Tagging System Research Articles

Indonesian part of speech tagging using maximum entropy markov model on Indonesian manually tagged corpus

This research discusses the development of a part of speech (POS) tagging system to solve the problem of word ambiguity. This paper presents a new method, namely maximum entropy markov model (MEMM) to solve word ambiguity on the Indonesian dataset. A manually labeled “Indonesian manually tagged corpus” was used as data. Furthermore, the corpus is processed using the entropy formula to obtain the weight of the value of the word being searched for, then calculating it into the MEMM Bigram and MEMM Trigram algorithms with the previously obtained rules to determine the part of speech (POS) tag that has the highest probability. The results obtained show POS tagging using the MEMM method has advantages over the methods used previously which used the same data. This paper improves a performance evaluation of research previously. The resulting average accuracy is 83.04% for the MEMM Bigram algorithm and 86.66% for the MEMM Trigram. The MEMM Trigram algorithm is better than the MEMM Bigram algorithm.

A novel silk fibroin protein-based fusion system for enhancing the expression of nanobodies in Escherichia coli.

Nanobodies show a great potential in biomedical and biotechnology applications. Bacterial expression is the most widely used expression system for nanobody production. However, the yield of nanobodies is relatively low compared to that of eukaryotic systems. In this study, the repetitive amino acid sequence motifs (GAGAGS) found in silk fibroin protein (SFP) were developed as a novel fusion tag (SF-tag) to enhance the expression of nanobodies in Escherichia coli. SF-tags of 1 to 5 hexapeptide units were fused to the C-terminus of 4G8, a nanobody against human epididymis protein 4 (HE4). The protein yield of 4G8 variants was increased by the extension of hexapeptide units and achieved a 2.5 ~ 7.1-fold increase compared with that of untagged 4G8 (protein yield of 4G8-5C = 0.307 mg/g vs that of untagged 4G8 = 0.043 mg/g). Moreover, the fusion of SF-tags not only had no significant effect on the affinity of 4G8, but also showed a slight increase in the thermal stability of SF-tag-fused 4G8 variants. The fusion of SF-tags increased the transcription of 4G8 by 2.3 ~ 7.0-fold, indicating SF-tags enhanced the protein expression at the transcriptional level. To verify the applicability of the SF-tags for other nanobody expression, we further investigated the protein expression of two other anti-HE4 nanobodies 1G8 and 3A3 upon fusion with the SF-tags. Results indicated that the SF-tags enhanced the protein expression up to 5.2-fold and 5.7-fold for 1G8 and 3A3, respectively. For the first time, this study reported a novel and versatile fusion tag system based on the SFP for improving nanobody expression in Escherichia coli, which may enhance its potential for wider applications. Key points • A silk fibroin protein–based fusion tag (SF-tag) was developed to enhance the expression of nanobodies in Escherichia coli.• The SF-tag enhanced the nanobody expression at the transcriptional level.• The fusion of SF-tag had no significant effect on the affinity of nanobodies and could slightly increase the thermal stability of nanobodies.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00253-022-11857-7.

IMPROVING FRIENDS RECOMMENDATION USING FP-GROWTH ALGORITHM IN SOCIAL TAGGING SYSTEM

Social tagging system are web-based sites that store user’s keywords called tags, continue to receive significant consideration in academic environment it became an interesting research topic, give good support for users to tag resources, communicate with friends as well as friend recommendation, due to increasingly acceptance of Web2.0. There is a constant growth in the number of users using social tagging. Friend recommendation is one of the most important aspects for overcoming information overloading problem and helps users to make choice. In this work we proposed improving friend recommendation using, to address the difficulty of tag ambiguities. The technique is consisted of the following stages: Apply FP-Growth algorithm to discovery the frequent events sets among the users, construct the combine trust graph, and then apply ant colony optimization Algorithm to joint trust graph to compute the optimal friend recommended through repetition. The results of our experiments on a Delicious dataset, using our model, precision improved in the range 0.1 % to 1.1 %, recall increased greatly in the range 21.85 % to 50.84 % and F2 increased in the range 31.31 % to 50.85 % approximately. When compared to other methods, the outcome demonstrates a significant improvement. For friend commendation in a social tagging system, the future approach is to apply various data mining methods, large scale datasets, and community detection.

