Specific Query Research Articles

Report of the 2020 British Nuclear Medicine Society survey of nuclear medicine equipment, workforce and workload.

The British Nuclear Medicine Society (BNMS) survey represents the only resource that brings together detailed information on equipment, workforce and workload from the practice of nuclear medicine in the UK. This article is a report of the most recent BNMS survey which was collected during 2019 and 2020. The survey used two methods to collect data: for equipment and workforce, participants created or updated existing online records; for workload information, respondees were asked to submit 12 months of data from local radiology information systems. Following the survey, the BNMS database contained a total of 191 sites (63% of known sites) having either equipment or workforce data or both. In total 39 centres provided workload data which included over 175 000 examinations. A combination of automated tools and visual inspection were used to clean, sort and validate submitted data into formats that allowed further analysis and extraction of useful parameters. Results are presented that the authors believe may be useful for nuclear medicine professionals and other stakeholders. Potential applications include benchmarking for service review and equipment replacement/updating. The survey represents a valuable resource that might be used by the BNMS secretariat to respond to specific queries from BNMS members.

Large-Scale Multimodal Piano Music Identification Using Marketplace Fingerprinting

This paper studies the problem of identifying piano music in various modalities using a single, unified approach called marketplace fingerprinting. The key defining characteristic of marketplace fingerprinting is choice: we consider a broad range of fingerprint designs based on a generalization of standard n-grams, and then select the fingerprint designs at runtime that are best for a specific query. We show that the large-scale retrieval problem can be framed as an economics problem in which a consumer and a store interact. In our analogy, the runtime search is like a consumer shopping in the store, the items for sale correspond to fingerprints, and purchasing an item corresponds to doing a fingerprint lookup in the database. Using basic principles of economics, we design an efficient marketplace in which the consumer has many options and adopts a rational buying strategy that explicitly considers the cost and expected utility of each item. We evaluate our marketplace fingerprinting approach on four different sheet music retrieval tasks involving sheet music images, MIDI files, and audio recordings. Using a database containing approximately 375,000 pages of sheet music, our method is able to achieve 0.91 mean reciprocal rank with sub-second average runtime on cell phone image queries. On all four retrieval tasks, the marketplace method substantially outperforms previous methods while simultaneously reducing average runtime. We present comprehensive experimental results, as well as detailed analyses to provide deeper intuition into system behavior.

Wasmati: An efficient static vulnerability scanner for WebAssembly

WebAssembly is a new binary instruction format that allows targeted compiled code written in high-level languages to be executed with near-native speed by the browser’s JavaScript engine. However, given that WebAssembly binaries can be compiled from unsafe languages like C/C++, classical code vulnerabilities such as buffer overflows or format strings can be transferred over from the original programs down to the cross-compiled binaries. As a result, this possibility of incorporating vulnerabilities in WebAssembly modules has widened the attack surface of modern web applications. This paper presents Wasmati, a static analysis tool for finding security vulnerabilities in WebAssembly binaries. It is based on the generation of a code property graph (CPG), a program representation previously adopted for detecting vulnerabilities in various languages but hitherto unapplied to WebAssembly. We formalize the definition of CPG for WebAssembly, introduce techniques to generate CPG for complex WebAssembly, and present four different query specification languages for finding vulnerabilities by traversing a program’s CPG. We implemented ten queries capturing different vulnerability types and extensively tested Wasmati on four heterogeneous datasets. We show that Wasmati can scale the generation of CPGs for large real-world applications and can efficiently find vulnerabilities for all our query types. We have also tested our tool on WebAssembly binaries collected in the wild and identified several potential vulnerabilities, some of which we have manually confirmed to exist unless the enclosing application properly sanitizes the interaction with such affected binaries.

