Conversion Method Research Articles

Analysis of EFT Transmission Characteristics in Armoured Shielded Cables

Abstract Electrical fast transient pulses (EFT) generated when a gas-isolated substation (GIS) is switched on and off. The EFT is transmitted to the control chamber through the secondary control cable, which will cause the failure of the control equipment. In this paper, the three-dimensional electromagnetic simulation software CST (Computer Simulation Technology) is used to study the transmission characteristics of EFT in armored shielded control cables. First, an EFT analog signal is generated using an interference generator. Analyze the difference between the EFT analog signal and the EFT model in the IEC standard. The conversion method of FFT is used to analyze the spectral characteristics of EFT analog signals. According to the structural parameters, a 20-meter-long model of an armored shielded control cable was built in the CST cable studio The effect of the grounding of the shield and armor layers on the attenuation and crosstalk of EFT signals in the cable is studied. Finally, the EFT experiment of 1m long armored shielded cable is carried out, and the reliability of the research method is verified by comparing with the simulation results.

Can we estimate which colors our participants see? Comparing results from different gamma correction methods

In experimental color research, one must ensure that color is displayed and described reliably. When monitors are involved, colors are displayed through device-dependent color systems. However, these values must be translated into device-independent color systems to interpret what people perceive, often involving techniques such as gamma correction. We sought to explore the feasibility of estimating gamma instead of relying on direct gamma measurements, which typically require specialized equipment like a chromameter. Potential solutions include a computerized perception-based gamma estimation task or adopting the industry-standard gamma value of 2.2. We compared these two solutions against the chromameter measurements in the context of a color-matching task. Thirty-nine participants visually matched red, yellow, green, and blue physical objects using a computerized color picker. Starting from these color choices, we applied two RGB-to-CIE Lab color conversion methods: one using a perception-based gamma estimation and another using the industry-standard gamma. Color values obtained with the chromameter differed from the other two methods by 6–15 JNDs. Small differences existed between the results obtained using the perception-based task and the industry-standard gamma. Thus, we conclude that when standard viewing conditions cannot be assumed, adopting a gamma value of 2.2 should suffice.

Emotional expressivity and self-regulation as indicators of social emotions in older preschool children: Evaluating the effectiveness of development

Introduction. The article presents a theoretical analysis of the main ideas on the problem of social emotions and social competence in the context of the development of self-regulation and interaction skills, as well as the role of parents in this process. The purpose of the article is to substantiate the effectiveness of the development of certain indicators of social emotions in older preschool children, such as emotional expressivity and self–regulation, using an innovative method of reflective conversation. Materials and Methods. A narrative approach was used as a methodological basis of the study. The main research methods comprise the analysis of scholarly literature devoted to the problem of the development of social emotions in older preschool children; as well as evaluation methods, including observation (V. M. Kholmogorova and E. O. Smirnova’s ‘Primary orientation in children s’ relationships’), testing (R. M. Chumicheva’s inventory for determining the ability of a 3-7-year-old child to assess mental states of another person), situation analysis, the method of reflexive conversation, as well as methods of statistical data processing (criterion φ – Fisher angular transformation). 68 preschoolers participated in the study. Results. The authors substantiate that the study of emotional expression and regulation of emotions of older preschool children is significant for understanding and choosing techniques for developing appropriate interactive skills. The relationship between the socio-emotional competence of older preschool children and reflective conversation has been determined. It has been proven that children’s ability to regulate their own emotions contributes to increasing their overall social competence. As a result of comparing the data of primary and secondary assessment of the experimental and control groups according to the indicators established: assessment of the mental states of another person, initiative, sensitivity to peer influences and the prevailing emotional background, significant differences were revealed. Conclusions. The experimental study of the influence of reflexive conversation on the development of social emotions and skills of emotional self-regulation allowed us to establish a causal relationship between indicators of socio-emotional competence and the constructive algorithm for conducting reflexive conversation. The study concludes that reflective conversations contribute to the development of emotional expressivity and self-regulation as indicators of social emotions in older preschool children.

Modified H‐BEA Zeolites from Fluorinated Silica Slag Waste by Dry Gel Conversion Method for Shape‐Selective Acylation of 2‐Methoxynaphthalene

Modified H‐BEA Zeolites from Fluorinated Silica Slag Waste by Dry Gel Conversion Method for Shape‐Selective Acylation of 2‐Methoxynaphthalene

Prediction of Glass Transition Temperature of Polymers Using Simple Machine Learning.

