IDENTIFICATION AND RECOGNIZATION OF BAMBOO BASED ON CROSS-SECTIONAL IMAGES USING COMPUTER VISION

Identification of bamboo is of great importance to its conservation and uses. However, identify bamboo manually is complicated, expensive, and time-consuming. Here, we analyze the most evident and characteristic anatomical elements of cross section images, that’s a particularly vital breakthrough point. Meanwhile, we present a novel approach with respect to the automatic identification of bamboo on the basis of the cross-sectional images through computer vision.Two diverse transfer learning strategies were applied for the learning process, namely fine-tuning with fully connected layers and all layers, the results indicated that fine-tuning with all layers being trained with the dataset consisting of cross-sectional images of bamboo is an effective tool to identify and recognize intergenericbamboo, 100% accuracy on the training dataset was achieved while 98.7% accuracy was output on the testing dataset, suggesting the proposed method is quite effective and feasible, it’s beneficial to identify bamboo and protect bamboo in coutilization. More collection of bamboo species in the dataset in the near futuremight make EfficientNet more promising for identifying bamboo.  

Improving Photostability and Antifungal Performance of Bamboo with Nanostructured Zinc Oxide

We report on the formation of zinc oxide (ZnO) films with various morphologies on bamboo to simultaneously furnish it with excellent photostability and antifungal properties. A simple two-step process was adopted, consisting of generation of ZnO seeds on the bamboo surface followed by solution treatment to promote crystal growth. Effect of reaction conditions on film morphologies was systematically investigated. Results indicate morphologies of ZnO films can be tailored from nanoparticles to nanostructured networks and irregular aggregates at the micron scale with different crystallinities through specific combinations of reaction conditions. The photostability and antifungal performances of coated bamboo were greatly improved and highly dependent on both crystallinity and morphologies of ZnO films

The effect on the seasonal dynamics of soil N transformation resulting from biochar application in karst mountains

Nitrogen (N) is frequently a limiting element for primary productivity in karst ecosystems due to its low availability. N mineralization drives N availability and is important for improving N use efficiency in soils. While the use of biochar in agricultural and forest ecosystems has attracted great attention recently, little has been reported on the seasonal dynamics of soil N transformation in karst and its response to biochar application. Therefore, we conducted a pot experiment over 1 year using two types of biochar (rice husk biochar and wood biochar) as soil amendments. The results demonstrated that in the karst mountain region, the soil had the highest content of mineral N (19.41 mg/kg) during summer and the lowest content of mineral nitrogen (3.74 mg/kg) during winter. There was a significant positive correlation (p < 0.01) between soil mineral N content and temperature, and between soil temperature and urease activity. Thus, the higher temperatures during summer enhance soil urease activity, making it easier for soil N mineralization to occur, and increasing soil mineral N content. The soil mineral N content of the CK treatment was 2.61–209.42% higher than the other treatments, indicating that the biochar application reduced the soil mineral N content, which was supported by the negative net N mineralization. This may be due to biochar facilitating the adsorption and immobilization of nitrogen. The soil mineral N content of rice husk biochar was significantly higher than that of woody biochar by 109.55%, indicating that woody biochar would adsorb more N or more readily stimulate N immobilization than rice husk biochar. Furthermore, soil N immobilization (negative net N mineralization) after biochar application varied according to the season. The higher temperatures during summer promoted soil N immobilization more with biochar application. These results are crucial to understanding soil N transformation in karst mountains and guiding effective soil management

Automated quantitative assay of fibrosis characteristics in tuberculosis granulomas

IntroductionGranulomas, the pathological hallmark of Mycobacterium tuberculosis (Mtb) infection, are formed by different cell populations. Across various stages of tuberculosis conditions, most granulomas are classical caseous granulomas. They are composed of a necrotic center surrounded by multilayers of histocytes, with the outermost layer encircled by fibrosis. Although fibrosis characterizes the architecture of granulomas, little is known about the detailed parameters of fibrosis during this process.MethodsIn this study, samples were collected from patients with tuberculosis (spanning 16 organ types), and Mtb-infected marmosets and fibrotic collagen were characterized by second harmonic generation (SHG)/two-photon excited fluorescence (TPEF) microscopy using a stain-free, fully automated analysis program.ResultsHistopathological examination revealed that most granulomas share common features, including necrosis, solitary and compact structure, and especially the presence of multinuclear giant cells. Masson’s trichrome staining showed that different granuloma types have varying degrees of fibrosis. SHG imaging uncovered a higher proportion (4%~13%) of aggregated collagens than of disseminated type collagens (2%~5%) in granulomas from matched tissues. Furthermore, most of the aggregated collagen presented as short and thick clusters (200~620 µm), unlike the long and thick (200~300 µm) disseminated collagens within the matched tissues. Matrix metalloproteinase-9, which is involved in fibrosis and granuloma formation, was strongly expressed in the granulomas in different tissues.DiscussionOur data illustrated that different tuberculosis granulomas have some degree of fibrosis in which collagen strings are short and thick. Moreover, this study revealed that the SHG imaging program could contribute to uncovering the fibrosis characteristics of tuberculosis granulomas

Sensitivity of several selected mechanical properties of moso bamboo to moisture content change under the fibre saturation point

