•Fed-batch composting was achieved with feeding ratios of 5% and 10% but not 15%.•The thermophilic conditions were obtained due to bacterial self-heating.•The compost failure at the 15% treatment was ...mainly ascribed to excessive moisture.•Firmicutes et al. were the dominant degraders in the food waste compost.•Temperature was the key environmental factor for community succession.
To determine the suitable feeding ratio for fed-batch aerobic composting, four fermenters were operated by adding 0%, 5%, 10% or 15% of food waste every day. The results showed that the 5% and 10% treatments were able to maintain continuous thermophilic conditions, while the 15% treatment performed badly in regard to composting temperature, which was probably due to the negative effects of excessive moisture on microbial activity. As composting proceeded, both the 5% and the 10% treatments reached maturity and achieved weight losses of approximately 65%. High-throughput sequencing results indicated that Firmicutes, Proteobacteria, Bacteroidetes and Actinobacteria were the dominant phyla of the community structure. The communities sampled at the thermophilic phases had high similarity and relatively low diversity, while species diversity increased in the maturity phase. This study was devoted to optimizing the fed-batch composting process and assessing bacterial communities, both of which were supplied as a reference for practical application.
As one of the main appendages of skin, hair follicles play an important role in the process of skin regeneration. Hair follicle is a tiny organ formed by the interaction between epidermis and dermis, ...which has complex and fine structure and periodic growth characteristics. The hair growth cycle is divided into three continuous stages, growth (anagen), apoptosis-driven regression (catagen) and relative quiescence (telogen). And The Morphogenesis and cycle of hair follicles are regulated by a variety of signal pathways. When the signal molecules in the pathways are abnormal, it will affect the development and cycle of hair follicles, which will lead to hair follicle-related diseases.This article will review the structure, development, cycle and molecular regulation of hair follicles, in order to provide new ideas for solving diseases and forming functional hair follicle.
Next-generation e-Science features large-scale, compute-intensive workflows of many computing modules that are typically executed in a distributed manner. With the recent emergence of cloud computing ...and the rapid deployment of cloud infrastructures, an increasing number of scientific workflows have been shifted or are in active transition to cloud environments. As cloud computing makes computing a utility, scientists across different application domains are facing the same challenge of reducing financial cost in addition to meeting the traditional goal of performance optimization. We construct analytical models to quantify the network performance of scientific workflows using cloud-based computing resources, and formulate a task scheduling problem to minimize the workflow end-to-end delay under a user-specified financial constraint. We rigorously prove that the proposed problem is not only NP-complete but also non-approximable. We design a heuristic solution to this problem, and illustrate its performance superiority over existing methods through extensive simulations and real-life workflow experiments based on proof-of-concept implementation and deployment in a local cloud test bed.
This paper proposes an advanced model predictive control (MPC) scheme for the attitude tracking of coaxial drones under wind disturbances. Unlike most existing MPC setups, this scheme embeds ...steady-input, steady-output, and steady-state conditions into the optimization problem as decision variables. Consequently, the coaxial drone’s attitude can slide along the state manifold composed of a series of steady states. This allows it to move toward the optimal reachable equilibrium. To address disturbances that are difficult to accurately measure, an extended state observer is employed to estimate the disturbances in the prediction model. This design ensures that the algorithm maintains recursive stability even in the presence of disturbances. Finally, numerical simulations and flight tests are provided to confirm the effectiveness of the proposed method through comparison with other control algorithms.
Learning-based approaches have made substantial progress in capturing spatially-varying bidirectional reflectance distribution functions (SVBRDFs) from a single image with unknown lighting and ...geometry. However, most existing networks only consider per-pixel losses which limit their capability to recover local features such as smooth glossy regions. A few generative adversarial networks use multiple discriminators for different parameter maps, increasing network complexity. We present a novel end-to-end generative adversarial network (GAN) to recover appearance from a single picture of a nearly-flat surface lit by flash. We use a single unified adversarial framework for each parameter map. An attention module guides the network to focus on details of the maps. Furthermore, the SVBRDF map loss is combined to prevent paying excess attention to specular highlights. We demonstrate and evaluate our method on both public datasets and real data. Quantitative analysis and visual comparisons indicate that our method achieves better results than the state-of-the-art in most cases.