Robust Recombinant Expression of Human Placental Ribonuclease Inhibitor in Insect Cells.

Ribonuclease inhibitors (RIs) are an indispensable biotechnological tool for the detection and manipulation of RNA. Nowadays, due to the outbreak of COVID-19, highly sensitive detection of RNA has become more important than ever. Although the recombinant expression of RNase inhibitors is possible in E. coli, the robust expression is complicated by maintaining the redox potential and solubility by various expression tags. In the present paper we describe the expression of RI in baculovirus-infected High Five cells in large scale utilizing a modified transfer vector combining the beneficial properties of Profinity Exact Tag and pONE system. The recombinant RI is expressed at a high level in a fusion form, which is readily cleaved during on-column chromatography. A subsequent anion exchange chromatography was used as a polishing step to yield 12 mg native RI per liter of culture. RI expressed in insect cells shows higher thermal stability than the commercially available RI products (mainly produced in E. coli) based on temperature-dependent RNase inhibition studies. The endotoxin-free RI variant may also be applied in future therapeutics as a safe additive to increase mRNA stability in mRNA-based vaccines.

Modelling the strategies for improving maturity and resilience in medical oxygen supply chain through digital technologies

Purpose Improving the medical oxygen supply chain (MOSC) is important to cope with the uneven demand and supply seen in the MOSC when India faced the second wave of COVID-19. This improvisation increases the supply chain (SC) maturity and consequently the efficiency and resiliency to tackle oxygen shortage across the country and to prevent another similar scenario from ever happening. The purpose of this study is to identify and prioritize the solutions to overcome the issues faced by the MOSC during the second wave of COVID-19 cases in India and in turn reduce the extent of casualties in the expected third wave. Design/methodology/approach This paper uses best worst method (BWM) and fuzzy technique for order performance by similarity to ideal solution to classify the sub-criteria for solutions to solve major SC issues. BWM is used to determine the weights of the sub-criteria and fuzzy technique for order performance by similarity to ideal solution for the final ranking of the solutions to be adopted. Findings The result of this study shows that the Internet of Things based tagging system is the best solution followed by horizontal and vertical integration of SC in making a resilient and digitized MOSC capable of handling general bottlenecks during a possible third wave. Research limitations/implications The research provides insights that can enable the personnel involved in MOSC. Proper understanding will help the practitioners involved in the SC to effectively tailor the operations and to allocate the resources available in an effective and dynamic manner by minimizing or eliminating the pre-existing bottlenecks within the SC. Originality/value The proposed framework provides an accurate ranking and decision-making tool for the implementation of the solutions for the maturity of the MOSC.

UHF RFID Temperature Sensor Tag Integrated into a Textile Yarn.

This paper presents the design of an ultra high-frequency (UHF) radio frequency identification (RFID) sensor tag integrated into a textile yarn and manufactured using the E-Thread® technology. The temperature detection concept is based on the modification of the impedance matching between RFID tag’s antenna and the chip. This modification is created by the change in the resistance of a thermistor integrated within the tag system due to a temperature variation. Moreover, in order to obtain an environment independent detection, a differential approach is proposed that avoids the use of a pre-calibration phase by the use of a reference tag. Experimental characterization demonstrates the RFID sensor’s potential of detecting a temperature variation or a temperature threshold between and 70 °C through the variation of the transmitted differential activation power.

