Characteristics Of Process Research Articles

Femtosecond laser direct writing wedge metallic microcavities for terahertz sensing

Metallic resonators allow the manipulation of electromagnetic fields in subwavelength volumes for strong light-matter interaction, underpinning emerging flat-optics devices. Metamaterials designed with optimized effective mode volume (Veff) for stimulating and maximizing the utilization of high-density photons are highly desirable for sensing applications. Here, we demonstrate a bowtie-type terahertz (THz) metallic aperture metamaterial structure with low Veff for enhanced biosensing. The device leverages the inherent characteristic of the femtosecond laser fabrication process enabling wedge cavities down to 3 µm by tailoring the pulse energy, whose sensing performance is superior to trapezoidal ones. Such a substrate-free, microcavity metallic metamaterial sensor with extremely strong interactions achieves an experimentally normalized sensitivity of 0.654 RIU−1, and demonstrates the detection of L-proline down to 0.87 nmol. These findings provide new insights into the design and optimization of efficient THz metamaterials with tightly confined fields for ultrasensitive biomolecular detection.

학습 효과가 높은 수업과 낮은 수업의 학습 과정과 평가의 특성에 관한 연구

Objectives The purpose of this study is to explore the characteristics of instructions recognized as having a high learning effect and as having a low learning effect. Methods For this purpose, we conducted written interviews using online platform with 18 prospective instructors who are experiencing the pre-instructor course at the graduate school of education. It was designed to focus on instructions experienced before, not on instructions currently being taken, and through this, the process and effect of learning could be reported more objectively. The collected qualitative data were analyzed using a thematic anal-ysis method, and the learning process of instructions with high learning effects and instructions with low learning effects were derived and presented in a diagram. Results As a result of the study, 3 main categories, 9 themes, and 19 subcategories were derived as character-istics of the learning process included in instruction with high learning effect, and the amount of learning load, dif-ficulty, and responsibility perceived by learners were also confirmed along with the learning burden factors. As for the instruction with low learning effect, 3 main categories, 9 themes, and 18 subcategories were derived, and these included ‘no task’ and ‘no burden’. In the instruction with high learning effect, the focus of assignments and evaluations was on the learning process and performance, and improvement and feedback were made through the feedback of the instructor. In the instruction with low learning effect, the focus of assignments and evaluations was on organizing, summarizing, and general evaluation, and it was difficult to confirm improvement and feedback through instructor's feedback. Moreover, the difficulty and amount of learning load in the class were burden factors that appeared in both classes with high and low learning effects. Considering these results, instructors need to consider ways to have explanatory power to effectively deliver class content by analyzing learners' levels rather than reducing the difficulty and amount of learning. Conclusions Based on these findings, recommendations were provided to guide professors in aiming for and de-signing effective instructions.

Dynamics of neuronal firing modulated by high-frequency electrical pulse stimulations at axons in rat hippocampus

Objective. The development of electrical pulse stimulations in brain, including deep brain stimulation, is promising for treating various brain diseases. However, the mechanisms of brain stimulations are not yet fully understood. Previous studies have shown that the commonly used high-frequency stimulation (HFS) can increase the firing of neurons and modulate the pattern of neuronal firing. Because the generation of neuronal firing in brain is a nonlinear process, investigating the characteristics of nonlinear dynamics induced by HFS could be helpful to reveal more mechanisms of brain stimulations. The aim of present study is to investigate the fractal properties in the neuronal firing generated by HFS. Approach. HFS pulse sequences with a constant frequency 100 Hz were applied in the afferent fiber tracts of rat hippocampal CA1 region. Unit spikes of both the pyramidal cells and the interneurons in the downstream area of stimulations were recorded. Two fractal indexes—the Fano factor and Hurst exponent were calculated to evaluate the changes of long-range temporal correlations (LRTCs), a typical characteristic of fractal process, in spike sequences of neuronal firing. Main results. Neuronal firing at both baseline and during HFS exhibited LRTCs over multiple time scales. In addition, the LRTCs significantly increased during HFS, which was confirmed by simulation data of both randomly shuffled sequences and surrogate sequences. Conclusion. The purely periodic stimulation of HFS pulses, a non-fractal process without LRTCs, can increase rather than decrease the LRTCs in neuronal firing. Significance. The finding provides new nonlinear mechanisms of brain stimulation and suggests that LRTCs could be a new biomarker to evaluate the nonlinear effects of HFS.

