Search Results (43)

Direct Air Capture (DAC) is emerging as a critical climate change mitigation strategy, offering a pathway to actively remove atmospheric CO₂. This comprehensive review synthesizes advancements in DAC technologies, with a particular emphasis on the pivotal role of nanostructured solid sorbent materials. The work critically evaluates the characteristics, performance, and limitations of key nanomaterial classes, including metal–organic frameworks (MOFs), covalent organic frameworks (COFs), zeolites, amine-functionalized polymers, porous carbons, and layered double hydroxides (LDHs), alongside solid-supported ionic liquids, highlighting their varied CO₂ uptake capacities, regeneration energy requirements, and crucial water sensitivities. Beyond traditional temperature/pressure swing adsorption, the review delves into innovative DAC methodologies such as Moisture Swing Adsorption (MSA), Electro Swing Adsorption (ESA), Passive DAC, and CO₂-Binding Organic Liquids (CO₂ BOLs), detailing their unique mechanisms and potential for reduced energy footprints. Despite significant progress, the widespread deployment of DAC faces formidable challenges, notably high capital and operational costs (currently USD 300–USD 1000/tCO₂), substantial energy demands (1500–2400 kWh/tCO₂), water interference, scalability hurdles, and sorbent degradation. Furthermore, this review comprehensively examines the burgeoning global DAC market, its diverse applications, and the critical socio-economic barriers to adoption, particularly in developing countries. A comparative analysis of DAC within the broader carbon removal landscape (e.g., CCS, BECCS, afforestation) is also provided, alongside an address to the essential, often overlooked, environmental considerations for the sustainable production, regeneration, and disposal of spent nanomaterials, including insights from Life Cycle Assessments. The nuanced techno-economic landscape has been thoroughly summarized, highlighting that commercial viability is a multi-faceted challenge involving material performance, synthesis cost, regeneration energy, scalability, and long-term stability. It has been reiterated that no single ‘best’ material exists, but rather a portfolio of technologies will be necessary, with the ultimate success dependent on system-level integration and the availability of low-carbon energy. The review paper contributes to a holistic understanding of cutting-edge DAC technologies, bridging material science innovations with real-world implementation challenges and opportunities, thereby identifying critical knowledge gaps and pathways toward a net-zero carbon future. Full article

The antioxidant capacity and modulation of oxidative stress by industrially processed açaí pulp extract from the Amazon (APEA) and its major anthocyanins, cyanidin 3-glucoside (C3G) and cyanidin-3-O-rutinoside (C3R), were evaluated as potential strategies for preventing cardiovascular diseases. The APEA was chemically characterized using ultrafast liquid chromatography-mass spectrometry (UFLC-MS), which revealed six main phenolic compounds. Notably, 9-(2,3-dihydroxypropoxy)-9-oxononanoic acid, acanthoside B, roseoside, cinchonine, and nonanedioate were identified for the first time in açaí extracts. In vitro antioxidant assays demonstrated that APEA exhibited strong DPPH- and ABTS-radical-scavenging activities (up to 80% inhibition and 65 mmol TE/100g DW, respectively) and showed ferrous- and copper-ion-chelating activities comparable to those of EDTA-Na₂ at higher concentrations (up to 95% inhibition). Hydroxyl and superoxide radical scavenging activities reached 80% inhibition, similar to that of ascorbic acid. In H₂O₂-treated H9c2 cardiomyocytes, APEA significantly reduced the intracellular ROS levels by 46.9%, comparable to the effect of N-acetylcysteine. APEA also attenuated menadione-induced oxidative stress in H9c2 cells, as shown by a significant reduction in CellROX fluorescence (p < 0.05). In vivo, APEA (100 mg/kg) significantly reduced CCl-induced hepatic lipid peroxidation (MDA levels), restored glutathione (GSH), and increased the antioxidant enzymes CAT, GPx, and SOD, demonstrating superior effects to C3G and C3R, especially after 21 days of treatment (p < 0.001). These findings suggest that Amazonian açaí pulp (APEA) retains potent antioxidant activity after industrial processing, with protective effects against oxidative damage in cardiomyocytes and hepatic tissue, highlighting its potential as a functional food ingredient with cardioprotective and hepatoprotective properties. Full article