FEATURES OF THE FORMATION FUTURE PRIMARY SCHOOL TEACHER’S CRITICAL THINKING

The article investigated the features of the formation future primary school teacher’s critical thinking. Currently it was found the concept of forming critical thinking of the individual is recognized worldwide and implemented at all levels of education. Based on the study of a number of scientific papers, it is established that the analytical component of primary school teacher’s critical thinking is organically present at all stages of work with younger students, it allows to track positive and negative changes, as well as identify errors and inaccuracies in solving professional problems. It is noted that the development of critical thinking among students requires such an organization of educational work, which will be aimed at stimulating the understanding of the material and the formation of their own judgments and creation independent approaches to solving various scientific problems. Methods and techniques of formation future primary school teacher’s critical thinking are considered. It is noted the methodical ways and methods of forming critical thinking are working with different types of texts, visual methods and techniques of organizing information, asking questions, educational discussion, methods of reflection. The main methods and techniques for forming critical thinking of future primary school teachers are: cluster (“bunch”), “brainstorming”, Insert (interactive tag system for effective reading and thinking), mental map method, “written discussion”, project techniques . It is noted to form students’ skills of critical thinking – the task of all disciplines of the educational program of training future primary school teachers. It is determined that sufficient opportunities for the formation of critical thinking are seen in the inclusion in the educational process of such forms of independent work as compiling structural and logical schemes, annotations, writing and defending essays, reviewing essays by colleagues, scientific articles; creative works, creative reports, project activities, etc. It is established that there are many methods and techniques for forming critical thinking and depending on the specifics of the discipline being studied and the goals pursued by the teacher, it is possible to use certain types of these techniques, as well as their combination.

Live Imaging of RNA Transport and Translation in Xenopus Retinal Axons.

In neurons, specific mRNAs are transported into axons, where their local translation supports essential cellular functions. Over the years, our knowledge of the molecular mechanisms underlying axonal mRNA translation has rapidly expanded. However, tools to study mRNA localization and translation in real time with high spatial precision were not available until recently. Here, we present a live imaging approach to examine axonal mRNA trafficking and translation simultaneously in Xenopus retinal ganglion cells (RGCs), using in vitro synthesized fluorescently labeled mRNAs coupled with a genetically encoded protein tagging system to visualize synthesizing peptides at single-molecule resolution. We further describe the process of image analysis in detail, thus providing a methodology that can be used to investigate new research questions in the field.

An On-Body UHF RFID Tag With DDRR Antenna for Healthcare Data Streaming Applications

This paper describes the development of a Direct Driven Resonant Radiator (DDRR) antenna for an ultra-low power UHF RFID tag system, integrating an accelerometer for movement tracking using a passive backscattering communications link. An outline of a system intended for healthcare applications involving wireless movement detection, such as therapeutic recovery exercises is described. The tag comprises of a UHF RFID transponder connected to a 4 cm (0.115λ) diameter, 1 mm thick (0.0028λ) skin-mounted antenna. Offbody read ranges of 3.6 m with 1 kB/s data communication are achieved. The DDRR radiation pattern is a limiting factor in movement tracking, offering only limited angles of detection, which could be improved with spatial diversity in the reader antennas.

Personalised resource recommendation method for collaborative tagging system based on machine learning

In order to overcome the low feasibility of traditional resource recommendation methods, this paper proposes a personalised resource recommendation method based on machine learning. Firstly, the user-based collaborative filtering algorithm is used to calculate user personalised similarity, and then content-based collaborative filtering algorithm is used to calculate resource content similarity through cosine similarity. Combined with user similarity and resource content similarity, a hybrid computing model of resource similarity is established, and personalised recommendation is realised through statistical machine learning. The experimental results show that: the F-measure value of the method can reach 0.97, the coverage rate is maintained above 50%, the popularity is above 0.8, and the MAE value is always the minimum, and its precision is always higher than that of the contrast method. It shows that the proposed method can effectively improve the precision and feasibility of personalised recommendation results.

In Vivo Visualization of Mobile mRNA Particles in Plants Using BglG.

Cells have developed mechanisms for cytoplasmic RNA transport and localization that participate in the regulation and subcellular localization of protein synthesis. In addition, plants can exchange RNA molecules between cells through plasmodesmata and to distant tissues in the phloem. These mechanisms are hijacked by RNA viruses to establish their replication complexes and to disseminate their genomes throughout the plant organism with the help of virus-encoded movement proteins (MP). Live imaging of RNA molecules is a fundamental approach to understand the regulation and molecular basis of these processes. The most widely used experimental systems for the in vivo visualization of genetically encoded RNA molecules are based on fluorescently tagged RNA binding proteins that bind to specific motifs inserted into the RNA, thus allowing the tracking of the specific RNA molecule by fluorescent microscopy. Recently, we developed the use of the E. coli RNA binding protein BglG for the imaging of RNAs tagged with BglG-binding sites in planta. We describe here the detailed method by which we use this in vivo RNA tagging system for the real-time imaging of Tobacco mosaic virus (TMV) MP mRNA.

