Processing Mechanisms Research Articles

Cognitive flexibility and affective flexibility: Processing mechanisms and impact on mental health

Cognitive flexibility and affective flexibility: Processing mechanisms and impact on mental health

THE EFFECT OF ELECTRIC PULSE TREATMENT ON THE PROPERTIES OF HEMP FIBRE

The production of competitive textile products can be ensured by using natural, environmentally friendly fibres, which include hemp fibre, as raw materials. To expand the possibility of its use, an essential operation is the pre-treatment of the fibre. The use of electric pulse processing of hemp fibre will provide the ability to control the depth of cottonization, select optimal parameters that collectively evaluate the spinning ability of the fibre and correspond to the permissible similar indicators of cotton fibre. The purpose of the work done is to study the mechanism of electric pulse processing of hemp fibre by identifying its structural characteristics under various processing modes for further use. The work carried out studies of the process of cottonization of hemp fibre by a physical-mechanical method using an electric pulse discharge from 500 to 2500 cycles. An effective mode of electric pulse processing of fibres has been established, amounting to 2500 pulses of electric discharges, which makes it possible to obtain cottonized hemp fibre with the required spinning ability. The parameters of cottonized hemp fibre have been determined, allowing the use of hemp cottonin to produce mixed yarn using a card spinning system on cotton spinning equipment.

Exploring the Effects of Different Processing Techniques on the Antitussive Expectorant of Platycodon grandiflorus by Metabonomics and Pharmacologic Methods

Background and Purpose Platycodon grandiflorum is a traditional Chinese herbal medicine, which can disperse lung, promote pharynx, dispel phlegm and expel pus. Its processing history was first seen in the “Zhou Hou Bei Ji Fang” of the Jin Dynasty in China. Through processing, effective substances in plants can be enriched and negative substances can be reduced. Therefore, this study explored the effects of different processing methods on the antitussive and expectorant effects of Platycodon grandiflorum through metabolomics and pharmacology, aiming to provide a theoretical basis for clinical application. Experimental Approach The changes of metabolites before and after processing of Platycodon grandiflorum were analyzed by Nexera UHPLC LC-30A-HILIC-Orbitrap-Q Exactive HF-X platform. The antitussive and expectorant effects of processed Platycodon grandiflorum were verified by mouse concentrated ammonia induced cough method and tracheal phenol red drainage method. Key Results After processing, some metabolites of Platycodon grandiflorum changed, among which 24 kinds of terpenoid metabolites changed significantly. Through the experiment of ammonia-induced cough in mice and phenol red expectorant experiment, it was found that fresh JZI 40%, fresh CZ 80%, dry JZZ 40% and dry JZI 80% had obvious antitussive effect, and dry JZZ 40% had obvious expectorant effect. Conclusions and Implications Some processing methods can indeed further improve the antitussive and expectorant effects of Platycodon grandiflorum, which may be due to the effect of increasing the content of triterpenoids after processing, but the mechanism of processing to improve the effect of relieving cough and expectorant needs further study.

Computer Allied Intelligence in the Education Resource-Sharing Based inContract Deep Learning

A resource-sharing platform is an online space where individuals or organizations can exchange or access various resources, such as knowledge, skills, tools, or assets. These platforms facilitate collaboration and cooperation among users by providing a centralized hub for sharing resources efficiently. In university higher education, a resource-sharing platform serves as a vital tool for students, faculty, and staff to optimize access to a wide array of educational resources. These platforms enable the sharing of academic materials, such as textbooks, lecture notes, and research papers, fostering collaborative learning environments. This paper proposed the proposed method of Distributed Consensus Blockchain Deep Learning (dCBDL) for a resource-sharing deep learning platform in higher education aims to revolutionize collaborative learning and resource utilization. Initially, the dCBDL model uses a blockchain network that serves as the underlying infrastructure for the platform. This blockchain will store transaction records, verify the authenticity of shared resources, and ensure data integrity and immutability. The proposed model uses smart contracts and decentralized storage with a consensus mechanism for data processing in higher education. Finally, the proposed dCBDL model uses the deep learning model for the classification and assessment of student performance in higher education. The proposed model achieves a classification accuracy of 98% which is significantly higher than the conventional techniques such as blockchain architecture and SVM and LSTM classifiers.