Background: Periodontal disease (PD) is a chronic inflammatory condition associated with dysbiotic biofilm, leading to the destruction of bone and periodontal ligament. Scaling and root planing (SRP) is the gold-standard treatment for PD, but some patients may not respond adequately, necessitating adjunctive therapies. This study investigated the antimicrobial activity of diacetylcurcumin (DAC), a modified curcumin, against multispecies subgingival biofilm associated with periodontitis. Methods: The biofilm, containing 40 bacterial species, was cultured for seven days in the Calgary apparatus. Treatments with DAC (200 μg/mL), 0.12% chlorhexidine (CHX), and a vehicle (control) were applied twice daily for 1 min, starting on the third day. On the seventh day, biofilms were analyzed for metabolic activity (MA) and bacterial counts via DNA-DNA hybridization. DAC toxicity was tested on Galleria mellonella larvae. Results: DAC reduced biofilm metabolic activity by 51%, while CHX achieved 88% reduction compared to the vehicle (p < 0.05). DAC also significantly decreased counts of key periodontal pathogens, including P. gingivalis, T. forsythia, P. intermedia, and A. actinomycetemcomitans (p < 0.05). At the tested concentration, DAC showed no toxicity in larvae. Conclusions: These findings suggest that DAC effectively reduces biofilm activity and periodontal pathogen counts, presenting a promising adjunctive therapy for PD. Full article

In this paper, a pixel circuit consists of four MOSFETs and one capacitor is proposed for Organic Light-Emitting Diode on Silicon (OLEDoS) microdisplays. The proposed pixel circuit enhances luminance uniformity by compensating for the threshold voltage variation of the driving transistors by the capacitive coupling effect. Even with a threshold voltage variation of ±20 mV, the HSPICE simulation results reveal that the driving current offset stays between −0.89 and 0.70 LSB, which is more than seven times smaller than that of the conventional 2T1C pixel circuit. Additionally, a two-stage DAC driving scheme has been utilized to achieve 256 gray levels, aiming to reduce the accuracy requirements for the DAC circuit. The proposed pixel circuit demonstrates significant potential in high-performance OLEDoS microdisplay applications. Full article

This study proposes a high-frequency Pulse Amplitude-Modulation Temporal-Interference (PAM-TI) current stimulation device, which utilizes two sets of Amplitude-modulated transcranial alternating current stimulation (AM-tACS): one AM frequency at f0 (where f0 = 2 kHz) (source 1) and the other AM frequency at f1 = f0 + $△$f (where f1 = 2.01 kHz) (source 2), to generate a $△$f (where $△$f = 10 Hz) envelope modulated at a fc (where fc = 100 kHz) high carrier frequency. The high carrier frequency reduces body impedance and conserves more stimulation power, allowing it to penetrate the skin and reach the subcutaneous region. The proposed PAM-TI technique elevates the two current sources to a 100 kHz carrier frequency. Instead of the challenges associated with generating high-frequency stimulation currents using an MCU and DAC, the proposed PAM-TI stimulation device achieves this by simply utilizing a pair of complementary pulse-width modulations (PWMs). The push–pull technique is employed to balance the charging currents between the anode and cathode, synchronizing the current timing of Source 1 and Source 2 under the fc modulation condition. To minimize signal attenuation, the PAM circuit is integrated directly into the electrode, ensuring the high-frequency signal is generated close to the body and preventing degradation from long wires. Additionally, a dry pin-type spring-loaded electrode is used to reduce interference caused by hair when placed on the head. The device’s validity and current directionality were verified using a scalp tissue-mimicking phantom composed of agar and saline. Full article

