Search Results (54)

This systematic mapping review and bibliometric analysis examines Scopus-indexed research on computer vision, image processing, and deep learning applied to wood and timber materials and products. A rule-based Scopus search (TITLE-ABS-KEY, 9 December 2025), combining wood and timber terms with imaging and computer vision terminology, followed by duplicate removal and structured exclusions, retained 1019 papers (1983–2026, early access) covering surface inspection, internal imaging, species identification, processing operations (log-yard/sawmill/panels), automation, dimensional metrology, and image-based property/structure characterization. The papers were classified into nine application categories and three methodological classes using improved rule-based classification with weighted scoring and exclusion rules. Paper output continues to accelerate, with 63.7% of papers published since 2016; Wood Surface Quality Control dominates (48.3%), followed by 3D and Internal Wood Imaging (13.6%), Wood Microstructure and Characterization (10.1%), and Wood Species and Origin Identification (10.6%). Methodologically, classical computer vision prevails (73.6%). Deep learning accounts for 26.4% of the corpus overall and 48.8% of papers from 2023–2026 (early access), while classical computer vision remains prevalent (70.1%) across most categories; the dataset totals 11,961 citations (mean: 11.74 per paper). Validation on 97 papers showed 80.41% accuracy for methodological classification and 70.1% for application categories. We quantitatively map method evolution across the nine categories, introducing a tailored taxonomy and tracking the shift from classical vision to deep learning at the category level. The remaining gaps include dimensional measurement automation, warp detection, sawing optimization, and benchmark datasets, with future directions emphasizing Vision Transformers, multi-modal sensing, edge computing, and explainable AI for certification. Full article

This work presents a fully integrated, two-stage, deep class-AB power amplifier (PA) operating at a center frequency of 60 GHz. High efficiency and suppression of third-order intermodulation products are targeted, achieving improved linearity compared to reported state-of-the-art designs. A current combining architecture is also employed to enhance the output power capability. The PA is designed in a 22 nm FD-SOI CMOS technology and is optimized through a complete schematic-to-layout design flow. Post-layout simulations indicate that the PA achieves a peak power-added efficiency (PAE) of 28%, a saturated output power ($P_{sat}$) of 20.2 dBm, and a maximum large-signal gain ($G_{max}$) of 19.6 dB at 60 GHz, evaluated at an operating temperature of 60 °C. The design maintains high linearity across the targeted output power range, exhibiting effective suppression of third-order intermodulation distortion (IMD3), which enhances its suitability for spectrally efficient modulation schemes. Full article

This work presents a direct conversion transmitter (DCT) for 5G new radio (NR) that eliminates the RF driver by directly feeding a single stage cascode PA through a baseband buffer amplifier and passive up-conversion mixer. The baseband interface uses Class-AB buffers to hold the output capacitor voltage, enabling accurate sampling at the PA input. A mixer switch is selected for minimal on-resistance variation over the required baseband swing. The PA is designed with separate I and Q voltage inputs and a current summing structure. The PA operates at 2.5 V; other blocks use 1.2 V. Post-layout two-tone simulations at 5 GHz indicate 21 dBm output saturation power and −36.1 dBc of IMD3 at 9 dB PBO power while removing the driver to inter stage matching network of a two-stage design. The results validate a compact, driverless architecture for integrated transmitters. Full article

This paper presents a high-efficiency, nW-level operational transconductance amplifier (OTA) capable of operating at 0.3 V with rail-to-rail input and output. The design utilizes a bulk-driven technique in the input stage to extend the common-mode input range under ultra-low-voltage conditions. A simplified intermediate stage ensures reliable MOS operation at ultra-low-voltage levels while reducing power consumption, and a modified Class-AB controlled output stage facilitates rail-to-rail output and enhances current efficiency. Fabricated using SMIC 0.18 $\mathsf{\mu }$m technology and operating at a 0.3 V supply, the OTA achieves a DC gain of 63.07 dB, phase margin of 61.5°, a gain-bandwidth product of 37.68 kHz, and a slew rate of 21.85 V/ms while consuming only 123 nW with a 60 pF load. The design also demonstrates superior small-signal figures of merit (12.25 MHz·pF/$\mathsf{\mu }$W) and large-signal figures of merit (10.66 V/$\mathsf{\mu }$s·pF/$\mathsf{\mu }$W) compared to state-of-the-art low-voltage OTAs. These results indicate that the proposed amplifier offers a balanced solution of low power consumption, wide bandwidth, and high slew rate, making it well-suited for energy-constrained applications such as portable electronics, IoT sensors, and biomedical devices. Full article

