Cisco Dal Vivo Volume 2 Torrent
Bubba Lual
When serving a large volume of data collection and annotation, we faced some challenges on task distribution, anti-scamming and AI model training. We adopted the Apache Pulsar and NoSQL database solution to resolve those pain points and keep the flexibility.
Together with a unified computing engine like Spark, Apache Pulsar is able to boost the efficiency of our risk-control decision deployment. Thus, we are able to provide merchants and consumers with safe, convenient, and efficient services.
The messaging team at BIGO found themselves overwhelmed by the massive amounts of data when using Kafka. They then started to learn Apache Pulsar and ran some tests with it, after which they believed Pulsar could be a solution to their challenges. They use Pulsar as a key component in their real-time messaging architecture, which has helped them reduce the hardware cost by 50%.
Cisco IoT Control Center is among the world's largest IoT platforms, with numerous data centers spread across continents, hosting thousands of applications for the management of hundreds of millions of IoT devices, including connected cars and wireless phones. Cisco underwent a two-year process of transforming their platform into a cloud-native GitOps platform, where Pulsar replaced legacy message queue services and is deployed across multiple Kubernetes clusters.
Discord encountered the task of enhancing its live streaming machine learning platform to tackle safety and personalization concerns, like restricting spam access or safeguarding Discord users' accounts from potential breaches. The current setup was designed for heuristics, not for machine learning. The necessity for a reliable, scalable, and real-time solution prompted them to consider incorporating Apache Flink, Pulsar, and Iceberg.
At Flipkart, there are multiple use-cases for high throughput messaging like streaming/batch pipelines, ordered processing, auditing, etc. Pulsar offers different kinds of isolation mechanisms: cluster peering, isolation groups, produce/dispatch quotas, etc. We identified that offering topic-as-a-service can take away operational complexity for these teams and help us enforce stricter SLAs around uptime and geo-replication. Therefore we approached building a scalable and multi-tenant platform with Pulsar as the choice of backend.
Keytop redesigned its messaging system by using Apache Pulsar as the backbone of its architecture. Its geo-replication feature helps Keytop securely store mission-critical data across multiple data centers.
Currently, our service supports log query and monitoring for many businesses, and processes tens of terabytes of data every day. With Pulsar, we can scale up partitions and merge partitions easily, and process millions of topics.
Modern IT and application environments are increasingly complex, transitioning to cloud, and large in scale. The managed resources, services and applications in these environments generate tremendous data that needs to be observed, consumed and analyzed in real time (or later) by management tools to create insights and to drive operational actions and decisions.
The heart of Netdata Cloud is Pulsar. Almost every message coming from and going to the open source agents passes through Pulsar. Pulsar's infinite number of topics has given us the flexibility we needed and in some cases, every single Netdata Agent has its own unique Pulsar topic.
Apache Pulsar has multi-layer and segment-centric architecture and supports geo-replication. We can query data with PulsarSQL, and create complex processing logic without deploying other systems with Pulsar Functions.
Pulsar has a flexible design and its performance is already good enough for many use cases. The NTT Software Innovation Center ran different performance tests and implemented its own subscription model in Pulsar to further improve its performance. This has allowed them to use one Pulsar topic to support 100K consumers in their IoT scenario.
Apache Pulsar offers server as well as client side support for the structured streaming. We have been using Pulsar for asynchronous communication among microservices in our Nutanix Beam app for over an year in production.
We choose Pulsar for its ability to manage distributed transactions within a microservice architecture and its feature flexibility. Pulsar now plays an essential part in helping our AI-powered order execution system to find the optimal strategy in real time.
Pulsar guarantees data consistency and durability while maintaining strict SLAs for throughput and latency. Furthermore, Apache Pulsar integrates Pulsar Functions, a lambda style framework to write serverless functions to natively process data immediately upon arrival. This serverless stream processing approach is ideal for lightweight processing tasks like filtering, data routing and transformations.
After nearly 10 years of development of Tencent Game big data, the daily data transmission volume can reach 1.7 trillion. As the key component of the big data platform, the MQ system is critical to provide real-time service operational quality assurance, which requires the support of various applications such as real-time game operational service, real-time index data analysis, and real-time personalized recommendation.
Apache Pulsar (upon which TurtleQueue is built) builds on top of the same foundation and improves on it. It exposes a cursor that advances to consume the next message. The cursor's position can be changed to something else, like the beginning of the queue.