Due to the openness of communication channels and the sensitivity of the data being collected and transmitted, securing data access and communication in IoT systems requires robust ECC-based authentication and key agreement (AKA) protocols. However, designing an AKA protocol for IoT presents significant challenges, as most IoT sensors are deployed in resource-constrained, unattended environments with limited computational power, connectivity, and storage. To achieve anonymous authentication, existing solutions typically rely on shared temporary public keys to mask device IDs or validate sender certificates, which increases the computational overhead. Furthermore, these protocols often fail to address crucial security concerns, such as nonresistance to ephemeral secret leakage (ESL) attacks and a lack of perfect forward security. To mitigate the computational burden, we propose a dynamic authenticated credentials (DACs) synchronization framework for anonymous authentication. Then, we introduce an ECC-based AKA scheme that employs DACs in place of temporary public keys or sender credentials, enabling efficient and secure anonymous authentication. The security of the proposed protocol was rigorously verified under the Real-or-Oracle model and validated using ProVerif. Performance comparisons demonstrate that our scheme offered significant improvements in security, with an over 37% reduction in communication cost and computational overhead. Full article

Smart cities increasingly rely on the Internet of Things (IoT) to enhance infrastructure and public services. However, many existing IoT frameworks face challenges related to security, privacy, scalability, efficiency, and low latency. This paper introduces the Blockchain and Federated Learning for IoT (BFLIoT) framework as a solution to these issues. In the proposed method, the framework first collects real-time data, such as traffic flow and environmental conditions, then normalizes, encrypts, and securely stores it on a blockchain to ensure tamper-proof data management. In the second phase, the Data Authorization Center (DAC) uses advanced cryptographic techniques to manage secure data access and control through key generation. Additionally, edge computing devices process data locally, reducing the load on central servers, while federated learning enables distributed model training, ensuring data privacy. This approach provides a scalable, secure, efficient, and low-latency solution for IoT applications in smart cities. A comprehensive security proof demonstrates BFLIoT’s resilience against advanced cyber threats, while performance simulations validate its effectiveness, showing significant improvements in throughput, reliability, energy efficiency, and reduced delay for smart city applications. Full article

In order to improve quality assurance in wafer manufacturing, there are strict process requirements. Besides the well-known residency time constraints (RTCs), a dual-arm cluster tool also requires each robot arm to execute a specific set of tasks. We call such a tool an arm task-constrained dual-arm cluster tool (ATC-DACT). To do this, one of the arms is identified as the dirty one and the other as the clean one. The dirty one can deal with raw wafers, while the clean one can deal with processed wafers. This requirement raises a new problem for scheduling a cluster tool. This paper discusses the scheduling problem of ATC-DACTs with RTCs. Due to the arm task constraints, the proven, effective swap strategy is no longer applicable to ATC-DACTs, making the scheduling problem difficult. To address this problem, we explicitly describe the robot waiting as an event and build a Petri net (PN) model. Then, we propose a hybrid task sequence (HTS) as an operation strategy by combining the swap and backward strategies. Based on the HTS, the necessary and sufficient conditions for schedulability are established; also, a linear programming model is developed. We then develop an algorithm using these results to optimally schedule the system. Industrial case studies demonstrate the application of this method. Full article

Thiosemicarbazones and their metal complexes have been studied for their biological activities against bacteria, cancer cells and protozoa. Short-term in vitro treatment with one gold (III) complex (C3) and its salicyl-thiosemicarbazone ligand (C4) selectively inhibited proliferation of T. gondii. Transmission Electron Microscopy (TEM) detected transient structural alterations in the parasitophorous vacuole membrane and the tachyzoite cytoplasm, but the mitochondrial membrane potential appeared unaffected by these compounds. Proteins potentially interacting with C3 and C4 were identified using differential affinity chromatography coupled with mass spectrometry (DAC-MS). Moreover, long-term in vitro treatment was performed to investigate parasitostatic or parasiticidal activity of the compounds. DAC-MS identified 50 ribosomal proteins binding both compounds, and continuous drug treatments for up to 6 days caused the loss of efficacy. Parasite tolerance to both compounds was, however, rapidly lost in their absence and regained shortly after re-exposure. Proteome analyses of six T. gondii ME49 clones adapted to C3 and C4 compared to the non-adapted wildtype revealed overexpression of ribosomal proteins, of two transmembrane proteins involved in exocytosis and of an alpha/beta hydrolase fold domain-containing protein. Results suggest that C3 and C4 may interfere with protein biosynthesis and that adaptation may be associated with the upregulated expression of tachyzoite transmembrane proteins and transporters, suggesting that the in vitro drug tolerance in T. gondii might be due to reversible, non-drug specific stress-responses mediated by phenotypic plasticity. Full article

