Browse Articles

Biochromatic potential of Pseudomonas aeruginosa from grapes: molecular profiling, antimicrobial action and eco-friendly dye applications

Author Correction: Cyclododecane-based high-intactness and clean transfer method for fabricating suspended two-dimensional materials

Stack-based static WebAssembly binary slicing and mutation for generating valid sub-binaries

Abstract WebAssembly is a low-level binary format originally designed to enable high-performance applications to run in web browsers. As WebAssembly is increasingly being ported to various environments, the security verification of WebAssembly execution environments is becoming more critical. While a wide variety of WebAssembly binaries is required to verify these environments, collecting binaries from the wild poses clear limitations. To meet this demand, techniques for automatically generating WebAssembly binaries are necessary. However, automatic generation of WebAssembly binaries must consider not only syntactic validity but also the potential lack of diversity in the generated binaries. To overcome these challenges, this paper proposes a series of algorithms for generating valid and semantically rich sub-binaries from a given base WebAssembly binary. First, closure slices are extracted from the base WebAssembly binary using static program slicing. Then, a stack balance correction algorithm is applied to the closure slices to construct syntactically complete functions. Finally, the generated functions are assembled into a complete WebAssembly binary, and instruction-level mutation is applied to introduce diversity. Several experiments were designed to demonstrate the effectiveness and efficiency of these algorithms, and the evaluation results showed that the proposed algorithms are highly promising in generating sub-binaries.

Trivalent titanium in high-titanium lunar ilmenite

Assessing sustainable development and environmental pollution dynamics in Somalia

Graphene-inspired porous polymer network for ethane/ethylene separation and methane purification

Enhanced control of continuous stirred tank reactor with two-degree-of-freedom PID driven by Kirchhoff’s law algorithm

Abstract This study examines the use of Kirchhoff’s law algorithm (KLA) to calibrate a two-degree-of-freedom PID (2DOF-PID) controller for temperature regulation in a non-linear continuous stirred tank reactor (CSTR). The reactor model shows strong thermal nonlinearity. It also shows a noticeable time delay. This is based on the coupled mass and energy balance equations. This makes accurate temperature control much more difficult. These effects were addressed by KLA, which is formulated as a physics-based optimization method rather than a learning or data-driven method. The algorithm produced a set of controller gains that yielded faster, more stable responses by treating the current–voltage equilibrium of electrical circuits as an energy-balanced search method. The optimally tuned 2DOF-PID controller has lower rise and settling times, and minimal steady-state error, compared with the other standard optimizers tested in an identical manner. The results show that combining KLA with controller design can improve both robustness and control accuracy for non-linear thermal systems.

Programmable multiscale energy release in synergistic energetic composites with three dimensional printed architectures

Advancing plant disease classification using an attention-based CNN for intra-dataset and cross- dataset training

Abstract The precise classification of plant diseases is crucial for ensuring food security for all people and boosting agricultural productivity. Although there has been significant progress in this field using deep learning approaches, cross-dataset training hasn’t drawn as much attention from researchers as intra-dataset training has. Moreover, very few models have successfully blended intra-dataset and cross-dataset training approaches. This paper proposes a novel attention-based Convolutional Neural Network (CNN) to overcome these limitations. The model improves feature extraction and classification accuracy across multiple datasets by using attention mechanisms. It was tested on five datasets (Digipathos, Northern Leaf Blight (NLB), PlantVillage, PlantDoc, and the CD&S dataset) that covered leaf diseases of both corn and potatoes. During intra-dataset training, the model achieved the highest classification accuracy of 99.38% when trained on images of potato leaves from the PlantVillage dataset. During cross-dataset training, the model exhibited the highest average classification accuracy of 82.93% for corn leaf diseases when trained on images from the CD&S dataset with their backgrounds removed. When compared to the techniques taken into consideration in this study under comparable experimental conditions, the results demonstrate improved performance. This study shows how the model may be flexible for both intra- and cross-datasets, offering a flexible way to categorize diseases that affect plants. Because of its ability to generalize across different datasets, it may be helpful in real-world agricultural applications with a wide variety of image quality and situations. This encourages the advancement of precision farming techniques and disease control.

Photolytic oxidation of ammonium chloride as a source of Cl2 in the atmosphere

Epidemiology and cardiometabolic care in adults with ASCVD and high 10-year ASCVD risk: 2021 WHO STEPS study in Iran

Abstract Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of mortality and health burden worldwide. We aimed to assess ASCVD epidemiology, 10-year risk, and cardiometabolic care using nationally representative data in Iran. Using the 2021 Iran STEPS study, a cross-sectional analysis was conducted to evaluate ASCVD (self-reported myocardial infarction, angina, revascularization, or stroke) prevalence and annual event rate. The 2013 AHA/ACC pooled cohort equations estimated 10-year ASCVD risk in 10,298 participants aged 40–75 without ASCVD. Cardiometabolic care for hypertension, diabetes mellitus (DM), and hypercholesterolemia was assessed, along with statin use and cardiovascular health (CVH) metrics. Among 27,822 participants, representing 57.5 million adults, ASCVD prevalence was 7.4%. Among those without ASCVD, 19.1% had an intermediate and 5.4% had a high ASCVD risk. In the ASCVD group, hypertension and DM affected 77.0% and 34.7%, yet only 12.5% and 14.3% of the entire ASCVD group had them controlled, respectively. In adults without ASCVD, 2.9–5.3% of the entire risk groups achieved hypertension targets, 2.5–16.8% achieved glycemic targets, and 7.7–16.7% achieved lipid goals, despite condition prevalence spanning 47.4–94.4% for hypertension, 7.2–59.3% for DM, and 33.5–48.7% for hypercholesterolemia. CVH metrics were also unfavorable. The study revealed a high ASCVD burden and future risks with gaps in coverage, treatment, and control.

