Chemical defoliants are widely used in cotton (Gossypium L.) to accelerate leaf abscission and boll maturation, as well as, to facilitate mechanical harvesting. The current study was conducted to determine the interactive effect of cotton cultivars and spraying time of defoliant on defoliation, boll opening, fibre yield and quality. An experiment was performed with four cultivars and three defoliant spraying time during 2019 and 2020 in split plot design with three replications. At harvest, the defoliation and boll opening rate of all treatments after spraying defoliant was 94.6 and 85.4%, while the blank control (water) was 73.9 and 79.1%, respectively. After spraying defoliant, the effects of defoliation rate, boll opening rate, fibre yield and quality were different among cultivars, indicating that different cultivars had different responses to defoliant. Among them, L7619 was the most sensitive to defoliant, with the average defoliation rate of 95.6% and a seed cotton yield reduction of 882.9 kg/ha. Among the different time of applications, late spraying (17 September, B3) of defoliant recorded the highest defoliation rate (97.3%), boll opening rate (89.8%), seed cotton yield (3991 kg/ha) and steadily increased the fibre strength by 0.59 cN/tex compared with the control. Late spraying of defoliant had little or even no adverse effect on the remaining fibre quality traits (length, uniformity, micronaire and elongation). In general, these results suggested that the appropriate time for spraying defoliant can be determined based on the sensitivity of the cotton cultivar, the weather conditions at the field and the harvest time.

A novel concept—the contact-based landing on a mobile platform—is proposed in this paper. An adaptive backstepping controller is designed to deal with the unknown disturbances in the interactive process, and the contact-based landing mission is implemented under the hybrid force/motion control framework. A rotorcraft aerial vehicle system and a ground mobile platform are designed to conduct flight experiments, evaluating the feasibility of the proposed landing scheme and control strategy. To the best of our knowledge, this is the first time a rotorcraft unmanned aerial vehicle has been implemented to conduct a contact-based landing. To improve system autonomy in future applications, vision-based recognition and localization methods are studied, contributing to the detection of a partially occluded cooperative object or at a close range. The proposed recognition algorithms are tested on a ground platform and evaluated in several simulated scenarios, indicating the algorithm’s effectiveness.

Streptococcus agalactiae (S. agalactiae) infection is a significant cause of mastitis, resulting in loss of cellular homeostasis and tissue damage. Autophagy plays an essential function in cell survival, defense, and the preservation of cellular homeostasis, and is often part of the response to pathogenic challenge. However, the effect of autophagy induced by S. agalactiae in bovine mammary epithelial cells (bMECs) is mainly unknown. So in this study, an intracellular S. agalactiae infection model was established. Through evaluating the autophagy-related indicators, we observed that after S. agalactiae infection, a significant quantity of LC3-I was converted to LC3-II, p62 was degraded, and levels of Beclin1 and Bcl2 increased significantly in bMECs, indicating that S. agalactiae induced autophagy. The increase in levels of LAMP2 and LysoTracker Deep Red fluorescent spots indicated that lysosomes had participated in the degradation of autophagic contents. After autophagy was activated by rapamycin (Rapa), the amount of p-Akt and p-mTOR decreased significantly, whilst the amount of intracellular S. agalactiae increased significantly. Whereas the autophagy was inhibited by 3-methyladenine (3MA), the number of intracellular pathogens decreased. In conclusion, the results demonstrated that S. agalactiae could induce autophagy through PI3K/Akt/mTOR pathway and utilize autophagy to survive in bMECs.

With the increase of crewed space missions and the rise of space microbiology, the research of microbes grown under microgravity environment has been attracting more attention. The research scope in space microbiology has been extended beyond pathogens directly related to spaceflight. Y. pestis, the causative agent of plague, is also of interest to researchers. After being cultivated for 40 consecutive passages in either simulated microgravity (SMG) or normal gravity (NG) conditions, the Y. pestis strain 201 cultures were analysed regarding their phenotypic features. By using crystal violet staining assays, increased biofilm amount was detected in Y. pestis grown under SMG condition. Besides that, the damage degrees of Hela cell caused by SMG-grown Y. pestis were found diminished in comparison to those under NG condition. Consistent with this observation, the death course was delayed in mice infected with SMG-grown Y. pestis, suggesting that microgravity condition can contribute the attenuated virulence. RNA-seq-based transcriptomics analysis showed that a total of 218 genes were differentially regulated, of which 91 upregulated and 127 downregulated. We found that dozens of virulence-associated genes were downregulated, which partially explained the reduced virulence of Y. pestis under SMG condition. Our study demonstrated that long-term exposure to SMG influences the pathogenesis and biofilm formation ability of Y. pestis, which provides a novel avenue to study the mechanism of physiology and virulence of this pathogen. Microgravity enhanced the ability of biofilm formation and reduced the virulence and cytotoxicity of Y. pestis. Many virulence-associated genes of Y. pestis were differentially regulated in response to the stimulated microgravity. However, there is no molecular evidence to explain the enhanced biofilm formation ability, which requires further research. Taken together, the phenotype changes of Y. pestis under SMG conditions can provide us a new research direction of its potential pathogenesis.

