Large-scale Projects Research Articles

Development and validation of the Open-Source Automatic Bowel Preparation Scale.

Insufficient bowel preparation accounts for up to 42% of missed adenomas in colonoscopy. However, major analysis programs found no correlation between adenoma detection rate and the human-rated Boston Bowel Preparation Scale (BBPS), indicating limitations of the scale. We therefore aimed to develop an open-source automatic bowel preparation scale (OSABPS) based on artificial intelligence that is correlated to the polyp detection rate (PDR). OSABPS was trained on 50,000 frames from 20 colonoscopies from three hospitals. It involved quantifying the presence of fecal matter within the colonoscopy frames, using an approach termed the fecal ratio - the proportion of pixels identified as feces (F) relative to those identified as mucosal tissue (M) (OSABPS = F/M) - thereby making 0 the optimal score indicating a perfect cleansing. Youden's J was used to set the threshold, as it determines the optimal balance between sensitivity and specificity. The algorithm was then tested on 1,405 colonoscopies from three hospitals (internal validation), and 5,525 frames from a public colonoscopy database (Nerthus, external validation). Internal validation: OSABPS correlated significantly with BBPS (Pearson's r = -.42, P<.001). A threshold of .09 OSABPS was determined using Youden's J. PDR was higher for colonoscopies below the threshold of Youden's J (Two proportion z-test, P<.001). External validation: OSABPS correlated significantly with BBPS (Pearson's r = -.70, P<.001). OSABPS can automatically, instantly and without human bias assess bowel preparation quality. Colonoscopies with an OSABPS > .09 should be considered for reexamination. OSABPS' open-source nature allows free implementation.

Safety, efficacy and immunogenicity of aerosolized Ad5-nCoV COVID-19 vaccine in a non-inferiority randomized controlled trial

This phase 3, observer-blinded, non-inferiority randomized trial (ClinicalTrials.gov: NCT05517642), conducted from September 2022 to May 2023 at three Malaysian sites, involved 540 adults previously vaccinated with three COVID-19 doses. Participants were randomized 1:1 to receive either one dose of inhaled Recombinant COVID-19 Vaccine (Ad5-nCoV-IH) or intramuscular tozinameran (BNT-IM). The study assessed safety, vaccine efficacy (VE) and immunogenicity against SARS-CoV-2 variants. The primary outcome was the non-inferiority of anti-spike protein receptor-binding domain (S-RBD IgG) antibodies, with a 97.5% confidence interval lower limit for the geometric mean concentration (GMC) ratio >0.67. Ad5-nCoV-IH showed lower immunogenicity than BNT-IM, with a GMC ratio of 0.22 and a seroconversion rate difference of -71.91%. Adverse drug reactions (ADRs) were less frequent with Ad5-nCoV-IH (39.26%) compared to BNT-IM (64.68%). No serious vaccine-related adverse events were reported. Both vaccines had comparable efficacy against COVID-19 variants. This study was funded by Tianjin Biomedical Science and Technology Major Project.

Application of Building Information Modelling in Construction and Demolition Waste Management: Systematic Review and Future Trends Supported by a Conceptual Framework

The architecture, engineering, construction, and operations industry faces an urgent need to enhance construction and demolition waste management in urban areas, driven by increasing demolition and construction activities and a desire to align with sustainable practices and the circular economy principles. To address this need, a systematic literature review on the building information modelling methodology was conducted, employing a structured protocol and specific tools for the analysis of academic studies, based on PRISMA guidelines and StArt software (version 3.4 BETA). Ninety relevant studies published between 1998 and 2024, were analysed and selected from the Web of Science, Scopus, and Engineering Village databases. Findings indicate that China leads in publications with 34%, followed by Brazil (8%) and the United Kingdom (7%). The analysis emphasises the use of drones and LiDAR scanners for precise spatial data, processed by 3D reconstruction tools like Pix4D and FARO As-Built. Revit excels in 3D modelling, providing a robust platform for visualisation and analysis. Visual programming tools such as Dynamo automate processes and optimise material reuse. The study presents a conceptual framework that integrates these technologies with the principles of the circular economy, clarifying the interactions and practical applications that promote the sustainable management of demolition waste from urban buildings and process efficiency. Although the approach promotes material reuse and sustainability, it still faces barriers such as the need for waste segregation at the source, the adaptation of innovative technologies, like the iPhone 15 Pro LiDAR and thermal cameras, as well as associated costs. These factors may limit its adoption in larger-scale projects, particularly due to the increased complexity of buildings.