Background: Agricultural production plays a vital role in the global economy by integrating different sectors and promoting capital circulation across industries. In this context, the dairy sector emerges as a promising avenue for investment. This study aims to assess the economic feasibility of establishing a dairy plant for the production of parmesan and mozzarella cheeses in Lavras, MG, considering both deterministic and probabilistic scenarios. Methods: The analysis was conducted in three stages: data collection, deterministic economic feasibility analysis using traditional financial indicators (NPV, IRR, profitability rate, and payback), and a probabilistic assessment using the Monte Carlo simulation with 100,000 iterations to incorporate uncertainty into the model. Results: The deterministic results indicated a positive Net Present Value (NPV), Internal Rate of Return (IRR) exceeding the Minimum Attractiveness Rate (MAR), and a profitability rate above 1.5, validating the investment’s viability. The probabilistic analysis reinforced these findings, with over 80% of simulated scenarios resulting in a positive NPV and over 77% showing IRR above the MAR. Key variables influencing profitability included market share, Class AB cheese consumer percentage, parmesan markup, operational costs, and per capita cheese consumption. Conclusions: The study confirms the economic feasibility of implementing the proposed dairy plant. The integration of Monte Carlo Simulation enhanced the robustness of the analysis by accounting for uncertainty, providing valuable insights for strategic decision-making. The project presents strong potential for regional development, job creation, and income generation. Full article

The development of efficient and sustainable hydrogen storage materials is a key challenge for realizing hydrogen as a clean and flexible energy carrier. Among various options, metal hydrides offer high volumetric storage density and operational safety, yet their application is limited by thermodynamic, kinetic, and compositional constraints. In this work, we investigate the potential of machine learning (ML) to predict key thermodynamic properties—equilibrium plateau pressure, enthalpy, and entropy of hydride formation—based solely on alloy composition using Magpie-generated descriptors. We significantly expand an existing experimental dataset from ~400 to 806 entries and assess the impact of dataset size and data augmentation, using the PADRE algorithm, on model performance. Models including Support Vector Machines and Gradient Boosted Random Forests were trained and optimized via grid search and cross-validation. Results show a marked improvement in predictive accuracy with increased dataset size, while data augmentation benefits are limited to smaller datasets and do not improve accuracy in underrepresented pressure regimes. Furthermore, clustering and cross-validation analyses highlight the limited generalizability of models across different material classes, though high accuracy is achieved when training and testing within a single hydride family (e.g., AB₂). The study demonstrates the viability and limitations of ML for accelerating hydride discovery, emphasizing the importance of dataset diversity and representation for robust property prediction. Full article

To meet the requirements of integrated accelerometers for a high-precision reference voltage under wide supply voltage range, high current drive capability, and low power consumption, this paper presents a bandgap reference operational amplifier (op-amp) circuit implemented in CMOS/BiCMOS technology. The proposed design employs a folded-cascode input stage, a push–pull Class-AB output stage, an adaptive output switching mechanism, and a composite frequency compensation scheme. In addition, overcurrent protection and low-frequency noise suppression techniques are incorporated to balance low static power consumption with high load-driving capability. Simulation results show that, under the typical process corner (TT), with VDD = 3 V and T = 25 °C, the op-amp achieves an output swing of 0.2 V~2.8 V, a low-frequency gain of 102~118 dB, a PSRR of 90 dB at 60 Hz, overcurrent protection of ±25 mA, and a phase margin exceeding 48.8° with a 10 μF capacitive load. Across the entire supply voltage range, the static current remains below 150 μA, while maintaining a line regulation better than 150 μV/V and a load regulation better than 150 μV/mA. These results verify the feasibility of achieving both high drive capability and high stability under stringent power constraints, making the proposed design well-suited as a bandgap reference buffer stage for integrated accelerometers, with strong engineering practicality and potential for broad application. Full article

