McKinsey & Company (United States)

This study investigates the shear behavior of reinforced concrete diaphragms strengthened with externally bonded fiber-reinforced polymer (FRP) composites. Conventional diaphragm retrofits, such as concrete overlays, steel trusses, reinforced collectors, or additional shear walls, are often costly, time-consuming, and increase seismic mass. FRP retrofits offer a more efficient alternative with a high strength-to-weight ratio, chemical inertness, cost-effectiveness, and minimized downtime. This research aims to develop experimentally validated design guidance for FRP retrofits of reinforced concrete diaphragms to increase shear resistance. Six cantilever diaphragm specimens, approximately 2.6×3.0×0.1 m, were subjected to reversed cyclic loading. Five specimens were retrofitted to have additional shear strength using various FRP configurations, while one served as a baseline. The test results were compared to understand the effect of varying FRP parameters, e.g., composite modulus, coverage, sheet orientation, and FRP anchor layout, on response parameters such as stiffness, FRP strains, strength and ductility. All retrofitted specimens exhibited similar behavior up to a peak load that was on average 27% greater than the control specimen, with peak strength governed by FRP debonding initiated at diagonal shear cracks. Variations in composite modulus, sheet width, spacing, and anchorage did not affect response up to peak load, provided the retrofits maintained constant ply stiffness. End anchorage promoted load path redundancy after debonding, allowing sustained load levels after the peak. However, intermediate FRP anchors, while not significantly impacting peak shear strength, led to localized FRP rupture and reduced deformation capacity, suggesting that they should be designed to fail before the FRP sheet. Measured FRP strains at peak load were generally consistent with backcalculated values based on peak shear strength and averaged 20% higher than the design shear debonding strain from ACI PRC-440.2R.

Peptidecoassembly and self-assemblyare complex processes that enable the formation of intricate nanoscalestructures, facilitating the development of novel functional biomaterials.In this study, we explore stereocomplexation-driven enantiomeric coassembly,focusing on the distinctive structures of 'block heterochiral'peptides. Using the model amphipathic peptide KFE8 (FKFEFKFE), whichconsists of two FKFE blocks, we created homochiral peptides made ofrepeat units with the same chirality (LL and DD) or heterochiral variantswith opposite chirality units (LD and DL). We examined the pairwiseassembly behaviors of these identical peptides, which differ onlyin segmented stereoisomerization. We analyzed the nano-, micro-, andmacroscale properties of LL/LD, LL/DL, DD/LD, and DD/DL, each representingtwo equimolar stereoisomers mixed before solubilization ('premixed')to enable potential coassembly or self-sorting within a single, well-mixedmonomer phase. We also used 'postmixed systems', which wereassembled separately and combined only before data collection foreach technique (e.g., LL+LD) as controls. Our data show that homochiralor heterochiral peptide pairs with matching N-terminal chirality coassemble,while a mismatch in N-terminal chirality promotes self-sorting behavior.

Purpose:Glaucoma, a leading cause of irreversible vision loss, often remains undiagnosed due to its asymptomatic progression and the limitations of existing screening methods. This study aimed to validate an artificial intelligence machine learning algorithm for the camera-agnostic detection of glaucomatous optic neuropathy using macula-centered fundus images.Methods:Data were collected from EyePACS, a teleretinal screening system, comprising 25,000 macula-centered fundus images from 12,500 patients at U.S. primary care centers. A secondary dataset from the Philadelphia Telemedicine Glaucoma Follow-up Study was used for independent validation. A convolutional neural network was developed to detect glaucomatous optic neuropathy. Expert-graded fundus images served as the ground truth. Images underwent quality filtering to ensure the visibility of the optic nerve. Bilateral images were analyzed to produce patient-level diagnoses. Validation involved a secondary dataset of fundus images.Results:The sensitivity and specificity of the algorithm in detecting glaucomatous optic neuropathy is calculated in comparison to expert grading. From the EyePACS dataset, 21,792 images (10,986 subjects) met quality standards. The algorithm demonstrated a sensitivity of 90.6% and specificity of 90.5%. Validation on the secondary dataset (200 fundus images from 100 subjects) resulted in a sensitivity of 96.4% and specificity of 85.3%.Conclusions:The algorithm achieved high sensitivity and specificity in detecting glaucomatous optic neuropathy using macula-centered fundus images, demonstrating its potential for integration into diverse clinical settings. Its camera-agnostic design and robust performance offer a scalable solution for improving glaucoma screening pathways, making them more accessible and efficient.