Pathways to cost-optimal and net-zero emissions irrigation in the United States

Comparative genomics and biocontrol potential of five Bacillus strains isolated from grapevine rhizosphere

Eco-sustainable magnetoresistive sensors towards disposable magnetoelectronics

Abstract This work presents a holistic integration of environmental sustainability and enhanced sensing performance throughout the full lifecycle of magnetoresistive sensors. Utilizing industry-scale screen-printing techniques combined with eco-friendly inks (formulated from engineered Fe/Fe 3 O 4 core-shell magnetic microparticles, bioderived polymeric binders, and water solvent), the fabrication process avoids harsh treatments and hazardous chemicals. The resulting sensors, constructed entirely from naturally sourced materials, inherently exhibit biocompatibility, biodegradability, and environmentally benign recyclability. These properties collectively demonstrate key attributes for a sustainable life cycle. Through rational engineering of the Fe/Fe 3 O 4 core-shell structure particles, two synergistic mechanisms are activated within the composite: spin-dependent hopping across Fe 3 O 4 shell grain boundaries and in situ magnetic flux concentration induced by Fe cores, thereby yielding an order-of-magnitude enhancement in low-field sensitivity relative to sputtered Fe film and printed Fe 3 O 4 particle-based counterparts, resulting in a higher magnetoresistance ratio at 10 mT relative to all printed magnetoresistive sensors reported previously. The convergence of eco-sustainability and high performance enables previously unattainable disposable magnetoelectronics, unlocking new opportunities for environmentally responsible and user-safe transient electronics and Internet of Things (IoT) applications.

Ligand Confinement for Fast‐Decay Cu─I Chain Scintillators Enabling High‐Resolution X‐ray Imaging and 3D Tomography

ABSTRACT Chain‐like one‐dimensional (1D) copper(I) iodide cluster complexes are promising scintillator candidates due to their enhanced x‐ray absorption, robust frameworks, and excellent photostability. However, their emission efficiencies remain significantly lower than those of zero‐dimensional analogues. Herein, we propose a ligand‐confinement strategy that employs sterically hindered, electronically tuned pyrimidine‐based bridging ligands to simultaneously boost x‐ray excited luminescence (XEL) and accelerate decay dynamics in 1D Cu–I cluster scintillators. Rigid, compact bidentate ligands increase structural rigidity while reducing the organic fraction for enhanced x‐ray absorption. Meanwhile, asymmetric substituents induce coupled spatial and electronic confinement, giving rise to quantum‐wire‐like electronic states that promote radiative transitions. As a result, CuI(4‐Mepym) exhibits a six‐fold enhancement in photoluminescence quantum yield compared to CuI(2‐Mepym) , together with a fast decay lifetime of 1.28 µs, surpassing most reported copper(I) iodide cluster complexes. Combined with high stability, good solution processability, and a light yield comparable to commercial LuAG:Ce (∼25 000 ph MeV −1 ), CuI(4‐Mepym) breaks the conventional brightness–speed trade‐off and enables high‐resolution static imaging (>20 lp mm −1 ), artifact‐free dynamic x‐ray imaging, and high‐fidelity 3D tomography. This work establishes ligand confinement as an effective design principle for developing high‐brightness, fast‐decay 1D Cu–I cluster scintillators for advanced x‐ray imaging applications.

Differential miRNA expression during replicative senescence of dental pulp stem cells with potential for forensic age assessment

Thermosensory reconfiguration of the auxin transcriptional pathway to drive root cell growth

Addressing gaps in cancer cachexia care among healthcare professionals at Uganda Cancer Institute

Structural dynamics of the midnolin-proteasome during ubiquitin-independent substrate turnover

Highly Sensitive All‐Polymer Short‐Wavelength Infrared Photodetectors for Complementary Metal Oxide Semiconductor Integrated Imaging Enabled by Dual‐Acceptor n‐Type Polymers

ABSTRACT Short‐wavelength infrared (SWIR) organic photodetectors (OPDs), particularly all‐polymer ones, hold substantial commercial promise in vital monitoring and imaging. However, the development of all‐polymer SWIR OPDs has been limited by the lack of high‐performance n‐type ultralow‐bandgap polymer semiconductors. Herein, we report two dual‐acceptor polymers (ThDPP‐CNBTz and ThDPP‐CNBSz), with dicyano‐benzothiadiazole/benzoselenidazole as strong acceptor units, diketopyrrolopyrrole as a sub‐strong acceptor unit, and thiophene as a donor moiety. Both polymers possess ultralow optical bandgaps and deep HOMO/LUMO, making them ideal acceptor materials for all‐polymer SWIR OPDs. Owing to more efficient charge generation and transport, ThDPP‐CNBTz‐based all‐polymer OPDs show superior responsivity ≥0.150 A W −1 from 780 to 1060 nm. The ThDPP‐CNBSz‐based OPDs show lower noise currents, attributed to the larger thermal activation energy of dark current and lower trap density. As a result, ThDPP‐CNBTz‐ and ThDPP‐CNBSz‐based OPDs deliver similar specific detectivity, exceeding 10 12 Jones in the spectral range of 780–1140 nm and 350–1240 nm, respectively. Furthermore, ThDPP‐CNBTz‐based stretchable OPDs show a small performance attenuation after 1000 cycles of stretching at 20% strain, heralding potential application in wearable vital monitoring. By monolithically integrating PDPP‐3T:ThDPP‐CNBTz‐based OPDs with silicon‐based readout integrated circuits, high‐resolution imaging has also been demonstrated for infrared penetration and material discrimination.