About

Xin Ma is an Assistant Professor of Chemistry whose research focuses on the development and application of mass spectrometry imaging (MSI)-based tools for spatially resolved metabolomics and disease screening and diagnosis. His work aims to develop new versatile MSI platforms, including a three-dimensional, high-sensitivity laser-based platform for single cell or tissue MSI studies, and methods for in-situ structural elucidation of metabolites, lipids, and glycans without extensive tissue derivatization or instrument modifications. He is also engaged in mechanistic studies of interactions of organic radicals with lipids to explore potential disease therapies. Xin Ma's research involves extensive collaborations with scientists at the Brain Institute of UVA through the Neuroscience Grant Challenge Initiative, applying bioanalytical techniques to investigate the pathogenesis of neurodegenerative diseases such as Alzheimer's disease. His efforts include developing a gentler, matrix-free laser desorption technique called LIAD, coupling it with soft ionization methods for broad compound coverage, and conducting structural elucidation of biomolecules through gas-phase ion-molecule reactions and high-resolution MSI. Additionally, his work explores the reactivity of organic polyradicals toward biomolecules, investigating lipid peroxidation mechanisms and synthesizing new radicals for potential therapeutic applications.

Research topics

• Artificial Intelligence
• Computer Science
• Political Science
• Data Mining
• Management
• Linguistics
• Mathematics education
• Speech recognition
• Algorithm
• Library science
• Acoustics
• Medicine
• Physics
• Chemistry
• Real-time computing
• Psychology
• Law
• Organic chemistry
• Mathematics
• Telecommunications

Selected publications

• Efficient Convolutional Network Model Incorporating a Multi-Attention Mechanism for Individual Recognition of Holstein Dairy Cows

  Animals · 2025-04-19 · 2 citations

  articleOpen access1st author

  Individual recognition of Holstein cows is the basis for realizing precision dairy farming. Current machine vision individual recognition systems usually rely on fixed vertical illumination and top-view camera perspectives or require complex camera systems, and these requirements limit their promotion in practical applications. To solve this problem, a lightweight Holstein cow individual recognition feature extraction network named CowBackNet is designed in this paper. This network is not affected by camera angle and lighting changes and is suitable for farm environments. Secondly, a fusion multi-attention mechanism approach was adopted to integrate the attention mechanism, inverse residual structure, and depth-separable convolution technique to design a new feature extraction module, LightCBAM. This module was placed in the corresponding layer of CowBackNet to enhance the model's ability to extract the key features of the cow's back image from different viewpoints. In addition, the CowBack dataset was constructed in this study to verify the model's ability to be applied in real scenarios, containing Holstein cowback images in real production environments under different viewpoints. The experimental results show that when using CowBackNet as a feature extraction network, the recognition accuracy reaches 88.30%, FLOPs are 0.727 G, and the model size is only 6.096 MB. Compared with the classical EfficientNetV2, the accuracy of CowBackNet is improved by 11.69%, the FLOPs are reduced by 0.001 G, and the number of parameters is also reduced by 14.6%. Therefore, the model developed in this paper shows good robustness in shooting angle, light change, and real production data, which not only improves the recognition accuracy but also optimizes the computational efficiency of the model, which is of great practical application value for realizing precision farming.

  PublisherOA PDFDOI

• Recognition of Sheep Feeding Behavior in Sheepfolds Using Fusion Spectrogram Depth Features and Acoustic Features

  Animals · 2024 · 5 citations

  • Computer Science
  • Artificial Intelligence
  • Acoustics

  In precision feeding, non-contact and pressure-free monitoring of sheep feeding behavior is crucial for health monitoring and optimizing production management. The experimental conditions and real-world environments differ when using acoustic sensors to identify sheep feeding behaviors, leading to discrepancies and consequently posing challenges for achieving high-accuracy classification in complex production environments. This study enhances the classification performance by integrating the deep spectrogram features and acoustic characteristics associated with feeding behavior. We conducted the task of collecting sound data in actual production environments, considering noise and complex surroundings. The method included evaluating and filtering the optimal acoustic features, utilizing a customized convolutional neural network (SheepVGG-Lite) to extract Short-Time Fourier Transform (STFT) spectrograms and Constant Q Transform (CQT) spectrograms' deep features, employing cross-spectrogram feature fusion and assessing classification performance through a support vector machine (SVM). Results indicate that the fusion of cross-spectral features significantly improved classification performance, achieving a classification accuracy of 96.47%. These findings highlight the value of integrating acoustic features with spectrogram deep features for accurately recognizing sheep feeding behavior.

