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A machine learning assisted truncated adaptive EWMA chart for robust process monitoring

Revealing tattoo traditions in ancient Nubia through multispectral imaging

Evidence for tattooing in ancient Nubia is long-standing, although no systematic studies have compared application techniques, motifs, and the demography of tattooed individuals. We surveyed 1,048 Meroitic to medieval (c. 350 BCE–1400 CE) human remains from Semna South (n = 589), Kulubnarti (n = 406), and the Qinifab School site (n = 53). We recorded where skin preservation was sufficient for tattoo observation and used multispectral imaging methods to identify motifs and application techniques. We documented tattooing in 27 individuals of both sexes, ranging from infants to older adults. A shift in both motifs and methods used is apparent in the medieval Christian period. With at least 19% of Kulubnarti individuals displaying tattoos, this investigation demonstrates the importance of systematic surveys to detect tattooing and illuminate varying practices over time.

Sustainable engineering of fiber-reinforced geopolymer-treated low plasticity clay linking geomechanics and microstructure through support vector machines

Carbon uptake dynamics of cement-based materials: Linking market structure, material use, and the carbon cycle

Cement-based products sequester CO 2 in the atmosphere throughout their life cycle. The extent of sequestration highly depends on the context. We implement a bottom–up model of different cement end-use applications (buildings, pavements, bridges, pipelines, and other infrastructure) in the United States and Mexico to estimate the in-use and end-of-life carbon uptake in cement. We show that carbon uptake in 2024 could sequester approximately 13% of process emissions associated with cement consumption, which is around 6.7 Mt CO 2 . We observe a four-fold variation in the uptake per square area across all the states due to regional differences in the distribution of building types, concrete mix designs, and climates. The building sector uptake is almost twice as large as infrastructure systems. In Mexico, the current stock of cement-based products sequesters around one-quarter of the industry’s annual process emissions, implying the importance of local differences in end-use context, which can dramatically alter the extent of carbon uptake. Where prudent, enhancing carbon uptake in cement-based products is a valuable strategy to move toward carbon neutrality in the construction sector. The findings in this paper provide a fundamental shift in understanding how anthropogenic materials interact with the carbon cycle, which changes how national greenhouse gas inventories are calculated.

Blockchain and digital twin integration for predictive and secure pandemic alerting

Rapid morphological change in an urban bird due to COVID-19 restrictions

The COVID-19 pandemic provided a natural experiment to test the impacts of human activity on urban-dwelling wildlife. Urban dark-eyed juncos differ in bill shape and size in Los Angeles in comparison to local wildlands. We measured juncos that hatched before, during, and after COVID-19 restrictions at a Los Angeles college campus. Birds that hatched during and soon after COVID-19 restrictions had bills that resembled those of local wildland birds. Yet, bills rapidly returned to pre-COVID-19 morphology in birds hatched in the years following pandemic restrictions. Thus, human activity (and lack thereof) underlies rapid morphological change in an urban bird.

Biological evaluation of chelated trace minerals with multi-strain probiotics and enzymes on production performance of broiler chickens

Cortical tracking of sign language: The role of language knowledge in tracking of different articulators

In sign languages, linguistic information is transmitted through the simultaneous movement of several bodily articulators. This study investigates cortical tracking of sign language and whether experience and knowledge of sign language can modulate the tracking. We used a camera with a depth sensor to record videos of semispontaneous sign language narratives while tracking articulators’ movement in 3D space. These videos served to characterize the temporal periodicity of the sign language visual signal and as stimuli for the experiment. Using magnetoencephalography (MEG), we recorded the neurophysiological activity of two groups of hearing participants—proficient signers and sign-naive individuals—while they watched videos in a known and unknown sign language. Coherence between the preprocessed MEG data and the visual linguistic signal extracted from different articulators was used as measure of brain-language tracking. The results show that neural activity tracks sign language input in delta frequency band (0.5 to 2.5 Hz), reflecting the slower periodicity associated with articulator movements. Both groups of participants show similar tracking in occipital areas, reflecting low-level visual processing of the videos. Proficient signers show stronger synchronization compared to sign-naive controls for linguistically relevant articulators in the right temporal cortex. Proficient signers also show greater tracking for the known compared to the unknown sign language. These findings confirm that cortical tracking of language is a feature of language processing beyond the auditory domain, and is modulated by language experience.