Polymer materials have garnered significant attention due to their exceptional mechanical properties and diverse industrial applications. Understanding the glass transition temperature (Tg) of polymers is critical to prevent operational failures at specific temperatures. Traditional methods for measuring Tg, such as differential scanning calorimetry (DSC) and dynamic mechanical analysis, while accurate, are often time-consuming, costly, and susceptible to inaccuracies due to random and uncertain factors. To address these limitations, the aim of the present study is to investigate the potential of Simplified Molecular Input Line Entry System (SMILES) as descriptors in simple machine learning models to predict Tg efficiently and reliably. Five models were utilized: k-nearest neighbors (KNNs), support vector regression (SVR), extreme gradient boosting (XGBoost), artificial neural network (ANN), and recurrent neural network (RNN). SMILES descriptors were converted into numerical data using either One Hot Encoding (OHE) or Natural Language Processing (NLP). The study found that SMILES inputs with fewer than 200 characters were inadequate for accurately describing compound structures, while inputs exceeding 200 characters diminished model performance due to the curse of dimensionality. The ANN model achieved the highest R2 value of 0.79; however, the XGB model, with an R2 value of 0.774, exhibited the highest stability and shorter training times compared to other models, making it the preferred choice for Tg prediction. The efficiency of the OHE method over NLP was demonstrated by faster training times across the KNN, SVR, XGB, and ANN models. Validation of new polymer data showed the XGB model's robustness, with an average prediction deviation of 9.76 from actual Tg values. These findings underscore the importance of optimizing SMILES conversion methods and model parameters to enhance prediction reliability. Future research should focus on improving model accuracy and generalizability by incorporating additional features and advanced techniques. This study contributes to the development of efficient and reliable predictive models for polymer properties, facilitating the design and application of new polymer materials.

Ternary phase diagram and investigation of slurry conversion of 1:1 sulfamethazine-acetylsalicylic acid cocrystal

Successful production of 1:1 sulfamethazine-acetylsalicylic acid (SMZ-ASA) cocrystal was achieved through slow solvent evaporation, liquid-assisted grinding, and slurry conversion method. SCXRD, PXRD, DSC, FTIR, and Raman spectroscopy were employed to characterize the cocrystal. Ternary phase diagrams (TPD) for SMZ and ASA in acetonitrile (ACN) and deionized water (DIW) has been constructed at 25 ℃. Using TPD of the incongruent system, slurry compositions for stable production of cocrystal was determined in both the solvents. The cocrystal conversion process in slurry was monitored using in-situ Raman spectroscopy. Intermittent sampling was also carried out to determine the purity of the solid phase from the slurry using offline PXRD. In-situ Raman and offline PXRD measurements confirmed fast conversion of the pure coformer crystals to the cocrystal in ACN, within a span of 5 minutes. However, the conversion in DIW was much slower and the in-situ Raman measurements significantly underpredicted the transformation time in comparison to offline PXRD analysis. The study highlights the utilization of TPD for developing the cocrystallization process and the need for multiple characterization techniques for monitoring cocrystallization.

Lignocellulosic biomass in circular economy: A techno-transition in carbon neutrality towards sustainable energy production

The ongoing energy crisis and global warming threat represent major challenges of the century. Our dependence on conventional fuels has reached to a critical level where attempts are made to reduce the greenhouse gases (GHGs) emission and impede its ramifications. Simultaneously, it is projected to have alternative greener energy resources to reduce the deleterious effect of biofuels on humans and the environment. The lignocellulosic biomass (LCB, an abundant feedstock) constitutes an important renewable resource with potential to replace non-renewable ones for energy production. The shift in the usage of natural resources projects biofuels on the forefront to overcome the growing energy crisis and offer a sustainable solution to the global warming to minimize its impact at the global scale. Offering a long-term viability, biofuels upholds a key component in the economic prosperity of a nation. This article highlights important aspects of feedstock selection, a concise and comprehensive account of the pre-treatment procedures, and enzymatic saccharification of the LCB employed in the biofuel production. Considering the biomass heterogeneity and optimization in predicting and managing the outputs and huge capital and operating expenditures, the study presents integration of the microbial saccharification with established biofuel technologies towards enhancing efficiency and overall productivity. Additionally, an account of the artificial technology and machine learning approaches employed in harnessing renewable resources and reducing greenhouse gas emissions, have been added. Holding a greater promise, the review adds to the need of developing robust and efficient LCB conversion methods to scale up and excel in sustainable energy production for a greener future.