  PublisherOA PDFDOI

• Practice and Understanding of “Secondary-Tertiary Combination” in Reconstructing Underground Development System

  Springer series in geomechanics and geoengineering · 2023-01-01

  book-chapter
  PublisherDOI

• A Comparative Analysis of the Contents of “Acid-Base Neutralization Titration” in the New and Old Editions of the Textbook Published by People’s Education Press Based on Core Competencies in China

  Advances in Social Sciences Research Journal · 2023

  1st authorCorresponding
  • Computer Science
  • Political Science
  • Artificial Intelligence

  In the new edition of the high school chemistry textbook, published by People’s Education Press in China in 2019, the knowledge of “Acid-Base Neutralization Titration” is extracted as an independent class hour from the content of “The Application of pH” in the old edition textbook published in 2004. Based on the idea of Chinese core competencies in chemistry, the contents of “Acid-Base Neutralization Titration” in the 2019 edition and the 2004 edition of Chinese high school chemistry textbooks are compared and analyzed in this paper. It is found that the new edition of textbook is optimized in many aspects, for example, a variety of columns are set up, exercises are simplified, and the content is more concise and organized. At the same time, some suggestions are presented about the approaches to cultivating students’ core competencies and the improvement of calculation method of the examples in the new edition of textbooks.

  PublisherDOI

• Mitigating GNSS Multipath Effects Using XGBoost Integrated Classifier Based on Consistency Checks

  International Journal of Antennas and Propagation · 2022 · 4 citations

  • Computer Science
  • Computer Science
  • Artificial Intelligence

  Under the influence of urban building roads, especially interference from multipath effects, global navigation satellite system (GNSS) receiver-related output signal distortion can affect the robustness of the positioning system and the final positioning accuracy. To deal with the above problems, this paper proposes a two-layer consistency-checks (CC) positioning model based on eXtreme Gradient Boosting (XGBoost) integrated learner. First, the model excludes the abnormal values from the correlated output of the first layer by the classical statistical distribution test method. Then, the remaining available measurements are used as the second-layer input, and the measurements are used as learning data using an integrated machine learning method, XGBoost, to efficiently detect and identify non-line-of-sight (NLOS), LOS, and other reflective multipath signals. In order to better mitigate errors in the dynamic relative positioning process, the second-layer checking process uses dynamic pseudorange differencing technique (DPDT) and weighted least squares method (WLS) to smooth the output outcome of the receiver. In the experimental part, we compare and analyze the proposed method with the existing methods from different perspectives in this paper, respectively. The results show that the performance of the model is significantly improved after applying the CC method, in which the average classification accuracy of the multipath signals in the target feature set can reach 91.6%. According to the final positioning results, the proposed method shows a significant accuracy improvement compared to the existing research methods.

  PublisherOA PDFDOI

• Energy recovery from tubular microbial electrolysis cell with stainless steel mesh as cathode

  Royal Society Open Science · 2017-12-01 · 16 citations

  articleOpen access1st author

  In comparison to the transportation and storage of hydrogen, methane has advantages in the practical application, while the emerging product termed as ‘biohythane’ could be an alternative to pure hydrogen or methane in a new form of energy recovery from microbial electrolysis cell (MEC). However, the cathodic catalyst even for biohythane still bothers the performance and cost of total MEC. Herein, we fabricated the MEC reactor with surrounding stainless steel mesh (SSM) to investigate the feasibility of stainless steel mesh as an alternative to precious metal in biohythane production. The columbic efficiency (CE) of anode was around at 80%, representing the SSM would not limit the activity of anodic biofilm; the SEM image and ATP results accordingly indicated the anodic biofilm was mature and well constructed. The main contribution of methanogens that quantified by qPCR belonged to the hydrogenotrophic group ( Methanobacteriales ) at cathode. The energy efficiency reached more than 100%, reached up to approximately 150%, potentially suggesting the energetic feasibility of the application to obtain biohythane with SSM in scale-up MEC. Benefiting from the likely tubular configuration, the ohmic resistance of cathode was very low, while the main limitation associated with charge transfer was mainly caused by biofilm formation. The total performances of SSM used in the tubular configuration for biohythane production provide an insight into the implementation of non-precious metal in future scale-up pilot with energy recovery.