Following the organism to map synthetic genomics

Synthetic genomics, or engineering biology at the level of whole genomes and whole organisms, is an emerging outgrowth of parts-based synthetic biology. This nascent subfield is also diverse and difficult to characterize. As social scientists investigating responsible research and innovation in synthetic genomics, we suggest that focusing on the organism is a fruitful approach to making sense of the diversity it encompasses. Here, we offer a heuristic in the form of a tagging system to organize projects by the roles the engineered organism is asked to perform. We suggest several reasons why this system is useful for understanding the current shape and future directions of the field, especially in light of the need to ask: how does engineering biology contribute to building a future of sustainable relationships with other creatures?

USE OF THE BMP SYSTEM FOR BLOCKING OF DANGEROUS ENERGIES DURING REALIZATION OF WORKS FROM REPAIR AND MAINTENANCE OF TECHNIQUE

Creating healthy and safe working conditions is the main task of the employer when performing high-risk work. Practice shows that the cause of accidents during the repair and maintenance of equipment are uncoordinated and erroneous actions of staff, resulting in incorrect supply of hazardous energy to the installation where people work. In order to prevent injuries at metallurgical enterprises there is a need to revise and modernize the existing approach to control the supply of hazardous energy during repairs, improve the current labeling system of access to repairs of technological equipment based on the experience of advanced world technologies. Audit). The BMP system is used to perform maintenance and repair of equipment, as well as any other cases where personnel need to enter the danger zone, and includes not only the actual process of blocking and marking, but also all other activities: documentation, organization of storage and issuance of BMP devices, training and testing of personnel knowledge According to the analysis, the current tag system at the metallurgical enterprises of Ukraine is inferior in efficiency to the BMP system, which allows you to almost completely eliminate the risks associated with the human factor in the repair and maintenance of equipment. The foreign experience of using hazardous energy blocking and labeling systems and the existing legal framework on this issue in Ukraine are analyzed. According to the results of research, the basic principles of using the BMP system at the enterprises of the metallurgical industry are established. The sequence of BMP procedure implementation is offered. The information on the basis of which the BMP map is formed is considered in detail. An important stage in the formation of this map is the assessment of industrial risks of exposure to hazardous energies in the process of repair and maintenance of equipment. The direction of further research on the implementation of the BMP system and the legalization of the BMP standard at the state level is substantiated.

Improving the regional Y-STR haplotype resolution utilizing haplogroup-determining Y-SNPs and the application of machine learning in Y-SNP haplogroup prediction in a forensic Y-STR database: A pilot study on male Chinese Yunnan Zhaoyang Han population

Improving the resolution of the current widely used Y-chromosomal short tandem repeat (Y-STR) dataset is of great importance for forensic investigators, and the current approach is limited, except for the addition of more Y-STR loci. In this research, a regional Y-DNA database was investigated to improve the Y-STR haplotype resolution utilizing a Y-SNP Pedigree Tagging System that includes 24 Y-chromosomal single nucleotide polymorphism (Y-SNP) loci. This pilot study was conducted in the Chinese Yunnan Zhaoyang Han population, and 3473 unrelated male individuals were enrolled. Based on data on the male haplogroups under different panels, the matched or near-matching (NM) Y-STR haplotype pairs from different haplogroups indicated the critical roles of haplogroups in improving the regional Y-STR haplotype resolution. A classic median-joining network analysis was performed using Y-STR or Y-STR/Y-SNP data to reconstruct population substructures, which revealed the ability of Y-SNPs to correct misclassifications from Y-STRs. Additionally, population substructures were reconstructed using multiple unsupervised or supervised dimensionality reduction methods, which indicated the potential of Y-STR haplotypes in predicting Y-SNP haplogroups. Haplogroup prediction models were built based on nine publicly accessible machine-learning (ML) approaches. The results showed that the best prediction accuracy score could reach 99.71% for major haplogroups and 98.54% for detailed haplogroups. Potential influences on prediction accuracy were assessed by adjusting the Y-STR locus numbers, selecting Y-STR loci with various mutabilities, and performing data processing. ML-based predictors generally presented a better prediction accuracy than two available predictors (Nevgen and EA-YPredictor). Three tree models were developed based on the Yfiler Plus panel with unprocessed input data, which showed their strong generalization ability in classifying various Chinese Han subgroups (validation dataset). In conclusion, this study revealed the significance and application prospects of Y-SNP haplogroups in improving regional Y-STR databases. Y-SNP haplogroups can be used to discriminate NM Y-STR haplotype pairs, and it is important for forensic Y-STR databases to develop haplogroup prediction tools to improve the accuracy of biogeographic ancestry inferences.

