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Background: Breast cancer poses a significant health risk to women worldwide, with approximately 30% being diagnosed annually in the United States. The identification of cancerous mammary tissues from non-cancerous ones during surgery is crucial for the complete removal of tumors. Results: Our study innovatively utilized machine learning techniques (Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN)) alongside Raman spectroscopy to streamline and hasten the differentiation of normal and late-stage cancerous mammary tissues in mice. The classification accuracy rates achieved by these models were 94.47% for RF, 96.76% for SVM, and 97.58% for CNN, respectively. To our best knowledge, this study was the first effort in comparing the effectiveness of these three machine-learning techniques in classifying breast cancer tissues based on their Raman spectra. Moreover, we innovatively identified specific spectral peaks that contribute to the molecular characteristics of the murine cancerous and non-cancerous tissues. Conclusions: Consequently, our integrated approach of machine learning and Raman spectroscopy presents a non-invasive, swift diagnostic tool for breast cancer, offering promising applications in intraoperative settings. [ABSTRACT FROM AUTHOR]

In view of problem of low precision of parameter identification based on least square method, a parameter identification method of mine-used robot driving system based on whale optimization algorithm was proposed. Driving system model of mine-used robot is established to determine parameters to be identified which are considered as individual position of whale colony. Fitness function is used to measure the individual position of whale colony. The optimal identification parameters can be obtained by continuously updating the individual position of whale colony with whale foraging strategy until the optimal individual position of whale colony is obtained. The simulation and experimental results show that the method has higher identification accuracy than the parameter identification method based on least square method.

Forest restoration and soil structure stabilization are the focus of forestry and ecology. However, the combined mechanisms of soil microorganisms and organic and inorganic aggregate binding agents on soil aggregation is unclear. In order to explore the effects of subtropical forest restoration types on soil aggregates and the underlying mechanisms, we collected soil samples from subtropical natural forests and coniferous and broad-leaved plantations that are commonly used for forest restoration. The mean weight diameter (MWD) of the soil aggregate was used to indicate the aggregates' stability. The soil microbial diversity and structure, the organic and inorganic aggregate binding agents including the mycorrhizal density, the glomalin-related soil protein and the Fe and Al oxides were investigated. Results showed that the Shannon and Simpson indices of soil microbial communities in the coniferous plantations were both significantly higher than those in the natural forests. At the annual level, compared with the natural forests, the plantations decreased the proportion of 0.25–1 mm aggregates while the MWD significantly increased. The forest type also significantly affected the mycorrhizal density, the easily extractable glomalin-related soil proteins (EEG) and the Fe oxide. A variance decomposition analysis showed that soil microbial communities, organic and inorganic binding agents, and their interactions together contributed to the aggregates' composition and stability by 75.07%. The MWD was positively correlated with the microbial diversity, mycorrhizal density and Fe oxide. We therefore suggest that the combined effects of the soil microbial communities and the organic (mycorrhizal density) and inorganic binding agents (Fe oxide) can be the main mechanisms of soil aggregation in the study area, resulting in a higher soil aggregate stability in the subtropical coniferous plantation than in the natural forest. [ABSTRACT FROM AUTHOR]

The randomness and time variability of power load are the main problems in the load modeling, in which the model error and measurement noise greatly affect the modeling accuracy. In this paper, an adaptive fuzzy logic strong tracking based load modeling method is proposed. The problems of load characteristics and parameter identification of load model are transformed into a real-time tracking of load. The optimal model set is first selected from the initial load model set, and according to the mixing probability, the state estimation and error covariance are mixed as the input of the filter. In order to reduce the model error in the parallel filtering, the strong tracking filter (STF) is constructed based on the orthogonality principle and the filter gain is adjusted by introducing a time-varying fading factor. The adaptive fuzzy logic strong tracking filter is constructed by combining the fuzzy logic with the STF to adjust the covariance matrix of the STF according to the change of measurement noise. Moreover, the weights of each sub model are updated in real time by the parallel filtering, and the sub models are fused to get a comprehensive load model which can reflect the actual load characteristics. The effectiveness of the method is verified by the simulation of IEEE 39-bus system. This method can establish an accurate load model and has good robustness. [ABSTRACT FROM AUTHOR]

Analysis of stable isotope composition is an important tool in research on plant physiological ecology. However, large‐scale patterns of leaf‐stable isotopes for aquatic macrophytes have received considerably less attention. In this study, we examined the spatial pattern of stable isotopes of carbon (δ13C) and nitrogen (δ15N) of macrophytes leaves collected across the arid zone of northwestern China (approximately 2.4 × 106 km2) and attempted to illustrate its relationship with environmental factors (i.e., temperature, precipitation, potential evapotranspiration, sediment total carbon and nitrogen). Our results showed that the mean values of the leaf δ13C and δ15N in the macrophytes sampled from the arid zone were −24.49‰ and 6.82‰, respectively, which were far less depleted than those measured of terrestrial plants. The order of averaged leaf δ13C from different life forms was as follows: submerged > floating‐leaved > emergent. Additionally, our studies indicated that the values of foliar δ13C values of all the aquatic macrophytes were only negatively associated with precipitation, but the foliar δ15N values were mainly associated with temperature, precipitation, and potential evapotranspiration. Therefore, we speculated that water‐relation factors are the leaf δ13C determinant of macrophytes in the arid zone of northwestern China, and the main factors affecting leaf δ15N values are the complex combination of water and energy factors. [ABSTRACT FROM AUTHOR]

Cracked teeth are the third most common cause of tooth loss, but there is no reliable imaging tool for the diagnosis of cracks. Here, we demonstrate the feasibility of indocyanine green near‐infrared fluorescence (ICG‐NIRF) dental imaging for the detection of enamel cracks and enamel–dentin cracks in vitro in the first (ICG‐NIRF‐I, 700–950 nm) and second (ICG‐NIRF‐II, 950–1700 nm) imaging windows with transmission excitation light, and compared ICG‐NIRF with conventional NIR illumination‐II (NIRi‐II) and X‐ray imaging. Dentin cracks were detected by CT scan, while most enamel cracks, undetectable under X‐ray imaging, were clearly visible in NIR images. We found that ICG‐NIRF‐II detected cracks more effectively than NIRi‐II, and that light orientation is an important factor for crack detection: an angled exposure obtained better image contrast of cracks than parallel exposure, as it created a shadow under the crack. Crack depth could be evaluated from the crack shadow in ICG‐NIRF and NIRi‐II images; from this shadow we could determine crack depth and discriminate enamel–dentin cracks from craze lines. Cracks could be observed clearly from ICG‐NIRF images with 1‐min ICG tooth immersion, although longer ICG immersion produced images with greater contrast. Overall, our data show that ICG‐NIRF dental imaging is a useful tool for diagnosing cracked teeth at an early stage. [ABSTRACT FROM AUTHOR]

In this study, we used rat animal model to compare the efficiency of indocyanine green (ICG)‐assisted dental near‐infrared fluorescence imaging with X‐ray imaging, and we optimized the imaging window for both unerupted and erupted molars. The results show that the morphology of the dental structures was observed clearly from ICG‐assisted dental images (especially through the endoscope). A better image contrast was easily acquired at the short imaging windows (<10 minutes) for unerupted and erupted molars. For unerupted molars, there is another optimized imaging window (48‐96 hours) with a prominent glow‐in‐the‐dark effect: only the molars remain bright. This study also revealed that the laser ablation of dental follicles can disrupt the molar development, and our method is able to efficiently detect laser‐treated molars and acquire the precise morphology. Thus, ICG‐assisted dental imaging has the potential to be a safer and more efficient imaging modality for the real‐time diagnosis of dental diseases. [ABSTRACT FROM AUTHOR]

Indocyanine green (ICG) has been widely used in medical imaging, such as in retinal angiography. Here, we describe a pilot ex vivo study of ICG‐assisted near‐infrared fluorescence (NIRF) dental imaging in the first (700–950 nm for ICG‐NIRF‐I) and second (1000–1700 nm for ICG‐NIRF‐II) NIR windows using human extracted teeth; our study is compared with the traditional prevalent X‐ray imaging and NIR II illumination (NIRi‐II, 1310 nm) without ICG enhancement. The results show that ICG fluorescence has much better imaging contrast in both windows compared with NIRi‐II (by quantitatively comparing NIR intensity of the critical neighboring structures, such as enamel and dentin). Cracked teeth, notoriously hard to diagnose by dental X‐ray and computed tomography, were clearly profiled in NIRF dental imaging. An insidious occlusal caries, missing in X‐ray imaging, became a bright dot that was readily observed in ICG‐NIRF‐I images. For dental decay, NIRF imaging with ICG enhancement could clearly delineate the decay boundary. NIRF in both windows distinguished interproximal and occlusal superficial caries. Overall, ICG‐assisted NIRF dental imaging has unique advantages in identifying cracked teeth and insidious caries. The two NIR imaging windows used in our study might one day serve as noninvasive and nonionizing‐radiation methods for the diagnosis of critical dental diseases in situ. [ABSTRACT FROM AUTHOR]