Simulation of Small-Scale Wind Turbine Performance with Taperless Blade

Utilizing wind turbines typically involves a large-scale project with extremely huge wind turbine sizes. Because of this, the use of wind turbines in Indonesia is not yet very common and widespread among the community. Basically, a wind turbine has blades; the number of blades on a wind turbine can affect the overall performance of the turbine. Large-scale wind turbine projects usually implement tapered blades, while small-scale projects use taperless blades. Therefore, in this research, a horizontal-axis wind turbine with taperless blades will be used as the object of study to find out the optimal number of taperless blades that can achieve the best performance of a small-scale wind turbine category. The method used in this research is to design a horizontal axis wind turbine equipped with taperless blades with varying numbers of blades, namely three blades, four blades, and five blades, and then simulate the turbine's performance with wind speeds of 3 m/s to 6 m/s. The present research found that the greater the number of turbine blades tends to produce greater power. This is proven by research results, where the highest power in a small-scale horizontal axis wind turbine produces a power of 20,30 Watts in a 5-blade turbine variation for the wind speed of 6 m/s.

Optimization of architectural design and construction with integrated BIM and PLM methodologies.

Digital transformation in the architecture industry encounters challenges such as data silos within design stages, between design and construction, and across the entire industry chain, including BIM and project management. This study introduces a pioneering approach for seamlessly integrating building information modeling (BIM) and product lifecycle management (PLM) within the management framework and collaborative workflows of architectural design and construction. The proposed methodology was implemented in two major projects, namely, the Wuhan Next-Generation Weather Radar Construction Project and the Hubei Center for Disease Control and Prevention Comprehensive Capacity Enhancement Project (Phase I), with the former being China's first end-to-end digitally integrated construction project. Compared with traditional projects, these implementations achieved improvements of 24.39% and 38.04%, respectively, in objective function values. The findings highlight the unique advantages of BIM-PLM integration in optimizing lifecycle management, enhancing cross-disciplinary, cross-enterprise, and cross-regional collaboration, improving project design efficiency and quality, and reducing costs and waste. This integration provides valuable insights into the digital advancement of the construction industry.

Tunnel-induced land subsidence assessment in a densely populated residential area using Sentinel-1 PS-InSAR

Land subsidence detection in residential areas based on advanced remotely sensed data is an effective technique to mitigate catastrophic disasters in time. Synthetic aperture radar (SAR) in spaceborne platforms is a highly sophisticated technique to estimate ground surface subsidence with millimeter accuracy for wide-area observation. SAR is beneficial for large-scale social infrastructure project planning and monitoring in densely populated residential areas. In this study, we applied a permanent scatterer (PS) interferometric SAR (PS-InSAR)-based technique for monitoring land subsidence in a tunnel construction site in the Greater Tokyo Area to investigate tunnel-induced ground surface subsidence. Sentinel-1 repeat-pass SAR data in ascending and descending orbital directions were used for continuous observation. Consecutively estimated interferograms based on repeat-pass SAR data were generated to monitor and detect tunnel-induced land subsidence as well as confirm long-term stability along the tunnel excavation path. A bidirectional displacement of the ground area parallel to the earth’s surface in the east–west direction and perpendicular to the earth’s surface in the up–down direction was estimated at a high-phase consistency location using a PS interferometric stacking technique. The resultant data were then analyzed to detect anomalies in the ground area in the spatiotemporal domains by performing displacement time-series analysis. An area near Higashi-Tsutsujigaoka’s local administrative region in the metropolitan center of Tokyo was observed to have 15-mm subsidence and 30-mm displacement in the east–west direction during August–October 2020. The conventional level survey results in the same ground area showed 15–20-mm subsidence above the tunnel excavation path. The findings of this study offer insights into understanding land subsidence in residential environments.