Radio frequency identification (RFID) stock control and geo-location data system from a moving vehicle

PurposeThe purpose of the research has been the primary consideration and evaluation of a cost effective, reliable, robust and simple process of radio frequency identification (RFID)-based stock control, asset management and monitoring of concrete safety bollards used in the road environment. Likewise, the consideration of the use of the same system and technology to other items in and around the general road infrastructure.Design/methodology/approachThe research approach undertaken has been an evaluation of the use of currently available RFID technology, with a key emphasis on low cost, ease of use, reliability and convenience. Practical field exercises completed in considering the relevant RFID tags and readers and associated software and apps and necessary software integration and development have been undertaken. At the same time, evaluating the specific limits created in the specific environment is being applied. Of particular interest has been the use of a moving scan in a vehicle drive-through or pass-bye, type reading system. This has been determined to be viable and completely practical, drastically reducing the key issue of time-taken. Practical application of the system from idea to real life application has been undertaken. The integration of the use of the RFID tag and reader system with necessary and related software to database upload and storage has been established. The creation of an online facility to allow the appropriate use of the data and to include the convenient output of an asset report has been undertaken.FindingsThe findings have provided the necessary insight confirming the use of RFID technology as a simple yet reliable, cost effective and adaptable stock control, asset management and geo-locating system in the road environment. The use of such systems in this particular environment is in its infancy, and is perhaps novel and original in the specific aspect of using the system to stock control, manage and monitor road safety concrete bollards and other roadside objects in the road environment.Originality/valueTo establish if in fact, stock control geo-locating can be reliably undertaken with the use of RFID tags and readers in the specific road and road construction environment, particularly with the use of moving RFID reading of passive tags. To establish the minimum requirements of a field usable RFID tag and reader, specifically applicable to the concrete safety bollards, however to other roadside furniture. To identify the minimum requirements of a function, simple app to minimise general requirements of the overall stock control and monitoring of the RFID-tagged objects. To establish the possibility of reading the tag data, global positioning system (GPS) location and video imaging footage as a single operation function. To determine the basic parameters or limits of the GPS geo-locating, on the proposed products selected and overall system. To determine the current best practice in respect of reasonable accuracy and detail in relation to price considerations to a fully function stock control and monitoring system. To identify the minimum requirements of an online database to receive, house and provide ongoing access to and report on the data. To identify the key differences and benefits between traditional stock control and monitoring systems, against that of proposed RFID tag, read and geo-locating system.

56 ‘Abducted Baby’ Simulation: Testing the System to Optimize Patient Safety on a Neonatal Intensive Care Unit