The Internet of Things (IoT) is the underlying technology that has enabled connecting daily apparatus to the Internet and enjoying the facilities of smart services. IoT marketing is experiencing an impressive 16.7% growth rate and is a nearly USD 300.3 billion market. These eye-catching figures have made it an attractive playground for cybercriminals. IoT devices are built using resource-constrained architecture to offer compact sizes and competitive prices. As a result, integrating sophisticated cybersecurity features is beyond the scope of the computational capabilities of IoT. All of these have contributed to a surge in IoT intrusion. This paper presents an LSTM-based Intrusion Detection System (IDS) with a Dynamic Access Control (DAC) algorithm that not only detects but also defends against intrusion. This novel approach has achieved an impressive 97.16% validation accuracy. Unlike most of the IDSs, the model of the proposed IDS has been selected and optimized through mathematical analysis. Additionally, it boasts the ability to identify a wider range of threats (14 to be exact) compared to other IDS solutions, translating to enhanced security. Furthermore, it has been fine-tuned to strike a balance between accurately flagging threats and minimizing false alarms. Its impressive performance metrics (precision, recall, and F1 score all hovering around 97%) showcase the potential of this innovative IDS to elevate IoT security. The proposed IDS boasts an impressive detection rate, exceeding 98%. This high accuracy instills confidence in its reliability. Furthermore, its lightning-fast response time, averaging under 1.2 s, positions it among the fastest intrusion detection systems available. Full article

In this paper, a wireless potentiostat code-named ElectroSense, for interfacing of wearable electrochemical biosensors, will be presented. The system is devoted to non-invasive monitoring of glucose in wearable medical applications. Differently from other potentiostats in literature, which use digital-to-analog converters (DACs) as discrete components or integrated in high-end microcontrollers, in this work the pulse width modulation (PWM) technique is exploited through PWM-DAC approach to generate signals. The ubiquitous presence of integrated PWM peripherals in low-end microcontrollers, which generally also integrate analog-to-digital converters (ADCs), enables both the generation and acquisition of read-out signals on a single cheap electronic device without additional hardware. By this way, system’s production costs, power consumption, and system’s size are greatly reduced with respect to other solutions. All these features allow the system’s adoption in wearable healthcare Internet-of-things (IoT) ecosystems. A description of both the sensing technology and the circuit will be discussed in detail, emphasizing advantages and drawbacks of the PWM-DAC approach. Experimental measurements will prove the efficacy of the proposed electronic system for non-invasive monitoring of glucose in wearable medical applications. Full article

Clinical studies revealed detrimental skeletal and vascular effects of the insulin sensitizer rosiglitazone. We have shown earlier that rosiglitazone accelerates osteoblast differentiation from human mesenchymal stem cells (hMSC) at the expense of increased oxidative stress and cell death. In calcifying human vascular cells, rosiglitazone stimulates pathological mineralization, an effect diminished by the antioxidant resveratrol. Here, we aimed to elucidate transcriptional networks underlying the rosiglitazone-enhanced mineralization phenotype. We performed genome-wide transcriptional profiling of osteogenic hMSCs treated with rosiglitazone for short-term periods of 1 up to 48 h during the first two days of differentiation, a phase that we show is sufficient for rosiglitazone stimulation of mineralization. Microarray-based mRNA expression analysis revealed 190 probes that were differently expressed in at least one condition compared to vehicle-treated control. This rosiglitazone gene signature contained well-known primary PPAR targets and was also endogenously regulated during osteogenic hMSC differentiation and osteoblast-like differentiation of vascular smooth muscle cells (VSMCs) into calcifying vascular cells (CVCs). Comparative analysis revealed rosiglitazone targets that were commonly enriched in osteoblasts and CVCs or specifically enriched in either osteoblasts or CVCs. Finally, we compared expression patterns of CVC-specific genes with patient expression data from carotid plaque versus intact adjacent tissue, and identified five rosiglitazone targets to be differentially regulated in CVCs and carotid plaque but not osteoblasts when compared to their non-mineralizing counterparts. These targets, i.e., PDK4, SDC4, SPRY4, TCF4 and DACT1, may specifically control extracellular matrix mineralization in vascular cells, and hence provide target candidates for further investigations to improve vascular health. Full article