A novel delay-affected two degree of freedom PID controller using physics-inspired optimization for robust control applications

CHARGE-MAP: An integrated framework to study the multicriteria EV charging infrastructure expansion problem

The widespread adoption of electric vehicles (EVs) in recent years has necessitated the development of effective charging infrastructures. However, charging infrastructure expansion is a multifaceted problem that requires careful consideration of the existing infrastructure, spatiotemporal distribution of charging demands, power-grid capacity, and budget constraints. To approach this complex problem, we present charge-map , a data-driven simulation-optimization framework, focused on ensuring meaningful charging experience for individual EV owners. charge-map integrates three modules: an agent-based simulation module that estimates spatiotemporal distribution of charging demands by modeling EV adopter mobility and charging behavior; an optimization module that determines optimal new charging station/charger locations and capacities, while minimizing expected detour distances and wait-times with a limited number of new stations; and a power module that determines how to connect the stations to the power grid while maintaining its stability. Using the state of Virginia (consisting of 95 counties and 38 independent cities) as a case study, our results show that charge-map can meet the demand of ∼ 198,600 predicted EVs with 1,305 new public charging stations and 2,164 new chargers. It reduces average detour distances for charging by 66% and wait-times at stations by 72% compared to the existing infrastructure. Furthermore, transformer capacity requirement analysis reveals that only 1.8% of residential transformers require upgrades, while over 80% of commercial charging locations can be supported with modest transformer infrastructure (25 to 50 kVA). This indicates that targeted investments can facilitate cost-effective EV integration. Consequently, charge-map provides policymakers and urban planners with crucial data-driven insights for effective EV charging infrastructure expansion.

Modelling, analysis, and stability assessment of wind turbine generator connected to a low inertia AC-DC microgrid with frequency support capability

Abstract Recently, the integration of renewable energy sources and the development of hybrid AC-DC grids have become increasingly noticeable. Such modern power systems with high penetration of converter-based power sources face many challenges, such as the reduction in the overall system inertia. One of the popular methods to enhance the system’s inertia is to utilize the energy stored in the rotors of wind turbine generators. Although many researchers have proposed effective strategies to address this problem. However, interaction dynamics that might arise between the connected components in a low-inertia AC/DC grid, considering the detailed modelling of each component, are not comprehensively addressed. Therefore, this paper presents a detailed modelling of a typical low-inertia AC/DC grid with frequency support capability offered by a wind generator. The overall system stability is evaluated with the help of the entire system state-space model. Additionally, the influence of varying system parameters on system dominant poles is analyzed to evaluate system stability margins. The study findings are justified through time-domain nonlinear simulations.

Interstep compatibility of a model for the prebiotic synthesis of RNA consistent with Hadean natural history

Models for prebiotic syntheses often have many steps, each separately validated by laboratory experiments. The challenge then asks whether these steps work together in natural geological environments, absent human intervention. Here, we analyze a six-step Discontinuous Synthesis Model (DSM) for the prebiotic formation of RNA, proposed to be the first informational molecule to support Darwinian evolution, and life, on Earth and/or Mars. DSM requires that borate in multiple steps guide the formation of pentoses from simple carbohydrates and control phosphorylation, in all cases by binding adjacent HO-groups on key intermediates. However, adjacent HO-groups must react in two other steps, which borate might inhibit. Experiments here show that borate does not inhibit these two other steps, but rather facilitates them. This makes the six-step DSM a “no human intervention” route from simple precursors (1 to 3 carbons, 0 to 2 nitrogens) to oligomeric RNA with predominately 3’,5’-linkages at least 6 nucleotides long, but possibly much longer. The process i) exploits privileged chemistry in ii) intermittently irrigated aquifers constrained by basalt that iii) have borate iv) above a redox-neutral mantle v) having access to an atmosphere transiently reduced by a Vesta-sized impactor. In a possible coincidence, such an impact occurred most likely ca. 4.3 billion years ago (Ga), ~100 Mya before some molecular clocks date the divergence of the three kingdoms of life on Earth (4.2 Ga), and ca. 200 Mya before isotopically “light” carbon is reported in zircons dated at 4.1 Ga. This carbon may be the oldest trace of life ever proposed.