As part of a long-term experiment to determine the impacts of composted manure and straw amendments (replacing 50% of chemical fertilizer with composted pig manure, wheat straw return combined with chemical fertilizer, and setting no fertilizer and chemical fertilizer-only as controls) on rice-associated weeds in a rice (Oryza sativa L.)–wheat (Triticum aestivum L.) rotation system, species richness, abundance, density, and biomass of weeds were assessed during years 8 and 9. Fertilization decreased the species richness and total density of rice-associated weeds but increased their total biomass. The species richness and densities of broadleaf and sedge weeds decreased with fertilization, while species richness of grass weeds increased only with straw return and density was not significantly affected. The shoot biomass per square meter of grass and broadleaf weeds was significantly higher with fertilization treatments than with the no-fertilizer control, while that of sedge weeds declined with fertilizer application. With fertilization, the densities of monarch redstem (Ammannia baccifera L.) and smallflower umbrella sedge (Cyperus difformis L.) decreased, that of Chinese sprangletop [Leptochloa chinensis (L.) Nees] increased, and those of barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] and monochoria [Monochoria vaginalis (Burm. f.) C. Presl ex Kunth] were not significantly affected. Ammannia baccifera was the most abundant weed species in all treatments. Whereas composted pig manure plus fertilizer resulted in higher density of A. baccifera and lower shoot biomass per plant than chemical fertilizer only, wheat straw return plus chemical fertilizer caused lower density and shoot biomass of A. baccifera. Therefore, it may be possible that fertilization strategies that suppress specific weeds could be used as improved weed management program components in rice production systems.

No relevant studies have yet been conducted to explore which measurement can best predict the survival time of patients with cancer cachexia. This study aimed to identify an anthropometric measurement that could predict the 1-year survival of patients with cancer cachexia. We conducted a nested case–control study using data from a multicentre clinical investigation of cancer from 2013 to 2020. Cachexia was defined using the Fearon criteria. A total of 262 patients who survived less than 1 year and 262 patients who survived more than 1 year were included in this study. Six candidate variables were selected based on clinical experience and previous studies. Five variables, BMI, mid-arm circumference, mid-arm muscle circumference, calf circumference and triceps skin fold (TSF), were selected for inclusion in the multivariable model. In the conditional logistic regression analysis, TSF (P = 0·014) was identified as a significant independent protective factor. A similar result was observed in all patients with cancer cachexia (n 3084). In addition, a significantly stronger positive association between TSF and the 1-year survival of patients with cancer cachexia was observed in participants aged > 65 years (OR: 0·94; 95 % CI 0·89, 0·99) than in those aged ≤ 65 years (OR: 0·96; 95 % CI 0·93, 0·99; Pinteraction = 0·013) and in participants with no chronic disease (OR: 0·92; 95 % CI 0·87, 0·97) than in those with chronic disease (OR: 0·97; 95 % CI 0·94, 1·00; Pinteraction = 0·049). According to this study, TSF might be a good anthropometric measurement for predicting 1-year survival in patients with cancer cachexia.

ABSTRACT IMPACT: This study will provide the essential characterization of intrinsic neural activity in human brain organoids, both at the single cell and network levels, to harness for translational purposes. OBJECTIVES/GOALS: Brain organoids are 3D, stem cell-derived neural tissues that recapitulate neurodevelopment. However, to levy their full translational potential, a deeper understanding of their intrinsic neural activity is essential. Here, we present our preliminary analysis of maturing neural activity in human forebrain organoids. METHODS/STUDY POPULATION: Forebrain organoids were generated from human iPSC lines derived from healthy volunteers. Linear microelectrode probes were employed to record spontaneous electrical activity from day 77, 100, and 130 organoids. Single unit recordings were collected during hour-long recordings, involving baseline recordings followed by glutamatergic blockade. Subsequently, tetrodotoxin, was used to abolish action potential firing. Single units were identified via spike sorting, and the spatiotemporal evolution of baseline neural properties and network dynamics was characterized. RESULTS/ANTICIPATED RESULTS: Nine organoids were recorded successfully (n=3 per timepoint). A significant difference in number of units was seen across age groups (F (2,6) = 6.4178, p = 0.0323). Post hoc comparisons by the Tukey HSD test showed significantly more units in day 130 (51.67 ±14.15) than day 77 (16.33 ±14.98) organoids. Mean firing rates were significantly different in organoids based on age, with drug condition also trending toward significance (F (6,12) = 9.97; p = 0.0028 and p = 0.08 respectively). Post hoc comparisons showed a higher baseline firing rate in day 130 (0.99Hz ±0.30) organoids than their day 77 counterparts at baseline (0.31Hz ±0.066) and glutamate blockade (0.31Hz ±0.045). Preliminary network analysis showed no modularity or small-world features; however, these features are expected to emerge as organoids mature. DISCUSSION/SIGNIFICANCE OF FINDINGS: Initial analysis of brain organoid activity demonstrates changes in single unit properties as they mature. Additional work in this area, as well as further network analyses, will confer better sense of how to rationally utilize brain organoids for translational purposes.

Hexangulaconulariids (Cambrian stages 1–2) are an extinct group of medusozoan polyps having a biradially symmetrical, fan-shaped periderm that is distinct from those of medusozoan polyps showing three-, four-, five-, or six-fold radial symmetry. Hexangulaconulariids exhibit substantial variation in gross morphology, including variation in the number of faces on each of the two major sides of the periderm. An intermediate taxon of hexangulaconulariids with ten faces (five on each major side) was expected. Here we describe a new hexangulaconulariid, Decimoconularia isofacialis new genus new species from Bed 5 of the Yanjiahe Formation (Cambrian Stage 2) in the Three Gorges area of Hubei Province, China. The new taxon differs from other hexangulaconulariids (Arthrochites, Hexaconularia, and Septuconularia) mainly in possessing a total of ten faces. The two lateral margins are each marked by a ridge in about the apertural half of the periderm and by a collinear furrow in about the apical half, while the five faces on each major side are bounded by a furrow in about the apertural half and by a collinear ridge in about the apical half. Among hexangulaconulariids, Decimoconularia and Septuconularia may be more closely related to each other than either genus is to Arthrochites or Hexaconularia.

UUID: http://zoobank.org/ca270a3b-25ee-4d1f-bdeb-91a963370e70

The accurate prediction of turbulent mixing induced by Rayleigh–Taylor (R–T), Richtmyer–Meshkov (R–M) and Kelvin–Helmholtz (K–H) instabilities is very important in understanding natural phenomena and improving engineering applications. In applications, the prediction of mixing with the Reynolds-averaged Navier–Stokes (RANS) equation remains the most widely used method. The RANS method involves two aspects, i.e. physical modelling and model coefficients. Generally, the latter is determined empirically; thus, there is a lack of universality. In this paper, inspired by the well-known Reynolds decomposition, we propose a methodology to determine the model coefficients with the following three steps: (i) preset a set of analytical RANS solutions by fully using the knowledge of mixing evolutions; (ii) simplify the differential RANS equations to algebraic equations by imposing the preset solutions to RANS equations; (iii) solve the algebraic equations approximately to give the values of the entire model coefficients. The specific application of this methodology in the widely used K–L mixing model shows that, using the same set of model coefficients determined from the current methodology, the K–L model successfully predicts the mixing evolutions in terms of different physical quantities (e.g. temporal scalings and spatial profiles), density ratios and problems (e.g. R–T, R–M, K–H and reshocked R–M mixings). It is possible to extend this methodology to other turbulence models characterised with self-similar evolutions, such as K-$\epsilon$ mixing models.

The 7 degrees of freedom (DOF) redundant manipulator greatly improves obstacle/singularity avoidance capability and operational flexibility. However, the inverse kinematics problem of this manipulator is very difficult to solve because it has an infinite number of solutions. This paper uses a new numerical sequence processing method with a closed-loop framework to solve the inverse kinematics of the 7-DOF redundant manipulator. Simulation and experiment show that this method has high commonality. No special structure of the robot is required, and this method has improved computational efficiency and reliability.

The study investigated novel wear and corrosion resistance of stainless steel and 316 stainless steel samples which were successfully prepared by laser melting deposition. Phase composition, microstructure, microhardness, wear resistance, and electrochemical corrosion resistance were studied. The experimental results showed that novel stainless steel was mainly composed of α-Fe and a few carbide phase (Cr, Fe)7C3. The microhardness of novel stainless steel was about 2.7 times greater than 316 stainless steel. Meanwhile, the specific wear rate of novel stainless steel and 316 stainless steel was 2.63 × 10−5 mm3/N m and 1.63 × 10−4 mm3/N m, respectively. The wear volume of 316 stainless steel was 6.19 times greater than novel stainless steel. The corrosion current and the corrosion potential of novel stainless steel and 316 stainless steel were 1.02 × 10−7 A/cm2 and 1.5 × 10−7 A/cm2, and −138.8 mV, −135.9 mV, respectively, in 3.5 wt% NaCl solution. Therefore, both microhardness and wear resistance of novel stainless steel were greatly improved, with high corrosion resistance.