The modelling of wildfire spread involves managing uncertainties from various sources, typically addressed through probabilistic rather than deterministic approaches. Natural random variability in the dynamics of the fire front can be directly captured by integrating stochastic noise into the fire front tracking model. To achieve this, a Gaussian noise is introduced into the level-set model using a stochastic level-set approach in the wildfire spread simulator “ spark ”. The incorporation of stochasticity into the fire spread model enables the simulation to capture variability in fire front growth. The model is calibrated and validated by comparing the stochastic fire spread simulations to observed fire data. The developed model is also compared to a specific case of fire spread simulation created using the Wildland-Urban Fire Dynamic Simulator ( wfds ). This comparative analysis provides a conclusive evaluation, highlighting the performance and capabilities of the stochastic approach in capturing the uncertainties and complexities of fire behavior.

In the Broadband Service Provider (BSP) industry, billing data can originate from various sources like customer subscriptions, payment platforms and network telemetry. The data is often imported using Comma Separated Values (CSV) file uploads from billing systems. To get the best outcome of the Software as a Service (SaaS) platform the data must be cleaned up and standardized prior to feeding to the product. The smallest error rate in billing data can lead to revenue leakage for a business. Poor data hygiene is a leading cause of billing system projects failing to meet their targets. BSPs cannot afford to have data management as a reactive measure anymore. Ensuring data quality before feeding into critical products is imperative for a successful business, however, the scope of such efforts is not always simple. Using automation for cleaning and restructuring of data with Extract, Transform and Load (ETL) tools ensures an effective and reliable methodology of data accuracy. Product adoption is as much reliant on operations and training, as it is on high accuracy in billing and network data. In modern broadband services, having healthy data is key to a strong foothold in the BSP market.

Private economic actors wield unprecedented influence over the enjoyment of human rights, yet legal systems remain uneven in their regulation of corporate responsibility. Against this backdrop, this article examines a largely underexplored post‐Brexit trajectory, the regulatory divergence in the implementation of the UN Guiding Principles on Business and Human Rights (UNGPs). While the broader effects of the withdrawal of the UK from the EU have been extensively scrutinised, little attention has been paid to how each jurisdiction has sought to prevent and mitigate corporate human rights abuses. Situating its analysis within the UNGP framework, the article offers a comparative examination of the EU emphasis on preventative regulation and the UK reliance on a largely minimalist adjudicative framework. It argues that the UK risks being shaped by external legal pressures while lacking a coherent domestic agenda. Northern Ireland, partially aligned with EU law, is presented both as an example of this fragmented approach to business and human rights regulation and as a hybrid space where the effects of ongoing regulatory developments might be traced and assessed. Ultimately, the analysis situates this divergence within a wider contest over the legitimacy of transnational human rights governance, where state apathy remains a critical but neglected factor in addressing corporate accountability.

Liquid Crystalline Nanoparticles In article number 2506077, Guoxing Liao, LinGe Wang, and co-workers prepared spherical liquid crystalline nanoparticles using a liquid crystalline polymer as the core-forming block during polymerization-induced self-assembly. Further analysis confirmed the straight main-chain conformation of the core-forming block, which exhibits unique birefringence as lyotropic liquid crystal behaviour in nanoparticle formations under polarized optical microscopy.

The East Siberian Sea–Chukchi Sea Prograded Margin (ESCPM) and the Makarov Oceanic Basin (MOB) include interconnected sedimentary accumulations with gradual facies transitions that occupy a significant part of the Amerasia Basin and the adjacent Siberian Arctic continental margin. The ESCPM contains a succession of Cenozoic clinothem featuring shelf-margin progradation caused by a rapid influx of siliciclastic material from NE Asia into the adjacent Amerasia Basin, and represents a single tectono-sedimentary element (TSE) as per the volume's terminology. The MOB is a most distant part of the Arctic Ocean and is isolated from continental depositional systems. It consists of two first-order sedimentary accumulations with distinct depositional styles and provenances. The lower, Passive Margin TSE is composed of a fragment of the presumably Paleozoic–Mesozoic Barents and North Kara passive continental margin. The upper, Synoceanic TSE was formed following the separation of the continental block of the Lomonosov Ridge from the Eurasian continental margin at c. 56 Ma and during the opening of the Eurasian Basin. It includes mostly Eocene–Holocene hemipelagic and pelagic deposits and ice-rafted sediments. Each of these accumulations is characterized as a TSE, and the MOB itself is considered as a composite TSE. Assessments of petroleum potential in both elements rely on regional geological constraints, sedimentary architecture and modelling. Direct hydrocarbon indicators have been detected in seismic profiles in both the ESCPM and the MOB. In the latter, petroleum generation is likely to have begun in the Jurassic or Late Cretaceous, peaking in the Paleocene and possibly extending into the Miocene. Reservoir rocks are inferred in Cretaceous and Cenozoic strata. In the ESCPM TSE, Paleocene–middle Eocene sedimentary successions are considered to include potential source rocks, associated with main flooding surfaces and clinothem bottomset deposits.