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In recent years, robot manipulator arms have become increasingly prevalent and are playing pivotal roles across various industries. Their ability to replace human labor in arduous and hazardous tasks has positioned them as indispensable assets. Consequently, there has been a surge in research efforts aimed at enhancing their operational performance. The imperative to improve their efficiency and effectiveness has garnered significant attention within the research community. In this study, a novel fault-tolerant control (FTC) scheme for robot manipulators to handle the effects of the unknown input is proposed to aid robots in achieving good tracking performance. In the first step, an extended state observer (ESO) is constructed to approximate both velocities and the unknown input in the robot system. The observer offers estimation information with good accuracy and quick convergence. The estimated signals are then combined with computed torque control (CTC), which is a useful control technique for trajectory tracking of robot manipulator systems, to construct an active FTC to decrease the influences of the unknown input. The proposed algorithm does not require velocity measurement in the design process. In addition, with a novel design approach, the combination of controller and observer provides a novel control signal that delivers higher tracking performance compared to the traditional design approach. The global and asymptotic stability of the suggested technique is proved through the Lyapunov theory. Finally, simulations are implemented on a 2-degree-of-freedom (DOF) robot manipulator to validate the efficiency of the proposed controller–observer method.

Wind power is increasingly seen as a global, sustainable, and eco-friendly energy option. However, one significant obstacle to further wind energy investment is the high failure rate of wind turbines. The gearbox plays a pivotal role in turbine performance. In recent years, there has been a surge in the focus on gearbox fault diagnosis, reflecting its criticality and prevalence in the industry. Time synchronous averaging (TSA) is a primary technique to identify faults in wind turbine gearboxes using mechanical vibration signals. Generally, implementing TSA requires a device that is capable of recording the phase information of a rotary shaft. Nevertheless, there are situations in which the installation of such a device poses difficulties. For instance, gearboxes that are in use cannot be halted to allow for the installation of a device, and sealed gearboxes provide challenges while being inserted into the device. This research presents an innovative technical way to improve the TSA method without requiring a phase signal. The proposed method has the advantage of extracting the shaft rotation angle signal from the measured acceleration signal, even in non-stationary conditions where the rotational speed varies over time. The effectiveness of the proposed method is validated through measured datasets from wind turbine gearboxes with actual faults and a dataset from a gear system with variable rotational speeds.

Abstract This study aimed to develop a robust predictive model for tetracycline (TC) adsorption onto biochar (BC) by employing machine learning techniques to investigate the underlying driving factors. Four machine learning algorithms, namely Random Forest (RF), Gradient Boosting Decision Tree (GBDT), eXtreme Gradient Boosting (XGBoost) and Artificial Neural Networks (ANN), were used to model the adsorption of TC on BC using the data from 295 adsorption experiments. The analysis revealed that the RF model had the highest predictive accuracy (R2 = 0.9625) compared to ANN (R2 = 0.9410), GBDT (R2 = 0.9152), and XGBoost (R2 = 0.9592) models. This study revealed that BC with a specific surface area (S (BET)) exceeding 380 cm3·g−1 and particle sizes ranging between 2.5 and 14.0 nm displayed the greatest efficiency in TC adsorption. The TC-to-BC ratio was identified as the most influential factor affecting adsorption efficiency, with a weight of 0.595. The concentration gradient between the adsorbate and adsorbent was demonstrated to be the principal driving force behind TC adsorption by BC. A predictive model was successfully developed to estimate the sorption performance of various types of BC for TC based on their properties, thereby facilitating the selection of appropriate BC for TC wastewater treatment.

Cellular agriculture holds the potential to address sustainability, food security, and agricultural resilience. Within the cell-based meat supply chain, one of the key steps is developing sustainable scaffolding. In this study, we evaluated the impact of decellularized banana leaves, various coating materials including soy protein and gelatine, and different cell seeding strategies on cell viability, cell growth, cell alignment, and the response of the materials to thermal processing. Kinetics of the quality degradation of the scaffolds with and without cells were determined through kinetics equations. The efficiency of decellularization was verified through DNA quantification, which decreased from 445 ng/mg in fresh banana leaves to non-detectable levels in the decellularized samples. The alignment of cells on gelatin-coated samples was the highest among the samples, with a dominant orientation of 65.8°, compared to soy-coated and uncoated samples, with dominant orientations of 9.2° and −6.3°, respectively. The kinetics of shrinkage indicated that coating with soy and the presence of cells increased the activation energy due to the higher energy required for protein denaturation. The kinetics of area changes in plain scaffolds without cells followed a first-order pattern, while with seeded cells a second-order pattern was followed. Overall, the results showed that decellularized banana leaves provide sustainable scaffoldings for cellular agriculture applications. In addition, soy coating provided many benefits for decellularized samples by supporting cell adhesion and cell proliferation.

Lipoarabinomannan (LAM) is a promising target biomarker for diagnosing subclinical and clinical tuberculosis (TB). Urine LAM (uLAM) testing using rapid diagnostic tests (RDTs) has been approved for people living with HIV (PLWH), however there is limited data regarding uLAM levels in HIV-negative (HIV-ve) adults with clinical TB. We conducted a clinical study of adults presenting with clinical TB-related symptoms at the National Lung Hospital in Hanoi, Vietnam. The uLAM concentrations were measured using electrochemiluminescent (ECL) immunoassays and compared to a microbiological reference standard (MRS) using GeneXpert Ultra and TB culture testing. Estimated uLAM concentrations above plate specific calculated limit of detection (LOD) were considered uLAM positive. Additional microbiological testing was conducted for possible extrapulmonary TB (EPTB). Among 745 participants enrolled, 335 (44.9%) participants with presumptive pulmonary TB (PTB) and 6 (11.3%) participants with presumptive EPTB had confirmed TB disease. Overall, the S/A antibody pair had a sensitivity of 39% (95% Confidence Interval [CI] 0.33, 0.44) and a specificity of 97% (95% CI 0.96, 0.99) compared to the MRS. The F/A antibody pair had a sensitivity of 41% (95% CI 0.35, 0.47) and a specificity of 79% (95% CI 0.75, 0.84). S/A provided greater discriminatory ability compared to F/A for both individuals with presumptive PTB (AUROC: 0.74 vs 0.63, p

The alkylation reaction was used to couple zerumbone with the 3-substituted quinazolinone-4(3H)-ones and quinolines, resulting in the formation of 11 new conjugates. Their structures were fully characterized by 1D-, 2D-NMR, and HRMS spectral data. The evaluation of their anti-inflammatory activity was examined by inhibiting NO production in RAW 267.4 cells. Screening for their cytotoxic activity was performed using three human cancer cell lines HepG2, SK-LU-1, and MCF-7. The results indicated that all 11 novel conjugates exhibited potent cytotoxic activity against the tested cell lines with IC50 values in the range of 1.01–9.86 µg/mL, which were stronger than those of the parent compound zerumbone. In silico EGFR inhibitory activity was also performed by docking and molecular dynamics simulation studies to find out the most potent compounds based on the main interactions of zerumbone derivatives 16a-k with important amino acids of EGFR (PDB ID 4HJO) protein in its active site.