Next-generation e-Science features large-scale, compute-intensive workflows of many computing modules that are typically executed in a distributed manner. With the recent emergence of cloud computing ...and the rapid deployment of cloud infrastructures, an increasing number of scientific workflows have been shifted or are in active transition to cloud environments. As cloud computing makes computing a utility, scientists across different application domains are facing the same challenge of reducing financial cost in addition to meeting the traditional goal of performance optimization. We develop a prototype generic workflow system by leveraging existing technologies for a quick evaluation of scientific workflow optimization strategies. We construct analytical models to quantify the network performance of scientific workflows using cloud-based computing resources, and formulate a task scheduling problem to minimize the workflow end-to-end delay under a user-specified financial constraint. We rigorously prove that the proposed problem is not only NP-complete but also non-approximable. We design a heuristic solution to this problem, and illustrate its performance superiority over existing methods through extensive simulations and real-life workflow experiments based on proof-of-concept implementation and deployment in a local cloud testbed.
Pancreatic adenocarcinoma (PAAD) has a poor prognosis with high individual variation in the treatment response among patients; however, there is no standard molecular typing method for PAAD prognosis ...in clinical practice. We analyzed DNA methylation data from The Cancer Genome Atlas database, which identified 1235 differentially methylated DNA genes between PAAD and adjacent tissue samples. Among these, 78 methylation markers independently affecting PAAD prognosis were identified after adjusting for significant clinical factors. Based on these genes, two subtypes of PAAD were identified through consistent clustering. Fourteen specifically methylated genes were further identified to be associated with survival. Further analyses of the transcriptome data identified 301 differentially expressed cancer driver genes between the two PAAD subtypes and the degree of immune cell infiltration differed significantly between the subtypes. The 14 specific genes characterizing the unique methylation patterns of the subtypes were used to construct a Bayesian network-based prognostic prediction model for typing that showed good predictive value (area under the curve value of 0.937). This study provides new insight into the heterogeneity of pancreatic tumors from an epigenetic perspective, offering new strategies and targets for personalized treatment plan evaluation and precision medicine for patients with PAAD.
In this study, SnO2-Sb2O3/GAC particle electrodes were prepared using the dip-calcination method. The particle electrodes were characterized by scanning electron microscopy (SEM), X-ray diffraction ...(XRD), Brunauer Emmett Teller (BET), thermogravimetric test and linear sweep voltammetry (LSV), which proved that the metal oxide was successfully loaded on the granular activated carbon and exhibited high electrocatalytic activity and thermal stability. The effects of initial pH, electrolytic voltage, electrolyte concentration, initial phenol concentration and particle electrode dosage on the performance of the three-dimensional (3D) electrocatalytic oxidation in phenol degradation were investigated. The results showed that under the optimal conditions, the removal rates of phenol and chemical oxygen demand (COD) were 99.65% and 67.16%, respectively. Finally, it was found that the novel particle electrodes had the ability of stable operation, maintaining high-efficiency operation no less than 15 times, which further highlights their robustness and durability.
As fixed compression ratio is used in traditional deep space exploration image transmission application, the same compression code rate is allocated to each image. However, since the information of ...each image in a space observation mission is nonuniform, the image with more information will inevitably lead to more compression distortion than the image with less information. Obviously, it's not an efficient way to transmit information in terms of data importance or overall distortion. Therefore, we proposed a combinatorial optimal bit rate allocation algorithm to improve the efficiency of image transmission in space application. Different from traditional method, the rate-distortion model of wavelet coefficients for each image in a transmission task was built, and under the overall maximum transmission rate constraint, an bit-rate optimal allocation was applied for each image to minimize the overall distortion of a batch of images. The proposed algorithm can be widely used in image compression algorithm with embedded code stream characteristics, such as JPEG2000 and SPIHT. Experimental results shows that in the range of 2.6 to 10 compression ratio, the algorithm can reduce image distortion MSB by 40%∼64% at the same overall transmission code rate, which equivalent to improvement of PSNR 3 dB to 5.4 dB.
The incorporation of the cognitive radio (CR) technology as a spectrum management tool in satellite communication has attracted considerable research attention because the CR allows the coexistence ...of the primary and secondary networks using the same resources. In this paper, satellites and their users are considered as a primary network, and the terrestrial base stations (BSs) and their users are considered as a secondary network. Besides, it is considered that terrestrial users cause interference to satellite users due to technical and environmental constraints. This interference reduces satellite users' satisfaction with downloads rate. In such a cognitive satellite network environment, content placement may also cause a decrease in user satisfaction. The successful download probability (SDP) is analyzed in this work based on different terrestrial user density. To utilize the satellite cache resources effectively, we propose two transmission strategies based on the terrestrial user density, namely, the multi-point cooperative transmission strategy (CT) and the parallel transmission strategy (PT). In addition, based on the cache service probability we determine the ratio of content distribution most popular content (MPC) and general popular content (GPC) and optimize the content placement process using the utility function in CT mode. Through computer simulation, we give numerical results of our method. The obtained numerical results show that the proposed strategies are effective in content placement.
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