Search Results (147)

Heavy metal contamination in natural waters and soils poses a significant environmental challenge, necessitating efficient and sustainable water treatment solutions. This study presents the computational design of low-density polyethylene (LDPE) films functionalized with iron oxide (Fe₃O₄) nanoparticles (NPs) for enhanced water purification applications. Composite materials containing 5%, 10%, and 15% were synthesized and characterized in terms of adsorption efficiency, surface morphology, and reusability. Advanced molecular modeling using BIOVIA Pipeline was employed to investigate charge distribution, functional group behaviour, and atomic-scale interactions between polymer chains and metal ions. The computational results revealed structure–property relationships crucial for optimizing adsorption performance and understanding geochemically driven interaction mechanisms. The LDPE/Fe₃O₄ composites demonstrated significant removal efficiency of Cu²⁺ and Ni²⁺ ions, along with favourable mechanical properties and regeneration potential. These findings highlight the synergistic role of mineral–polymer interfaces in water remediation, presenting a scalable approach to designing multifunctional polymeric materials for environmental applications. This study contributes to the growing field of polymer-based adsorbents, reinforcing their value in sustainable water treatment technologies and environmental protection efforts. Full article

Background/Objectives: This case study presents the first documented use of a low-cost, simulated, patient-specific three-dimensional (3D) printed model to support presurgical planning for an infant with Apert syndrome in a resource-limited setting. The primary objectives are to (1) demonstrate the value of 3D printing as a simulation tool for preoperative planning in low-resource environments and (2) identify opportunities for future AI-enhanced simulation models in craniofacial surgical planning. Methods: High-resolution CT data were segmented using InVesalius 3, with mesh refinement performed in ANSYS SpaceClaim (version 2021). The cranial model was fabricated using fused deposition modeling (FDM) on a Creality Ender-3 printer with Acrylonitrile Butadiene Styrene (ABS) filament. Results: The resulting 3D-printed simulated model enabled the surgical team to assess cranial anatomy, simulate incision placement, and rehearse osteotomies. These steps contributed to a reduction in operative time and fewer complications during surgery. Conclusions: This case demonstrates the value of accessible 3D printing as a simulation tool in surgical planning within low-resource settings. Building on this success, the study highlights potential points for AI integration, such as automated image segmentation and model reconstruction, to increase efficiency and scalability in future 3D-printed simulation models. Full article

Graphene-based micro-ring modulators are promising candidates for next-generation optical interconnects, offering compact footprints, broadband operation, and CMOS compatibility. However, most demonstrations to date have relied on conventional straight bus coupling geometries, which limit design flexibility and require extremely small coupling gaps to reach critical coupling. This work presents a comprehensive comparative analysis of straight, bent, and racetrack bus geometries in graphene-on-silicon nitride (Si₃N₄) micro-ring modulators operating near 1.31 µm. Based on finite-difference time-domain simulation results, a proposed racetrack-based modulator structure demonstrates that extending the coupling region enables critical coupling at larger gaps—up to 300 nm—while preserving high modulation efficiency. With only 6–12% graphene coverage, this geometry achieves extinction ratios of up to 28 dB and supports electrical bandwidths approaching 90 GHz. Findings from this work highlight a new co-design framework for coupling geometry and graphene coverage, offering a pathway to high-speed and high-modulation-depth graphene photonic modulators suitable for scalable integration in next-generation photonic interconnects devices. Full article

Current temperature sensors require regular recalibration to maintain reliable temperature measurement. Photonic/quantum-based approaches have the potential to radically change the practice of thermometry through provision of in situ traceability, potentially through practical primary thermometry, without the need for sensor recalibration. This article gives an overview of the European Partnership in Metrology (EPM) project: Photonic and quantum sensors for practical integrated primary thermometry (PhoQuS-T), which aims to develop sensors based on photonic ring resonators and optomechanical resonators for robust, small-scale, integrated, and wide-range temperature measurement. The different phases of the project will be presented. The development of the integrated optical practical primary thermometer operating from 4 K to 500 K will be reached by a combination of different sensing techniques: with the optomechanical sensor, quantum thermometry below 10 K will provide a quantum reference for the optical noise thermometry (operating in the range 4 K to 300 K), whilst using the high-resolution photonic (ring resonator) sensor the temperature range to be extended from 80 K to 500 K. The important issues of robust fibre-to-chip coupling will be addressed, and application case studies of the developed sensors in ion-trap monitoring and quantum-based pressure standards will be discussed. Full article

