The problem of robust output tracking control is considered for a class of uncertain nonlinear systems with full state constraints. Such a class of uncertain nonlinear systems have a similar structure to uncertain strict-feedback nonlinear systems with virtual control coefficients, and is called quasi-strict-feedback nonlinear systems. Moreover, the system uncertainties are not required to satisfy strict triangularity condition or any other matching conditions, and are only assumed to mathematically guarantee the existence of solutions to differential equations which describe some actual systems, and to not destroy the stabilisability of any uncertain systems. In this paper, such a class of uncertainties is called universal uncertainties. For such a class of uncertain nonlinear systems, based on an integral inequality approach, instead of Lyapunov stability theory, by combining the self-compensating and self-tuning approach with the nonlinear transformed functions (NTFs), a class of output tracking control schemes with a rather simple structure is proposed such that (i) all the system states satisfy the state constraints; and (ii) the output tracking error is uniformly exponentially bounded. Finally, a numerical example similar to those that have been considered in control literature are given to demonstrate the simplicity of the proposed design approach.
General movements (GMs) refer to infants’ spontaneous motor activities before the emergence of voluntary motor activity. Abnormal GMs in neonates have been regarded as a marker of poor neurodevelopmental outcomes, with preliminary findings in autism. To examine the relation between abnormal GMs in neonates and autism risk, videos of neonates (n = 76) extracted from a Japanese birth cohort were retrospectively exploited. A manual assessment of GMs was completed using the General Movement Assessment Optimality Score (GMOS-R) rated by professionals blinded from all clinical information. An automated assessment of several features of neonates’ motor activity was also conducted using videos of neonates. Outcome measures were the M-CHAT score at 18 months to document autistic risk status and the Strengths and Difficulties Questionnaire (SDQ) at four years to measure non-autistic general psychopathology. The GMOS-R total score and subscores significantly predicted the autistic risk status according to M-CHAT, but not any SDQ scales or the Total Difficulties score. In the manual assessment of GM, “Global poorness of motion” was the most informative feature in predicting ASD risk. The classification performance systematically increased with the addition of automatically extracted features, as indicated by the Loglikelihood tests. In contrast, the DeLong tests for comparison of AUC failed to reach statistical significance. Such improvement came mainly from incorporating information about the imbalance in motion strength between the upper and lower limbs, and was more marked for awake babies. This finding confirms the relevance of considering abnormal motor patterns in neonates as an early marker of autistic risk.
This study investigates the impact of low-pressure cold plasma (LPCP) on the properties of dried chili pods (Capsicum annuum L.). LPCPs were applied at 0, 10, and 20 W for 5, 10, and 15 min, including a control group (P5M0W-P15M0W), with plasma energy inputs of 3.0-18.0 kJ, and all analyses were completed within 48h after treatment. Statistical analysis revealed significant effects of power, time, and their interaction (p < 0.001). LPCP reduced moisture (9.3 to 5.9%), volatile oil (2.2 to 1.0%), and hardness (20.6 to 3.9N). Capsanthin declined from 8.75 to 1.24g kg(-1)DW. Capsaicin and dihydrocapsaicin decreased from 1.75 and 0.70-1.18 and 0.47 mg g(-1)DW, respectively, reducing pungency from 3923 to 2649 SHU. Total phenolics decreased from 194 to 144 mgGAE 100g(-1)DW, whereas flavonoids increased up to 14.8 mgQE 100g(-1)DW. Ascorbic acid declined (2.38 to 1.42 mg g(-1)DW), but antioxidant activity (DPPH) remained stable (46.7%-49.7%). Microbial load was reduced by >2.5 log (4.54 to 1.93 log(CFU g(-1))). Regression confirmed strong dose-response relationships for bioactive degradation and microbial inactivation (R-2 = 0.725-0.988). LPCP improved microbial safety of dried chili pods, but caused significant losses in color and pungency. Further optimization is needed to balance microbial inactivation with quality retention.
Microtubules are dynamic cytoskeletal polymers whose lattice architecture regulates force generation, nucleotide hydrolysis, and recognition by motor proteins and microtubule-associated proteins (MAPs). Microtubule-stabilizing agents (MSAs), including taxanes and laulimalide/peloruside-site ligands, suppress depolymerization by binding to defined lattice sites, yet stabilization is not structurally neutral. How ligand chemistry reshapes lattice organization and function remains unresolved. Here, we address three mechanistic questions. First, do distinct ligand classes induce defined lattice states? Using X-ray fiber diffraction, we show that MSAs selectively stabilize two preferred longitudinal conformations, a compact state (~4.06 nm monomer rise) and an expanded state (~4.17 nm), while modulating lateral organization reflected in shifts in mean MT radius. These axial spacings cluster around discrete values across chemotypes, indicating stabilization of preexisting conformational minima rather than continuous distortion. Second, are these states interconvertible upon changes in ligand occupancy? Time-resolved diffraction reveals that longitudinal transitions occur within seconds of ligand addition even at substoichiometric occupancy, whereas, lateral equilibration proceeds slower, consistent with redistribution within heterogeneous protofilament organizations. Third, do such structural states alter nucleotide hydrolysis and motor/MAP behavior? Expanded lattices are associated with reduced apparent GTP hydrolysis rates under steady-state assembly conditions and altered kinesin motility, whereas compact lattices preferentially promote tau binding and distinct motor interaction profiles. Together, these findings establish longitudinal lattice conformation as a regulatory parameter and position MSAs as chemical tools that bias a dynamic structural landscape with predictable catalytic and transport consequences.
This study examines the impact of generative artificial intelligence (GenAI) advice on ethical judgment in accounting and auditing, particularly in comparison to conditions involving no advice and/or advice from a human auditor. We employ an experimental design, in which the independent variable consists of five distinct advice conditions, varying by source (GenAI or human auditor) and by framing context (deontological or consequentialist). We simulate an experimental scenario in which financial controllers either consider or disregard advice from external auditors during audit negotiations. In this context, accounting majors are used as proxies for financial controllers working in the finance department. To assess how these conditions influence ethical judgment, we conducted several logistic regression analyses. Participants were accounting majors recruited from seven leading universities in Japan. The results provide compelling evidence that receiving advice, whether from GenAI or a human auditor, increases the likelihood of making a deontological judgment (i.e., a judgment grounded in moral duties, rules, or principles), compared to receiving no advice. This suggests that the impact of GenAI advice closely mirrors that of human auditors. Further analysis revealed that among participants receiving GenAI advice, those exhibiting a higher degree of algorithm appreciation (i.e., the tendency to perceive algorithmic advice as more credible) were significantly more inclined to make deontological judgments. Moreover, when comparing advice from GenAI and human auditors directly, the findings confirm that the effects of moral advice from both sources were remarkably similar. However, contextual factors played a critical role: participants with greater familiarity with consolidated accounting standards (KNOW) and those who had completed internships at accounting firms (INTER) were more likely to make deontological judgments—even when exposed to consequentialist advice (i.e., advice oriented toward maximizing overall welfare). These findings offer important implications for accounting ethics education and highlight the need to consider individual differences and contextual factors in algorithm-assisted decision-making. The study also acknowledges several limitations and suggests directions for future research.