DFT-guided photostable chitosan-derived carbon quantum dots as colloidal antibacterial and bioimaging agents

Revealing the risk of macroplastic ingestion to marine wildlife

Fabrication of synergistic calix[4]arene–PVC–MWCNT–graphite films for fast and sustainable adsorption of dye pollution

Recruiting ESCRT to single-chain heterotrimer peptide MHCI releases antigen-presenting vesicles that stimulate T cells selectively

Immune cells naturally secrete extracellular antigen-presenting vesicles (APVs) displaying peptide:MHC complexes to facilitate the initiation, expansion, maintenance, or silencing of immune responses. Previous work has sought to manufacture and purify these vesicles for cell-free immunotherapies. In this study, APV assembly and release is achieved in nonimmune cells by transfecting a single-chain heterotrimer (SCT) peptide major histocompatibility complex I (pMHCI) construct containing an ESCRT- and ALIX-binding region (EABR) sequence appended to the cytoplasmic tail; this EABR sequence recruits ESCRT proteins to induce the budding of APVs displaying SCT pMHCI. A comparison of multiple pMHCI constructs shows that inducing the release of APVs by the addition of an EABR sequence generalizes across SCT pMHCI constructs. Purified pMHCI/EABR APVs selectively stimulate IFN-γ release from T cells presenting their cognate T cell receptor, demonstrating the potential use of these vesicles as a form of cell-free immunotherapy.

Developing a straightforward and robust approach for investigating reservoir compartmentalization based on chemical composition heterogeneities

The paradox of intervention: Resilience in adaptive multirole coordination networks

Complex adaptive networks exhibit remarkable resilience, driven by the dynamic interplay of structure (interactions) and function (state). While static-network analyses offer valuable insights, understanding how structure and function coevolve under external interventions is critical for explaining system-level adaptation. Using a unique dataset of clandestine criminal networks, we combine empirical observations with computational modeling to test the impact of various interventions on network adaptation. Our analysis examines how networks with specialized roles adapt and form emergent structures to optimize cost–benefit trade-offs. We find that emergent sparsely connected networks exhibit greater resilience, revealing a security–efficiency trade-off. Notably, interventions can trigger a “criminal opacity amplification” effect, where criminal activity increases despite reduced network visibility. While node isolation fragments networks, it strengthens remaining active ties. In contrast, increasing a node’s connectivity (analogous to social reintegration) can unintentionally boost criminal coordination, increasing activity or connectivity. Failed interventions often lead to temporary functional surges before reverting to baseline. Surprisingly, stimulating connectivity destabilizes networks. Effective interventions require precise calibration to node roles, connection types, and external conditions. These findings challenge conventional assumptions about connectivity and intervention efficacy in complex adaptive systems across diverse domains.

Micro aluminum-air batteries for extended operational duration of small-scale quadrotors

Dual-targeted ping-pong CAR T cells: Leveraging peripheral expansion to improve solid tumor immunotherapy

Clinical responses to CD19-directed CAR T cell therapy in B cell malignancies are strongly associated with robust CAR T cell expansion in the peripheral blood. In contrast, CAR T cells targeting solid tumors do not encounter cognate antigen in the periphery, resulting in limited expansion and subtherapeutic peak concentrations. To overcome this, we engineered dual-targeted and dual-costimulated CAR T cells (CD19/28ζ-M5BBζ) that recognize CD19+ B cells, thereby promoting peripheral expansion and increasing the pool of solid tumor-directed CAR T cells available for tumor infiltration without the need for lymphodepletion. In immunocompetent C57BL/6 mouse models of pancreatic ductal adenocarcinoma and melanoma, these dual-targeted CAR T cells demonstrated enhanced peripheral expansion, improved anti-tumor efficacy, and increased survival without added dysfunction or toxicity compared to single antigen-targeted CAR T cells. We translated our findings to human CAR T cells by developing a pancreatic/xenograft model with CD19 + B cells in the periphery and again demonstrated that treatment with dual CAR T cells showed significantly enhanced tumor clearance and survival compared to single antigen-targeted CAR T cells. In conclusion, we demonstrate that dual-targeted CAR T cells boost peripheral expansion, and anti-tumor efficacy, providing a strategy for enhancing outcomes for patients treated with clinical CAR T products targeting solid tumors.