This paper presents the first hybrid supply modulator (HSM) designed for envelope tracking power amplifiers (ET-PAs) in base station applications. The focus is on a rail-to-rail Class-AB linear amplifier (LA) optimized for high-voltage and wide-bandwidth operation. The LA is designed using 130 nm BCD technology, utilizing Laterally Diffused Metal-Oxide Semiconductor (LDMOS) transistors for high-voltage operation and incorporating shielding MOSFETs to protect the low-voltage devices. The circuit utilizes dual power supply domains (5 V and 30 V) to improve power efficiency. The proposed LA achieves a bandwidth of 100 MHz and a slew rate of +1003/−852 V/$\mathsf{\mu }\mathrm{s}$, with a quiescent power consumption of 0.89 W. Transient simulations using a 50 MHz bandwidth 5G NR envelope input demonstrate that the proposed HSM achieves a power efficiency of 83%. Consequently, the proposed HSM supports high-output (100 W) wideband 5G NR transmission with enhanced efficiency. Full article

Neighbourhood variation in socioeconomic deprivation is recognised as a small but meaningful determinant of adolescent mental health, yet the mechanisms through which the effects operate remain poorly understood. This study used #BeeWell survey data collected from adolescents in Greater Manchester (England) in 2021–2023 (life satisfaction: N = 27,009; emotional difficulties: N = 26,461). Through Latent Growth Mixture Modelling, we identified four non-linear trajectories of life satisfaction (Consistently High (71.0%), Improving (8.7%), Deteriorating (6.3%), and Consistently Low (13.9%); entropy = 0.66) and three non-linear trajectories of emotional difficulties (Low/Lessening (53.7%), Sub-Clinical (38.3%), and Elevated/Worsening (8.0%); entropy = 0.61). Using a multi-level mediation framework we assessed (1) whether neighbourhood deprivation predicted trajectory class membership and (2) the extent to which effects of deprivation operate through aspects of Community Wellbeing, as measured by the Co-op Community Wellbeing Index (CWI). Greater deprivation increased the odds of following Deteriorating (OR = 1.081, [1.023, 1.12]) and Consistently Low (OR = 1.084, [1.051, 1.119]) life satisfaction trajectories and reduced the odds of following a Sub-Clinical emotional difficulties trajectory (OR = 0.975, [0.954, 0.996]). Mediation analyses revealed that the effects of deprivation on Consistently Low life satisfaction partially operate through Equality (ab = 0.016, [0.002, 0.029]) and Housing, Space, and Environment (ab = −0.026, [−0.046, −0.006]). Further indirect effects were observed for Housing, Space, and Environment, which reduced likelihood of Sub-Clinical emotional difficulties for those living in deprived neighbourhoods (ab = −0.026, [−0.045, −0.008]). The findings highlight the distinct effects of neighbourhood deprivation on affective and evaluative domains of adolescent mental health and the protective effect of housing and related environmental factors in disadvantaged contexts, advancing our understanding of the mechanisms underpinning neighbourhood effects on dual-state adolescent mental health. Full article