After comparing different streaming and messaging tools, vivo began to learn Apache Pulsar and explored its features in scalability, fault tolerance, and load balancing. As vivo put Apache Pulsar into use, it summarized some useful practices in bundle and data management. vivo built its monitoring architecture based on Pulsar and created its customized Pulsar metrics for better observability.
We adopted Pulsar because of its great performance, scalability and multi-tenancy capability. Indeed, Pulsar has played an important role to provide our 100+ services in various areas such as e-commerce, media, advertising and more.
Copyright 2024 The Apache Software Foundation. All Rights Reserved. Apache, Pulsar, Apache Pulsar, and the Apache feather logo are trademarks or registered trademarks of The Apache Software Foundation.
Exogenously providing engineered Uox with enhanced half-life is one of the important urate-lowering treatments for gout. The potential of PAT101, a recombinant human albumin (rHA)-conjugated variant, was evaluated and compared as a novel gout treatment through various in vivo studies with PAT101 and competing drugs.
The half-life of PAT101 in single-dose treated TG mice was more than doubled compared to pegloticase. In SD rats with 4 weeks of repeated administration of rasburicase, only 24% of Uox activity remained, whereas in PAT101, it was maintained by 86%. In the Uox KO model, the survival rate of PAT101 was comparable to that of pegloticase. In addition, human PBMC-based CD4+/CD8+ T-cell activation analysis demonstrated that PAT101 has a lower immune response compared to the original drug, rasburicase.
Here, we investigated the characteristics of PAT101 as a therapeutic Uox as follows: in vivo extended serum half-life profiles in mice and rats, in vivo therapeutic efficacy through plasma uric acid reduction in chronic Uox-KO mice model, and potential for low immunogenicity as measured in a T-cell immunogenicity assay. Results have shown that the conjugation of rHA to a selective site of AfUox leads to an extended half-life through an FcRn-mediated recycling system as well as a volume-induced renal filtration evasion mechanism. Above all, the low immunogenicity compared to rasburicase suggests that PAT101 is a promising gout treatment that overcomes several issues reported in previous treatments.
The production of PAT101 involved a process flow with upstream and downstream procedures. In the upstream phase, the cell stock C321delA.exp.[pDule C11RS][pTAC AfUox 174 Amb] was cultivated in 2xYT media supplemented with kanamycin (35 μg/mL) and tetracycline (10 μg/mL). The seed culture was scaled up to a 5 L fed-batch culture with the addition of 1 mM IPTG and 3 mM frTet for induction. After 14 hrs, cells were harvested by centrifugation at 8000 rpm for 15 min at 4 C. In the downstream phase, the cell pellet was lysed using a high-pressure microfluidizer in a 20 mM sodium phosphate buffer (SPB) pH 7.0. The lysate was purified using cation exchange chromatography. The purified AfUox-174 frTet was used for recombinant human albumin conjugation, where albumin reacted with a crosslinker (TCO-MAL) for 2 hrs, followed by crosslinker removal through diafiltration. Uox-174frTet and rHA-TCO were conjugated at a 1:6 molar ratio in a SP pH 7.0 for 1 h. After conjugation, the mixture was desalted and subjected to two-step chromatography purification. First, cation exchange chromatography (SP Sepharose FF) was performed with SPB pH 6.0. Then, anion exchange chromatography (Q Sepharose FF) was carried out with SPB pH 7.0, resulting in the purified PAT101.
Experiments were performed in accordance with the guidelines on the Care and Use of Laboratory Animals after approval from the Institutional Animal Care and Use the Committees of Kbio Health (KBIO-IACUC), Gwangju Institute of Science and Technology (GIST) and Ajou University (AJOU). The approval number was specified for each study.
After mixing the plasma and uric acid at 105.3 M in assay buffer (7.5 g/L triethanolamine and 0.38 g/L EDTA at pH 8.9), it was loaded onto the heated UV-STAR microplates at 30C incubator for 10 min, and the absorbance change (initial rate) was measured using a microplate reader (293 nm). Enzyme activity in plasma was quantified as specific activity (mU/mL), where one unit (mU) of activity indicated the quantity of enzyme catalyzing the oxidation of 1.0 nmol of uric acid per minute at 30 C. Plasma pharmacokinetic parameters were calculated using non-compartmental analysis (NCA) with WinNonlin software (version 8.1.0, Pharsight Corporation, Mountain View, California) or PK solver [23].
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