The monolithic integration of III-V semiconductors with silicon (Si) is a critical step toward advancing optoelectronic and photonic devices. In this work, we present GaAs nanoheteroepitaxy (NHE) on Si nanotips using gas-source molecular beam epitaxy (GS-MBE). We discuss the selective growth of fully relaxed GaAs nanoislands on complementary metal oxide semiconductor (CMOS)-compatible Si(001) nanotip wafers. Nanotip wafers were fabricated using a state-of-the-art 0.13 μm SiGe Bipolar CMOS pilot line on 200 mm wafers. Our investigation focuses on understanding the influence of the growth conditions on the morphology, crystalline structure, and defect formation of the GaAs islands. The morphological, structural, and optical properties of the GaAs islands were characterized using scanning electron microscopy, high-resolution X-ray diffraction, and photoluminescence spectroscopy. For samples with less deposition, the GaAs islands exhibit a monomodal size distribution, with an average effective diameter ranging between 100 and 280 nm. These islands display four distinct facet orientations corresponding to the {001} planes. As the deposition increases, larger islands with multiple crystallographic facets emerge, accompanied by a transition from a monomodal to a bimodal growth mode. Single twinning is observed in all samples. However, with increasing deposition, not only a bimodal size distribution occurs, but also the volume fraction of the twinned material increases significantly. These findings shed light on the growth dynamics of nanoheteroepitaxial GaAs and contribute to ongoing efforts toward CMOS-compatible Si-based nanophotonic technologies. Full article

Background: Recurrent vomiting in infantile hypertrophic pyloric stenosis (IHPS) leads to metabolic alkalosis and a respiratory-driven compensatory hypercapnia. Alkalosis has been identified as the main causal factor for respiratory depression on admission. The value of contribution of hemoglobin and carbon dioxide partial pressure to this phenomenon will be evaluated. Materials and Methods: A retrospective cohort study was conducted on 105 infants with IHPS. The acid/base status, including levels of hemoglobin and lactate, were recorded. Statistical comparisons, correlation analysis, linear regression and multivariate regression analysis were applied. Results: Hypercapnia was associated with hemoconcentration. We found a positive correlation was found between pCO₂ and hemoglobin (p = 0.042). The multivariate linear regression analysis showed that pCO₂ is dependent on hemoglobin (p = 0.002). Lactate, which is used as a marker for anaerobic glycolysis, showed no systematic correlation with pCO₂. Conclusions: An increase in carbon dioxide cannot easily be attributed to a reduced transport function of carbon dioxide due to hemoglobin deficiency. Further investigation is needed to determine the extent to which low hemoglobin levels and increased pCO₂ interact with hemoconcentration to contribute to respiratory problems. Full article

The 32-bit floating-point (FP32) format has many useful applications, particularly in computing and neural network systems. The classic 32-bit fixed-point (FXP32) format often introduces lower quality of representation (i.e., precision), making it unsuitable for real deployment, despite offering faster computations and reduced computational cost, which positively impacts energy efficiency. In this paper, we propose a switched FXP32 format able to compete with or surpass the widely used FP32 format across a wide variance range. It actually proposes switching between the possible values of key parameters according to the variance level of the data modeled with the Laplacian distribution. Precision analysis is achieved using the signal-to-quantization noise ratio (SQNR) as a performance metric, introduced based on the analogy between digital formats and quantization. Theoretical SQNR results provided in a wide range of variance confirm the design objectives. Experimental and simulation results obtained using neural network weights further support the approach. The strong agreement between the experiment, simulation, and theory indicates the efficiency of this proposal in encoding Laplacian data, as well as its potential applicability in neural networks. Full article

Devices employing cryptographic approaches have to be resistant to physical attacks. Side-Channel Analysis (SCA) and Fault Injection (FI) attacks are frequently used to reveal cryptographic keys. In this paper, we present a combined SCA and laser illumination attack against an Elliptic Curve Scalar Multiplication accelerator, while using different equipment for the measurement of its power traces, i.e., we performed the measurements using a current probe from Riscure and a differential probe from Teledyne LeCroy, with an attack success of 70% and 90%, respectively. Our experiments showed that laser illumination increased the power consumption of the chip, especially its static power consumption, but the success of the horizontal power analysis attacks changed insignificantly. After applying 100% of the laser beam output power and illuminating the smallest area of 143 µm², we observed an offset of 17 mV in the measured trace. We assume that using a laser with a high laser beam power, as well as concentrating on measuring and analysing only static current, can significantly improve the attack’s success. The attacks exploiting the Static Current under Laser Illumination (SCuLI attacks) are novel, and their potential has not yet been fully investigated. These attacks can be especially dangerous against cryptographic chips manufactured in downscaling technologies. If such attacks are feasible, appropriate countermeasures have to be proposed in the future. Full article