The Spiral Aspects of Multiverse Formation: Continuous Big Bang and Everyverse Connection

Abstract: The Spiral Multiverse Theory suggests a continuous, spiral pattern universe from the same singularity connected by a common point as everyverse, challenging the conventional Big Bang theory. Every universe starts with a bang. An interdimensional quasar serves as the portal connecting all of the universes to everyverse. Individual universes are connected, but they are observably stable. The theory offers a fresh viewpoint on cosmic evolution and a possible path for practical research by presenting the idea of interdimensional quasars as portals for multiverse travel. The research explores the unique characteristics of the multi-bang process. The study suggests that each universe undergoes its own inflation without observable changes in the cosmic microwave background.

Адаптационный потенциал сотрудников органов внутренних дел как ресурс при преодолении профессионального выгорания

Introduction. The phenomenon of “professional burnout”appears to be of special interest among scientists. Although there have been many studies of the nature of its occurrence and dynamics, there is no unity in understanding the ways to prevent and correct changes of mental and socio-psychological functions caused by personalitydeformation. According to A. K. Markova, specialists of “human-human” professions, working constantly with people, are more at risk of professional deformation than employees of “human-technology” and “human-nature” professions. Supporting this idea, we should note that under conditions of high responsibility, pressure and increasing demandsnot always corresponding the inner resources, this problem becomes especially important. The destructive effect affects mental process and personal characteristics, leading to negative changes in the professional activities of police officers. The mission of police officers to protect the public against criminals and other unlawful encroachments becomes, metaphorically speaking, “transparent” due to professional burnout, in particular, depersonalisation (negligent approach to duties and cynical attitude towards citizens). That is why, it is important to determine in time individuals being more prone to professional burnout, to reveal signs indicating its occurrence, and to develop a methodology stimulating adaptive potential and extension of tunnel thinking provoked by high stress. Methods. The following psychological methods were used: the method of assessment of adaptive abilities - “MOAS” (developed on the basis of Kettell’s Test). This method helped to assess the respondents’ personal characteristics “closeness – sociability”, “emotional instability - emotional stability”, “shyness – courage”, “trustfulness – suspiciousness”, “self-confidence – anxiety”, “relaxation – tension”; the Maslach Burnout Inventory (MBI) adapted by N. E. Vodopyanova, which helped to determine the level of professional burnout on the following three scales: emotional exhaustion, depersonalisation, and reduction of professional achievements; thePearson correlationmethod (statistical analysis of the data). Results. The results determined four groups of respondents: with high, satisfactory, low, unsatisfactory levels of adaptive potential. The majority of respondents (70.5 %) have insufficient adaptive potential for coping with stressful situations, rational assessment of requirements and personal resources. Besides, employees with low level of adaptive abilities are more prone to professional burnout, especially depersonalisation.