Objective: Falciparum malaria is a major global health concern, affecting more than half of the world’s population and causing over half a million deaths annually. Red cell invasion is a crucial step in the parasite’s life cycle, where the parasite invade human erythrocytes to sustain infection and ensure survival. Two parasite proteins, Apical Membrane Antigen 1 (AMA-1) and Rhoptry Neck Protein 2 (RON2), are involved in tight junction formation, which is an essential step in parasite invasion of the red blood cell. Targeting the AMA-1 and RON2 interaction with inhibitors halts the formation of the tight junction, thereby preventing parasite invasion, which is detrimental to parasite survival. This study leverages machine learning (ML) to predict potential small molecule inhibitors of the AMA-1–RON2 interaction, providing putative antimalaria compounds for further chemotherapeutic exploration. Method: Data was retrieved from the PubChem database (AID 720542), comprising 364,447 inhibitors and non-inhibitors of the AMA-1–RON2 interaction. The data was processed by computing Morgan fingerprints and divided into training and testing with an 80:20 ratio, and the classes in the training data were balanced using the Synthetic Minority Oversampling Technique. Five ML models developed comprised Random Forest (RF), Gradient Boost Machines (GBMs), CatBoost (CB), AdaBoost (AB) and Support Vector Machine (SVM). The performances of the models were evaluated using accuracy, F1 score, and receiver operating characteristic—area under the curve (ROC-AUC) and validated using held-out data and a y-randomization test. An applicability domain analysis was carried out using the Tanimoto distance with a threshold set at 0.04 to ascertain the sample space where the models predict with confidence. Results: The GBMs model emerged as the best, achieving 89% accuracy and a ROC-AUC of 92%. CB and RF had accuracies of 88% and 87%, and ROC-AUC scores of 93% and 91%, respectively. Conclusions: Experimentally validated inhibitors of the AMA-1–RON2 interaction could serve as starting blocks for the next-generation antimalarial drugs. The models were deployed as a web-based application, known as PLASMOpred. Full article

Energy-efficient integrated circuits require scaled-down supply voltages, posing challenges for analog design, particularly for operational transconductance amplifiers (OTAs) essential in high-accuracy CMOS feedback systems. Below 1 V, gate-driven OTAs are limited in common-mode input range and minimum supply voltage. This work investigates CMOS Bulk-Driven (BD) sub-threshold techniques as an efficient alternative for ultra-low voltage (ULV) and ultra-low power (ULP) designs. Although BD overcomes MOS threshold voltage limitations, historical challenges like lower transconductance, latch-up, and layout complexity hindered its use. Recent advancements in CMOS processes and the need for ULP solutions have revived industrial interest in BD. Through theoretical analysis and computer simulations, we explore BD topologies for ULP OTA input stages, classifying them as tailed/tail-less and class A/AB, evaluating their effectiveness for robust analog design, while offering valuable insights for circuit designers. Full article

Seasonal variability significantly influences the fate and transport of antibiotics (Abs) in wastewater stabilization ponds by affecting their concentration, degradation kinetics, sorption behavior, and ecological interactions. This study investigated the influence of seasonal variability for a large number of Ab classes—eleven sulfonamides (SAs), eight fluoroquinolones (FQs), five macrolides (MLs), one diaminopyrimidine (DIA), two tetracyclines (TETs), two lincosamides (LICs), and three phenicols (Phens)—on their fate and transport in an artificial stabilization pond system (SPS) receiving treated WWTP effluent. Two sampling campaigns were conducted during China’s long-lasting seasons (summer and winter). The detection frequency for sulfamethoxazole (SMX), sulfapyridine (SPY), and ofloxacin (OFX) was 100%, for sulfamethazine (SMZ) 63.3%, and for clindamycin (CLN) 83.3% in both seasons. The detection frequency for the other Abs was equal or below 50% in both seasons. In addition, the maximum concentration of SMX, SMZ, SPY, OFX, and CLN in summer was 10.51, 19.37, 6.93, 22, and 4.04 ng/L, respectively, and 4.27, 0.14, 3.15, 9.29, and 8.78, respectively, in winter). The rest of the Abs were either detected in summer or winter. It was observed that environmental fluctuations (such as temperature, precipitation, SPS flow patterns, light intensity), differences in antibiotic use and consumption between seasons, and differences in physicochemical properties of the Abs were the main factors influencing their fate and transport within the SPS. The potential environmental risks of Abs detected in the SPS were assessed using the risk quotient (RQ) approach. Typically, RQs in summer were remarkably higher than in winter. Norfloxacin and chlortetracycline posed a medium risk in summer; however, ofloxacin posed a medium risk in winter and a high risk in summer. Therefore, management strategies should consider the dynamic nature of antibiotic contamination, accounting for seasonal influences on fate and transport within the studied SPS and maybe for other wastewater stabilization ponds by adjusting operational practices, optimizing treatment processes, and implementing source control measures to mitigate the environmental impacts of seasonal antibiotic variability. Full article