Distributed Denial of Service (DDoS) and Address Resolution Protocol (ARP) attacks pose significant threats to the security of Software-Defined Internet of Things (SD-IoT) networks. The standard Software-Defined Networking (SDN) architecture faces challenges in effectively detecting, preventing, and mitigating these attacks due to its centralized control and limited intelligence. In this paper, we present P4-HLDMC, a novel collaborative secure framework that combines machine learning (ML), stateful P4, and a hierarchical logically distributed multi-controller architecture. P4-HLDMC overcomes the limitations of the standard SDN architecture, ensuring scalability, performance, and an efficient response to attacks. It comprises four modules: the multi-controller dedicated interface (MCDI) for real-time attack detection through a distributed alert channel (DAC), the MSMPF, a P4-enabled stateful multi-state matching pipeline function for analyzing IoT network traffic using nine state tables, the modified ensemble voting (MEV) algorithm with six classifiers for enhanced detection of anomalies in P4-extracted traffic patterns, and an attack mitigation process distributed among multiple controllers to effectively handle larger-scale attacks. We validate our framework using diverse test cases and real-world IoT network traffic datasets, demonstrating high detection rates, low false-alarm rates, low latency, and short detection times compared to existing methods. Our work introduces the first integrated framework combining ML, stateful P4, and SDN-based multi-controller architecture for DDoS and ARP detection in IoT networks. Full article

Direct air capture (DAC) is considered one of the mitigation strategies in most of the future scenarios trying to limit global temperature to 1.5 °C. Given the high expectations placed on DAC for future decarbonisation, this study presents an extensive review of DAC technologies, exploring a number of techno-economic aspects, including an updated collection of the current and planned DAC projects around the world. A dedicated analysis focused on the production of synthetic methane, methanol, and diesel from DAC and electrolytic hydrogen in the European Union (EU) is also performed, where the carbon footprint is analysed for different scenarios and energy sources. The results show that the maximum grid carbon intensity to obtain negative emissions with DAC is estimated at 468 gCO₂e/kWh, which is compliant with most of the EU countries’ current grid mix. Using only photovoltaics (PV) and wind, negative emissions of at least −0.81 tCO₂e/tCO₂ captured can be achieved. The maximum grid intensities allowing a reduction of the synthetic fuels carbon footprint compared with their fossil-fuels counterparts range between 96 and 151 gCO₂e/kWh. However, to comply with the Renewable Energy Directive II (REDII) sustainability criteria to produce renewable fuels of non-biological origin, the maximum stays between 30.2 to 38.8 gCO₂e/kWh. Only when using PV and wind is the EU average able to comply with the REDII threshold for all scenarios and fuels, with fuel emissions ranging from 19.3 to 25.8 gCO₂e/MJ. These results highlight the importance of using renewable energies for the production of synthetic fuels compliant with the EU regulations that can help reduce emissions from difficult-to-decarbonise sectors. Full article

With the increasing complexity of the workpiece surfaces in aerospace and automotive molding and other areas, an increasing number of cutting tools with different shapes and performance have become necessary. A new kind of cutting tool is developed with a double-arc revolving surface at the tool’s end to improve the processing quality in numerical control milling, referred to as a double-arc cutting tool (DACT) in this paper. The parametric geometric model of the DACT is established. Three types of cutting-edge curves are proposed (a cutting edge with a constant helix angle, a cutting edge with a constant pitch, and an orthogonal spiral cutting edge). Corresponding numerical simulation results are also provided as graphical representations. A DACT is manufactured and tested to verify its feasibility. Finally, two contrast experiments are conducted to prove that DACT has a higher processing quality than a ball-end mill (BEM). The advantage of the DACT is verified, which provides a theoretical basis for higher quality machining. The parametric design and application research provides a new method and theoretical basis for other new types of cutting tools. Full article