasis: a review

Myiasis is the infestation of tissues, organs of living vertebrate, animals and humans by certain dipterans fly larvae which feed on the host’s tissues and body fluids, often causing extensive damage to the host tissues if left untreated. Oral Myiasis is a rare pathology and is associated with poor oral hygiene, alcoholism, senility, suppurating lesions, severe halitosis. It arises from invasion of body tissues or cavities of living animals by maggots or larvae of certain species of flies. It occurs in tropical areas with poor living conditions and insufficient public and personal hygiene. Mouth-breathing during sleep, alcoholism, mental handicap, cerebral palsy and hemiplegia may facilitate the development of myiasis. The commonest clinical manifestations of myiasis infestation include inflammatory and allergic reactions. Ear, eye and respiratory tract infestations are also frequently encountered. Human myiasis may affect the skin, bones, intestines and body cavities. Treatment consists of manual removal of maggots, broad spectrum antibiotics and oral therapy with Ivermecti

A Bibliometric Perspective Survey of IoT controlled AI based Swarm robots

Robotics is the ­new-age domain of technology that deals with bringing a collaboration of all disciplines of sciences and engineering to create a mechanical machine that may or may not work entirely independently but definitely focuses on making human lives much easier. It has repeatedly shown its ability to change lives at home and in the industry. As the field of robotics research grows and reaches new worlds, the military is one area where advances can have a significant impact, and the government is aware of this. Military technology has come a long way from the days where soldiers had to walk into traps, putting their own lives in danger for their fellow soldiers, to today, when soldiers have robots walk into the same traps with possibility and result of zero human casualties. High-risk military operations such as mine detection, bomb defusing, fighter pilot aviation, and entering enemy territory without complete knowledge of what is to come are all tasks that can be programmed in a way that makes them accustomed to scenarios like these, either by intensive machine learning algorithms or artificially intelligent robot systems. Military soldiers are human capital; they are not self-driving robots; they are living beings with emotions, fears, and weaknesses, and they will almost always be unreliable as compared to computers and robots. They are easily affected by environmental effects and are vulnerable to external influences. The government\u27s costs for deployed troops, such as training and salaries, are extremely high. As a result, the solution is to build AI robots for defence operations that can sense, collect data by observing surroundings as any human soldier would, and report it back to a workstation where it can be used for strategy building and planning on what the next step should be during a mission, thus making the army better prepared for any kind of trouble that might be on their way. In this paper, the survey and bibliometric analysis of AI-based IoT managed Swarm Robots from the Scopus repository is discussed, which analyses research by area, notable authors, organizations, funding agencies and countries. Statistical analysis of literature published as journals, articles and papers that aids in understanding the global influence of publication is called Bibliometric analysis. This paper is a thorough analysis of 84 research papers as obtained from the Scopus repository on the 3rd of April 2021. GPS Visualizer, Gephi, wordcloud, and ScienceScape are open source softwares used in the visualization review. As previously mentioned, the visualization assists in a quick and easy interpretation of the different viewpoints in a particular study domain pursuit

AutoMix: Automatically Mixing Language Models

Large language models (LLMs) are now available in various sizes and configurations from cloud API providers. While this diversity offers a broad spectrum of choices, effectively leveraging the options to optimize computational cost and performance remains challenging. In this work, we present AutoMix, an approach that strategically routes queries to larger LMs, based on the approximate correctness of outputs from a smaller LM. Central to AutoMix is a few-shot self-verification mechanism, which estimates the reliability of its own outputs without requiring training. Given that verifications can be noisy, we employ a meta verifier in AutoMix to refine the accuracy of these assessments. Our experiments using LLAMA2-13/70B, on five context-grounded reasoning datasets demonstrate that AutoMix surpasses established baselines, improving the incremental benefit per cost by up to 89%. Our code and data are available at https://github.com/automix-llm/automix.Comment: The first two authors contributed equally. Work started and partly done during Aman's internship at Google. This version adds results on mixing 3 models, and will be presented at the workshop on robustness of zero/few-shot learning in foundation models, Neurips 202

Kajian Potensi Energi Arus Laut Sebagai Energi Alternatif Untuk Pembangkit Listrik Di Perarian Selat Lembeh, Sulawesi Utara

Kebutuhan akan energi listrik terus mengalami peningkatan dan sumber energi utamanya adalah energi konvensional yang ketersediannya terbatas di alam, untuk itu diperlukan adanya pencarian sumber energi lain yang terbarukan. Selat Lembeh merupakan wilayah perairan sempit yang berada di antara Laut Maluku yang dipengaruhi oleh massa air dari Pasifik dan Laut Sulawesi yang dipengaruhi oleh massa air dari Hindia. Penelitian ini bertujuan untuk mengetahui karakteristik arus laut serta mengetahui potensi arus laut sebagai sumber energi alternatif pembangkit listrik. Pengolahan data terdiri dari analisa data arus dan pasang surut, pemodelan numerik, dan menghitung estimasi rapat daya. Penelitian ini menggunakan metode kuantitatif dan penentuan lokasi dengan sampling area. Berdasarkan hasil penelitian, rapat daya terbesar yang dihasilkan yaitu pada musim barat, sebesar 120,02 kW/m2

Optimization of a GCaMP calcium indicator for neural activity imaging

© The Author(s), 2012. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Journal of Neuroscience 32 (2012): 13819-13840, doi:10.1523/JNEUROSCI.2601-12.2012.Genetically encoded calcium indicators (GECIs) are powerful tools for systems neuroscience. Recent efforts in protein engineering have significantly increased the performance of GECIs. The state-of-the art single-wavelength GECI, GCaMP3, has been deployed in a number of model organisms and can reliably detect three or more action potentials in short bursts in several systems in vivo. Through protein structure determination, targeted mutagenesis, high-throughput screening, and a battery of in vitro assays, we have increased the dynamic range of GCaMP3 by severalfold, creating a family of “GCaMP5” sensors. We tested GCaMP5s in several systems: cultured neurons and astrocytes, mouse retina, and in vivo in Caenorhabditis chemosensory neurons, Drosophila larval neuromuscular junction and adult antennal lobe, zebrafish retina and tectum, and mouse visual cortex. Signal-to-noise ratio was improved by at least 2- to 3-fold. In the visual cortex, two GCaMP5 variants detected twice as many visual stimulus-responsive cells as GCaMP3. By combining in vivo imaging with electrophysiology we show that GCaMP5 fluorescence provides a more reliable measure of neuronal activity than its predecessor GCaMP3. GCaMP5 allows more sensitive detection of neural activity in vivo and may find widespread applications for cellular imaging in general.A.F. has been supported by a European Molecular Biology Organization long-term fellowship. Work in H.B.’s laboratory was funded by the National Institutes of Health (NIH) Nanomedicine Development Center “Optical Control of Biological Function,” and work in S.S.-H.W.’s laboratory was funded by NIH R01 NS045193

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning