Publications by authors named "Haiquan Ding"

Background: Most sows will experience negative energy balance during lactation resulting in impaired follicular development. This study aimed to treat 28-day lactating sows with altrenogest (ALT) to suppress follicle enlargement during lactation, and to assess the estrus and reproductive performance post-weaning.

Methods: In this study, we conducted two trials.

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  • Nucleotide-binding domain-like receptors (NLRs) play a key role in the female immune response in the endometrium, particularly during pregnancy, where they help maintain a healthy maternal-fetal environment.
  • This study examined NLR expression in sheep (ovine) endometrial tissues at different stages: the estrous cycle and early pregnancy, using various molecular analysis techniques.
  • Findings showed that while most NLRs decreased in expression during early pregnancy, NLRP7 levels increased, indicating a shift in immune regulation necessary for a successful pregnancy.
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The flower is the main organ that produces essential oils in many plants. The yield of raw flowers and the number of secretory epidermal cells are the main factors for essential oil production. The cultivated rose species "Pingyin 1" in China was used to study the effect of on floral organ development.

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Aramid fibers with low density and high strength, modulus, and thermal resistance are widely used in applications such as bulletproof vests and cables. However, owing to their chemical structure, they are sensitive to ultraviolet light, which degrades the fibers' useful mechanical properties. In this study, titanium dioxide (TiO) nanoparticles were synthesized both on the aramid III fiber surface and in the interfacial space between the fibrils/microfibrils in supercritical carbon dioxide (scCO) to improve the UV resistance of aramid fibers.

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Blood constituent examination is an important means of health diagnosis. For blood constituent examination, we usually adopt the method of drawing blood, which bring pain and the risk of cross infection to the patient. Near infrared spectrum spectroscopy (NIRS) is a research hotspot in noninvasive blood constituent examination.

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  • The paper focuses on optimizing the detector distance to enhance signal intensity in the dermis layer of the skin while minimizing interference from the epidermis and subcutaneous layers.
  • It involves an analysis of skin structure, the calculation of tissue optical parameters, and the establishment of a Monte Carlo model centered on glucose absorption in the near-infrared spectrum.
  • Results indicate that a detector distance of 1 mm maximizes photon energy absorption in the dermis, making it ideal for non-invasive biochemical measurements.
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To facilitate non-invasive diagnosis of anemia, specific equipment was developed, and non-invasive hemoglobin (HB) detection method based on back propagation artificial neural network (BP-ANN) was studied. In this paper, we combined a broadband light source composed of 9 LEDs with grating spectrograph and Si photodiode array, and then developed a high-performance spectrophotometric system. By using this equipment, fingertip spectra of 109 volunteers were measured.

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Subtracted blood volume spectrometry (SBVS) can eliminate the background information in near infrared spectroscopy (NIRS) noninvasive biochemical sensing. However, the spectrum obtained by this method is accompanied by serious noises which are to the disadvantage of the calibration models. Empirical mode decomposition (EMD) was applied to restrict the noises in order to improve the performance of subtracted blood volume spectrometry.

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High signal-to-noise ratio (SNR) of system is necessary to obtain accurate blood components in near infrared noninvasive biochemical analysis. In order to improve SNR of analytical system, high-efficiency double compound parabolic concentrator (DCPC) system was researched, which was aimed at increasing light utilization efficiency. Firstly, with the request of collection efficiency in near infrared noninvasive biochemical analysis, the characteristic of emergent rays through compound parabolic concentrator (CPC) was analyzed.

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  • The study aimed to enhance the signal-to-noise ratio (SNR) of near-infrared spectra to improve the accuracy of calibration models for noninvasive hemoglobin monitoring.
  • Empirical mode decomposition (EMD) was applied to 81 fingertip absorption curves, ultimately analyzing 78 samples after outlier removal.
  • The results showed a significant improvement in prediction accuracy, with the correlation coefficient rising from 0.74 to 0.87 and the root mean square error of prediction (RMSEP) decreasing from 12.85 to 8.08 g/L, confirming EMD's effectiveness in this application.
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In noninvasive biochemical detection, the differential spectrum method based on the change in blood volume can eliminate the interference of human tissue background in theory, and obtain effective spectrum information of blood. In order to demonstrate the effectiveness of the differential spectrum method, simulated experiment was designed. Biological molecules solutions were used for simulating serum sample, filters with different absorption characteristic were used for simulating interference of tissue background, and an adjustable path-length cell was used for simulating blood volume change.

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  • The spectral subtraction method can reduce interference in noninvasive biochemical sensing by eliminating background from human tissue but struggles with unknown pathlengths of the subtracted spectrum.
  • An experiment demonstrated that using orthogonal signal correction helps to address pathlength-related issues in blood volume spectrometry.
  • Results showed significant improvements in prediction accuracy, with RMSECV dropping from 90.17 to 31.62 mg x dL(-1) and the correlation coefficient rising from 0.9787 to 0.9968, highlighting the method's effectiveness for practical applications.
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  • A near infrared spectral correction model was developed to assess the quality of jujube from Southern Xinjiang by analyzing key influential factors affecting online testing results.
  • The study involved defining collection conditions like measurement specifics and device parameters, using a near infrared spectrometer and a custom attachment to gather quality spectra of jujube.
  • The resulting model achieved 8%-10% relative error in sugar degree measurement, optimized the spectra size to 1/10 of the original, and reduced processing time to just 3 seconds for effective online quality detection.
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In noninvasive blood glucose measurement, it is difficult to keep the contact area between skin and internal reflectance element uniform while the mid-infrared spectra of human skin are taken, and this would lead to path-length variations. To study the effect of path-length variations on PLSR calibration model, in the present paper, according to the correlation coefficients between path-lengths and glucose concentrations, two PLSR models were achieved respectively and RMSECV were 31.3 and 4.

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"Digital agriculture" or "precision agriculture" is an important direction of modern agriculture technique. It is the combination of the modern information technique and traditional agriculture and becomes a hotspot field in international agriculture research in recent years. As a nondestructive, real-time, effective and exact analysis technique, near infrared spectroscopy, by which precision agriculture could be carried out, has vast prospect in agrology and gradually gained the recognition.

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In the early nineties of last century, great importance had been gradually attached to the potential of near-infrared spectroscopy (NIRS) in the human body noninvasive biochemical examination. However, the human body is extremely complex. Although research teams have made some achievements in experimental simulations and in-vitro analysis, there is still no substantive breakthrough in clinical application now.

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Diabetes seriously endanger human health, and noninvasive glucose sensing is the expectation of both doctors and patients. Physiological background is complicated, volatile and mixed with a variety of tissue information, resulting in direct measurement of the body's near infrared spectra difficult to truly reflect the concentration change in glucose. As a matter of fact, blood volume is always changing, but human tissue background and the concentration of blood components are constant in a short period.

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The present paper proposed how to select characteristic near-infrared wavelength for soil total nitrogen by using successive projection algorithm (SPA). Spectral data are compressed by SPA in the first place to obtain the raw wavelengths. Then the group of wavelengths derived from SPA is screened by their contributions to the total nitrogen.

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