Copy-and-patch compilation: a fast compilation algorithm for high-level languages and bytecode

Fast compilation is important when compilation occurs at runtime, such as query compilers in modern database systems and WebAssembly virtual machines in modern browsers. We present copy-and-patch, an extremely fast compilation technique that also produces good quality code. It is capable of lowering both high-level languages and low-level bytecode programs to binary code, by stitching together code from a large library of binary implementation variants. We call these binary implementations stencils because they have holes where missing values must be inserted during code generation. We show how to construct a stencil library and describe the copy-and-patch algorithm that generates optimized binary code. We demonstrate two use cases of copy-and-patch: a compiler for a high-level C-like language intended for metaprogramming and a compiler for WebAssembly. Our high-level language compiler has negligible compilation cost: it produces code from an AST in less time than it takes to construct the AST. We have implemented an SQL database query compiler on top of this metaprogramming system and show that on TPC-H database benchmarks, copy-and-patch generates code two orders of magnitude faster than LLVM -O0 and three orders of magnitude faster than higher optimization levels. The generated code runs an order of magnitude faster than interpretation and 14% faster than LLVM -O0. Our WebAssembly compiler generates code 4.9X-6.5X faster than Liftoff, the WebAssembly baseline compiler in Google Chrome. The generated code also outperforms Liftoff's by 39%-63% on the Coremark and PolyBenchC WebAssembly benchmarks.

An objective systematic comparison of the most common adverse events of COVID-19 vaccines

Background: Vaccination is an important tool in the fight against pandemics. However, the associated adverse events (AEs) may negatively impact the public perception of vaccines, therefore leading to decreased vaccination willingness. Interestingly, pharmacovigilance data of the three COVID-19 vaccines with a two-dose schedule approved in the EU (AstraZeneca, BioNTech and Moderna) already revealed country-specific differences in their safety profile early on (as of February 2021), at a time when the accumulated occurrence of specific AEs was not yet known. In the safety outcome assessment presented here, we aimed to establish whether these country-specific differences in pharmacovigilance data could be explained by differences in the frequency of AEs as reported in the respective approval studies of each vaccine. Methods: A systematic search was performed to identify all publications regarding the randomized controlled trials (RCTs) of two-dose vaccines approved in the EU (AstraZeneca, BioNTech and Moderna), including regulatory reports and journal articles. All obtained safety data was manually entered into an SQL database. In order to enable the comparability among the data, the solicited AEs for all vaccines (i.e. those AEs actively sought after vaccination) were investigated. The data was standardized to promote comparability and overcome data heterogeneity and complexity. Findings: Twelve documents regarding the RCTs for the three COVID-19 vaccines with a two-dose schedule approved in the EU (AstraZeneca, BioNTech and Moderna) were included in the safety outcome analysis. The entire safety data compiled in the SQL database amounted to 66 different study arms. The data structure revealed 13 different age thresholds or ranges and three different data sets regarding doses (first dose vs. second dose vs. all doses). After standardization and identification of subgroups, the analyses demonstrated that the highest rates of AEs occur after the first dose with the AstraZeneca vaccine, whereas with Moderna and BioNTech most AEs occur after the second dose. Astonishingly, the absolute frequencies of each AE after the first AstraZeneca dose correspond to those of the second dose of the mRNA vaccines (BioNTech and Moderna). Reversely, the absolute frequencies of the same AEs after the second AstraZeneca dose correspond to those of the first dose with the mRNA vaccines. The most common AEs with any vaccine were fatigue, headache and myalgia. Moreover, middle-aged subjects (18 to 55 years) had more side effects than older individuals (> 55 years), an observation that persisted among vaccines. Interpretation: This is the first indirect comparison of these vaccines that uses all available RCT data. The absolute frequency of each AE is similar between the first AstraZeneca dose and the second dose of BioNTech or Moderna; their occurrence was thus independent of platform (vector or mRNA) or the vaccine itself. This assessment demonstrates that the varying frequencies of AEs reported in early pharmacovigilance data for the vaccines in distinct countries, at a time when the accumulated occurrence of specific AEs with certain vaccines was not yet known, cannot be explained by different frequencies being reported in the respective RCTs. Conclusion: The approach presented here could help to objectify future discussions on vaccine preferences. Therefore, it may serve as basis for future public awareness campaigns and may also allow the comparison of vaccine performance in different subgroups (e.g. virus variants, high-risk patients). This approach may also be applied to a broad range of other challenges across the R&D process and various disease categories.

