Search Results (107)

In this article, a low-power low-intermediate-frequency (Low-IF) receiver front-end is presented for Bluetooth Low Energy (BLE) body area network (BAN) applications. The receiver employs an input matching network, an inductorless self-biased inverter-based low-noise transconductance amplifier (LNTA), a single-balanced passive mixer, a common-gate transimpedance amplifier (TIA), and a Gm-C complex filter for image suppression. Native MOS devices are adopted to support low-voltage operation and reduce static power consumption. The interstage on-chip coupling capacitor between the RF front-end and the TIA is removed by aligning the DC operating points of the two stages. The receiver front-end is implemented in a 55 nm standard CMOS process and occupies an active area of 0.081 ${\mathrm{mm}}^2$, excluding bonding pads. Post-layout simulations show that the proposed design achieves 45.2 dB gain, 7.2 dB noise figure, and 28.1 dB image rejection ratio over the 2.4–2.48 GHz band, while consuming 537 $\mathsf{\mu }$W. The proposed front-end is suitable for low-power BLE BAN sensor nodes. Full article

This work presents a systematic design flow for the fundamental building blocks (namely, the low-noise amplifier and the down-conversion mixer) of an analog receiver for 5G backhauling systems implemented in SiGe BiCMOS technology. The proposed methodology enables the sizing and optimization of receiver blocks up to post-layout simulations, starting from the specified performance requirements. It accounts for both the parasitic effects of active devices and the distributed effects of interconnects. The design flow was applied using STMicroelectronics BiCMOS55X technology to develop low-noise amplifiers and D-band to E-band downconverters capable of covering the 130–150 GHz and 150–165 GHz sub-bands. Preliminary measurement results obtained from both the standalone LNA blocks and the complete receivers are presented and discussed. Full article

Sextortion has rapidly expanded into a global cyber-enabled crime that leverages anonymous digital communication and decentralized payment systems. This study examines the financial infrastructures underlying contemporary sextortion by conducting a two-phase analysis of 87 confirmed cases involving cryptocurrency payments. Using blockchain forensic tools and open-source intelligence, the research traces fund movements across perpetrator-controlled wallets, identifies laundering techniques such as mixers, peel-chain transfers, and exchange-based cash-outs, and links these behaviors to narrative patterns within victim reports. The results reveal a dual-tier ecosystem in which mass-produced, multilingual extortion scripts coexist with divergent laundering typologies that differentiate lower-value, high-volume scams from more organized and higher-yield operations. By integrating qualitative and quantitative evidence, this study provides a forensic framework for detecting illicit cryptocurrency activity, improving threat classification, and strengthening investigative and regulatory responses to sextortion and related crypto-enabled interpersonal crimes. Full article

This study aimed to evaluate the efficacy of a palm oil-free structured lipid (SL) as a lipid base in sandwich-type cookie fillings. SL was enzymatically interesterified from a blend of soybean oil, high-oleic peanut oil, and crambe hard fat (34:34:32). Four fillings (30% fat) were prepared using either SL or commercial shortening (CS), with processing by mixer (F1, F2) or ball mill (F3, F4). Commercial sandwich cookies were included as a reference Standard. SL exhibited an improved lipid profile, containing up to 14% less saturated fatty acids, higher levels of monounsaturated (34.5%), and increased long-chain fatty acids (~18% C22:0). Physicochemical analyses were conducted over a storage period of 180 days, including evaluations of texture, particle distribution, color, water activity, oil loss, and oxidative stability. Among the formulations, F4 demonstrated the highest firmness (at ~121.1 N) and the smallest D₅₀ (~80 µm). However, it also exhibited lower oxidative stability (induction period: ~6.75 to 14.6 h) compared to CS-based fillings (~36 to 42.5 h), along with a higher oil loss (≥4.7%). Sensory of F4 yielded an overall acceptance index ≥ 70%, though it received lower scores for waxiness. Overall, the SL showed promising potential as a structuring fat in the fillings. Full article

The increasing global demand for cleaner transportation has intensified the importance of efficient AdBlue^® (AUS32) production, a key chemical in selective catalytic reduction (SCR) systems that reduces nitrogen oxides (NOx) emissions from diesel engines. This work presents a computational fluid dynamics (CFD) simulation study of the urea–water mixing process within a high shear mixer (HSM), aiming to enhance the sustainability of AdBlue^® manufacturing. The model evaluates the hydrodynamic characteristics critical to optimising the dissolution of urea pellets in deionised water, which conventionally requires significant preheating. Experimental validation was conducted by comparing pressure drop simulation results with operational data from an active industrial facility in the United Kingdom. Therefore, this study validates the CFD model against an industrial two-stage Rotor–stator under real operating conditions. The computational framework combines a refined mesh with the k-ω SST turbulent model to resolve flow structures and capture near-wall effects and shear stress transport in complex flow domains. The results reveal opportunities for process optimisation, particularly in reducing thermal energy input without compromising solubility, thus offering a more sustainable pathway for AdBlue^® production. The main contribution of this work is to close existing gaps in industrial practice and propose and computationally validate strategies to improve the numerical design of HSM for solid dissolution. Full article