Predictive Modelling of Land Cover Changes in the Greater Amanzule Peatlands Using Multi-Source Remote Sensing and Machine Learning Techniques

The Greater Amanzule Peatlands (GAP) in Ghana is an important biodiversity hotspot facing increasing pressure from anthropogenic land-use activities driven by rapid agricultural plantation expansion, urbanisation, and the burgeoning oil and gas industry. Accurate measurement of how these pressures alter land cover over time, along with the projection of future changes, is crucial for sustainable management. This study aims to analyse these changes from 2010 to 2020 and predict future scenarios up to 2040 using multi-source remote sensing and machine learning techniques. Optical, radar, and topographical remote sensing data from Landsat-7, Landsat-8, ALOS/PALSAR, and Shuttle Radar Topography Mission derived digital elevation models (DEMs) were integrated to perform land cover change analysis using Random Forest (RF), while Cellular Automata Artificial Neural Networks (CA-ANNs) were employed for predictive modelling. The classification model achieved overall accuracies of 93% in 2010 and 94% in both 2015 and 2020, with weighted F1 scores of 80.0%, 75.8%, and 75.7%, respectively. Validation of the predictive model yielded a Kappa value of 0.70, with an overall accuracy rate of 80%, ensuring reliable spatial predictions of future land cover dynamics. Findings reveal a 12% expansion in peatland cover, equivalent to approximately 6570 ± 308.59 hectares, despite declines in specific peatland types. Concurrently, anthropogenic land uses have increased, evidenced by an 85% rise in rubber plantations (from 30,530 ± 110.96 hectares to 56,617 ± 220.90 hectares) and a 6% reduction in natural forest cover (5965 ± 353.72 hectares). Sparse vegetation, including smallholder farms, decreased by 35% from 45,064 ± 163.79 hectares to 29,424 ± 114.81 hectares. Projections for 2030 and 2040 indicate minimal changes based on current trends; however, they do not consider potential impacts from climate change, large-scale development projects, and demographic shifts, necessitating cautious interpretation. The results highlight areas of stability and vulnerability within the understudied GAP region, offering critical insights for developing targeted conservation strategies. Additionally, the methodological framework, which combines optical, radar, and topographical data with machine learning, provides a robust approach for accurate and detailed landscape-scale monitoring of tropical peatlands that is applicable to other regions facing similar environmental challenges.

Belite–ye’elimite–ferrite cements produced from London Clay

London Clay (LC) is generated in significant quantities from major infrastructure development projects within and around London, UK. Excavated LC spoils are typically landfilled or used for landscaping purposes with minimal value. This study investigates the feasibility of producing belite–ye’elimite–ferrite (BYF) cements using LC in combination with kaolin or low-grade bauxite. Six cement clinkers with varying compositions were synthesised at 1300°C. The phase composition of the synthesised clinkers was quantified using X-ray diffraction analysis (XRD) coupled with Rietveld refinement. The hydration behaviour, phase assemblage evolution and mechanical performance of the cements were examined using isothermal calorimetry, XRD, thermogravimetric analysis and compressive strength testing, respectively, up to 90 days of curing. It is demonstrated that LC can be used either on its own or with kaolin or low-grade bauxite to produce BYF cements with a wide range of composition: 31 to 64 wt% belite, 9.3 to 27 wt% ye’elimite and 2.1 to 31 wt% ferrite. The use of LC as the sole alumina source resulted in low compressive strength at early stages. Nevertheless, the strength developed over time, reaching 27.8 MPa at 90 days (0.5 w/b). Possible approaches to develop LC further for producing viable BYF cements are discussed.