4IR Applications in the Transport Industry: Systematic Review of the State of the Art with Respect to Data Collection and Processing Mechanisms

Transportation systems through the ages have seen drastic evolutions in terms of transportation methods, speed of transport, infrastructure, technology, connectivity, influence on the environment, and accessibility. The massive transformation seen in the transportation sector has been fueled by the Industrial Revolutions, which have continued expansion and progress into the fourth Industrial Revolution. However, the methodologies of data collection and processing used by the many drivers of this progress differ. In order to achieve a better understanding of the impact of these technologies, in this study, we methodically reviewed the literature on the subject of the data collection and processing mechanisms of 4IR technologies in the context of transport. Gaps in present practices are identified in the study, especially with regard to the integration and scalability of these technologies in transportation networks. In order to fully reap the rewards of 4IR technologies, it is also necessary to apply standardized methods for data gathering and processing. In this report, we offer insights into current obstacles and make recommendations for future research to solve these concerns through a comprehensive evaluation of the literature, with the goal of promoting the development of intelligent and sustainable transportation systems.

Spatiotemporal Neural Network for Sublexical Information Processing: An Intracranial SEEG Study.

Words offer a unique opportunity to separate the processing mechanisms of object subcomponents from those of the whole object, because the phonological or semantic information provided by the word subcomponents (i.e., sublexical information) can conflict with that provided by the whole word (i.e., lexical information). Previous studies have revealed some of the specific brain regions and temporal information involved in sublexical information processing. However, a comprehensive spatiotemporal neural network for sublexical processing remains to be fully elucidated due to the low temporal or spatial resolutions of previous neuroimaging studies. In this study, we recorded stereoelectroencephalography (SEEG) signals with high spatial and temporal resolutions from a large sample of 39 epilepsy patients (both sexes) during a Chinese character oral reading task. We explored the activated brain regions and their connectivity related to three sublexical effects: phonological regularity (whether the whole character's pronunciation aligns with its phonetic radical), phonological consistency (whether characters with the same phonetic radical share the same pronunciation), and semantic transparency (whether the whole character's meaning aligns with its semantic radical). The results revealed that sublexical effects existed in the inferior frontal gyrus, precentral and postcentral gyri, temporal lobe, and middle occipital gyrus. Additionally, connectivity from the middle occipital gyrus to the postcentral gyrus and from postcentral gyrus to the fusiform gyrus was associated with the sublexical effects. These findings provide valuable insights into the spatiotemporal dynamics of sublexical processing and object recognition in the brain.Significance statement Elucidating the intricate neural mechanisms underlying sublexical processing is crucial for understanding the intricacies of language comprehension and object recognition in the human brain. This study employed intracranial stereoelectroencephalography (SEEG) recordings to investigate the spatiotemporal dynamics of sublexical processing during a Chinese character reading task. We constructed a neural network for sublexical processing and depicted its temporal sequence in different brain regions. Furthermore, we identified the information flow within this network and observed its variation with the reading of characters containing different sublexical information. These findings not only advance our understanding of the cerebral mechanisms governing sublexical processing but also offer insights into the broader framework of object recognition processes.

Widely targeted metabolomics analysis reveals the effect of soybean hull polysaccharides on nonvolatile components of plant-based yogurt and its metabolic pattern

Soybean hull polysaccharides (SHPS) enhance the physicochemical properties of plant-based yogurt. However, their effects on the nutritional profile and biochemical mechanisms remain unclear. This study aimed to assess the impact of SHPS addition on the nonvolatile components of plant-based yogurt and its underlying mechanisms through widely targeted metabolomics analysis. The results demonstrated that the addition of SHPS (0.2 %–1.0 % w/v) enhanced the levels of free amino acids, sugars, and organic acids, with the addition of 0.6 % w/v being particularly effective in improving yogurt quality. Widely targeted metabolomics analysis revealed 278 differential metabolites between yogurt supplemented with 0.6 % SHPS (SPY) and the control sample. SHPS increased the content of various metabolites, including amino acids and derivatives, saccharides, organic acids, and flavonoids, among others. Key metabolic pathways affected by SHPS included pantothenate and CoA biosynthesis; valine, leucine, and isoleucine biosynthesis; and benzoate degradation. As the primary component of SHPS, galacturonic acid affected the metabolic products in yogurt by participating in the pentose and glucuronate interconversions and ascorbate and aldarate metabolism pathways. These findings elucidate the role of SHPS in modulating the nutritional composition of plant-based yogurt, offering valuable insights into its functional mechanisms in food processing.