Background: The efficiency of vermicomposting in reducing antibiotic resistance genes (ARGs) in dairy manure may be compromised by co-pollutants like arsenic (As) and microplastics. Specifically, plasmids serving as carriers and vectors of ARGs were largely distributed in this process. However, the impact of As and microplastics on plasmids carrying ARGs during vermicomposting is largely unknown. Methods: This study utilized a controlled experimental design and applied plasmid metagenomics to investigate the individual and combined effects of As and polyethylene terephthalate (PET) microplastics on plasmid-mediated ARG dynamics during vermicomposting. Results: We found that vermicomposting alone mainly enriched non-mobilizable plasmids, while PET microplastics selectively promoted conjugative and mobilizable plasmids, whereas As significantly increased all plasmid types. Moreover, both PET or As alone and combined exposure (PET and As) increased total ARG abundance, with their combination inducing synergistic ARG enrichment despite unchanged total plasmid abundance. Furthermore, co-occurrence network analysis combined with ARGs/plasmid ratio assessments demonstrated that As influences ARGs through co-selective pressure by enriching ARGs co-localized with As resistance genes (e.g., the ars operon) on plasmids while simultaneously promoting horizontal gene transfer (HGT) via activation of oxidative stress and SOS response pathways. In contrast, PET primarily facilitates ARG dissemination through a “metabolism-resistance” coupling strategy by enriching colonizing bacteria with PET-degrading capacity. Their co-exposure formed As-enrichment hotspots on PET microplastic surfaces, functioning as a “super-mixer” that selectively screened for superbugs carrying potent resistance mechanisms (e.g., bla_OXA-50 and mdtB/mdtE). Conclusions: This study provides the first plasmidome-level evidence of synergistic ARG propagation by As and PET microplastics during vermicomposting, highlighting mobile genetic elements’ critical role in co-pollutant risk assessments. Full article

This study is motivated by the severe tribological regime of PA6 composites in VR platforms operating under dry or boundary lubrication, where alternating shear during foot rotation, localised contact pressures, and third-body abrasion concurrently challenge wear resistance and retention of strength. This paper presents the results of research into the properties of composites based on polyamide PA6 and molybdenum disulphide, obtained by combining the components through high-intensity mechanochemical activation in a planetary mill and classical mixing in a turbulence mixer. We demonstrate that varying the energy of the premixing stage (mechanochemical activation versus low-energy premixing) serves as an effective means of interfacial engineering in PA6/MoS₂ composites, enabling simultaneous enhancement of mechanical and tribological properties at low filler contents. Analysis of experimental composite samples using Fourier-transform infrared spectroscopy (FTIR) indicates the interaction between MoS₂ and oxygen-containing groups of polyamide while maintaining its overall chemical composition. According to the TG-DSC curves, modification of polyamide leads to an increase in the melting temperature by 2 °C, while mechanical activation ensures stronger interaction between the matrix and the filler. Compared to pure PA6, the tensile strength of composites increases by 10–20% for mechanoactivated materials and by 5–10% for materials obtained by conventional methods. The mechanical activation effect is observed even at minimal amounts (0.25 and 0.5%) of MoS₂ in composites. The toughness of all composites, regardless of the mixing method, increases by 5–7% compared to pure polyamide. All composites show a 10–20% reduction in the coefficient of friction on steel. Simultaneously, the water absorption of composites becomes 5–20% higher than that of the original material, which indicates a change in structure and an increase in porosity. The obtained composite materials are planned to be used for manufacturing platforms for the movement of virtual reality (VR) operators. Full article