Building Information Modeling Applications in Civil Infrastructure: A Bibliometric Analysis from 2020 to 2024

Building Information Modeling (BIM) has emerged as a transformative technology in the Architecture, Engineering, and Construction (AEC) industry, with increasing application in civil infrastructure projects. This study comprehensively reviews the research landscape of BIM applications in civil infrastructure through bibliometric analysis. Based on data from the Web of Science database, 646 relevant papers published between 2020 and 2024 were collected, and 416 papers were selected for in-depth analysis after screening. Using bibliometric methods, the analysis reveals the evolution of research trends, identifies key contributors and influential publications, and maps the knowledge structure of the field. Our study shows a significant increase in research output over the past five years, particularly in studies focusing on the integration of BIM with emerging technologies such as Digital Twins, the Internet of Things (IoT), and Machine Learning. The results indicate that the United States, China, and the United Kingdom lead in terms of research output and citation impact. Additionally, based on clustering results and representative keywords, several key research clusters were identified, including BIM in infrastructure lifecycle management, BIM collaboration in large-scale projects, and BIM for sustainable infrastructure design.

Sailing along the global tobacco supply chain: public health insights of innovative database project

Abstract Background Tobacco control commonly focuses on reducing tobacco demand rather than tobacco supply. This paper presents findings from a major four-year project on the tobacco supply chain. Transnational Tobacco and Leaf Companies (TTLCs) and other tobacco supply chain companies argue that provision of livelihoods, exports and corporate social responsibility (CSR) exonerates tobacco. Our objective was to consider these claims. Methods This paper presents the results of three studies: a literature review and two analyses of data from the innovative Tobacco Supply Chain Database (TSCD). Study 1: A scoping review of academic literature (n = 124 papers) reviewing how the tobacco supply chain embeds the tobacco industry as a development actor. Study 2: The statistical association between countries hosting TTLC subsidiaries (TSCD) and TTLC interference in health policy (Global Tobacco Industry Interference Index) was analysed (n = 76 countries). Study 3: Document and website analysis of TSCD non-TTLC tobacco supply chain companies comparing descriptions of CSR and tobacco supply chain involvement (n = 80 companies). Results Study 1: Although there are instances of advantages of involvement in the tobacco supply chain, TTLCs tends to be associated with declines in tobacco workers’ income, equality, quality of life (cultural and health and wellbeing) and nations’ environment and economy. Study 2: Countries that hosted more TTLCs had more policy interference (farming subsidiaries p=.046, tobacco product manufacturing subsidiaries p=.008). Study 3: Non-TTLC companies often lack transparency regarding their connection to tobacco. For example, 68% linked to CSR activity on their homepage whereas only 16% linked to involvement in the tobacco supply chain. Conclusions Tobacco supply chain involvement is detrimental to public health, the environment and governance. Countries and companies should seek to extricate themselves from the tobacco supply chain. Key messages • Tobacco supply chain involvement weakens public health governance despite CSR activities. Lack of transparency on supply chain involvement by companies is thus a concern. • The new Tobacco Supply Chain Database illuminates previously hidden areas of the tobacco supply chain: the location of tobacco industry subsidiaries and presence of independent companies.

3DCellComposer - A Versatile Pipeline Utilizing 2D Cell Segmentation Methods for 3D Cell Segmentation.