RESTART: a stepped-care approach to facilitate return to work for employees with psychological distress: design of a randomized controlled trial

BackgroundCommon mental health problems, such as stress, anxiety and depression, are highly prevalent among workers and often lead to long-term absenteeism and work disability. Effective elements found in previous researched interventions were to explicitly focus on return to work (RTW) and not solely on symptom reduction, to take into account the employees’ cognition towards RTW and to include the workplace environment. Based on these elements, a stepped-care approach was developed. The aim of this paper is to present the study design of a randomized controlled trial (RESTART), evaluating the effectiveness of the stepped-care approach on lasting RTW and the implementation process.MethodsRESTART is a randomized controlled trial with a 2 × 2 factorial design and a follow-up of one year. Employees eligible for this study are those who reported sick within 2 to 8 weeks with psychological distress based on a distress screener. Participants will be randomized to a group receiving a tailored e-Health app or usual care, as well as randomized to a group receiving a Participatory Approach (PA; conversational method) in the workplace or usual care. The PA will however only be provided in case of persistent sickness absence at 8 weeks. Measurements take place at baseline, after the e-Health intervention period (3 months), and after the PA intervention period (6 months) and 12 months. Primary outcome is lasting RTW, defined as full RTW in previous or equal work for at least four consecutive weeks. Secondary outcomes are (the severity of) stress-related symptoms, total number of sickness absence days, self-efficacy for RTW and self-reported health. A process evaluation including a realist evaluation will also be conducted.DiscussionEarly intervention that focuses on RTW, the cognition towards RTW despite symptoms and involves the workplace environment, plays a crucial role in managing sickness absence among employees with psychological distress. If effective, the stepped-care approach is relevant for employees, employers and society as a whole.Trial RegistrationISRCTN: 90663076. Registered on 5 October 2023.

A low-power thermoelectric power generation system based on a periodic thermoelectric power generation method in the form of heat pulses

In today's increasingly serious energy problems, thermoelectric power generation is now widely used as one of the cleanest energy conversion methods. In this paper, we proposed a way of generating thermoelectric power periodically in the form of heat pulses and design an experimental system with low power consumption of fan blades. In contrast to conventional thermoelectric power generation with continuous contact with the heat source, this method maintains the temperature gradient between the hot and cold sides at a larger value for a longer period using periodic contact of the thermoelectric generator (TEG) with the surface of the heat source in the form of heat pulses. So it enhances the efficiency of thermoelectric power generation. The output power of the heat-pulsed thermoelectric power generation from a single TEG with heat sink is 19.81 mW with an efficiency of 6.05 %, which is an improvement of 23 % and 10.8 % over the conventional method. The whole system has an output power of 63.3 mW, an improvement of 293 %. This clean and efficient new type of TEG system can be widely used in the future in areas such as petrochemical waste heat treatment and self-supply of energy for Internet of Things (IoT) sensors.

Characteristics of solar to hydrogen-rich fuel production integrating parabolic trough collectors with partially rotatable tracking strategies

To achieve carbon neutrality, hydrogen and solar energy are receiving increasing attention. Concentrated solar thermal energy by parabolic trough collectors can be used to drive methanol cracking reactions for distributed hydrogen-rich syngas production. In this scenario, the collector is characterized by its small size and easy to integrate with hydrogen utilization equipment. However, parabolic trough collectors use a single-axis strategy with inherent large cosine loss, resulting in a low annual efficiency. The partially rotatable tracking is an advanced tracking strategy, which considers the trade-off between performance and cost compared to double-axis tracking strategies, and shows great potential for applications in distributed solar thermochemical reactions. In this study, solar to hydrogen-rich fuel production integrating parabolic trough collectors with the partially rotatable tracking strategy is proposed. The effect of the partially rotatable tracking strategy on the solar thermochemical conversion of methanol cracking is revealed. An annual normalized optical improvement of 40%∼54% is realized over a latitude range of 0∼50° by means of an optimal daily rotation angle. The solar thermochemical reactor with the partially rotatable tracking strategy has the less irreversibility loss during the concentrating process and the higher thermochemical efficiency. The results show that in three Chinese cities (Beijing, Lhasa and Guangzhou) with different latitudes and irradiation conditions, a partial north-south rotation strategy yields an additional 17.42%, 11.62% and 6.22% of chemical energy per year from the sun, while a partial east-west rotation strategy yields an additional 14.91%, 19.35% and 15.37% per year from the sun. The encouraging results indicate a promising method for the effective conversion of solar energy to chemical energy of hydrogen-rich fuels.