The moisture dependence of different mechanical properties of bamboo has not been fully understood. In this work, the longitudinal tensile modulus, bending modulus, and compressive and shearing strength parallel to the grain were determined for bamboo of ages 0.5, 1.5, 2.5, and 4.5 years under different moisture contents (MC) to elucidate the sensitivity of different mechanical properties of bamboo to MC change. The results showed that the four mechanical properties of bamboo respond differently to MC changes. Compressive and shearing strength parallel to the grain were most sensitive to MC changes, followed by longitudinal tensile modulus, then bending modulus. This can be partially explained by the different responses of the three main components in the plant cell wall to MC change. For tensile modulus and bending modulus, the effect of bamboo age on the sensitivity to MC change was insignificant, while young bamboo (0.5 years old) was more sensitive to MC changes for shear strength and less sensitive for compression strength than older bamboo

Chemistry And Behavioral Studies Identify Chiral Cyclopropanes As Selective α4β2-Nicotinic Acetylcholine Receptor Partial Agonists Exhibiting An Antidepressant Profile

Despite their discovery in the early 20th century and intensive study over the last 20 years, nicotinic acetylcholine receptors (nAChRs) are still far from being well understood. Only a few chemical entities targeting nAChRs are currently undergoing clinical trials, and even fewer have reached the marketplace. In our efforts to discover novel and truly selective nAChR ligands, we designed and synthesized a series of chiral cyclopropane-containing α4β2-specific ligands that display low nanomolar binding affinities and excellent subtype selectivity while acting as partial agonists at α4β2-nAChRs. Their favorable antidepressant-like properties were demonstrated in the classical mouse forced swim test. Preliminary ADMET studies and broad screening toward other common neurotransmitter receptors were also carried out to further evaluate their safety profile and eliminate their potential off-target activity. These highly potent cyclopropane ligands possess superior subtype selectivity compared to other α4β2-nAChR agonists reported to date, including the marketed drug varenicline, and therefore may fully satisfy the crucial prerequisite for avoiding adverse side effects. These novel chemical entities could potentially be advanced to the clinic as new drug candidates for treating depression. © 2011 American Chemical Society

Machine learning versus classical electrocardiographic criteria for echocardiographic left ventricular hypertrophy in a pre-participation cohort

Background: Classical electrocardiographic (ECG) criteria for left ventricular hypertrophy (LVH) are well studied in older populations and patients with hypertension. Their utility in young pre-participation cohorts is unclear.Aims: We aimed to develop machine learning models for detection of echocardiogram-diagnosed LVH from ECG, and compare these models with classical criteria.Methods: Between November 2009 and December 2014, pre-participation screening ECG and subsequent echocardiographic data was collected from 17 310 males aged 16 to 23, who reported for medical screening prior to military conscription. A final diagnosis of LVH was made during echocardiography, defined by a left ventricular mass index >115 g/m2. The continuous and threshold forms of classical ECG criteria (Sokolow–Lyon, Romhilt–Estes, Modified Cornell, Cornell Product, and Cornell) were compared against machine learning models (Logistic Regression, GLMNet, Random Forests, Gradient Boosting Machines) using receiver-operating characteristics curve analysis. We also compared the important variables identified by machine learning models with the input variables of classical criteria.Results: Prevalence of echocardiographic LVH in this population was 0.82% (143/17310). Classical ECG criteria had poor performance in predicting LVH. Machine learning methods achieved superior performance: Logistic Regression (area under the curve [AUC], 0.811; 95% confidence interval [CI], 0.738–0.884), GLMNet (AUC, 0.873; 95% CI, 0.817–0.929), Random Forest (AUC, 0.824; 95% CI, 0.749–0.898), Gradient Boosting Machines (AUC, 0.800; 95% CI, 0.738–0.862).Conclusions: Machine learning methods are superior to classical ECG criteria in diagnosing echocardiographic LVH in the context of pre-participation screening

Study on the Swelling Characteristics of Bamboo Based on Its Graded Hierarchical Structure

To understand the swelling characteristics of bamboo under its gradient structure, different parts of bamboo specimens have been soaked in solutions of different electrolytes. The results showed that the swelling extent of bamboo in solution is mainly influenced by chemical activity and molecular dimension of the solute. The dimensional increase in bamboo after swelling is mainly observed in the tangential and radial direction, and the largest dimensional increase as a result of swelling occurred in intermediary bamboo. High-concentration strong electrolytes will cause a certain degree of recrystallization in the bamboo specimen, especially in intermediary bamboo, resulting in an increase in its mass. In summary, the conclusion is that the removal of wax and tabaxir before swelling and the avoidance of using strong electrolytes as swelling solutions tend to improve the efficiency of swelling bamboo

Moisture Dependence of Indentation Deformation and Mechanical Properties of Masson Pine (Pinus Massoniana Lamb) Cell Walls as Related to Microfibrilar Angle

To better understand how microfibrillar angle (MFA) and moisture content influence the mechanical performances of wood at the cell wall level, the nanoindentation technique was used to measure the indentation modulus, hardness, indentation creep rate (ICR), residual plastic deformation (RPD), and elastic recovery deformation (ERD) of Masson pine (Pinus massoniana Lamb) wood cell walls with small (16°), medium (27°), and large (38°) MFA values at 5, 8, and 11% MC, respectively. The results show cell wall elastic modulus was negatively correlated to moisture content, but the specific trend was to some extent affected by the value of MFA. MFA has a negative influence on cell wall elastic modulus across the range of all tested moisture contents. Cell wall hardness decreased significantly with increase of moisture content for all three MFA values, whereas the effect of MFA was insignificant. RPD and ERD of cell walls responded differently to the change of moisture content and MFA. In general, RPD is more sensitive to moisture content than MFA, whereas ERD and ICR are more sensitive to MFA than the low moisture content range as defined in this study