Plant Phenotyping on Mobile Devices

Plants phenotyping is a fast and non-destructive method to obtain the physiological features of plants, compared with the expensive and time costing chemical analysis with plant sampling. Through plant phenotyping, scientists and farmers can tell plant health status more accurately compared to visual inspection, thus avoid the waste in time and resources and even to predict the productivity. However, the size and price of current plant phenotyping equipment restrict them from being widely applied at a farmer’s household level. Everyday field operation is barely achieved because of the availability of easy-to-carry and cost-effective equipment such as hyper-spectrum cameras, infrared cameras and thermal cameras. A plant phenotyping tool on mobile devices will make plant phenotyping technology more accessible to ordinary farmers and researchers. This application incorporates the use of physical optics, plant science models, and image processing ability of smartphones. With our special optical design, multispectral instead of RGB (red, green and blue) images can be obtained from the smartphones with fairly low cost. Through quick image processing on the smartphones, the APP will provide accurate plant physiological features predictions such as water, chlorophyll, and nitrogen. The sophisticated prediction models are applied which are provided by the Purdue’s plant phenotyping team. Once widely adopted, the information collected by the smartphones with the developed APP will be sent back to Purdue’s plant health big-data database. The feedback will not only allow us to improve our models, but also provide farmers and agricultural researchers easy access to real-time crop plant health data

The Next-Gen Crop Nutrient Stress Identification with High-Precision Sensing Technology in Digital Agriculture

Crop yields are facing significant losses from nutrient deficiencies. Over-fertilizing also has negative economic and environmental impacts. It is challenging to optimize fertilizing without an accurate diagnosis. Recently, plant phenotyping has demonstrated outstanding capabilities in estimating crop traits. As one of the leading technologies, LeafSpec, provides high-quality crop image data for improving phenotyping quality. In this study, novel algorithms are developed for LeafSpec to identify crop nutrient deficiencies more accurately. Combined with UAV system, this technology will bring growers a robust solution for fertilizing diagnosis and scientific crop management

A new p-terphenyl derivative from the insect-derived fungus Aspergillus candidus Bdf-2 and the synergistic effects of terphenyllin

A new p-terphenyl derivative 4″-deoxy-2′-methoxyterphenyllin (1), along with six known p-terphenyl derivatives (2–7), a known flavonoid derivative dechlorochlorflavonin (8) and a known fellutanine A (9), were isolated from the insect-derived strain of the fungus Aspergillus candidus Bdf-2, associated with Blaptica dubia. The structure of 1 was established by the analysis of the 1D and 2D NMR and HR-ESI-MS spectra. Compounds 1–9 were evaluated for antibacterial activities against Staphylococcus aureus ATCC29213, Escherichia coli ATCC25922 and Ralstonia solanacearum, and for antioxidant activities. Synergistic effects of compound 2 with the other compounds were also investigated. As a result, compound 6 displayed the best antibacterial activities in all single compound with MIC value of 32 µg/mL against S. aureus ATCC29213 and R. solanacearum, respectively. However, no antibacterial effect against E. coli ATCC25922 was detected from any single compound. The combination of 2 + 6 exhibited obvious synergistic effect against S. aureus ATCC29213 and the MIC value was 4 µg/mL. Compound 6 also showed the best antioxidant activity as a single compound with an IC50 value of 17.62 µg/mL. Combinations of 5 + 6, 2 + 4 + 5 and 2 + 4 + 5 + 6 displayed synergistic effect and their antioxidant activities were better than that of any single compound

Between Satire and Politics: Tracing British Perception of China in Punch’s Cartoons

Cartooning China: Punch, Power & Politics in the Victorian Era von Amy Matthewson bietet verschiedene Einblicke in die Beziehung zwischen der berühmten britischen Zeitschrift Punch und der chinesisch-britischen Politik im Viktorianischen Zeitalter. Amy Matthewson kontextualisiert die Cartoons und Textsatiren über China und die Chinesen von Punch mit der spezifischen Geschichte der britisch-chinesischen Politik. Matthewson argumentiert, dass Punch eine wichtige Rolle bei der Konstruktion einer festen Vorstellung über China und die Chinesen in der britischen populären Imagination spielte, welche die britische Selbstwahrnehmung und ihre Rolle in der Welt offenbart.Cartooning China: Punch, Power & Politics in the Victorian Era by Amy Matthewson provides various insights into the relationship between the famous British magazine Punch and Sino-British politics in the Victorian era. By contextualizing Punch’s cartoons and textual satires of China and the Chinese with the specific history of Sino-British politics, Matthewson argues that Punch played an important role in constructing a fixed idea of China and the Chinese in the British popular imagination, which reveals British self-perception and its role in the world