Classification and identification of extreme wind events by CNNs based on Shapelets and improved GASF-GADF

In this manuscript, we propose an automatic classification and recognition method for extreme wind events based on Convolutional Neural Networks (CNNs) and combining the Shapelet Transform (ST) algorithm with the improved Gramian Angular Summation Field - Gramian Angular Difference Field (GASF-GADF) 2D images construction format. First, a CNN model suitable for wind speed time series 2D images classification and recognition among five mainstream CNNs (ResNet-50, ShuffleNet0.5 × , DenseNet-121, EfficientNet-B2, and EfficientNetV2-S) is preferred based on the basic Gramian Angular Field (GAF) method; then, the improved GASF-GADF images construction format is proposed, and the optimal CNN is used to compare the classification and recognition results based on other three image conversion methods: Markov Transition Field (MTF), GASF, GADF. Last, it is proposed to utilize the ST algorithm to extract the feature subsequence Shapelets of wind speed time series to further improve the classification and recognition effect on extreme wind events. The effectiveness and applicability of the proposed method were verified through three extreme wind event datasets in this paper.The results show that the combination of Shapelets and the improved GASF-GADF images transformation method proposed in this paper can effectively enhance the classification and recognition of extreme wind events by CNNs. Among them, EfficientNetV2-S combined with the method proposed in this paper achieves 99.50%, 99.50% and 97.50% recognition Accuracy for thunderstorm, gust front and typhoon, respectively. Meanwhile, it still has good robustness for extreme wind events disturbed by noise.

Sea Voyage Interview as a conversational method for strengthening the sense of psychological safety and security

The Sea Voyage Interview is a new and original method grounded in attachment narrative therapy, which serves as a therapeutic metaphorical framework to enhance clients’ narratives relating to safety and security, and to cope with the latter’s loss. It encourages clients to introspect and enrich their narratives by integrating cognitive and affective information, thereby improving threat identification and response strategies. This interview process acknowledges the distortions people create in their stories to feel secure, without judging the veracity of these narratives. The method employs a systemic approach, emphasizing context in shaping a sense of security and incorporates a playful element with kinetic sand and figurines to facilitate expression. It is non-diagnostic, designed for adult therapy, and does not explore childhood safety experiences, leaving this to established instruments. The Sea Voyage Interview prioritizes flexible conversational guidance, focussing on perceived threats, coping mechanisms, and psychological resources to foster a strengthened sense of security.

Controllable Metal–Organic Framework‐Derived NiCo‐Layered Double Hydroxide Nanosheets on Vertical Graphene as Mott–Schottky Heterostructure for High‐Performance Hybrid Supercapacitor

Layered double hydroxide (LDH) is considered a highly promising electrode material for supercapacitors (SCs) due to its high theoretical specific capacitance. However, LDH powders often suffer from poor electrical conductivity, structure pulverization, slow charge transport, and insufficient active sites. Herein, a self‐supporting electrode with a Mott–Schottky heterostructure has been designed for high‐performance SCs. The electrode consists of low crystallinity NiCo‐LDH nanosheets and vertical graphene (VG) directly grown on carbon cloth. The LDH was converted from a metal–organic framework (MOF) by the sol–gel method. This self‐supporting electrode provides fast charge transfer, reducing the pulverization effect and energy barrier. The Mott–Schottky heterostructure of LDH@VG regulates electron density and enhances electron transfer, as confirmed by density functional theory calculation. The optimized LDH@VG heterostructure electrode exhibits an excellent areal capacitance of 5513.8 mF cm−2 and rate capability of 82.1%. Furthermore, the fabricated hybrid SC demonstrates excellent energy density of 404.8 μWh cm−2 at 1.6 mW cm−2 and a remarkable cycling life, with a capacitance of 92.0% after 10 000 cycles. This work not only provides a simple dip‐coating and MOF conversion method to synthesize heterojunction‐based electrodes, but also broadens the horizon for designing advanced electrode materials for SCs.