This study presents the development and evaluation of a technology for producing geopolymer-based granulates, which act as sustainable substitutes for natural aggregates by utilizing waste materials. The technology is demonstrated to be energy-efficient compared to other manufactured aggregate processes (such as sintering), as it relies on a cold-bonding process and achieves self-hardening at room temperature. The granulation of geopolymer materials using an intensive counter-current mixer represents an innovative solution in the field of producing substitutes for natural aggregates. Coal fly ash (CFA) was used as the primary aluminosilicate precursor, with composite regrind from decommissioned wind turbine blades (CR) and steelmaking dust (SD) tested as additives. Reactive solids and alkaline activator liquids were mixed and granulated in a single operation using an intensive counter-current mixer; moistening and surface powdering were applied to improve granule sphericity. The granules were cold-cured at room temperature and characterized after 28 days by grain size distribution, crushing resistance, water absorption, abrasion (micro-Deval), SEM/EDS and leaching tests. The results indicate that the additives significantly improved the mechanical performance: PM + PK granules reached crushing strengths > 6 MPa, while CFA + SD granules reached > 11 MPa, exceeding many commercial lightweight aggregates (such as LECA or Lytag), as detailed in the paper. The CFA + CR granulates exhibited a compact microstructure and the effective immobilization of several heavy metals, whereas the CFA + DS samples demonstrated the excessive leaching of Cr, Pb and Mo. The process achieved a high solid-to-liquid ratio (>2.0), reducing activator consumption. Composite regrind is recommended as a promising additive. Full article

This paper presents the design and implementation of a wideband diode-based down-converter operating from 60 to 90 GHz with a variable flat conversion gain. The proposed down-converter is implemented utilizing the Miniature Hybrid-Microwave Integrated Circuit (MHMIC) technology. It is composed of a wideband double-balanced mixer, a Local Oscillator (LO) chain, and a differential TransImpedance Amplifier (TIA) with a variable gain. The designed mixer uses a novel topology exhibiting minimum reflection and high isolation between the RF and LO ports across a wide operating frequency of 30 GHz. In this topology, two balanced detectors generate the differential IF signal with minimum reflection. The characteristic impedance ($Z_0$) of the mixer is set to be $70.7$$\Omega$, to minimize trace widths to reduce the mutual coupling and increasing the bandwidth. The OPA 657 is the core of the designed differential TIA with a variable gain. In addition, the LO chain of the down-converter utilized a combination of an active (×2) and a passive (×3) multiplier to generate enough RF power in the desired frequency range. Also, a WR-12 waveguide to Substrate Integrated Waveguide (SIW) transition is designed for the RF and LO ports that operates through the E-band. The proposed down-converter demonstrates excellent performance, with a high isolation between RF and LO ports exceeding 22 dB and a maximum conversion gain of $-5$ dB, and a response with a variation of ±5 dB across the band. The proposed mixer exhibits a return loss of better than 10 dB at both RF and LO ports, and it consumes a power of 560 mW. Full article

Robots are increasingly emerging as effective platforms to overcome a wide range of challenges in agriculture. Beyond functioning as standalone systems, agricultural robots are proving valuable as collaborative platforms, capable of supporting and integrating with humans and other technologies and agricultural activities. In this study, we designed and implemented an automated system embedded in a ground-based robotic platform to support spraying drone operations. The system consists of a robotic platform that carries the spraying drone along with all necessary support devices, including a water tank, chemical reservoirs, a mixer, generators for drone battery charging, and a top landing pad. The system is controlled with a mobile app that calculates the total amount of water and chemicals required and sends commands to the platform to prepare the application mixture. The input information in the app includes the field area, application rate, and up to three chemical dosages simultaneously. Additionally, the platform allows the drone to take off from and land on it, enhancing both safety and operability. A set of pumps was used to deliver water and chemicals as specified in the mobile app. To automate pump control, we used Arduino technology, including both the microcontroller and a programming environment for coding and designing the mobile app. To validate the system’s effectiveness, we individually measured the amount of water and chemical delivered to the mixer tank and compared it with conventional manual methods for calculating chemical quantities and preparation time. The system demonstrated consistent results, achieving high precision and accuracy in delivering the correct amount. This study advances the field of agricultural robotics by highlighting the role of collaborative platforms. Particularly, the system presents a valuable and low-cost solution for small farms and experimental research. Full article

This study investigates the combined use of electron beam irradiation (EBI) and nanotechnology to develop improved food packaging films. EBI, commonly applied for sterilization, can alter polymer microstructure, while irradiated cellulose nanocrystals (CNCs) offer enhanced functionality when incorporated into biopolymer matrices. Here, CNCs were irradiated with doses up to 50 kGy, leading to the formation of carboxyl and aldehyde groups, confirmed by FTIR analysis, as a consequence of the initial formation of free radicals and peroxides that may subsist in that original form or be converted into various carbonyl groups. Flexible films were obtained by incorporating pristine and EB-irradiated CNCs in an internal mixer, using minute amounts of poly(ethylene oxide) (PEO) to facilitate the dispersion of the filler within the polymer matrix. The resulting PLA/PEO/CNC films were evaluated for their mechanical, thermal, barrier, and antioxidant properties. The results showed that structural modifications of CNCs led to significant enhancements in the performance of the composite films, including a 30% improvement in water barrier properties and a 50% increase in antioxidant activity. These findings underscore the potential of irradiated CNCs as effective additives in biopolymer-based active packaging, offering a sustainable approach to reduce dependence on synthetic preservatives and potentially extend the shelf life of food products. Full article