C-terminal residues of DNA polymerase β and E3 ligase required for ubiquitin-linked proteolysis of oxidative DNA-protein crosslinks

Free radicals produce in DNA a large variety of base and deoxyribose lesions that are corrected by the base excision DNA repair (BER) system. However, the C1′-oxidized abasic residue 2-deoxyribonolactone (dL) traps DNA repair lyases in covalent DNA-protein crosslinks (DPC), including the core BER enzyme DNA polymerase beta (Polβ). Polβ-DPC are rapidly processed in mammalian cells by proteasome-dependent digestion. Blocking the proteasome causes oxidative Polβ-DPC to accumulate in a ubiquitylated form, and this accumulation is toxic to human cells. In the current study, we investigated the mechanism of Polβ-DPC processing in cells exposed to the dL-inducing oxidant 1,10-copper-ortho-phenanthroline. Alanine substitution of either or both of two Polβ C-terminal residues, lysine-206 and lysine-244, enhanced the accumulation of mutant Polβ-DPC relative to the wild-type protein, and removal of the mutant DPC was diminished. Substitution of the N-terminal lysines 41, 61, and 81 did not affect Polβ-DPC processing. For Polβ with the C-terminal lysine substitutions, the amount of ubiquitin in the stabilized DPC was lowered by ∼40 % relative to wild-type Polβ. Suppression of the HECT domain-containing E3 ubiquitin ligase TRIP12 augmented the formation of oxidative Polβ-DPC and prevented Polβ-DPC removal in oxidant-treated cells. Consistent with the toxicity of accumulated oxidative Polβ-DPC, TRIP12 knockdown increased oxidant-mediated cytotoxicity. Thus, ubiquitylation of lysine-206 and lysine-244 by TRIP12 is necessary for digestion of Polβ-DPC by the proteasome as the rapid first steps of DPC repair to prevent their cytotoxic accumulation. Understanding how DPC formed with Polβ or other AP lyases are repaired in vivo is an important step in revealing how cells cope with the toxic potential of such adducts.

Maize Dek51 encodes a DEAD-box RNA helicase essential for pre-rRNA processing and seed development

Pre-rRNA processing is essential to ribosome biosynthesis. However, the processing mechanism is not fully understood in plants. Here, we report a DEAD-box RNA helicase DEK51 that mediates the 3' end processing of 18S and 5.8S pre-rRNA in maize (Zea mays L.). DEK51 is localized in the nucleolus, and loss of DEK51 arrests maize seed development and blocks the 3' end processing of 18S and 5.8S pre-rRNA. DEK51 interacts with putative key factors in nuclear RNA exosome-mediated pre-rRNA processing, including ZmMTR4, ZmSMO4, ZmRRP44A, and ZmRRP6L2. This suggests that DEK51 facilitates pre-rRNA processing by interacting with the exosome. Loss of ZmMTR4 function arrests seed development and blocks the 3' end processing of 18S and 5.8S pre-rRNA, similar to dek51. DEK51 also interacts with endonucleases ZmUTP24 and ZmRCL1, suggesting that it may also be involved in the cleavage at site A2. These results show the critical role of DEK51 in promoting 3' end processing of pre-rRNA.