Comprehensive Analysis of Allulose Production: A Review and Update.

Advancements in D-allulose production have seen significant strides in recent years, focusing on enzymatic conversion methods. Key developments include traditional immobilization techniques, the discovery of novel enzymes, directed evolution studies, and biosynthesis through metabolic pathway modification. Enzymatic conversion, particularly utilizing D-allulose 3-epimerase, remains fundamental for industrial-scale production. Innovative immobilization strategies, such as functionalized nano-beads and magnetic MOF nanoparticles, have significantly enhanced enzyme stability and reusability. Directed evolution has led to improved enzyme thermostability and catalytic efficiency, while synthetic biology methods, including phosphorylation-driven and thermodynamics-driven pathways, have optimized production processes. High-throughput screening methods have been crucial in identifying and refining enzyme variants for industrial applications. Collectively, these advancements not only enhance production efficiency and cost-effectiveness but also adhere to sustainable and economically viable manufacturing practices. The past five years have witnessed critical developments with significant potential impact on the commercial viability and global demand for allulose.

Reimagining speech: a scoping review of deep learning-based methods for non-parallel voice conversion

Reimagining speech: a scoping review of deep learning-based methods for non-parallel voice conversion

A novel molecular structure parameter determination method for biomass thermochemical conversion mechanism investigation

The low-grade energy properties and high O content of biomass limit its efficient energy utilization. Torrefaction is known to be one of the most promising thermochemical conversion methods for upgrading biomass. 250 °C Gas-pressurized (GP) torrefaction realizes deep decomposition of hemicellulose in biomass to as high as 99.7% by deoxygenation and aromatization. However, the above thermochemical conversion mechanism at molecular-level is currently scant. Here, a novel molecular structural parameter method and pure hemicellulose torrefaction were employed to investigate the thermochemical conversion mechanism. Results demonstrate that O content of 250 °C GP torrefied hemicellulose was as low as 28.8 wt%, which was considerably lower than 44.6 wt% of traditional torrefied hemicellulose. There are five deoxygenation mechanisms of hemicellulose during the GP torrefaction: deacetylation, decarbonylation, dehydroxylation, ring opening and cyclization reactions to produce CO2/CH3COOH, CO, H2O, ketones/aldehydes and furans. The deoxygenation and aromatization reactions cause the chemical structure of hemicellulose evolution significantly, these mechanisms are: active hemicellulose undergo aromatization reaction through cyclization and deoxidation to generate preliminary 2-ring furans polymer, followed by stepwise polymerization reactions to form 4-ring and 6-ring furans polymers. These polymerization reactions further greatly enhance deoxygenation reaction. A thermochemical conversion mechanism model is developed based on the above investigation. This work provides a novel method for determining the molecular structure and reaction mechanism of thermochemical converted biomass.

LiFe0.3Mn0.7PO4-on-MXene heterostructures as highly reversible cathode materials for Lithium-ion batteries

Two-dimensional (2D) heterostructure materials, incorporating the collective strengths and synergetic properties of individual building blocks, have attracted great interest as a novel paradigm in electrode materials science. The family of 2D transition metal carbides and nitrides (e.g., MXenes) has become an appealing platform for fabricating functional materials with strong application performance. Herein, a 2D LiFe0.3Mn0.7PO4 (LFMP)–on-MXene heterostructure composite is prepared through an electrostatic self-assembly procedure. The functional groups on the surface of MXenes possess highly electronegative properties that facilitate the incorporation of LFMPs into MXenes to construct heterostructure composites. The special heterostructure of nanosized-LiFe0.3Mn0.7PO4 and MXene provides rapid Li+ and electron transport in the cathodes. This LiFe0.3Mn0.7PO4-3.0 wt% MXene composite can exhibit an excellent rate capability of 98.3 mAh g−1 at 50C and a very stable cycling performance with a capacity retention of 94.3 % at 5C after 1000 cycles. Furthermore, NaFe0.3Mn0.7PO4-3.0 wt% MXene with stable cyclability can be obtained by an electrochemical conversion method with LiFe0.3Mn0.7PO4-3.0 wt% MXene. Ex-situ XRD suggests that LiFe0.3Mn0.7PO4-on-MXene achieves a highly reversible structural evolution with a solid solution phase transformation (LFMP→LixFe0.3Mn0.7PO4 (LxFMP), LxFMP→LFMP) and a two-phase reaction (LxFMP←→Fe0.3Mn0.7PO4 (FMP)). This work provides a new direction for the use of MXenes to fabricate 2D heterostructures for lithium-ion batteries.