Si-based photonics has garnered considerable attention as a future device for complementary metal–oxide–semiconductor (CMOS) computing. However, few studies have investigated Si-based light sources highly compatible with Si ultra large-scale integration processing. In this study, we observed stable light emission at room temperature from superatom-like β–FeSi₂–core/Si–shell quantum dots (QDs). The β–FeSi₂–core/Si–shell QDs, with an areal density as high as ~10¹¹ cm⁻² were fabricated by self-aligned silicide process of Fe–silicide capped Si–QDs on ~3.0 nm SiO₂/n–Si (100) substrates, followed by SiH₄ exposure at 400 °C. From the room temperature photoluminescence characteristics, β–FeSi₂ core/Si–shell QDs can be regarded as active elements in optical applications because they offer the advantages of photonic signal processing capabilities and can be combined with electronic logic control and data storage. Full article

The current range of the jaguar (Panthera onca) spans sixty degrees of latitude across eighteen countries in the Western Hemisphere and covers approximately 7,000,000 km². Throughout this geographical breadth, jaguars represent an essential component of native biological diversity, but conflict revolving around real and perceived jaguar depredation on livestock is a factor in jaguar mortality. We developed a structured questionnaire to evaluate the effectiveness of anti-depredation strategies from northern Mexico to Argentina, collecting data from 11 countries and 248 livestock operations, 194 with efficacy metrics, and 24 with benefit–cost ratios (value of the livestock losses averted/cost of the intervention). Using coarse categories, 11 intervention types were tested. Techniques effectively reducing livestock losses were documented across the entire livestock operation size (2–130,000 ha, 5–30,000 head) and biome spectrum. While the techniques varied in complexity and required levels of investment, successful reductions in depredation were achieved at all levels. We conclude that anti-depredation strategies are highly effective, and when benefits are evaluated, they surpass costs, sometimes substantially. Given the proven efficacy and cost-effectiveness of the techniques described in this paper, we advocate for broader application across the species range to increase tolerance towards jaguars and a more effective human–jaguar coexistence. Full article

We investigate integrated silicon ring resonators with regard to the influence of design parameters and intra-wafer variations. First, we show the effect of different ring radii and gaps between ring and bus waveguide on optical properties (peak width, finesse, Q factor, and extinction ratio), from which we calculate the resonators’ coupling and loss coefficients. The dependence on the gap of these properties is discussed at the wafer scale. Second, by incorporating the spectra of 2242 resonators from 59 nominally identical dies on a 200 mm wafer, we show how these properties depend on the resonators’ position on the wafer. Third, we demonstrate how curve fitting of loss and coupling coefficients as a function of the gaps can be used to estimate the optimal gap that realizes critical coupling with a significantly reduced number of manufactured test structures needed to find optimal design parameters. Full article