Brain mechanisms of rumination and negative self-referential processing in adolescent depression

BackgroundDepression is linked to cognitive biases towards more negative and less positive self-relevant information. Rumination, perseverative negative thinking about the past and the self, may contribute to these biases. Methods159 adolescents (12–18 years), with a range of depression symptoms, completed the SRET during fMRI. Multiple regressions tested associations between conventional self-report and ecological momentary assessment (EMA) measured rumination, and neural and behavioral responses during a self-referent encoding task (SRET). ResultsHigher rumination (conventional self-report and EMA) was associated with more negative and fewer positive words endorsed and recalled. Higher self-reported (but not EMA) rumination was associated with higher accuracy in recognizing negative words and greater insula and dorsal anterior cingulate activity to negative versus positive words. LimitationsThe sample included mostly non-Hispanic White participants with household incomes above the national average, highlighting the need for replication in more diverse samples. Word endorsement discrepancies required fMRI analyses to model neural response to viewing negative versus positive words. ConclusionsAdolescents with higher rumination endorsed and recalled more negative and fewer positive words and recognized more negative words during the SRET. Higher insula reactivity, a key region for modulating externally-oriented attention and internally-oriented self-referential processes, may contribute to links between rumination and negative memory biases. These findings provide insight into neurocognitive mechanisms underlying depression.

Ultrafast dynamics and internal processing mechanism of silica glass under double-pulse femtosecond laser irradiation

Femtosecond laser-induced plasma filaments have potential for various applications including attosecond physics, spectroscopy, and microprocessing. However, the use of plasma filaments to generate high-aspect-ratio internal modifications remains low-efficiency. Here, we experimentally demonstrated high-efficiency internal processing using plasma filaments induced by a double-pulse femtosecond laser. The processing mechanism was revealed through an investigation of the ultrafast dynamics of plasma filaments in experiments and simulations. We found that the excitation region of the first pulse (P1) exerted a temporal effect on the propagation and absorption of the second pulse (P2) due to the evolution of excited electrons, thus resulting in different processing characterizations. At a smaller inter-pulse delay (IPD), electrons and self-trapped excitons induced by P1 improved the absorption of P2 in the shallow region. Consequently, the main excitation regions of P1 and P2 were separated, resulting in a lower density of energy deposition and weak modifications. Whereas, at a larger IPD, P2 penetrated a deeper region with the relaxation of electrons and excitons induced by P1, leading to a better overlap of excitation regions between P2 and P1, thus improving the density of energy deposition and achieving efficient microprocessing. Besides, at an infinite IPD, P2 behaved like P1, but no modification was obtained owing to the complete energy diffusion of P1. Therefore, controlling the electron dynamic and energy diffusion contributes to the improvement of modification efficiency. Furthermore, the distribution of electron densities on the cross section was estimated to precisely analyze the microprocessing. These results are expected to aid in a better understanding of the interaction mechanism between dielectrics and intense ultrafast lasers and be useful for microprocessing applications.

A Systemic Review of the Brain Mechanism of Humor Processing

As a universal linguistic phenomenon, humor has gradually become an interdisciplinary research topic. Domestic and international scholars have expanded the study of humor, yet there is a paucity of evaluations on the brain mechanisms underlying humor perception. This paper primarily introduces the concept of humor, the major theoretical frameworks of humor, and the key findings from domestic and international research on the neural mechanisms of humor. Furthermore, this paper synthesizes the existing issues in humor research in order to provide clues and guidance for future investigations of humor.

Robust iterative value conversion: Deep reinforcement learning for neurochip-driven edge robots

A neurochip is a device that reproduces the signal processing mechanisms of brain neurons and calculates Spiking Neural Networks (SNNs) with low power consumption and at high speed. Thus, neurochips are attracting attention from edge robot applications, which suffer from limited battery capacity. This paper aims to achieve deep reinforcement learning (DRL) that acquires SNN policies suitable for neurochip implementation. Since DRL requires a complex function approximation, we focus on conversion techniques from Floating Point NN (FPNN) because it is one of the most feasible SNN techniques. However, DRL requires conversions to SNNs for every policy update to collect the learning samples for a DRL-learning cycle, which updates the FPNN policy and collects the SNN policy samples. Accumulative conversion errors can significantly degrade the performance of the SNN policies. We propose Robust Iterative Value Conversion (RIVC) as a DRL that incorporates conversion error reduction and robustness to conversion errors. To reduce them, FPNN is optimized with the same number of quantization bits as an SNN. The FPNN output is not significantly changed by quantization. To robustify the conversion error, an FPNN policy that is applied with quantization is updated to increase the gap between the probability of selecting the optimal action and other actions. This step prevents unexpected replacements of the policy’s optimal actions. We verified RIVC’s effectiveness on a neurochip-driven robot. The results showed that RIVC consumed 1/15 times less power and increased the calculation speed by five times more than an edge CPU (quad-core ARM Cortex-A72). The previous framework with no countermeasures against conversion errors failed to train the policies. Videos from our experiments are available: https://youtu.be/Q5Z0-BvK1Tc.