Dietary Supplements: A Survey of the Opinion of First-Year Professional Pharmacy Students

Introduction Pharmacists need to be at the forefront in advising consumers of dietary supplements (DS) about quality, claims, labeling, safety, efficacy, DS-drug interactions, and other aspects. Yet, the knowledge base of pharmacists and pharmacists-in-training about DS appears to be below expectation. Objective The goal of the study is to evaluate pharmacy student opinions about DS. Methodology A survey questionnaire was developed, tested, and distributed among students who were enrolled in the Drug Information class, which is a 2-credit hour mandatory course for all first professional pharmacy students at Howard University, College of Pharmacy. The data was analyzed using SPSS statistical analysis software. Results A total of 42 students (15 male, 27 female) participated in the survey. Of these, 25 respondents (59.5%) felt comfortable about their knowledge of DS, while only 14 (33.4%) reported participation in counselling (p=0.0281). Most respondents (29; 69%) had used DS in the past, while 21 (50%) claimed they used DS at the time of the survey. To a specific query in the questionnaire regarding lycopene-containing food items, 28 (66.7%) agreed they would use such foods in the future for health benefits. Analysis of the survey data revealed no statistical differences between the responses of male and female students (p>0.05 for all the five questionnaire items). Conclusion In a survey of 42 pharmacy students at Howard University College Pharmacy, over half (59.5%) felt comfortable about their knowledge of DS. About one-third students (33%) reported they were involved in patient counseling and interaction. Over two-third respondents (69%) took DS in the past, while half were taking DS at the time of the survey.

NLQ into SQL translation using computational linguistics

This research discusses the implementation experiment of an automatic translation of an unstructured Natural Language Question (NLQ) into a Structured Query Language (SQL) statement. SQL is used as a Relational DataBase (RDB) interaction language with special query syntax and a computer- executable artificial language. This way, DataBase (DB) administrators or general users with little or no SQL querying abilities can perform queries on RDBs in an interactive manner. The main goal of this work is to exploit a manually written rule- based mapping constraints algorithm. This algorithm maps NLQ tokens’ semantic/syntactic information into RDB elements’ semantic roles (i.e., value, attribute) via pairing and matching means. The matching RDB elements, called “identified lexica”, are then mapped into the SQL clauses consistently for SQL generation and execution. The matching process uses a computational linguistic analysis mapping algorithm, represented in the MetaTables. This mapping algorithm proved to be efficient especially with small RDBs with an accuracy of 95% and is about 93% accurate with larger RDBS.

Construct a variable-length fragment library for de novo protein structure prediction.

Although remarkable achievements, such as AlphaFold2, have been made in end-to-end structure prediction, fragment libraries remain essential for de novo protein structure prediction, which can help explore and understand the protein-folding mechanism. In this work, we developed a variable-length fragment library (VFlib). In VFlib, a master structure database was first constructed from the Protein Data Bank through sequence clustering. The hidden Markov model (HMM) profile of each protein in the master structure database was generated by HHsuite, and the secondary structure of each protein was calculated by DSSP. For the query sequence, the HMM-profile was first constructed. Then, variable-length fragments were retrieved from the master structure database through dynamically variable-length profile-profile comparison. A complete method for chopping the query HMM-profile during this process was proposed to obtain fragments with increased diversity. Finally, secondary structure information was used to further screen the retrieved fragments to generate the final fragment library of specific query sequence. The experimental results obtained with a set of 120 nonredundant proteins show that the global precision and coverage of the fragment library generated by VFlib were 55.04% and 94.95% at the RMSD cutoff of 1.5Å, respectively. Compared with the benchmark method of NNMake, the global precision of our fragment library had increased by 62.89% with equivalent coverage. Furthermore, the fragments generated by VFlib and NNMake were used to predict structure models through fragment assembly. Controlled experimental results demonstrate that the average TM-score of VFlib was 16.00% higher than that of NNMake.