Acousto-Drag Photovoltaic Effect by Piezoelectric Integration of Two-Dimensional Semiconductors.

Light-to-electricity conversion is crucial for energy harvesting and photodetection, requiring efficient electron-hole pair separation to prevent recombination. Traditional junction-based mechanisms using built-in electric fields fail in nonbarrier regions. Homogeneous material harvesting under a photovoltaic effect is appealing but is only realized in noncentrosymmetric systems via a bulk photovoltaic effect. Here we report the realization of a photovoltaic effect by employing surface acoustic waves (SAWs) to generate zero-bias photocurrent in the conventional layered semiconductor MoSe2. SAWs induce periodic modulation to electronic bands and drag the photoexcited pairs toward the traveling direction. The photocurrent is extracted from a local barrier. The separation of generation and extraction processes suppresses recombination and yields a large nonlocal photoresponse. We distinguish the acousto-electric drag and electron-hole pair separation effect by fabricating devices of different configurations. The acousto-drag photovoltaic effect, enabled by piezoelectric integration, offers an efficient light-to-electricity conversion method, independent of semiconductor crystal symmetry.

Synthesis of biochar-doped MgO catalyst for highly efficient conversion of glucose into formic acid at low temperatures

Formic acid (FA) is not only a significant platform chemical but also a promising candidate for hydrogen storage. Although homogeneous catalysts are commonly employed for the conversion of carbohydrate biomass into FA, which often come with substantial costs and inadequate reusability. It is noteworthy that there has been an increasing focus on the development of heterogeneous catalysts in this area, which aim to address these limitations and offer advantages such as easier separation and better reusability. Herein, an eco-friendly and efficient method for the catalytic conversion of glucose to FA by utilizing a biochar-MgO (BC-MgO) catalyst, which is prepared through pyrolysis of coconut husk biochar impregnated with magnesium chloride (MgCl2), is proposed. The FA yield at 74.6% is attained from glucose at 60 °C within only 3 h, utilizing a mere 0.1 g of catalyst and hydrogen peroxide (H2O2) amount of 100%. In conjunction with random forest (RF) algorithms and box-behnken experimental designs, further optimization resulted in an increased yield of 79.1%, with a selectivity of 82.7%, in only 3.8 h at 67 °C, employing 0.1 g of catalyst amount and 125% H2O2 amounts. Notably, the BC-MgO catalyst retains its catalytic efficiency over multiple cycles, only requiring a simple straightforward regeneration procedure. The mechanism underlying the glucose conversion to FA reaction system is demystified via kinetic modeling, time-gradient studies, and model compounds experiments. Life cycle assessment (LCA) indicates that when used for glucose conversion to FA, BC-MgO catalysts generate lower CO2 emissions than traditional homogeneous catalysts such as LiOH. Concurrently, an operation cost analysis indicates that operation cost of FA production from glucose is 4.1 $/kg with the BC-MgO catalyst, which is lower than LiOH catalyst (7.5 $/kg), evidencing the dual advantage of economic viability and an improved environmental impact inherent to this novel process.

Electrically interfaced Brillouin-active waveguide for microwave photonic measurements

New strategies for converting signals between optical and microwave domains could play a pivotal role in advancing both classical and quantum technologies. Traditional approaches to optical-to-microwave transduction typically perturb or destroy the information encoded on intensity of the light field, eliminating the possibility for further processing or distribution of these signals. In this paper, we introduce an optical-to-microwave conversion method that allows for both detection and spectral analysis of microwave photonic signals without degradation of their information content. This functionality is demonstrated using an optomechanical waveguide integrated with a piezoelectric transducer. Efficient electromechanical and optomechanical coupling within this system permits bidirectional optical-to-microwave conversion with a quantum efficiency of up to −54.16 dB. Leveraging the preservation of the optical field envelope in intramodal Brillouin scattering, we demonstrate a multi-channel microwave photonic filter by transmitting an optical signal through a series of electro-optomechanical waveguide segments, each with distinct resonance frequencies. Such electro-optomechanical systems could offer flexible strategies for remote sensing, channelization, and spectrum analysis in microwave photonics.