Effect of process parameters on the mechanical properties of wires produced from A356 aluminum alloy chips by Continuous Friction Stir Extrusion: Experiments and numerical simulation

Recycling of metals is becoming crucial from an economic and environmental point of view. The solid-state recycling process Continuous Friction Stir Extrusion was used to produce wires out of A356-T6 chips. The mechanical properties of the produced wires were explored by varying the main process parameters. Characterization involved Vickers hardness tests, tensile tests, grain size measurements, and fracture surface analysis. It has been found that it is possible to achieve 77 % of the Ultimate Tensile Strength (UTS) and 92 % of Vickers hardness with respect to the as-fabricated A356 alloy. The average grain size increases with the tool rotational with values ranging from about 9 µm to about 11 µm. A 3D dedicated numerical model was used to predict the distributions and histories of primary field variables, and to calculate the Piwnik-Plata parameter, fostering a more in-depth understanding of the process mechanics. This allows for the precise prediction of unacceptable product quality of the bonding when the Plata and Piwnik parameters are low. Predicted temperature close to the rotating tool should reach 400 °C while the cochlea temperature should be below 100 °C for sound wires production thus avoiding early chip bonding and process failure.

Towards a better understanding of the surface smoothing effect in gas cluster ion beam processing with molecular dynamics simulation and experiment

In recent years, the application of gas cluster ion beam (GCIB) technology has made great progress. Due to the similar essence of a monoatomic ion beam, the GCIB also shows flashes of brilliance in material processing. It has been reported that smoothness can be greatly improved after the rough surface is bombarded by the GCIB. This indicates that the GCIB processing has great potential in optical fabrication. Although the surface smoothing effect has been investigated, there is still a lack of dynamic micro-analysis for GCIB processing, which is limited for better understanding the mechanism of smoothing effect. In this paper, the surface smoothing effect in GCIB processing is explicitly investigated with molecular dynamics (MD) simulation and experiment. The principle of GCIB processing is compared with the traditional monoatomic ion-beam based processing, and details of the MD simulation procedure are introduced. Based on this, the dynamic micro-analysis of GCIB processing is conducted under different processing conditions. The simulations reveal the phenomena of atomic removal and migration in GCIB processing, which plays an important role in explaining the mechanism of surface smoothing effect. The experiment was performed on the silicon substrate with the in-house GCIB processing machine. The results indicate that the initial rough surface with dense protrusions can be greatly smoothed, and the root mean square (RMS) value is reduced from 0.586 nm to 0.191 nm. Both simulation and experiment can provide a better understanding of smoothing effect mechanism in GCIB processing.

An Insight into the Mechanism of DNA Cleavage by DNA Endonuclease from the Hyperthermophilic Archaeon Pyrococcus furiosus.

Hyperthermophilic archaea such as Pyrococcus furiosus survive under very aggressive environmental conditions by occupying niches inaccessible to representatives of other domains of life. The ability to survive such severe living conditions must be ensured by extraordinarily efficient mechanisms of DNA processing, including repair. Therefore, in this study, we compared kinetics of conformational changes of DNA Endonuclease Q from P. furiosus during its interaction with various DNA substrates containing an analog of an apurinic/apyrimidinic site (F-site), hypoxanthine, uracil, 5,6-dihydrouracil, the α-anomer of adenosine, or 1,N6-ethenoadenosine. Our examination of DNA cleavage activity and fluorescence time courses characterizing conformational changes of the dye-labeled DNA substrates during the interaction with EndoQ revealed that the enzyme induces multiple conformational changes of DNA in the course of binding. Moreover, the obtained data suggested that the formation of the enzyme-substrate complex can proceed through dissimilar kinetic pathways, resulting in different types of DNA conformational changes, which probably allow the enzyme to perform its biological function at an extreme temperature.