  PublisherDOI

• Supplementary material from "Energy recovery from tubular microbial electrolysis cell with stainless steel mesh as cathode"

  Figshare · 2017-01-01

  articleOpen access1st authorCorresponding

  In comparison to the transportation and storage of hydrogen, methane take advantages in the practical application, while the emerging termed as ‘biohythane’ could be alternative to pure hydrogen or methane in new form of energy recovery from microbial electrolysis cell (MEC). However, the cathodic catalyst even for biohythane still bothers the performance and cost of total MEC, herein, we fabricated the MEC reactor with surrounding stainless steel mesh (SSM) to investigate the feasibility of stainless steel mesh as an alternative to precious metal in biohythane production. The columbic efficiency (CE) of anode was around at 80%, representing the SSM would not limit the activity of anodic biofilm, the SEM image and ATP results accordingly indicated the anodic biofilm was mature and well-constructed. The main contribution of methanogens that quantified by qPCR belonged to the hydrogenotrophic group (<i>Methanobacteriales</i>) at cathode. The energy efficiency reached more than 100%, reached up to approximately 150%, potentially suggesting the energetic feasibility of the application to obtain biohythane with SSM in scale-up MEC. Benefiting from the likely tubular configuration, the ohmic resistance of cathode was very low, while the main limitation associated with charge transfer was mainly caused by biofilm formation. The total performances of SSM used in the tubular configuration for biohythane production provide an insight into the implementation of non-precious metal in future scale-up pilot with energy recovery.

  PublisherDOI

• Waste water treatment system based on industrial ethernet

  Shanxi Chemical Industry · 2010-01-01

  article1st authorCorresponding

  The whole automatic control system for wastewater treatment is divided into three layers of control,monitoring and management.This article studies the layerization of the whole automatic control system for wastewater treatment,discusses the net configures and information communication means between different facilities in detail.Automatic control of the whole wastewater treatment system is well realized.

  Publisher

• A PMSM Sliding-mode Control System Based-on Exponential Reaching Law

  2010-09-01 · 35 citations

  articleSenior author

  A global sliding mode variable structure controller based on exponential reaching law is adopted to Permanent magnet Synchronous Motor. First, the controller can ensure sliding behavior throughout an entire response, we can specify the demands on the capability of the system to achieve a desired performance. Moreover, the controller is based on exponential reaching law, which overcome the drawbacks that we should give the range of the coefficient when confirm the controller in conventional sliding mode control. Theoretical analyses and computation for the proposed controller are described in details .Simulation show that the proposed sliding mode controller provides high-performance dynamic characteristics and is robust with regard to eternal disturbance.

  PublisherDOI

• Applied Research on the PROFIBUS Fieldbus in the SBR Waste Water Disposal Technology

  Shanxi Energy and Conservation · 2010-01-01

  article1st authorCorresponding

  This paper briefly introduces the characteristics of PROFIBUS Fieldbus. Through studing the SBR waste water disposal technology,which puts PROFIBUS Fieldbus technology into the sewage disposal process,it brings forward a plan of PROFIBUS-based automatic control system for sewage treatment,emphasizes PROFIBUS Fieldbus network structure,and studies sewage aeration process control.

  Publisher

Frequent coauthors

• Gang Tao

  Beijing Institute of Technology

  6 shared

• Xiuping Yue

  Taiyuan University of Technology

  2 shared

• Zhifeng Li

  China Huadian Corporation (China)

  2 shared

• Suresh M. Joshi

  2 shared

• Aijuan Zhou

  Taiyuan University of Technology

  2 shared

• Jian Zhou

  1 shared

• Hayang Kim

  1 shared

• Dengao Li

  Taiyuan University of Technology

  1 shared