Abstract: Current dental diagnosis, especially tooth abnormalities, relies largely on X‐ray–based imaging, a technique that requires specialized skills and suffers from ionizing radiation. Here, we present a pilot study in rats of an efficient, ionizing‐radiation–free and easy‐to‐use alternative for dental imaging. Postnatal rats at different ages were injected with indocyanine green and molars were imaged by a laboratory‐designed endoscopic near‐infrared (NIR) dental imaging system. The results indicate that the endoscopic NIR dental imaging can be used to observe the morphology of postnatal rat molars, especially at early postnatal stages when morphology of the molar is indistinguishable under visible conditions. A small abnormal cusp was observed and distinguished from the normal cusps by the NIR dental imaging system. Dental structures, such as unerupted molars, can be imaged as soon as 10 min after the injection of indocyanine green; imaging after 24 h shows improved imaging contrast. Overall, the endoscopic NIR fluorescence dental imaging system described here may be useful in dental research; this technique may serve as a safe, real‐time imaging tool for dental diagnosis and treatment beyond experimental systems in the future. [ABSTRACT FROM AUTHOR]

• Different sizes of anatomical regions (ROI percentages) have an effect on the compression ratio, and smaller ROI percentages can obtain higher compression ratio; • JPEGXT_OPT with ROI_PXL_SORT realize nearly-lossless compression and still maintain a relatively high compression ratio. • ROI-based JPEG_OPT method could achieve an even higher compression ratio (up to 30, saving about 97% storage space) under small ROI percentages. • Both JPEGXT_OPT and JPEG_OPT by amplifying Ns have a high compression ratio and low compression distortion without losing crucial diagnostic information. • MSSIM in combination with PRD could sufficiently evaluate the distortion of the reconstructed medical imaging by using the lossy compression algorithms. Currently, plenty of image data is generated that complicate storage and image transmission. Great efforts have been attempted on how to increase compression ratio (CR) without loss of critical diagnostic information. In this study, we designed two optimized JPEGXT (JPEGXT_OPT) and JPEG (JPEG_OPT) approaches by amplifying discrete cosine transform coefficients and using the entire anatomical region as ROI (region of interest). We found that ROI percentages have a great impact CR: smaller ROI percentages (10–30 %) could obtain a larger CR. Under the near-lossless compression, JPEGXT_OPT could have CRs up to 4.0 under small ROI percentages (10–30 %), while only ∼ 1.2 for large ROI percentages (90–100 %). JPEG_OPT could obtain a much higher CR: up to over 20.0 for both CT and MRI images under small ROI percentages (10 %-30 %), and over 10.0 in CT and 5.0 in MRI under large ROI percentages (90 %). Both of them show a compression efficiency than the DICOM-recommended JPEGXT and JEPG_2000. From the distortion analysis, MSSIM (Multiscale Structural Similarity) and PRD (percent ratio of distortion) indicate our methods have a less image distortion than DICOM-recommended JPEGXT (PDR > 20 %) and JPEG_2000: approximately 3.0 % PRD were seen under JPEG_OPT, while<0.15 % PRD were observed under JPEGXT_OPT. MSSIM > 0.98 was found in JPEG_OPT, which the reconstructed images have almost no changes in luminance, contrast, and structure, and this was confirmed by low PRD (about 3.0 %). Overall, our two methods could provide a high compression ratio of medical images without significant loss of important diagnostic information in reconstructed images. [ABSTRACT FROM AUTHOR]