Analysing thermal regime and transient by using numerical modelling for solid oxide electrolyser aided by solar radiation

The present paper focuses on analysing the thermal transient and regime for a Solid Oxide Electrolyser (SOE) system by means of the development of a numerical algorithm at high accuracy, built up ad hoc and run in a proper calculation environment. In particular, the algorithm also considers that the supply of thermal power takes place through a concentrated solar source, so it is designed also to receive the data library relating to solar radiation. The calculations are centred on the evaluation of the concentration factor to proceed with the dimensioning of the heat source and its management in order to guarantee the thermal power supply. The thermal transient model receives the SOE thermo-electrochemical model as input to integrate it into the larger thermal process of the overall structure, accounting for the effective thermal dispersion occurring to the external environment.The algorithm consents the calculation of the temperature profile, besides assessing the contributions of thermal power such as that required, disposed and possibly recovered by the system, and that can possibly be integrated to sustain the system itself. A specific query is dedicated to the switch-on and switch-off phase for which the device must comply with certain warnings, referring to the temperature limits and temperature gradient constraints.The thermal analyses are set as a function of the electro-thermal and feeding parameters of the SOE as voltage, electric current administered and cathodic mixture of H2O/H2.An application on a real case study was effected at the SOE test-station of “Fuel Cell and Hydrogen” Lab at the Department of Mechanical, Energy and Management Engineering of the University of Calabria, in Cosenza, Italy.The three possible exercises of functioning of SOE working regime, SOE start-up, SOE shut-down are analysed.The assessment about the start-up and shut-down phases reveals that these delicate phases have to be managed smartly time by time to observe the limitation on maximum temperature and temperature gradient.

Rethinking the framework constructed by counterfactual functional model.

The causal inference represented by counterfactual inference technology breathes new life into the current field of artificial intelligence. Although the fusion of causal inference and artificial intelligence has an excellent performance in many various applications, some theoretical justifications have not been well resolved. In this paper, we focus on two fundamental issues in causal inference: probabilistic evaluation of counterfactual queries and the assumptions used to evaluate causal effects. Both of these issues are closely related to counterfactual inference tasks. Among them, counterfactual queries focus on the outcome of the inference task, and the assumptions provide the preconditions for performing the inference task. Counterfactual queries are to consider the question of what kind of causality would arise if we artificially apply the conditions contrary to the facts. In general, to obtain a unique solution, the evaluation of counterfactual queries requires the assistance of a functional model. We analyze the limitations of the original functional model when evaluating a specific query and find that the model arrives at ambiguous conclusions when the unique probability solution is 0. In the task of estimating causal effects, the experiments are conducted under some strong assumptions, such as treatment-unit additivity. However, such assumptions are often insatiable in real-world tasks, and there is also a lack of scientific representation of the assumptions themselves. We propose a mild version of the treatment-unit additivity assumption coined as M-TUA based on the damped vibration equation in physics to alleviate this problem. M-TUA reduces the strength of the constraints in the original assumptions with reasonable formal expression.

MQALD: Evaluating the impact of modifiers in question answering over knowledge graphs

Question Answering (QA) over Knowledge Graphs (KG) aims to develop a system that is capable of answering users’ questions using the information coming from one or multiple Knowledge Graphs, like DBpedia, Wikidata, and so on. Question Answering systems need to translate the user’s question, written using natural language, into a query formulated through a specific data query language that is compliant with the underlying KG. This translation process is already non-trivial when trying to answer simple questions that involve a single triple pattern. It becomes even more troublesome when trying to cope with questions that require modifiers in the final query, i.e., aggregate functions, query forms, and so on. The attention over this last aspect is growing but has never been thoroughly addressed by the existing literature. Starting from the latest advances in this field, we want to further step in this direction. This work aims to provide a publicly available dataset designed for evaluating the performance of a QA system in translating articulated questions into a specific data query language. This dataset has also been used to evaluate three QA systems available at the state of the art.