A feature detection network based on self-attention mechanism for underwater image processing

Underwater image processing is seriously challenged by the absorption and scattering of light in water. This paper introduces a self supervised learning network that utilizes self attention mechanism for underwater visual applications. The goal is to improve the effectiveness and stability of underwater image feature detection. The combination of self attention mechanism enhances the sensitivity of the original network architecture to degraded features in blurred underwater images. A modified underwater image synthesis method is proposed for network training and evaluation to address the difficulties and high costs of obtaining underwater images. And a step-by-step training method was proposed, proving the effectiveness of this training method. The proposed network is trained using a step-by-step method and evaluated on various underwater image datasets. The experimental results show that the algorithm outperforms other methods in distribution, quantitative, and qualitative measurements, and exhibits enhanced feature detection ability in blurred images as water turbidity increases.

Attentional dynamics of evidence accumulation explain why more numerate people make better decisions under risk

In decisions under risk, more numerate people are typically more likely to choose the option with the highest expected value (EV) than less numerate ones. Prior research indicates that this finding cannot be explained by differences in the reliance on explicit EV calculation. The current work uses the attentional Drift Diffusion Model as a unified computational framework to formalize three candidate mechanisms of pre-decisional information search and processing—namely, attention allocation, amount of deliberation, and distorted processing of value—which may differ between more and less numerate people and explain differences in decision quality. Computational modeling of an eye-tracking experiment on risky choice demonstrates that numeracy is linked to how people allocate their attention across the options, how much evidence they require before committing to a choice, and also how strongly they distort currently non-attended information during preference formation. Together, especially the latter two mechanisms largely mediate the effect of numeracy on decision quality. Overall, the current work disentangles and quantifies latent aspects of the dynamics of preference formation, explicates how their interplay may give rise to manifest differences in decision quality, and thereby provides a fully formalized, mechanistic explanation for the link between numeracy and decision quality in risky choice.

Study on the polishing performance and mechanism of sapphire wafers by different types of degradable surfactants

Traditional chemical-mechanical polishing (CMP) slurry suffers from significant environmental pollution, and easy reaggregation of ultra-fine abrasives, all of which hinder its further application. In this study, the processing performance and mechanism of three different degradable surfactants to sapphire wafers were investigated, utilizing degradable aminomethylpropanol and xylitol as pH regulator and complexing agent of polishing slurry, respectively, which is aimed at solving the problem of the easy agglomeration of ultra-fine abrasives while achieving the super-precision and pollution-free process of sapphire wafers. After polishing, the surface roughness (Sa) of sapphire wafers decreases from 7.240 nm to 0.396 nm, which is 44.8 % lower than that without surfactant. Only <1 nm is the PV value, and there is a 12.9 % increase in the material removal rate. The action mechanism of biodegradable surfactants during CMP was revealed through TEM, XPS, electrochemical testing, contact angle measurement, and particle size analysis. The results showed that surfactants can effectively improve the wettability of the polishing slurry on the wafer and the dispersity of the ultra-fine abrasives in the slurry, thus facilitating the interfacial reaction between the sapphire surface and polishing slurry and the homogeneity of the material removal. This work truly realizes a green and pollution-free process that meets the requirements of ultra-smooth and efficient polishing of sapphire wafers.

The More, the Better? Exploring the Effects of Modal and Codal Redundancy on Learning and Cognitive Load: An Experimental Study

This study explores how receiving identical information from different sources affects learning and cognitive load, focusing on two types of redundancy: modal redundancy, where redundant information comes from two visual sources (images and written text), and codal redundancy, where redundant information comes from two sources of different modalities which utilize the same symbol system (spoken and written text). Using a 2 × 2 between-subjects design involving modal (yes/no) and codal (yes/no) redundancy, 158 participants completed twenty learning tasks, consisting of ten construction and ten recall tasks. Additionally, they rated their cognitive load by indicating their perceived task difficulty and mental load. Overall, results indicate positive main effects of modal redundancy and negative effects of codal redundancy on learning and cognitive load. Furthermore, significant interaction effects suggest that modal redundancy may counterbalance the negative effects of codal redundancy, implying a compensatory mechanism in cognitive processing for construction tasks. These results highlight the importance of considering both modal and codal redundancy and their interaction in instructional design.