Cell segmentation is crucial in bioimage informatics, as its accuracy directly impacts conclusions drawn from cellular analyses. While many approaches to 2D cell segmentation have been described, 3D cell segmentation has received much less attention. 3D segmentation faces significant challenges, including limited training data availability due to the difficulty of the task for human annotators, and inherent three-dimensional complexity. As a result, existing 3D cell segmentation methods often lack broad applicability across different imaging modalities. To address this, we developed a generalizable approach for using 2D cell segmentation methods to produce accurate 3D cell segmentations. We implemented this approach in 3DCellComposer, a versatile, open-source package that allows users to choose any existing 2D segmentation model appropriate for their tissue or cell type(s) without requiring any additional training. Importantly, we have enhanced our open source CellSegmentationEvaluator quality evaluation tool to support 3D images. It provides metrics that allow selection of the best approach for a given imaging source and modality, without the need for human annotations to assess performance. Using these metrics, we demonstrated that our approach produced high-quality 3D segmentations of tissue images, and that it could outperform an existing 3D segmentation method on the cell culture images with which it was trained. 3DCellComposer, when paired with well-trained 2D segmentation models, provides an important alternative to acquiring human-annotated 3D images for new sample types or imaging modalities and then training 3D segmentation models using them. It is expected to be of significant value for large scale projects such as the Human BioMolecular Atlas Program.

Photometric redshift estimation for CSST survey with LSTM neural networks

ABSTRACT Accurate estimation of photometric redshifts (photo-zs) is crucial for cosmological surveys. Various methods have been developed for this purpose, such as template fitting methods and machine learning techniques, each with its own applications, advantages, and limitations. In this study, we propose a new approach that utilizes a deep learning model based on recurrent neural networks with long short-term memory (LSTM) to predict photo-z. Unlike many existing machine learning models, our method requires only flux measurements from different observed filters as input. The model can automatically learn the complex relationships between the flux data across different wavelengths, eliminating the need for manually extracted or derived input features, thereby providing precise photo-z estimates. The effectiveness of our proposed model is evaluated using simulated data from the Chinese Space Station Telescope (CSST) sourced from the Hubble Space Telescope Advanced Camera for Surveys (HST-ACS) and the COSMOS catalogue, considering anticipated instrument effects of the future CSST. Results from experiments demonstrate that our LSTM model, compared to commonly used template fitting and machine learning approaches, requires minimal input parameters and achieves high precision in photo-z estimation. For instance, when trained on the same data set and provided only with photometric fluxes as input features, the proposed LSTM model yields one-third of the outliers $f_{\mathrm{out}}$ observed with a multi-layer perceptron neural network (MLP) model, while the normalized median absolute deviation $\rm \sigma _{NMAD}$ is only two-thirds that of the MLP model. This study presents a novel approach to accurately estimate photo-zs of galaxies using photometric data from large-scale survey projects.

Effect of Outpatient Pooling Scheme on the Medical Costs of Patients with Chronic Diseases -- Based on Multi-period DID Modeling

The establishment of a sound mechanism for covering outpatient medical bills under the basic medical insurance for urban employees is one of the major livelihood projects to deepen the reform of China's medical security system. This study utilizes the China Health and Retirement Longitudinal Study (CHARLS), combines the interview data from four periods from 2011 to 2018, empirically analyzes the impact of the outpatient pooling scheme on the total outpatient costs and personal burden of patients with chronic diseases by using a multi-period double-difference model and further validates it by using the double-difference propensity score matching method (PSM-DID). The results show that the implementation of the outpatient pooling scheme is conducive to reducing the healthcare burden of chronically ill patients. Although the outpatient co-ordination did not have a significant impact on the reduction of outpatient costs for patients with chronic diseases, it significantly reduced the self-treatment costs of patients with chronic diseases. Further research found that the policy had a greater impact on chronic disease patients with poorer health. Combined with the results of the study, this paper suggests gradually eliminating the differences in basic policy treatment between regions, guaranteeing the level of outpatient treatment for insured patients in different places, and promoting better utilization of the outpatient co-ordination policy effect.

Work-Related Stress and Coping: A Comparative Analysis of On-Site and Office-Based Workers in UK Building Construction.