Web-Based Ranking and Link Analysis of NAAC Accredited General Degree Colleges in West Bengal: A Webometric Study

This study examines the websites of 36 NAAC-accredited general degree colleges in West Bengal using Webometric indicators. Webometric data is acquired on the Google search engine using special query syntax and calculated different WIFs and WISER value of websites, the relationship between the ranks of all websites as defined by WISER indexing value and in-link impact value are also examined. According to the findings, Panihati Mahavidyalaya's website under West Bengal State University ranked first in Simple Web Impact Factor (SWIF) with 1887.912%, and Banipur Mahila Mahavidyalaya's websites (Sl. No. 5) ranked first in self-link WIF, INLWIF, and EWIF with 0.679803 SLWIF, 0.729064 ELWIFs, and 0.315271 RWIFs, respectively. Darjeeling Govt. College is ranked first, followed by Panihati Mahavidyalaya and Mugberia Gangadhar Mahavidyalaya, according to the WISER index value. This study may aid college administrators and webmasters in better comprehending the importance of these websites in making them user-friendly and informative websites that meet the needs of their users.

A Detailed Analysis of Workplace Foot and Ankle Injuries

Category:Trauma; Ankle; Hindfoot; Midfoot/ForefootIntroduction/Purpose:In 2018 over 96,000 foot and ankle injuries resulted in lost workdays. The average 2017-2018 workers compensation claim for ankle injuries was $17,210 for medical costs with an additional $13,276 of indemnity. Workplace foot injuries were similarly expensive, averaging $15,762 in medical costs and $11,866 in indemnity. These costs highlight the burden workplace foot and ankle injuries place on both workers and employers. This study analyzes the incidence, rate, and days lost from work due to foot and ankle injuries across different industries, age groups, and genders and compares these findings to other musculoskeletal injuries. These findings will help us better understand which industries are greater impacted by foot and ankle injuries and what factors may influence the occurrence and severity of these injuries.Methods:Workplace injury data was obtained using a special query from the Bureau of Labor Statistics Workplace Injuries and Illnesses Nonfatal Cases Involving Days Away From Work: Selected Characteristics database. Data included injury incidence, incidence rate per 10,000 workers, and median days missed from work due to injury. The data was grouped by injury location (all injuries, ankle injuries, and foot injuries), type of injury (fracture, sprain, amputation), and industry. Spearman correlation, one-way ANOVA, and independent samples t-test were used to identify the industries, sex, and ages associated with the highest rates and median days missed from work for each of these groups. Regression analysis was used to analyze changes in incidence rate over time. Incidence rate data was obtained for a seventeen-year period (2003-2019) and days lost from work data was obtained for a nine-year period (2011-2019). Data analysis was performed using SPSS statistics software, version 25.0.Results:The mining (44.85 foot,17.09 ankle), transportation/warehousing (16.82,16.29), and utilities (24.41,26.69) industries had three of the five highest average median days missed from work for both foot and ankle injuries. Of these, only transportation/warehousing (11.06,13.80) was among the five industries with the highest rates of foot and ankle injuries. There was a strong negative correlation (P<0.001) between age and rate of both foot and ankle injuries and a strong positive correlation (P<0.001) between age and median days missed from work. Males had significantly higher rates of foot injuries (5.31) than females (3.80; P<.0001). Males also had higher rates of ankle injuries (4.96) than females (4.88; P=.453). Regression analysis showed the incidence rate of ankle sprains, ankle fractures, foot sprains, and foot fractures decreased from 2003-2019.Conclusion:This study demonstrates that the incidence rate and severity of workplace foot and ankle injuries are influenced by workers' age, gender, and the industry they work in. It shows that industries with higher days missed often did not have higher rates of injuries. Our results have the potential to be used to identify industries in need of additional safeguards to protect workers from injury and provide companies with information about the industry norm for rates of employee injuries and days missed from work for these injuries.