Early detection of tuberculosis plays a critical role in effective treatment management. Like active tuberculosis, early identification of inactive forms such as latent or healed tuberculosis is essential to prevent future reactivation. In this study, we developed a deep-learning-based binary classification model to distinguish between active and inactive tuberculosis cases. Our model architecture incorporated an EfficientNet backbone with an MLP-Mixer classification head and was fine-tuned on a dataset annotated by Cheonan Soonchunhyang Hospital. To enhance predictive performance, we applied transfer learning using weights pre-trained on the JFT-300M dataset via the Noisy Student training method. Unlike conventional models, our approach achieved competitive results, with an accuracy of 96.3%, a sensitivity of 95.9%, and a specificity of 96.6% on the test set. These promising outcomes suggest that our model could serve as a valuable asset to support clinical decision-making and streamline early screening workflows for latent tuberculosis. Full article

Surface electromyography (sEMG) non-invasively captures the electrical activity generated by muscle contractions, offering valuable insights into motion intentions. While sEMG has been widely applied to general gesture recognition in rehabilitation, there has been limited exploration of specific, intricate daily tasks, such as the pouring action. Pouring is a common yet complex movement requiring precise muscle coordination and control, making it an ideal focus for rehabilitation studies. This research proposes a granular computing-based deep learning approach utilizing ConvMixer architecture enhanced with feature fusion and granular computing to improve gesture recognition accuracy. Our findings indicate that the addition of hand-crafted features significantly improves model performance; specifically, the ConvMixer model’s accuracy improved from 0.9512 to 0.9929. These results highlight the potential of our approach in rehabilitation technologies and assistive systems for restoring motor functions in daily activities. Full article

The increasing demand for critical metals essential for renewable energy technologies necessitates efficient and environmentally sustainable extraction methods. Ilmenite (FeTiO₃) and similar ore deposits serve as abundant sources of primary elements while also incorporating a suite of strategically significant trace elements, including REEs and Hf, among others. Mixer–settler units are extensively utilized in metal purification processes. It is important to develop approaches for tracking the metal’s extraction process online and optimizing flow dynamics. One widely adopted technique for evaluating the flow dynamics of the various components is the residence time distribution (RTD) measurement, which provides insights into the hydrodynamic behavior of process reactors. This study explored the application of radiotracer techniques for online monitoring of solvent extraction processes in hydrometallurgy, focusing on Hf recovery. A mixer–settler system was employed using di(2-ethylhexyl) phosphoric acid (D2EHPA) as the extractant and the 1M HNO₃ aqueous phase of Ti ore. The radiotracer ¹⁸¹Hf was synthesized via neutron activation and introduced into the system to track phase distribution and RTD. Real-time monitoring revealed over 95% extraction efficiency within 133 min (8000 s). The RTD studies validated system performance using perfect mixers in series and axial dispersion models. The calculated mean residence time of 100 min (6000 s) closely aligned with the theoretical 104 min (6240 s), confirming the model accuracy. The findings demonstrate the viability of radiotracers in monitoring solvent extraction, offering real-time insights into flow dynamics and extraction efficiency. Full article

The continuous synthesis of nanoparticles (NPs) has been actively studied due to its great potential to produce NPs with reproducible and controllable physicochemical properties. Here, we achieved the high throughput production of nanostructured lipid carriers (NLCs) using a coaxial turbulent jet mixer with an added heating system. This device, designed for the crossflow of precursor solution and non-solvent, combined with the heating system, efficiently dissolves solid lipids and surfactants. We reported the flow regime according to the Reynolds number (Re). Also, we confirmed the size controllability of NLCs as dependent on both Re and lipid concentration. The optimized synthesis yields NLCs around 80 nm, ideal for targeted drug delivery by enhanced permeability and retention (EPR) effect. The coaxial turbulent jet mixer enables effective mixing, producing uniform size distribution of NLCs. The NLCs prepared using the coaxial turbulent jet mixer were smaller, more uniform, and had higher drug loading compared to the NLCs synthesized by a bulk nanoprecipitation method, showcasing its potential for advancing nanomedicine. Full article