There are increasing mental health concerns in the construction industry workforce, with stress being a primary concern. This qualitative study investigates stress experiences and the management of stress in office-based and on-site workers in the UK building construction sector. This study can provide key insights for construction, but also potentially other industries which struggle with high stress levels among their employees. A total of 40 semi-structured interviews (20 on-site/20 office-based) were conducted at large-scale building construction projects in the southeast UK. Framework method analysis was used to derive an understanding of stress in the workplace and coping strategies. The study identified two major themes: the negative influence of work stress on personal and professional wellbeing, and the management of stress through proactive and reactive coping strategies. Results indicated that on-site workers frequently cited high workloads, tight deadlines, and safety concerns, whereas office-based workers tended to highlight job complexity and organisational pressures. Both population sub-groups reported stress affecting their work performance, with site-workers having the added concern of physical health and safety. Coping strategies among workers tended to rely on support networks, outside-the-workplace hobbies, and boundary-setting, among others. Stress remains a significant problem in the workplace and affects wellbeing; however, there are ways to mitigate the stress. Our findings could provide a foundation for intervention development.

SCARCE RESOURCES, GREAT CHALLENGE: CENTRAL ASIA'S WATER CRISIS AND ENVIRONMENTAL SUSTAINABILITY

Central Asia has limited water resources and increasing pressure on these resources. Large-scale irrigation projects initiated during the Soviet Union led to the over-exploitation of the Amu Darya and Sir Darya rivers and the dramatic drying up of Lake Aral. This process has caused extensive damage to the ecosystem, declines in agricultural productivity and serious problems in human health. The article analyses the historical origins and the current state of the water crisis in the region and examines the challenges of water resources management and sustainability efforts. It will also emphasise the importance of regional cooperation and modern water management policies. Central Asia's water crisis is not only an environmental problem but also a social and economic challenge. In this context, sustainable water management strategies are vital for the region to achieve its long-term development goals. Türkiye’s cooperation with the Central Asian states in this regard and transferring experience to them will contribute to the regional states' confidence in Türkiye and increase Türkiye’s prestige in the international arena. The article will use the Russian, English, Turkish and Uzbek source search method.

Incorporating translanguaging in English instruction: teachers’ beliefs, practices, and influencing factors

ABSTRACT The question of whether and to what extent should the learners’ language repertoire (LR) be incorporated into the teaching of English as an additional language has been controversial for decades. The findings reported in this paper are part of a large-scale research project funded by the Israeli Ministry of Education aiming to introduce a new multilingual education policy. This study investigates teachers’ beliefs and reported practices on the use of their learners’ LR in the teaching of English as an additional language. The background and contextual factors associated with teachers’ use of their learners’ LR were examined as well. Utilizing a mixed methods approach, data sources included online questionnaires (N = 253) distributed to EFL teachers, semi-structured interviews (N = 56), and focus groups (N = 5) with teachers and stakeholders (e.g. inspectors, counselors). The findings revealed two contradictory beliefs intertwined with teachers’ reported practices: a monolingual paradigm and a bi/multilingual perspective. Differences in teachers’ beliefs and reported practices were identified as a function of factors related to the teachers’ background, their role, and contextual factors related to the school setting. Implications for language teacher-training programs in contexts where English is taught as an additional language are also discussed.

A coupled scaled boundary finite element and phase-field algorithm for seismic loading

Seismic-induced damage, integral to the safety evaluations of major engineering projects, persists as a key focus of research worldwide. Based on the Scaled Boundary Finite Element Method (SBFEM) and the Phase-Field Method (PFM), a coupled algorithm tailored for reciprocal loading was introduced in this paper, integrating strategies including "closure constraints," "numerical threshold strategy," and "subdomain block integration." Adopting object-oriented principles, a universal coupling solution framework has been built and seamlessly embedded within GEODYNA, a self-developed finite element software system. The accuracy was validated through rigorous benchmark tests. The entire process of crack initiation, propagation, and dynamic opening-closing cycles in the Koyna concrete gravity dam was reproduced. Furthermore, the effect of mesh size and computational timestep on the structural seismic response, crack localization, and the extent of damage in the dam were explored. The outcomes demonstrated that the SBFEM-PFM coupling algorithm performs effectively and meets the engineering precision criteria for seismic evaluations and reinforcement analyses of crucial structures.