Morphometric characteristics as an indicator of the breeding process in carp

The study of the variability of exterior indicators in two-year-olds of three different strains of carp: the natural population of the Volga carp, the breed group of the Zagorsky carp and the butterfly carp breed. The research was carried out on the basis of the pond base of the experimental breeding farm of the VNIIPRH. It is shown that the introduction of the index of the relative size of the head to the total body surface into the analysis of a new breeding trait determines the significant discrepancy between the groups of the Volga carp and carp in the complex of morphotype features. It was found that the Volga carp is the most distant from the butterfly carp (the distance of the Mahalanobis is 13.18), as well as from the breed group of the Zagorsky carp (8,66). The breed groups of carp are located closer to each other (4.18). The greatest contribution to the separation of the studied groups of cyprinid fish is made by 7 morphotype features — body length, indices of pectoventral and antedorsal distance, length of snout, tail and dorsal fin, the ratio of head area to body area of fish. The relative head sizes of the carp breed groups are significantly higher than those of the Volga carp, which has not been selected in fish aquaculture. Thus, the head size of the Volga carp occupies 15.06%, and that of the carp after 7 generations of breeding — 15.93–16.82%. The Volga carp is characterized by higher values of body length and low values of relative head size, high back, fatness coefficient and body girth. It is shown that the relative size of the head can serve as an indicator of the difference in the breed groups of carp. An increase in the ratio of the head area to the surface of the entire fish is observed in the series: Volga carp — Zagorsky carp — butterfly. It is proposed to use this indicator as an additional characteristic of the breeding process and domestication of cyprinid fish.

Hierarchical multihead self-attention for time-series-based fault diagnosis

Fault diagnosis is important for maintaining the safety and effectiveness of chemical process. Considering the multivariate, nonlinear, and dynamic characteristic of chemical process, many time-series-based data-driven fault diagnosis methods have been developed in recent years. However, the existing methods have the problem of long-term dependency and is difficult to train due to the sequential way of training. To overcome these problems, a novel fault diagnosis method based on time-series and the hierarchical multi-head self-attention (HMSAN) is proposed for chemical process. First, a sliding window strategy is adopted to construct the normalized time-series dataset. Second, the HMSAN is developed to extract the time-relevant features from the time-series process data. It improves the basic self-attention model in both width and depth. With the multi-head structure, the HMSAN can pay attention to different aspects of the complicated chemical process and obtain the global dynamic features. However, the multiple heads in parallel lead to redundant information, which cannot improve the diagnosis performance. With the hierarchical structure, the redundant information is reduced and the deep local time-related features are further extracted. Besides, a novel many-to-one training strategy is introduced for HMSAN to simplify the training procedure and capture the long-term dependency. Finally, the effectiveness of the proposed method is demonstrated by two chemical cases. The experimental results show that the proposed method achieves a great performance on time-series industrial data and outperforms the state-of-art approaches.

Effect of jet milled ultrafine powder on porous tungsten emitter components by micro injection molding

Micro injection molding (μPIM) is currently the optimal solution for fabricating porous tungsten emitters with complex shapes. Considering the serious agglomeration of ultrafine powder, using this particle size for μPIM is detrimental to the molding of the components and the regulation of the pore structure. In this work, jet milling technology was applied as pretreatment to obtain uniformly dispersed ultrafine tungsten powder, and a needle-like porous tungsten emitter with uniform and adjustable pores was successfully prepared by μPIM. The effects of jet milling on the characteristics of ultrafine tungsten powder and μPIM process were investigated. After the jet milling treatment at 0.75 MPa and 12,000 rpm, the agglomerates in ultrafine powder were completely eliminated and the powder dispersion was optimized. The solid loading of feedstock was increased from 45% to 51%, and the corresponding rheological properties and debinding efficiency were also improved. Jet milled powder exhibited higher sintering activity and gained the same porosity (25%) at 1425 °C, lower than the 1500 °C of the as-received one. The porous tungsten obtained by jet milled powder had pores and skeletons with uniform size and distribution, which contributes to the adjustment of the pores. The pore size decreased from 338 nm to 263 nm, and the closed porosity decreased from 1.5% to 0.6%. This work is beneficial for further understanding the influence of jet milling on powder characteristics, μPIM process and pore characteristics, and highlights its potential application in the field of micro-pores complex parts.