Reliable Keyword Query Interpretation on Summary Graphs

The semantic gap between keyword queries and search intents behind them motivates intensive studies on keyword query interpretation, which aims to interpret a keyword query to structured queries (a.k.a. patterns) representing most possibly relevant search intents. However, there still lacks of study on an important issue: how to guarantee the patterns are "reliable", which means the structured queries can be evaluated as really existing results. In this paper, we regard the reliability as a new metric for ranking patterns, and present a keyword query interpretation approach to find both reliable and relevant pattern trees on an arbitrary summary graph of underlying data. Specifically, we firstly propose a reliability estimation model to measure how possibly a pattern tree can be evaluated as a nonempty result set by statistics under reasonable assumptions. Secondly, we develop constrained top-k search algorithms that guarantee to return the optimal pattern trees for a specific keyword query. Moreover, to improve the efficiency of online search, we also design elaborate indexes, search heuristics and pruning strategies. Lastly, we perform comprehensive experiments on two real-world datasets, DBpedia and Yago, with both QALD-9 queries and random queries. The observations indicate our approach improves the accuracy and overall quality of top-k results significantly.

Political and Economic Patterns in COVID-19 News: From Lockdown to Vaccination

The purpose of this study is to analyse COVID-19 related news published across different geographical places, in order to gain insights in reporting differences. The COVID-19 pandemic had a major outbreak in January 2020 and was followed by different preventive measures, lockdown, and finally by the process of vaccination. To date, more comprehensive analysis of news related to COVID-19 pandemic are missing, especially those which explain what aspects of this pandemic are being reported by newspapers inserted in different economies and belonging to different political alignments. Since LDA is often less coherent when there are news articles published across the world about an event and you look answers for specific queries. It is because of having semantically different content. To address this challenge, we performed pooling of news articles based on information retrieval using TF-IDF score in a data processing step and topic modeling using LDA with combination of 1 to 6 ngrams. We used VADER sentiment analyzer to analyze the differences in sentiments in news articles reported across different geographical places. The novelty of this study is to look at how COVID-19 pandemic was reported by the media, providing a comparison among countries in different political and economic contexts. Our findings suggest that the news reporting by newspapers with different political alignment support the reported content. Also, economic issues reported by newspapers depend on economy of the place where a newspaper resides.

Analytical grammar forms extraction as a new challenge for corpora (Case of conditional mood in Polish and Ukrainian)

A particular challenge for modern textual corpora is the tagging of analytical grammar categories. The com-ponents of these categories may be separated in certain contexts by other words or may even be inverted. A particular interest regarding the selection of analytical grammatical forms is centred around the conditional mood in some Slavic languages, as expressed by means of two words: a past verb form and the particle by/б/би/бы, which is why in most modern corpora, this category lacks a specific tag for these compound forms. The case of Polish is particularly complicated because the particle by may either be merged with the parti-ciple or used separately; furthermore, its separated form may contain a personal verb ending. Specific que-ries subject to experiment on Polish and Ukrainian corpora allow selecting the analytical forms in question.

Teknik Uji Penetrasi Web Server Menggunakan SQL Injection dengan SQLmap di Kalilinux

&lt;p&gt;&lt;em&gt;In recent years cases of cyber attacks that lead to website security have increased. The most widely used website hacking threat is sql injection. By using the sqlmap tool that runs on the Kalilinux operating system, attackers can easily take over very important user authentication data with their passwords. Attackers only use a special SQL query script using the python programming language will force the web server to output database information, tables, columns and data contents. This sql injection technique is not difficult, knowing how sql injection works is expected to be useful for web admins and web application developers to be able to secure user access from attackers. This attack simulation uses a virtual machine, by creating two virtual computers that are scripted as the attacker and the target server. By testing through this simulation, we can find out how the attack process and the consequences of attacks carried out by attackers.&lt;/em&gt;&lt;/p&gt;

Spatial mapping of subcellular disease pathways and cytoarchitecture to anatomical brain regions for multi‐scale brain simulation with The Virtual Brain