Acer yangbiense Y.S. Chen & Q.E. Yang (Aceraceae) is a threatened tree species endemic to China, formerly presumed to have declined to only five extant individuals, restricted to Yangbi County, Yunnan Province. Our surveys in 2016, however, located 577 individuals in 12 localities, but only three localities (with a total of 62 individuals) are protected. Nine localities are on private forest land. The population's size structure is an inverse J-curve, but there is a scarcity of trees of the smallest size class and of seedlings. Our surveys also showed that the habitat of A. yangbiense is degraded as a result of the negative effects of agriculture, logging and wood harvesting. Assessment with the IUCN Red List categories and criteria indicates that A. yangbiense should be recategorized from Critically Endangered to Endangered.

Octapyrgites elongatus n. gen. n. sp., a relatively rare, tetraradial olivooid (Cnidaria, Medusozoa), is described from Bed 5 of the Yanjiahe Formation (Cambrian Stage 2) near Yichang, China. Although similar to Olivooides and Quadrapyrgites from the Fortunian Stage in consisting of a partially corrugated (longitudinal) periderm with a quadrate (transverse) apical portion and V-shaped apertural lobes, O. elongatus is substantially larger than other olivooids. The elongate apical region of O. elongatus is similar to four-sided Anaconularia anomala (Barrande, 1867), though with a flat tip that may have been an adaption for a sessile mode of life. As in other olivooids, embryonic development in O. elongatus may have been direct. Last, the paucity of olivooids and the absence of pentaradial cnidarians and carinachitids in Cambrian Stage 2 indicate a marked decline in the disparity of cnidarians near the Fortunian–Cambrian Age 2 boundary, when by contrast bilaterians underwent rapid diversification.

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Extant medusozoans (phylum Cnidaria) are dominated by forms showing tetraradial symmetry, but stem-group medusozoans of early Cambrian age collectively exhibit tetra-, bi-, penta-, and hexaradial symmetry. Moreover, the developmental and evolutionary relationships between four-fold and other types of radial symmetry in medusozoans remain poorly understood. Here we describe a new hexangulaconulariid, Septuconularia yanjiaheensis new genus new species, from Bed 5 of the Yanjiahe Formation (Cambrian Stage 2) in the Three Gorges area of Hupei Province, China. The laterally compressed, biradially symmetrical periderm of this species possesses 14 gently tapered faces, the most of any hexangulaconulariid described thus far. The faces are bordered by longitudinal ridges and crossed by short, irregularly spaced transverse ribs. Longitudinally, the periderm consists of three regions that probably correspond, respectively, to an embryonic stage, a transient juvenile stage, and a long adult stage. Septuconularia yanjiaheensis may have been derived from six-faced Hexaconularia (Fortunian Stage), which is morphologically intermediate between Septuconularia yanjiaheensis and Arthrochites. Furthermore, conulariids sensu stricto, carinachitids, and hexangulaconulariids may constitute a monophyletic group united by possession of an organic or organophosphatic periderm exhibiting longitudinal (corner) sulci, a facial midline, and offset of transverse ribs along the facial midline.

UUID: http://zoobank.org/01a972aa-aef3-4eef-a9a5-c2d8c3dda615

The study of the relationship among the manufacturing process, the structure and the property of materials can help to develop the new materials. The material images contain the microstructures of materials, therefore, the quantitative analysis for the material images is the important means to study the characteristics of material structures. Generally, the quantitative analysis for the material microstructures is based on the exact segmentation of the materials images. However, most material microstructures are shown with various shapes and complex textures in images, and they seriously hinder the exact segmentation of the component elements. In this research, machine learning method and complex networks method are adopted to the challenge of automatic material image segmentation. Two segmentation tasks are completed: on the one hand, the images of the titanium alloy are segmented based on the pixel-level classification through feature extraction and machine learning algorithm; on the other hand, the ceramic images are segmented with the complex networks theory. In the first task, texture and shape features near each pixel in titanium alloy image are calculated, such as Gabor filters, Hu moments and GLCM (Gray-Level Co-occurrence Matrix) etc.. The feature vector for the pixel can be obtained by arraying these features. Then, classification is performed with the random forest model. Once each pixel is classified, the image segmentation is completed. In the second task, a complex network structure is built for the ceramic image. Then, a clustering algorithm of complex network is used to obtain network connection area. Finally, the clustered network structure is mapped back to the image and getting the contours among the component elements. The experimental results demonstrate that these methods can accurately segment material images.