Two-dimensional (2D) materials for 3D printed micro-supercapacitors and micro-batteries

Two-dimensional (2D) materials display a unique set of physical/chemical properties and are considered potential building blocks for the manufacturing of microstructured materials for a number of applications. Prominent applications range from advanced electronics to miniaturized electrochemical energy storage devices (EESDs). Herein, we present a comprehensive and critical review of the recent developments in design and microfabrication of 2D-driven microscale electrodes for three-dimensional (3D)-printed micro-supercapacitors and micro-batteries. Firstly, we systematically discuss the advantages and disadvantages associated with various microfabrication techniques such as stereolithography, fused deposition modeling, inkjet printing, and direct ink writing. Next, key parameters disclosing the relationship between the characteristics of 2D-based materials and extrusion-driven 3D printing process for the development of versatile and sustainable EESDs are highlighted. 2D materials utilized for the construction of microelectrodes for supercapacitors (e.g., electric double layer capacitors (EDLCs), pseudocapacitors, and hybrid capacitors) and batteries (e.g., Li-based systems and next-generation systems, e.g., sodium-ion batteries and zinc-ion batteries) along with their prominent electrochemical contributions in relation to obtained 3D-printed architectures are discussed in detail. To promote the development of 2D materials-driven high-performance microscale EESDs, the relevant challenges and future research opportunities are also addressed.

Experimental and numerical investigations into the fabrication of alumina ceramic surface microchannel by electrochemical discharge machining

The electrochemical discharge machining (ECDM) is an advanced and promising technology for fabricating micro structures. This method is effectively applicable for non-conductive hard and brittle materials micromachining, such as glass and ceramics. However, the ceramics high melting point and intense heat exchange effects during microchannel fabrication lead to the easy dissipation of thermal energy and the difficulty in processing. To address this issue and expanded the ECDM processing range. This paper dedicated to the investigation of the material removal mechanism and process characteristics for the alumina ceramic surfaces microchannels preparation. Firstly, this study explained the difference of the ECDM critical applied voltage and gas film generation mechanism by analyzing the volt-ampere characteristic curve of 20 wt% NaOH electrolyte with a tool immersed depth of 2 mm and 10 mm respectively. Then, a thermal removal finite element model (FEM) for ECDM was developed. The heat cumulative and intermittent cooling effects applied on the alumina ceramic surface dominated the materiel removal. Additionally, it can be found that the microchannel machining accuracy and bottom surface quality depended on the Gaussian heat source characteristics, gas film formation mechanism, heat accumulation effect, and temperatures spatial and temporal distribution. And a series of single factor experiments for evaluating the parametric studies such as the effect of discharge frequency, applied voltage, duty ratio and tool feed rate on the fabricated microchannel performance are executed. Finally, the complex three-dimensional structures of cross microchannel grid and zigzag microchannel array with variable depth were successfully fabricated on aluminum oxide ceramic surface. Notably, the results highlighted and enriched the ECDM stability, consistency and applicability for alumina ceramic surface microchannel fabrication.

Process and technical characteristics of traditional gilding technology on silver: experimental replication and analysis of silver gilded products

Process and technical characteristics of traditional gilding technology on silver: experimental replication and analysis of silver gilded products

Sediment production process and hydraulic characteristics of ephemeral gully erosion in granite hilly area