Infant abductions are rare distressing events. The Care Quality Commission recently highlighted inadequate protective measures in other trusts as a cause of major concern The aim of the study was to test our existing patient safety system in a real-life situation looking at human factors and equipment functionality.An activated baby tag was placed on a mannequin which was then put into a pram. A member of staff in disguise (the ‘abductor’) pushed the pram out of the neonatal unit by ‘tailgating’ another member of staff so that the doors would not automatically lock, replicating a potential real-life scenario that exploited a known risk. The aim was to see whether the mannequin could leave the hospital. The ‘abductor’ was eventually stopped from leaving. A detailed timeline of events was recorded and analysed. Safety was ensured and participants were individually debriefed as emotions were high.Our simulation highlighted points of excellence including a quick and calm response, the use of the panic button and appropriate persistent challenge of the ‘abductor’ without aggression. Important human factors were highlighted. There is no security staff in the hospital. The ward clerks called the porters directly, rather than dialling 2222 and saying ‘lockdown’, which triggers a lock of all doors out of the hospital. There were several system failures. The baby tag system did not alert the front of house. The panic button was broken, and a set of doors out of the hospital did not lock.Simulation is an effective tool to identify system failures and patient safety risks. This scenario highlighted deficiencies in our system and a lack of established procedures and training. A detailed action plan has been put in place. The panic alarm, door locking mechanism and system linking the baby alarm system to the front of house are being addressed. The option of an automatic lockdown on activation of the baby tag alarm system is being explored. Finally, a standard operating procedure is being written and learning disseminated in the department. We are planning to run this simulation in other areas of the hospital to optimize patient safety.

Analysis and Comparative Study of POS Tagging Techniques for National (Urdu) Language and other Regional Languages of Pakistan

Defining algorithms and techniques to enable computers to understand human language is the Natural Language Processing (NLP), which is an integral part of speech recognition. Parts of Speech (POS) is considered as one of the well understood problems of Natural Language Processing, in which natural language words and sentence are tagged or assigned grammatical classes, because tagging a single word by human hand is a time consuming and tedious job. To automate the tagging job is the way to automate the lexicons of the text of a language. Many of the languages are enriched with their POS tagging systems. Pakistani regional languages are less developed due to the many reasons and much of the work is needed in POS tagging system. Some of the regional languages have their POS tagging systems but still they need some more attention to refine their system. Some of the languages need to develop from the scratch. Balochi language has no any POS tagging system. This study presents the comparative analysis of POS tagging approaches for the national language (Urdu) and other regional languages of Pakistan. The approaches and their data sets used and their reported results are presented here

Near-infrared imaging in fission yeast using a genetically encoded phycocyanobilin biosynthesis system.

Near-infrared fluorescent protein (iRFP) is a bright and stable fluorescent protein with near-infrared excitation and emission maxima. Unlike the other conventional fluorescent proteins, iRFP requires biliverdin (BV) as a chromophore. Here, we report that phycocyanobilin (PCB) functions as a brighter chromophore for iRFP than BV, and that biosynthesis of PCB allows live-cell imaging with iRFP in the fission yeast Schizosaccharomyces pombe. We initially found that fission yeast cells did not produce BV and therefore did not show any iRFP fluorescence. The brightness of iRFP-PCB was higher than that of iRFP-BV both in vitro and in fission yeast. We introduced SynPCB2.1, a PCB biosynthesis system, into fission yeast, resulting in the brightest iRFP fluorescence. To make iRFP readily available in fission yeast, we developed an endogenous gene tagging system with iRFP and all-in-one integration plasmids carrying the iRFP-fused marker proteins together with SynPCB2.1. These tools not only enable the easy use of multiplexed live-cell imaging in fission yeast with a broader color palette, but also open the door to new opportunities for near-infrared fluorescence imaging in a wider range of living organisms. This article has an associated First Person interview with the first author of the paper.

A Low Cost, High-Reliability Receiver System for Reading Passive RFID Tags

Radio-Frequency Identification (RFID) is one of the leading enabling technologies of the Internet of Things (IoT) at low cost and high granularity scenarios. The cost of implementing IoT applications concerns the development and operation of receiver systems for reading labels. In this paper, we propose a low-cost receiver system based on off-the-shelf components allied to the development of a microstrip antenna. The proposed system is capable of receiving and processing digital signals scattered back from a passive RFID tag. The proposal relies on a Python application embedded in Raspberry Pi hardware, in which a bank of digital filters processes the signal. The proposal separates the received signal into sub-bands and implements a decision-maker that detects and codes radiofrequency carriers’ presence in sub-bands. Simulation using artificial random noise proves that the proposed and implemented decision-maker achieves 92% reliability for a Signal-to-Noise ratio between 1.6 dB and 2.3 dB. The evaluation of the printed dipole antennas pair for the RFID receiver system indicates a return loss of 19.22 dB for operation at 915 MHz.