AbstractBackgroundComprehensive knowledge bases as NeuroMMSig, a knowledge base of multimodal mechanistic signatures, catalog knowledge about Alzheimer's Disease (AD) and its underlying candidate mechanisms. Besides, digital atlases provide information about cytoarchitectonics and receptor densities, e.g. JuBrain at the EBRAINS platform of the Human Brain Project. However, a gap exists presently with respect to the integration of the various knowledge sources. The Virtual Brain (TVB) is a full brain simulation platform that integrates multimodal imaging data with mathematical brain networks. We present a methodology to map semantic information about AD to 3D brain atlases and to use it for simulations with TVB – increasing the biological plausibility of whole‐brain simulations and disease specificity.MethodOur framework allows topological assignment of brain‐related data from different sources to the Multimodal surface‐based cortical parcellation (MMP) of the Human Connectome Project. Our tool allows mapping of stochastic information from the literature database SCAIView to brain regions. The relevance score for a specific query is calculated for anatomy‐related words from the anatomic ontology Uberon, which we transfer by a unique matrix to MMP parcels. Re‐sampling by the fsaverage brain space of freesurfer allows interoperability with other atlases. In addition, atlas‐annotated data from EBRAINS and neuroimaging data are co‐registered with MMP, enabling knowledge integration into a standardized 3D brain space.ResultOur methodologic pipeline can be used as a software to map semantic information to the brain, which we demonstrate with NeuroMMSig pathways. We further demonstrate how the resulting maps constrain TVB simulations. Face validity is provided through reproducing group‐level (AD versus controls) results of simulations integrating subject‐specific positron emission tomography when semantic information about AD stages is integrated into TVB. We elucidate how brain maps derived from different semantic queries can change simulated brain dynamics fundamentally. Literature‐derived NMDA receptor densities show significant differences between AD and healthy controls. When used to constrain TVB models, this leads to an in silico disruption of functional subnetworks in AD.ConclusionWe developed a tool for mapping semantic knowledge to anatomical brain regions. This enables multi‐scale brain simulations with increases biological plausibility and disease‐specificity for translational research.

Knowledge Management in the Federal Company for Radioactive Waste Disposal (BGE)

Abstract. With completion of the restructuring of the nuclear waste disposal landscape in Germany, the competences for construction and running of repositories for radioactive waste products are since 2017 with the Federal Company for Radioactive Waste Disposal (BGE). The BGE has over 50 years of experience in the disposal of nuclear waste in Germany. Over a period of several decades substantial effort was put into the research and developmental work on nuclear waste disposal in Germany, which led to a considerable state of knowledge, both thematically and quantitatively; however, so far no consistent overview exists on the various works and therefore on the total state of knowledge, as these works only partially exist or existed in the very different organizations (diffuse and local) within the nuclear waste disposal landscape. The emerging loss of specialist knowledge in Germany caused by the withdrawal from nuclear energy and the recession of national mining activities is doing the rest. This imminent loss of knowledge must be taken into consideration as a critical factor, especially considering the age structure within the BGE and the simultaneously occurring processes on selection of a site for disposal of highly radioactive waste products. For this reason, in the division of research and development/knowledge management (R&amp;amp;D/KM) an independent department for knowledge management was created in order to establish an infrastructure for knowledge management and a connection between knowledge management platforms and knowledge carriers in the company. In addition to the collection and distribution of the available knowledge, current results from research and development are also to be fed into the “learning organization”. For this purpose, knowledge management provides a digital information basis, into which current results from research and development are also entered as a knowledge store. This knowledge store consisting of over 14 000 documents, contains mostly research reports and scientific publications, which are concerned with diverse topics for the final disposal of radioactive waste products in geological formations. The total stock of internal company documents available can be accessed with a browser-based text analysis software. Intelligent search algorithms render the textual contents accessible, combine them with synonyms and dictionaries deposited in the system and make the resulting hits of the search queries available for the user in order of importance in summarized and full text versions. Using specific query terms, as known from search machines or library servers, this software analyzes the available documents of the digital information basis and in a brief summary of results, in addition to a brief description of the contents, the naming of relevant keywords, the identification of sources, compilers, institutions, knowledge carriers and an extended optimized information analysis of hits, also provides the possibility to retrieve the complete document and the download. The research options can, in addition to the queries via the established internet search engines also be combined with queries via the incorporated information or databank catalogue of national and international scientific institutions or libraries, which are concerned with research programs relevant for repositories. In order to further increase and optimize the information possibilities for employees of the BGE, a variety of knowledge landscapes has been implemented in the intranet, which enable specific queries on topics, expert information, institution, country and persons. Using these tools a first essential target of knowledge management, the collection, availability and distribution of written down knowledge in the company has been achieved. For the development of person-related and group-related knowledge the department of knowledge management is compiling concepts, which can only be implemented together and jointly with them, as they border on certain interfaces in the organization/company. This particularly concerns measures that fall into the areas of human resources, such as personnel management and personnel strategies or in the area of the particular project; keyword lessons learnt.