Ephemeral gully (EG) erosion represents the early stage of large-scale gully (locally named as “Benggang”) development on Ultisols in the granite hilly area. However, the EG erosion process and the mechanism underlying sediment production have not been fully elucidated. In this study, a series of field scouring experiments were conducted under different flow discharge levels (10, 15, 20, 25, and 30 L·min−1), and the primary EGs in three typical soil layers with different weathering degrees (red soil layer (RL), transition layer (TL), and sandy layer (SL)) was dynamically monitored. The results indicated that the ratio of width to depth of the EGs rapidly decreased as the flow discharge increased. At 30 L·min−1, the average sediment yield and transport rate (Sr) of the SL were 4.85 and 5.39 times, greater than those of the RL, respectively. The sediment particles were concentrated within the 1–2 mm particle size range, accounting for over 35 %. In addition, the mean weight diameter of the sediment particles in the RL was the largest. The sediment distribution characteristics did not respond to flow changes but were affected by EG morphological changes. With increasing flow discharge, the flow shear stress and stream power increased. Further analysis revealed that the coupling effect of flow hydraulic characteristics and EG morphological evolution drove the EG erosion sediment production process, and the Sr of the SL was highly sensitive to flow discharge changes. The soil disintegration rate was an internal factor that directly affected soil loss in the EGs, with a path coefficient of 0.71. The bulk density, organic matter content, and sand content were all indirect influencing factors. The RL exhibited greater anti-erodibility than the other layers and could serve as an effective protective layerfor granite hilly areas. These findings provide a theoretical basis for improving soil loss management systems.

Dynamic Modeling Framework Based on Automatic Identification of Operating Conditions for Sintering Carbon Consumption Prediction

In iron and steel industry, sintering process requires huge carbon consumption. Achieving accurate and dynamic prediction of carbon consumption in this process is of evident significance to protect the environment and raise the economic efficiency of iron and steel industry. This paper develops an original dynamic modeling framework including automatic identification of operating conditions, modeling in different conditions, and dynamic prediction model of sintering carbon consumption. Firstly, an automatic kernel-based fuzzy C-means algorithm is presented for automatic identification of operating conditions. Dynamic relationships between the inputs and output of the model are analyzed by Copula Entropy, and then the relevant production data in each operating condition are determined by just-in-time learning method. Next, broad learning models are established under different operating conditions. Further, dynamic prediction model of sintering carbon consumption is designed, and the prediction error is adopted to quantify performance of the model and as one criteria to determine the update of production database. Finally, results of experiments using actual production data demonstrate the advantage and validity of the developed model compared with some advanced modeling methods. The developed model considers complex characteristics of the sintering process and presents a better dynamic performance and information mining performance.

The thermo-optical coefficient as an alternative probe for the structural arrest of polymeric glass formers

The most important, yet independent susceptibilities to characterize the canonical glass transition include the thermal expansion, the specific heat and the shear modulus. At the glass transition, all these susceptibilities show a step-like behaviour as a function of temperature. However, in principle, different susceptibilities provide different perspectives on the glass transition. Due to the effect of sample history and considerable kinetic influences on the thermal glass transition behaviour, the best way to evaluate these different perspectives is to investigate them simultaneously. In this publication, different perspectives on the dynamical freezing process are obtained by a single experimental method: Temperature-modulated optical refractometry (TMOR). TMOR is used to simultaneously investigate the dynamic thermal expansion and, indirectly, the shear viscosity of a model polymer, both contributing to the thermo-optical coefficient. It will be discussed how this thermo-optical property couples to the structural arrest designated as one of the characteristics of the solidification process of polymers.

Explicit Representation and Customized Fault Isolation Framework for Learning Temporal and Spatial Dependencies in Industrial Processes.

Typically, industrial processes possess both temporal and spatial dependencies due to intravariable dynamics and intervariable couplings. The two dependencies have different manifestations, indicating diverse process characteristics. However, the existing methods fail to separate temporal and spatial information well, leading to inappropriate representation and inaccurate fault detection and isolation results. This study proposes an explicit representation and customized fault isolation framework to tackle temporal and spatial characteristics, so as to identify and locate anomalies affecting different dependencies. First, we design a double-level separation method for temporal and spatial information. In the first level, we construct two independent auto-encoding modules to extract temporal correlation and spatial graph structure in parallel. In the second level, we propose an information aliasing loss function to guild the two modules to distinguish between temporal and spatial characteristics, further facilitating information separation. By monitoring the explicit temporal and spatial statistics obtained by the two modules, spatiotemporal dependencies of anomalies can be determined for subsequent isolation. Furthermore, we propose a customized isolation strategy for anomalies in temporal and spatial characteristics. By quantifying changes in intravariable temporal dynamics and intervariable spatial graph structure individually, temporal impact and spatial propagation of faults can be finely characterized and isolated. Three examples are adopted to verify the performance of the proposed framework, including a numerical example, a real condensing system of the thermal power plant process, and the Tennessee Eastman benchmark process.