Green upgrading of SPring-8 to produce stable, ultrabrilliant hard X-ray beams.

SPring-8-II is a major upgrade project of SPring-8 that was inaugurated in October 1997 as a third-generation synchrotron radiation light source. This upgrade project aims to achieve three goals simultaneously: achievement of excellent light source performance, refurbishment of aged systems, and significant reduction in power consumption for the entire facility. A small emittance of 50 pm rad will be achieved by (1) replacing the existing double-bend lattice structure with a five-bend achromat one, (2) lowering the stored beam energy from 8 to 6 GeV, (3) increasing the horizontal damping partition number from 1to 1.3, and (4) enhancing horizontal radiation damping by installing damping wigglers in long straight sections. The use of short-period in-vacuum undulators allows ultrabrilliant X-rays to be provided while keeping a high-energy spectral range even at the reduced electron-beam energy of 6 GeV. To reduce power consumption, the dedicated, aged injector system has been shut down and the high-performance linear accelerator of SACLA, a compact X-ray free-electron laser (XFEL) facility, is used as the injector of the ring in a time-shared manner. This allows the simultaneous operation of XFEL experiments at SACLA and full/top-up injection of the electron beam into the ring. This paper overviews the concept of the SPring-8-II project, the system design of the light source and the details of the accelerator component design.

SEGUID v2: Extending SEGUID checksums for circular, linear, single- and double-stranded biological sequences.

Synthetic biology involves combining different DNA fragments, each containing functional biological parts, to address specific problems. Fundamental gene-function research often requires cloning and propagating DNA fragments, such as those from the iGEM Parts Registry or Addgene, typically distributed as circular plasmids.Addgene's repository alone offers around 150,000 plasmids. To ensure data integrity, cryptographic checksums can be calculated for the sequences. Each sequence has a unique checksum, making checksums useful for validation and quick lookups of associated annotations. For example, the SEGUID checksum, uniquely identifies protein sequences with a 27-character string. The original SEGUID, while effective for protein sequences and single-stranded DNA (ssDNA), is not suitable for circular and double-stranded DNA (dsDNA) due to topological differences. Challenges include how to uniquely represent linear dsDNA, circular ssDNA, and circular dsDNA. To meet these needs, we propose SEGUID v2, which extends the original SEGUID to handle additional types of sequences. SEGUID v2 produces orientation and rotation invariant checksums for single-stranded, double-stranded, possibly staggered, linear, and circular DNA and RNA sequences. Customizable alphabets allow for other types of sequences. In contrast to the original SEGUID, which uses Base64, SEGUID v2 uses Base64url to encode the SHA-1 hash. This ensures SEGUID v2 checksums can be used as-is in filenames, regardless of platform, and in URLs, with minimal friction. SEGUID v2 is readily available for major programming languages, distributed under the MIT license. JavaScript package seguid is available on npm, Python package seguid on PyPi, R package seguid on CRAN, and a Tcl script on GitHub. These tools, along with documentation, examples, and an online SEGUID Calculator , can be found at https://www.seguid.org .

Working for the Workers? Infonavit’s Creation and Its Foundational Motivations, 1972-1976

As Mexican society urbanized rapidly from 1950 to 1970, housing became a major issue for city inhabitants. This article contributes a specific focus on Infonavit as a major social housing project of the Mexican government. I argue that the Echeverría government created Infonavit in 1972 as one of its social welfare packages for three key reasons: (1) to rejuvenate the PRI’s claim to revolutionary legitimacy, (2) to resolve the perceived ills of mass urbanization and to create ideal urban citizens, and (3) to support economic development. However, I also demonstrate that Infonavit operated as an institution with a core interest in improving the conditions of Mexican workers that was also informed by the goal of creating ideal citizens. Although the politics of Infonavit’s creation was closely linked with PRI legitimacy, Infonavit staff built an institute that was motivated to serve the housing needs of low-income Mexican workers.