How Search Engines Handle Suicide Queries

&#x0D; &#x0D; &#x0D; The suicide contagion effect posits that exposure to suicide- related content increases the likelihood of an individual engaging in suicidal behavior. Internet suicide-related queries correlate with suicide prevalence. However, suicide-related searches also lead people to access help resources. This article systematically evaluates the results returned from both general suicide terms and terms related to specific suicide means across three popular search engines—Google, Bing, DuckDuckGo— in both English and Spanish. We find that Bing and DuckDuckGo surface harmful content more often than Google. We assess whether search engines show suicide prevention hotline information, and find that 53% of English queries have this information, compared to 13% of Spanish queries. Looking across platforms, 55% of Google queries include hotline information, compared to 35% for Bing and 10% for DuckDuckGo. Specific suicide means queries are 20% more likely to surface harmful results on Bing and DuckDuckGo compared to general suicide term queries, with no difference on Google.&#x0D; &#x0D; &#x0D;

#StopAsianHate: Archiving and Analyzing Twitter Discourse in the Wake of the 2021 Atlanta Spa Shootings

AbstractOn March 16, 2021, six Asian women were killed in Atlanta, US, possibly out of racist motivations. This tragic event, now known as the 2021 Atlanta Spa Shootings, precipitated a massive increase in the volume of counter‐anti‐Asian declarations and discussion on social media platforms such as Twitter. In a pilot study to chronicle and profile public opinions, social movements and patterns in the global Twitter discourse we scraped the Twitter API using the query term “StopAsianHate”, obtaining more than 5.5 million tweets and their metadata. By using social movement analytical frameworks to analyze traffic peaks and the use of hashtags, we identified a set of more than 300 frequently used hashtags that can serve as specific query words in future archival ingest activities, as well as the dimensions of and current problems with this social movement. This suggests the utility of this approach for both archiving applications and social‐political analyses of emerging topics and concerns.

World wars and sociotechnical change in energy, food, and transport: A deep transitions perspective.

This paper explores the relationship between world wars and sociotechnical transitions in energy, food, and transport. We utilise and contribute to the Deep Transitions framework, which explores long-term, multi-systemic sociotechnical transitions and integrate a conceptual approach tailored to this particular topic. This approach bridges between historical literatures focused on world wars and sociotechnical perspectives. We explore in what ways the three sociotechnical systems of energy, food, and transport were influenced by the conditions of the First and Second World War and the extent to which these developments influenced lasting change. Our framework is based around three analytical steps: first, we analyse sociotechnical developments during wartime through the interpretive lens of mechanisms of total war. Second, we examine these developments in terms of how they can be interpreted as influencing the development of rules and meta-rules in sociotechnical systems. Third, we focus on the legacy of ‘total war’ utilising the concept of imprinting to examine the rules-based, infrastructural, and wider symbolic and cultural legacy of world wars in peacetime. This paper presents a novel interpretation of world war and sociotechnical transitions and contributes to a specific query of the Deep Transitions framework regarding the role of war in the emergence of the first deep transition. We consider the significance of this analysis in the context of sustainability transitions research.