Investment policy of construction enterprises under the conditions of marital state

Purpose. Studying the investment policy in construction in wartime conditions, namely: determining the general characteristics of the investment process in construction in wartime conditions; identification of factors affecting investment activity; analysis of the problems of investment activity in these conditions; development of recommendations for improvement of investment policy in construction in wartime conditions. Methodology. In the process of studying the investment policy of construction enterprises in the conditions of martial law, the following methods were used: expert assessment (allowed obtaining conclusions and recommendations regarding the possibilities of investing in construction projects in conditions of military conflict), scenario modeling (development of various scenarios investing in the construction sector made it possible to analyze the possible consequences and results of each of them), system analysis (taking into account the relationships between various aspects of the investment policy of construction enterprises and its impact on the economy and society as a whole) and marketing research (determining the needs and requirements of the market in relation to investments in the construction sector in the conditions of a military conflict). Findings. The authors indicated the main problems of construction financing: lack of long-term loans and investments for construction; high interest rates on loans; imperfect legislation in the field of construction; lack of transparency and efficiency in the management of public finances allocated for construction. It is proposed to take the following measures: to create conditions for attracting long-term loans and investments in construction; to reduce interest rates on loans; to improve legislation in the field of construction; to improve the transparency and efficiency of the management of public finances allocated for construction; to improve mechanisms of public-private partnership in the field of construction; to develop programs to stimulate housing construction for low-income citizens; to create conditions for the development of small and medium-sized enterprises in the field of construction. To form the investment attractiveness of the construction industry in Ukraine, the authors suggest creating a favorable investment climate that will guarantee investors the protection of their rights and interests; developing transparent and effective rules and procedures for regulation of construction; ensuring access to quality construction materials and equipment at competitive prices; improving the qualification and level of professional training of construction personnel. Originality. The article comprehensively researches the investment policy in construction in the conditions of war for the first time. The authors revealed new regularities in the development of the investment process in construction under martial law, developed recommendations for its improvement. Practical value. The results of the study can be used to form an effective investment policy in construction in wartime conditions. They can also be used to develop measures to support investment activities in construction under martial law.

Digital Light Processing 4D Printing of Poloxamer Micelles for Facile Fabrication of Multifunctional Biocompatible Hydrogels as Tailored Wearable Sensors.

The lack of both digital light processing (DLP) compatible and biocompatible photopolymers, along with inappropriate material properties required for wearable sensor applications, substantially hinders the employment of DLP 3D printing in the fabrication of multifunctional hydrogels. Herein, we discovered and implemented a photoreactive poloxamer derivative, Pluronic F-127 diacrylate, which overcomes these limitations and is optimized to achieve DLP 3D printed micelle-based hydrogels with high structural complexity, resolution, and precision. In addition, the dehydrated hydrogels exhibit a shape-memory effect and are conformally attached to the geometry of the detection point after rehydration, which implies the 4D printing characteristic of the fabrication process and is beneficial for the storage and application of the device. The excellent cytocompatibility and in vivo biocompatibility further strengthen the potential application of the poloxamer micelle-based hydrogels as a platform for multifunctional wearable systems. After processing them with a lithium chloride (LiCl) solution, multifunctional conductive ionic hydrogels with antifreezing and antiswelling properties along with good transparency and water retention are easily prepared. As capacitive flexible sensors, the DLP 3D printed micelle-based hydrogel devices exhibit excellent sensitivity, cycling stability, and durability in detecting multimodal deformations. Moreover, the DLP 3D printed conductive hydrogels are successfully applied as real-time human motion and tactile sensors with satisfactory sensing performances even in a -20 °C low-temperature environment.