A family of improved low-voltage switched-capacitor circuits is introduced. It is based on the utilization of multiple-output class AB/AB op-amp architectures that provide true sample and hold outputs that are not subject to a reset phase as with conventional switched-capacitor circuits. This feature essentially relaxes the op-amp slew rate requirements, allowing a higher speed and simple low-voltage operation. A power-efficient GB boosting technique based on resistive local common mode feedback is used to significantly improve the GB and internal/external slew rate of the op-amps with only a 36.5% additional power dissipation. Full article

Background: Digital impression techniques for edentulous patients present unique challenges due to the absence of stable anatomical landmarks and variable soft tissue morphology. While intraoral scanners have shown promising results in dentate patients, their application in edentulous cases remains problematic, with reported accuracy deviations ranging from 60.6 ± 11.9 μm to 67.2 ± 6.9 μm compared to conventional methods. Material and Methods: This pilot study employed a within-subject, repeated-measures design comparing four scanning protocols in a fully edentulous patient (age: 42, BMI: 24.3 kg/m², Cawood and Howell Class III). Digital scans were performed using iTero Element 5D and Trios 5 scanners (n = 10 scans per group), with and without a modified technique incorporating standardized reference points (1 mm diameter, 5 mm intervals) and systematic soft tissue management. A conventional impression-derived digital model served as the reference standard. Accuracy assessment utilized best-fit alignment and root mean square (RMS) calculations through Geomagic Control X software (version 2020.1.1). Results: The modified technique demonstrated significantly improved accuracy (Groups C/D: 57.8–59.7 μm) compared to standard protocols (Groups A/B: 66.9–68.2 μm) (p < 0.001). Mean scanning times were reduced by 37% with the modified technique (2:10 ± 0:09 min vs. 3:24 ± 0:15 min). Inter-operator reliability showed excellent agreement (ICC = 0.92, 95% CI: 0.88–0.95). Soft tissue management significantly improved vestibular area accuracy (48.7 ± 6.3 μm vs. 72.4 ± 8.9 μm, p < 0.001). Conclusions: The proposed scanning strategy incorporating reference points and systematic soft tissue management significantly improved both accuracy and efficiency in digital impressions of edentulous arches. The technique showed excellent reproducibility and potential clinical applicability across different scanner systems. These findings warrant validation through larger-scale clinical trials to establish definitive protocols for digital impression-taking in edentulous patients. Full article

High-precision, low-power MEMS accelerometers are extensively utilized across civilian applications. Closed-loop accelerometers employing switched-capacitor (SC) circuit topologies offer notable advantages, including low power consumption, high signal-to-noise ratio (SNR), and excellent linearity. Addressing the critical demand for high-precision, low-power MEMS accelerometers in modern geophones, this work focuses on the design and implementation of closed-loop interface ASICs (Application-Specific Integrated Circuits). The proposed interface circuit, based on switched-capacitor modulation technology, incorporates a low-noise charge amplifier, sample-and-hold circuit, integrator, and clock divider circuit. To minimize average power consumption, a switched operational amplifier (op-amp) technique is adopted, which temporarily disconnects idle op-amps from the power supply. Additionally, a class-AB output stage is employed to enhance the dynamic range of the circuit. The design was realized using a standard 0.35 μm CMOS process, culminating in the completion of layout design and small-scale engineering fabrication. The performance of the MEMS accelerometers was evaluated under a 3.3 V power supply, achieving a power consumption of 3.3 mW, an accelerometer noise density below 1 μg/√Hz, a sensitivity of 1.65 V/g, a measurement range of ±1 g, a nonlinearity of 0.15%, a bandwidth of 300 Hz, and a bias stability of approximately 36 μg. These results demonstrate the efficacy of the proposed design in meeting the stringent requirements of high-precision MEMS accelerometer applications. Full article