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ObjectiveAbnormal cognitive functioning is a core symptom of Major Depressive Disorder (MDD) and is strongly correlated with MDD prognosis. Current studies suggest that the occurrence of MDD may be related to oxidative stress-induced inflammation, hypothalamic-pituitary-adrenal axis disorders, diminished monoamine function and microbe-brain-gut axis, among other pathways. In recent years, the relationship between the immune-inflammatory response and MDD has been a hot topic of research, but how the relationship between immunoinflammation and cognitive function is manifested in MDD is still unclear. In this study, we examined cognitive function characteristics, serum inflammatory factors, brain-derived neurotrophic factor, and their correlations before and after pharmacological treatment(paroxetine hydrochloride tablets) in patients with first-episode major depressive disorder, aiming to identify objective biomarkers for cognitive function assessment.MethodsWe included 22 patients with first-episode major depressive disorder and 27 healthy volunteers from the community during the same period. The Hamilton Depression Scale-17 (HAMD-17) assessed the severity of depressive symptoms at baseline and after 8 weeks of treatment. The Repeatable Battery for the Assessment of Neuropsychological Status(RBANS) evaluated cognitive function, and serum samples were collected to determine levels of inflammatory and neurotrophic factors at these two time points. For healthy volunteers, only HAMD-17 scale scores, RBANS scale scores, and serum samples were taken at baseline. Spearman’s correlation analyzed the relationship between inflammatory factors, neurotrophic factors, and cognitive function. Multiple linear regression determined factors affecting cognitive function in first-time patients.ResultsBaseline findings indicated that patients’ IL-6 and TNF-α levels exceeded those of healthy individuals, while their IFN-α levels were below; their scores in language, attention, delayed memory, and the RBANS scale were also lower than healthy counterparts. Post-treatment, patients’ BDNF, IL-6, and TNF-α levels remained higher than those of healthy subjects, and their IFN-α levels were still lower; their language and attention scores were also inferior. Association analyses revealed an association between BDNF and visuospatial/constructional ability scores and language scores in patients with MDD at baseline, and a positive relationship between TNF-α and attention score. Multiple regression analysis indicated an association between TNF-α levels and attention scores in MDD patients at baseline.ConclusionsOur study concludes that TNF-α and BDNF correlate with cognitive function in MDD at baseline, and furthermore, TNF-α could potentially serve as an objective biomarker to support the assessment of attentional function at baseline.

Based on the Kim-Kim-Suzuki (KKS) phase field model coupled with the thermodynamic parameters, the transformation process from columnar dendrites to equiaxed crystals during directional solidification of aluminium alloy was simulated, and the effects of phase field parameters on the growth morphology and dendrite segregation were discussed. Furthermore, considering the effect of the microcosmic flow field, the convection influence gradient term is introduced into KKS formula near the solid-liquid interface, and the phase field model considering flow field was applied to the inherent convective environment of the actual roll casting process, also the multiple dendrites growth behavior of magnesium alloy under the action of microscopic convection was further explored. When coupling calculation of microscopic velocity field and pressure field, the staggered grid method was used to deal with the complex interface. The combined solution of Marker in Cell (MAC) algorithm and phase field discrete calculation was realized. In order to further describe the influence of convection on the solidification process, the roll casting experiments are used to verify the impact growth of multiple dendrites under convection. The results show that the dendrites undergo solute remelting and the dendrites melt into equiaxed crystals, showing the phenomenon of Columnar to Equiaxed Transition (CET).

In recent decades, there has been increasing interest in elucidating the role of sulfur-containing compounds in plant metabolism, particularly emphasizing their function as signaling molecules. Among these, thiocyanate (SCN−), a compound imbued with sulfur and nitrogen, has emerged as a significant environmental contaminant frequently detected in irrigation water. This compound is known for its potential to adversely impact plant growth and agricultural yield. Although adopting exogenous SCN− as a nitrogen source in plant cells has been the subject of thorough investigation, the fate of sulfur resulting from the assimilation of exogenous SCN− has not been fully explored. There is burgeoning curiosity in probing the fate of SCN− within plant systems, especially considering the possible generation of the gaseous signaling molecule, hydrogen sulfide (H2S) during the metabolism of SCN−. Notably, the endogenous synthesis of H2S occurs predominantly within chloroplasts, the cytosol, and mitochondria. In contrast, the production of H2S following the assimilation of exogenous SCN− is explicitly confined to chloroplasts and mitochondria. This phenomenon indicates complex interplay and communication among various subcellular organelles, influencing signal transduction and other vital physiological processes. This review, augmented by a small-scale experimental study, endeavors to provide insights into the functional characteristics of H2S signaling in plants subjected to SCN−-stress. Furthermore, a comparative analysis of the occurrence and trajectory of endogenous H2S and H2S derived from SCN−-assimilation within plant organisms was performed, providing a focused lens for a comprehensive examination of the multifaceted roles of H2S in rice plants. By delving into these dimensions, our objective is to enhance the understanding of the regulatory mechanisms employed by the gasotransmitter H2S in plant adaptations and responses to SCN−-stress, yielding invaluable insights into strategies for plant resilience and adaptive capabilities.