Sistem Pendukung Keputusan Sistem Pendukung Keputusan Untuk Menentukan Ekstrakurikuler Atletik Berdasarkan Bakat Siswa Menggunakan Metode Profile Matching

Prestasi atletik di SMP Negeri 17 Kota Cirebon harus dipertahankan dengan terus menggali dan mencari siswa yang memiliki potensi dan bakat di bidang atletik dari tahun ke tahun melalui kegiatan ekstrakurikuler. Namun terkait hal tersebut, tidak mudah bagi pihak sekolah untuk menentukan cabang olahraga mana yang sesuai dengan bakat siswa. Proses penentuan atletik siswa dilakukan melalui hasil tes masing-masing siswa. Hasil tes cenderung kurang objektif karena tidak ada faktor pendukung lainnya. Oleh karena itu, diperlukan suatu sistem yang dapat digunakan sebagai penelusuran dan penentuan bakat atletik siswa. Sistem Pendukung Keputusan dapat menjadi solusi untuk mempermudah dalam menentukan siswa atletik. Dengan adanya sistem ini diharapkan dapat memberikan informasi hasil penentuan kegiatan ekstrakurikuler atletik secara objektif. Penelitian ini menerapkan metode Profile Matching untuk menentukan ekstrakurikuler atletik siswa, dan sistem dibuat dalam bahasa pemrograman PHP dan SQL database menggunakan MySQL. Pada tahap perancangan sistem digambarkan menggunakan diagram UML. Hasil akhir dari penelitian ini diperoleh hasil penentuan cabang ekstrakurikuler atletik siswa dengan persentase keberhasilan perhitungan 100%.

On the review of electronic technologies applied to implantable medical devices

The development of electronic implantable medical devices (IMD) has been increasing over the years, targeting very diverse applications and implementing different technologies. The impact of IMDs in the treatment of different ailments like Parkinson’s disease, hearing impairment, heart arrhythmia, and chronic pain, among many others, has been notorious and inspired their exploration to treat other health problems. Even when there is great interest in the scientific community for the exploration and development of IMDs, no standards are ruling its development. This lack of standardization is the reason why the analysis of the tendencies of this area from the technical point of view becomes complex. The analysis of the tendencies in the development of IMD devices required the exploration of diverse sources, which describe heterogeneous systems using very different approaches and methodologies for similar problems. In this paper an open SQL database intended for collecting information from IMD publications is presented; at this point, more than 200 published works are feed in the database covering a period from 1974 to 2018. This database is extensible and enables researchers to find trends and explore the development of IMDs from a broader perspective. We also used this database as a proof of concept to explore some general trends in the design of IMDs based on the included works.

SENTIMENT ANALYSIS OF CURRENT TRENDING TOPICS ON TWITTER USER BASE

Twitter has now become the most common social platform to express views on any topic. A micro-blogging social media offers a way for people around the world to show their sentiments about any political, social and cultural subject of the time. In this paper, the sentimental analysis approach has been used to analyze the positive and negative sentiments of Twitter users about some top trending #tags around the globe. The data has been collected between the duration of March to April 2021. The collected data were processed by using the Python program and then transformed our data set with the help of the SQL database. We have used graphs and tables to present the data, collected under three hashtags; which were top trending topics on that particular era. The tweets were elaborated by positive, negative and neutral sentiments which were depicted in graphs. It is clear from the results and comparison that social media has a strong influence in the present era and can be highly helpful to use as a predictor of any political, social situation prevailing in any country or worldwide. It has also been helpful for business communities to analyze their products in the same manner to improve their business growth.

Aplikasi Pembelajaran Chord Gitar Bass Versi Rohani Menggunakan App Inventor 2 Dan MYSQL

Pada gereja Bethany Grace and Glory sebelumnya belum membuat sistem informasi panduan chord bass versi rohani untuk menunjang kegiatan peribadatan. Saat melakukan latihan untuk menyambut ibadah raya pada hari minggu atau ibadah lainnya, tim musik hanya mengandalkan selebaran kertas untuk menuliskan chord dari setiap lagu yang diaransemen untuk dinyanyikan saat latihan tiap minggu. Tujuan penulisan makalah ini adalah untuk mendeskripsikan hasil penelitian tentang Aplikasi Pembelajaran Chord Gitar Bass Menggunakan APP Inventor 2 dan MySQL Manokwari. Metode yang digunakan dalam penelitian ini adalah metode waterfall berbasis android. Selanjutnya aplikasi dirancang menggunakan Web Viewer yang terdapat pada App Inventor 2 dan My SQL (database) sebagai penyimpanan data. Dari hasil pengujian dan pengolahan data pada pembelajaran gitar bass elektrik dengan App Inventor berbasis android akan mempermudah pengguna dalam melakukan pembelajaran Chord Gitar Bass dalam pencarian judul lagu dan terdapat video mengenai kunci dasar dan teknik petik gitar bass. Aplikasi pembelajaran chord bass versi rohani berbasis android terdiri dari 2 tipe aktor yaitu admin dan pengguna.

Impact of Enterprise Resource Management System on Industrial Revolution 4.0

The world is going through its fourth industrial revolution right now. Managing large workspaces in big Enterprises has been made easy with the advent of particular software categories popularly known as ERP short for Enterprise Resource Planner. With ERPs, management of data from all kinds of fields of work like finance, operations, sales, manufacturing, marketing, sales, pre-sales/post-sales, HR, etc are easy now. What’s even more enticing about it all is that all of this can now be stored on Cloud storage and can be acces-sed from pretty much any device. This makes it incredibly easy for business owners to manage their enterprise from anywhere in the world, anytime. Our project tries to demonstrate the impact of the ERP software ecosystem using a prototypeERP system built using Codeigniter Framework built on PHP, and a front-end based on boot-strap with a comprehensive My-sql database and a Google Cloud Infrastructure. Our Project will make use of some open-source repositories and build on it a working prototype that can manage the data of a fictitious company.