Extreme climatic events, such as heat waves, are predicted to increase in frequency and intensity during the next hundred years, which may accelerate shifts in hydrological regimes and submerged macrophyte composition in freshwater ecosystems. Since macrophytes are profound components of aquatic systems, predicting their response to extreme climatic events is crucial for implementation of climate change adaptation strategies. We therefore performed an experiment in 24 outdoor enclosures (400 L) separating the impact of a 4 °C increase in mean temperature with the same increase, that is the same total amount of energy input, but resembling a climate scenario with extreme variability, oscillating between 0 °C and 8 °C above present conditions. We show that at the moderate nutrient conditions provided in our study, neither an increase in mean temperature nor heat waves lead to a shift from a plant-dominated to an algal-dominated system. Instead, we show that species-specific responses to climate change among submerged macrophytes may critically influence species composition and thereby ecosystem functioning. Our results also imply that more fluctuating temperatures affect the number of flowers produced per plant leading to less sexual reproduction. Our findings therefore suggest that predicted alterations in climate regimes may influence both plant interactions and reproductive strategies, which have the potential to inflict changes in biodiversity, community structure and ecosystem functioning. [ABSTRACT FROM AUTHOR]

The stereo vision results from the interaction between geometrical optics and visual psychology. Large depth will bring discomforts for the results of ghosting and flicker. The relevance of the ratio of jumping out depth (RJD) and electroencephalogram (EEG) gravity frequency (GF) was explored to reflect human health under different three-dimensional (3D) depth information (mainly the negative disparity) displayed on a three-dimensional television (3D-TV) with shutter glasses. EEG was obtained from 10 volunteers when they were watching 3D film segments with different negative disparities. The brain GF map shows that the depth information has a stronger influence on the frontal lobe than on the occipital lobe. For regression analysis, nonlinear curve fittings of GF to RJD in Fp1, F3, O2 and T5 channels were mainly performed when RJD ranged from 0 to 3.4, while linear fittings were performed in some special RJD ranges. It also confirms that RJD above 2.2 may lead to discomfort to human body. Finally, it suggests a suitable RJD range for people to watch from the objective method. The outcomes can be used as a guidance to decrease human discomforts induced by 3D production. [ABSTRACT FROM AUTHOR]

Variation in seed weight is common within and among plant species, but few studies have attempted to document the pattern of seed weight and germination attributes for aquatic macrophytes at a large scale. This study examined within-species variation in seed weight and germination attributes and the effects of environmental factors on seed traits of the submerged plant Potamogeton pectinatus in the arid zone of northwest China. Our results showed that the average seed weight was 0.24 g per 100 seeds with a coefficient of variation ( CV) of 28.4% among the eight P. pectinatus populations. The total germination fraction of seeds of P. pectinatus was relatively poor, less than 35% in seven P. pectinatus populations, and the lowest germination percentage found was only 2%. There were significant differences in seed weight, time to onset of germination, and total germination fraction among the eight different populations. Hierarchical partitioning analysis showed a strongly positive correlation between seed weight and water temperature and pH. Seed weight and the maternal environmental factors significantly affected both time to initiation of germination and total germination fraction. Our results suggest that (1) seed weight variation in P. pectinatus primarily is the result of temperature variation during fruit development; (2) relatively poor germination fraction suggests that seeds are relatively unimportant in the short-term survival of populations and that it may be another adaptive trait allowing plants to take place in the right place and at the right time, especially in harsh environment; and (3) variation in seed germination traits should be determined by local environmental and intrinsic factors that interact in a complex fashion. [ABSTRACT FROM AUTHOR]

Significance: X-ray imaging serves as the mainstream imaging in dentistry, but it involves risk of ionizing radiation. Aim: This study presents the feasibility of indocyanine green-assisted near-infrared fluorescence (ICG-NIRF) dental imaging with 785-nm NIR laser in the first (ICG-NIRF-I: 700 to 1000 nm) and second (ICG-NIRF-II: 1000 to 1700 nm) NIR wavelengths. Approach: Sprague Dawley rats with different postnatal days were used as animal models. ICG, as a fluorescence agent, was delivered to dental structures by subcutaneous injection (SC) and oral administration (OA). Results: For SC method, erupted and unerupted molars could be observed from ICG-NIRF images at a short imaging time (<1 min). ICG-NIRF-II could achieve a better image contrast in unerupted molars at 24 h after ICG injection. The OA could serve as a non-invasive method for ICG delivery; it could also cause the glow-in-dark effect in unerupted molars. For erupted molars, OA can be considered as mouthwash and exhibits outstanding performance for delivery of ICG dye; erupted molar structures could be observed at a short imaging time (<1 min) and low ICG dose (0.05 mg / kg). Conclusions: Overall, ICG-NIRF with mouthwash could perform in-vivo dental imaging in two NIR wavelengths at a short time and low ICG dose. [ABSTRACT FROM AUTHOR]