Water hammer diagnostics is an important fracturing diagnosis technique to evaluate fracture locations and other downhole events in fracturing. The evaluation results are obtained by analyzing shut-in water hammer pressure signal. The field-sampled water hammer signal is often disturbed by noise interference. Noise interference exists in various pumping stages during water hammer diagnostics, with significantly different frequency range and energy distribution. Clarifying the differences in frequency range and energy distribution between effective water hammer signals and noise is the basis of setting specific filtering parameters, including filtering frequency range and energy thresholds. Filtering specifically could separate the effective signal and noise, which is the key to ensuring the accuracy of water hammer diagnosis. As an emerging technique, there is a lack of research on the frequency range and energy distribution of effective signals in water hammer diagnostics. In this paper, the frequency range and energy distribution characteristics of field-sampled water hammer signals were clarified quantitatively and qualitatively for the first time by a newly proposed comprehensive water hammer segmentation-energy analysis method. The water hammer signals were preprocessed and divided into three segments, including pre-shut-in, water hammer oscillation, and leak-off segment. Then, the three segments were analyzed by energy analysis and correlation analysis. The results indicated that, one aspect, the frequency range of water hammer oscillation spans from 0 to 0.65 Hz, considered as effective water hammer signal. The pre-shut-in and leak-off segment ranges from 0 to 0.35 Hz and 0--0.2 Hz respectively. Meanwhile, odd harmonics were manifested in water hammer oscillation segment, with the harmonic frequencies ranging approximately from 0.07 to 0.75 Hz. Whereas integer harmonics were observed in pre-shut-in segment, ranging from 6 to 40 Hz. The other aspect, the energy distribution of water hammer signals was analyzed in different frequency ranges. In 0--1 Hz, an exponential decay was observed in all three segments. In 1--100 Hz, a periodical energy distribution was observed in pre-shut-in segment, an exponential decay was observed in water hammer oscillation, and an even energy distribution was observed in leak-off segment. In 100--500 Hz, an even energy distribution was observed in those three segments, yet the highest magnitude was noted in leak-off segment. In this study, the effective frequency range and energy distribution characteristics of the field-sampled water hammer signals in different segments were sufficiently elucidated quantitatively and qualitatively for the first time, laying the groundwork for optimizing the filtering parameters of the field filtering models and advancing the accuracy of identifying downhole event locations. [ABSTRACT FROM AUTHOR]

In this paper, the problem of adaptive fuzzy tracking control is considered for a class of uncertain nonaffine nonlinear systems with external disturbances, multiple time delays, and nonsymmetric saturation constrains. First, the mean value theorem is employed to deal with the nonaffine term with input nonlinearity. Then, a new adaptive fuzzy tracking controller with parameter updating laws is designed by using fuzzy approximation technique. Moreover, it is shown that all the closed-loop signals are bounded and the tracking errors can asymptotically converge to zero via the Lyapunov stability analysis. Finally, the simulation example for van der Pol oscillator system is worked out to verify the effectiveness of the proposed adaptive fuzzy design approach.

Fracture propagation is affected by multi-metal-veins formed by geological diagenesis in shale during the hydraulic fracturing. However, the influence of multi-metal-veins on fractures propagation remains unclear. To solve the problem, based on the semi-circle bending (SCB) test and the extended finite element (XFEM) theory, the interaction between multi-metal-veins and fractures is investigated. The experimental results reveal that the fractures usually deflect at the upper or lower interfaces between metal veins and rocks (e.g. the specimen S-2), which is different from the propagation behavior of fractures in calcite veins. Meanwhile, the fracture toughness of the specimen S-1 is 24.40% higher than that of the specimen S-2, indicating that the increasing of total thickness of multiple metal veins increases the resistance to the fracture vertical propagation. The simulation results show that the increasing of the number, total thickness of veins, the modulus difference between veins and rock, the approach angle and the notch angle all increase the resistance of the fracture passing through metal veins. The maximum deviation distance (Dmax) of the fracture decreases with the number of veins, while thickness combination types of metal veins do not affect Dmax. The reduction of the notch angle leads to the more tortuous fracture propagation path. Finally, we propose a new comprehensive fracture network pattern. Fracture networks are divided into two categories, including orthogonal fracture networks and sub-orthogonal fracture networks, and then divided into six sub-categories further. The research results will provide reference for hydraulic fracturing of shale reservoirs containing multi-metal-veins. [ABSTRACT FROM AUTHOR]