Background. Food allergies (FAs) are a significant public health concern, affecting 6–8% of children worldwide, with a growing prevalence. Schools are high-risk environments for allergic reactions, including anaphylaxis, which can be life-threatening. Alarmingly, up to 16–18% of children with FAs experience allergic reactions at school, often due to accidental exposure. Additionally, up to 25% of anaphylactic reactions in schools occur in children with no prior diagnosis of FA, emphasizing the critical need for school-wide preparedness and robust emergency action plans. School nurses play a pivotal role in managing FAs through individualized health plans, emergency preparedness, staff training, and psychosocial support. This review aims to evaluate the multifaceted role of school nurses in ensuring the safety, health, and psychosocial well-being of children with FAs. It also seeks to identify systemic challenges and gaps in allergy management to inform targeted interventions and future research. Methods. This comprehensive review synthesizes evidence on the role of school nurses in FA management. A systematic literature search was conducted across PubMed, CINAHL, Scopus, and Cochrane, targeting studies published between 2014 and 2024. The search identified 6313 articles, of which 5490 remained after duplicate removal. After title and abstract screening, 60 articles were selected for full-text evaluation, with 59 included in the final review. Thematic analysis identified six domains: preventive measures, emergency preparedness, communication, health outcomes, psychosocial support, and systemic challenges. Results. The review highlights the critical contributions of school nurses to FA management. They improve safety by implementing Individualized Health Plans (IHPs) and Emergency Action Plans (EAPs), ensuring timely administration of epinephrine and reducing delays during emergencies. Preventive strategies, such as allergen-free zones and comprehensive training for staff, minimize exposure risks. Psychosocial interventions led by nurses alleviate stigma, bullying, and anxiety, enhancing the quality of life for children with FAs. Despite these benefits, barriers persist, including insufficient nurse-to-student ratios, limited access to emergency resources like stock epinephrine, and disparities in allergy management across socioeconomic and geographic contexts. Conclusions. School nurses are integral to managing FAs, ensuring safety, fostering inclusion, and addressing psychosocial needs. Addressing systemic barriers and ensuring equitable resource distribution are essential to optimize their impact. Future research should focus on the long-term outcomes of nurse-led interventions, strategies to reduce disparities, and the potential role of digital tools in improving allergy management. Full article

While past research has emphasized the importance of late blight infection detection and classification, anticipating the potato late blight infection is crucial from the economic point of view as it helps to significantly reduce the production cost. Furthermore, it is necessary to minimize the exposure of potatoes to harmful chemicals and pesticides due to their potential adverse effects on the human immune system. Our work is based on the precise classification of late blight infections in potatoes in European countries using real-time data from 1980 to 2000. To predict the potato late blight outbreak, we incorporated several hybrid machine learning models, as well as a unique combination of stacking classifier and logistic regression, achieving the highest prediction accuracy of 87.22%. Further enhancements of these models and the use of new data sources may lead to a higher late blight prediction accuracy and, consequently, a higher efficiency in managing potatoes’ health. Full article

The widespread use of IoT devices has led to the generation of a huge amount of data and driven the need for analytical solutions in many areas of human activities, such as the field of smart agriculture. Continuous monitoring of crop growth stages enables timely interventions, such as control of weeds and plant diseases, as well as pest control, ensuring optimal development. Decision-making systems in smart agriculture involve image analysis with the potential to increase productivity, efficiency and sustainability. By applying Convolutional Neural Networks (CNNs), state recognition and classification can be performed based on images from specific locations. Thus, we have developed a solution for early problem detection and resource management optimization. The main concept of the proposed solution relies on a direct connection between Cloud and Edge devices, which is achieved through Fog computing. The goal of our work is creation of a deep learning model for image classification that can be optimized and adapted for implementation on devices with limited hardware resources at the level of Fog computing. This could increase the importance of image processing in the reduction of agricultural operating costs and manual labor. As a result of the off-load data processing at Edge and Fog devices, the system responsiveness can be improved, the costs associated with data transmission and storage can be reduced, and the overall system reliability and security can be increased. The proposed solution can choose classification algorithms to find a trade-off between size and accuracy of the model optimized for devices with limited hardware resources. After testing our model for tomato disease classification compiled for execution on FPGA, it was found that the decrease in test accuracy is as small as 0.83% (from 96.29% to 95.46%). Full article

The behavior of two polymeric protective paint coatings (epoxy and polyurethane) applied over an epoxy primer coating on steel plates was investigated in this study, focusing on their role in providing anticorrosive protection against various climatic stress factors. Among the numerous climatic factors that can affect the lifetime of anticorrosive coatings, the following were selected for this work: dry heat, UV radiation, humidity, and extreme conditions such as salt fog, marine atmosphere, and alpine atmosphere. The objective was to determine the remaining lifetime of these protective coatings before replacement is needed to prevent damage to the equipment they protect. The behavior of these polymeric materials under the mentioned factors was analyzed based on the variation in the tangent of the dielectric loss angle (tg δ) with frequency. From the interpretation of the experimental results, it was found that the polyurethane paint coating (P2) exhibits superior resistance to climatic degradation compared to the epoxy paint coating (P1). Furthermore, a comparison of tg δ values for the P1 and P2 coatings revealed that the initial (unaged) P2 coating performs better as an insulator (dielectric) than the P1 coating. Comprehensive information is provided to the users of polymeric anticorrosive protection materials, highlighting the extent to which climatic factors can affect the performance of the equipment they protect and determining the appropriate timing for replacing the coatings. Full article