An Enhanced Image Patch Tensor Decompostion for Infrared Small Target Detection

Infrared small-target detection is a key technology for the infrared search and track system (IRST), but some problems still exist, such as false detections in complex backgrounds and clutter. To solve these problems, a novel image patch tensor (IPT) model for infrared small-target detection is proposed. First, to better estimate the background component, we utilize the Laplace operator to approximate the background tensor rank. Secondly, we combined local gradient features and highlighted area indicators to model the local targets prior, which can effectively suppress the complex background clutter. The proposed model was solved by the alternating direction method of multipliers (ADMM). The experimental results on various scenes show that our model achieves an excellent performance in suppressing strong edge clutter and estimating small targets

Study of SPRC Impact Resistance Based on the Weibull Distribution and the Response Surface Method

Silica-fume–polyvinyl-alcohol-fiber-reinforced concrete (SPRC) is a green and environmentally friendly composite material incorporating silica fume and polyvinyl alcohol fiber into concrete. To study the impact resistance of SPRC, compressive-strength and drop hammer impact tests were conducted on SPRC with different silica-fume and polyvinyl-alcohol-fiber contents. The mechanical and impact resistance properties of the SPRC were comprehensively analyzed in terms of the compressive strength, ductility ratio and impact-energy-dissipation variation. Based on the impact resistance of the SPRC, the impact life of SPRC with different failure probabilities was predicted by incorporating the Weibull distribution model, and an impact damage evolution equation for SPRC was established. The impact life of SPRC under the action of silica-fume content, polyvinyl-alcohol-fiber content and failure probability was analyzed in depth by the response surface method (RSM). The research results show that, when the content of silica fume is 10% and the content of polyvinyl alcohol fiber is 1%, the compressive strength and impact resistance of SPRC are the best. The RSM response model can effectively predict and describe the impact life of SPRC specimens under the action of three factors

Work–family conflict categories and support strategies for married female nurses: a latent profile analysis

ObjectiveTo clarify subgroups of married female nurses experiencing work–family conflict (WFC), explore the factors associated with the subgroups, and determine how desired support strategies differ among the subgroups.MethodsData was collected from a sample of 646 married female nurses from public hospitals in Zhejiang Province, China, in December 2021. Latent profile analysis was used to group the participants, and multiple logistic regression was used to identify factors associated with higher WFC. The STROBE criteria were used to report results.ResultsAccording to latent profile analysis, there were three distinct profiles of WFC among married female nurses: “low-conflict type,” “work-dominant-conflict type,” and “high-conflict type.” These profiles differed in the number of children, night shifts, family economic burden, childcare during working hours, family harmony, colleague support, and nurse–patient relationships. Nurses with multiple children, higher pressures in childcare during working hours, heavier family economic burdens, lower family harmony, lower colleague support, and poorer nurse–patient relationships are more likely to be classified as “high-conflict type” nurses.ConclusionThis study found that married female nurses experience different types of WFCs. The structure of these WFCs and their associated factors suggests that customized intervention strategies can be developed to address the specific needs of married female nurses

Experimental Study on the Mechanics and Impact Resistance of Multiphase Lightweight Aggregate Concrete

Multiphase lightweight aggregate concrete (MLAC) is a green composite building material prepared by replacing part of the crushed stone in concrete with other coarse aggregates to save construction ore resources. For the best MLAC performance in this paper, four kinds of coarse aggregate—coal gangue ceramsite, fly ash ceramsite, pumice and coral—were used in different dosages (10%, 20%, 30% and 40%) of the total coarse aggregate replacement. Mechanical property and impact resistance tests on each MLAC group showed that, when coal gangue ceramsite was 20%, the mechanical properties and impact resistance of concrete were the best. The compressive, flexural and splitting tensile strength and impact energy dissipation increased by 29.25, 19.93, 13.89 and 8.2%, respectively, compared with benchmark concrete. The impact loss evolution equation established by the two-parameter Weibull distribution model effectively describes the damage evolution process of MLAC under dynamic loading. The results of a comprehensive performance evaluation of four multiphase light aggregate concretes are coal gangue ceramsite concrete (CGC) > fly ash ceramsite concrete (FAC) > coral aggregate concrete (CC) > pumice aggregate concrete (PC)