ALPACA - a level-set based sharp-interface multiresolution solver for conservation laws

ALPACA is a simulation environment for simulating hyperbolic and (incompletely) parabolic conservation laws with multiple distinct and immiscible phases. As prominent example, consider the compressible Navier-Stokes equations (NSE). Solutions to these equations give insight and understanding of many important engineering applications. Numerical simulations of nonlinear parabolic systems of equations are very challenging for their complex nonlinear dynamics including the propagations of discontinuities such as shocks and phase interfaces. Accurate predictions require high temporal and spatial resolutions for such multi-scale problems. We utilize low dissipation high-resolution methods to capture the dynamics inside the separate phases. Their interaction is modeled by a sharp-interface level-set method with conservative interface-interaction. This allows to accurately locate the interface position and to easily prescribe arbitrary coupling conditions. We tackle the resulting immense computational loads by using a block-based multiresolution (MR) algorithm and adaptive local time stepping. The level-set treatment is integrated into the MR algorithm with little overhead by employing a smart tagging system and adaptive storage of the fluid data in the MR nodes. We embed these methods in a C++20 object-oriented modular framework using state-of-the-art programming paradigms. Furthermore, our implementation is capable to exploit the multiple levels of parallelism in modern high-performance computing (HPC) systems efficiently. We demonstrate the capabilities of our framework by simulating a variety of compressible multi-phase flow problems. Problem-sizes are of O(1010) effective degree of freedom (DOFs). By the use of MR, we typically achieve memory and compute compressions of >90%. We demonstrate near-optimal parallel performance for scaling runs using O(104) cores, regardless of the employed numerical models. Program summaryProgram Title: ALPACA - Adaptive Level-set Parallel Code AlpacaCPC Library link to program files:https://doi.org/10.17632/5zr3sg83ct.1Developer's repository link:https://gitlab.lrz.de/nanoshock/ALPACALicensing provisions: GPLv3Programming language: C++20Supplementary material: Code: Copy of the git repository, Videos: Air-helium shock bubble interaction (front and back view), Air-R22 shock bubble interaction, Three bubble shock interface interaction.Nature of problem: Numerical simulation of conservation laws such as the compressible Navier-Stokes equation with several interacting gaseous and liquid phases remains challenging even today. These flows often involve singularities such as shocks and interfaces as well as instabilities driven by their interaction. The inherent highly nonlinear dynamics of those systems leads to a broad range of temporal and spatial scales that have to be resolved. There exists a variety of mutually exclusive numerical models that are able to tackle these challenges. Those, however, are computationally expensive and require computational power that is offered only by large-scale state-of-the-art distributed-memory machines.Solution method: We have developed a modular simulation environment for conservation laws allowing exchange of numerical methods without loss of parallel performance. Computational efficiency is enhanced by employing multi-resolution schemes with adaptive local-time stepping. Our block-based implementation of these schemes is parallelized using the Message Passing Interface and exploits vectorization capabilities of the compute hardware. To simulate distinct and immiscible phases inside the computational domain, we utilize a sharp-interface level-set method. The level-set method allows to accurately locate the interface position and to easily prescribe arbitrary coupling conditions. The narrow-band approach reduces the computational load of the level-set method. We extend this method by a smart tagging system that exploits the block-based nature of the algorithm and further reduces the computational load. The simulation framework is written in modern C++20 and provides a Python interface for integration in Machine Learning and Uncertainty Quantification toolchains. We use parallel HDF5 in combination with XDMF to output field quantities. CMake is used as build system. We have completely annotated the source code using doxygen-style comments, allowing automated documentation generation in different formats. The source code is equipped with CI/CD-automated unit tests and an exhaustive integration test suite.Additional comments including restrictions and unusual features: ALPACA relies on open-source third-party libraries for input and testing. These are packaged as git submodules and automatically integrated. ALPACA is tested on Linux and macOS.