Разработка алгоритма комплексной методики оценки технического состояния цилиндропоршневой группы судовой двигательной установки на основе показателей масляной системы

The algorithm of a complex methodology for assessing the technical condition of the cylinder piston group of a marine propulsion system is being investigated. Wear is a continuous process characteristic of all working mechanisms. Studies aimed at identifying factors contributing to the degradation of system elements of devices provide the basis for the development of preventive measures to reduce their effects. Knowledge of the technical condition of marine engine components is important for the development of measures that increase the reliability of equipment and reduce the risks of emergency situations. Some of the main approaches to modeling and evaluating the state of the cylinder-piston system of marine diesel engines are presented. To solve the problems of assessing the technical condition of the cylinder piston group during operation, classical methods of statistical data analysis are considered, methods that artificially increase the size of the data sample are proposed, machine learning methods are analyzed and the most effective for use are determined. An integrated approach is being created to study the operation process of a cylinder-piston group of diesel marine engines based on a combination of statistical methods, machine learning methods and probabilistic forecasting. A diagram of the properties of the studied parameters is illustrated for constructing a model for analyzing a cylinder-piston group system. Machine learning algorithms used to study systems are presented. The proposed technique allows, using the results of indirect measurements (data from lubrication analyses), to determine the technical condition of the engine system, in particular the cylinder piston group.

Isocitrate dehydrogenase 2 regulates the proliferation of triple-negative breast cancer through the ferroptosis pathway.

Triple-negative breast cancer (TNBC) is currently the type of breast cancer with the worst prognosis; it lacks specific treatments, such as ER/PR antagonistic endocrine and anti-HER2 targeted therapies. Although immunotherapy with immune checkpoints has shown some efficacy in many solid tumors, clinical data in TNBC suggest significant limitations. The essence of ferroptosis is the impaired metabolism of intracellular lipid oxides, which in turn causes the activation and abnormalities of the immune system, including ROS, and not only plays an important role in liver injury and organ aging but also a large amount of data points to the close correlation between the ferroptosis process and tumor development. In this study, through the analysis of large-throughput biological data of breast tumors, combined with the characteristics of the biological process of ferroptosis, the specific gene IDH2 was found to be significantly highly expressed in TNBC and functionally correlated with ferroptosis. Through clinical specimens validated at the gene and protein levels, in vitro tumor cell line validation, and in vivo mouse models, we found that the high expression of IDH2 in TNBC has a role in inhibiting the ferroptosis process in TNBC, thus promoting the proliferation of TNBC cells and other malignant features.

Treatment of Spray Paint Wastewater by a Coupled Electro-Fenton and SBR Technology

Spray painting wastewater is industrial wastewater created during the painting process; its composition is complicated, comprising a significant number of difficult biodegradable organic matter; nevertheless, the existing technology is not optimal, and the process cannot reach the desired criteria. The water quality of the entry has a higher demand for investment and occupying a vast land. High maintenance expenses, high water quality after treatment, and other issues exist. In this study, the oily spray paint wastewater was treated using an electrochemical and Fenton process, which has a high oxidation capacity, a fast oxidation rate, and a wide application of the characteristics of the Electro-Fenton process used in the pretreatment of spray paint wastewater. This study focuses on the electrochemical optimization and improvement of the Fenton technique, and it employs Fe2+ and H2O2 generated by the electrochemical approach as a continuous source of Fenton reagent. Simultaneously, electrode-related oxidation may destroy organic matter, effectively reducing the concentration of organic matter in spray paint wastewater, and when paired with the traditional Sequencing Batch Reactor Activated Sludge Process (SBR) operation treatment mode, offers a comprehensive process idea. While improving the efficiency and quality of spray paint wastewater treatment, the cost should be kept as low as feasible in order to provide effective reference schemes for spray paint wastewater treatment, allowing for future study.