Cloud workflow scheduling is a significant topic in both commercial and industrial applications. However, the growing scale of workflow has made such a scheduling problem increasingly challenging. ...Many current algorithms often deal with small- or medium-scale problems (e.g., less than 1000 tasks) and face difficulties in providing satisfactory solutions when dealing with the large-scale problems, due to the curse of dimensionality. To this aim, this article proposes a dynamic group learning distributed particle swarm optimization (DGLDPSO) for large-scale optimization and extends it for the large-scale cloud workflow scheduling. DGLDPSO is efficient for large-scale optimization due to its following two advantages. First, the entire population is divided into many groups, and these groups are coevolved by using the master-slave multigroup distributed model, forming a distributed PSO (DPSO) to enhance the algorithm diversity. Second, a dynamic group learning (DGL) strategy is adopted for DPSO to balance diversity and convergence. When applied DGLDPSO into the large-scale cloud workflow scheduling, an adaptive renumber strategy (ARS) is further developed to make solutions relate to the resource characteristic and to make the searching behavior meaningful rather than aimless. Experiments are conducted on the large-scale benchmark functions set and the large-scale cloud workflow scheduling instances to further investigate the performance of DGLDPSO. The comparison results show that DGLDPSO is better than or at least comparable to other state-of-the-art large-scale optimization algorithms and workflow scheduling algorithms.
Engineering the adsorption of molecules on active sites is an integral and challenging part for the design of highly efficient transition‐metal‐based catalysts for methanol dehydrogenation. A ...Mott–Schottky catalyst composed of Ni nanoparticles and tailorable nitrogen‐doped carbon‐foam (Ni/NCF) and thus tunable adsorption energy is presented for highly efficient and selective dehydrogenation of gas‐phase methanol to hydrogen and CO even under relatively high weight hourly space velocities (WHSV). Both theoretical and experimental results reveal the key role of the rectifying contact at the Ni/NCF boundaries in tailoring the electron density of Ni species and enhancing the absorption energies of methanol molecules, which leads to a remarkably high turnover frequency (TOF) value (356 mol methanol mol−1 Ni h−1 at 350 °C), outpacing previously reported bench‐marked transition‐metal catalysts 10‐fold.
Active boundaries: The ability of Mott–Schottky‐type nanocatalysts to change the adsorption energy of methanol molecules for highly efficient and selective dehydrogenation of gas‐phase methanol was achieved by constructing a Ni nanoparticle/N‐doped carbon‐foam catalyst. The electron redistribution along the Ni‐N‐doped carbon phase boundaries promotes adsorption and activation of methanol, thus boosting methanol dehydrogenation.
In this study Illumina MiSeq was performed to investigate microbial diversity in soil, leaves, grape, grape juice and wine. A total of 1,043,102 fungal Internal Transcribed Spacer (ITS) reads and ...2,422,188 high quality bacterial 16S rDNA sequences were used for taxonomic classification, revealed five fungal and eight bacterial phyla. At the genus level, the dominant fungi were Ascomycota, Sordariales, Tetracladium and Geomyces in soil, Aureobasidium and Pleosporaceae in grapes leaves, Aureobasidium in grape and grape juice. The dominant bacteria were Kaistobacter, Arthrobacter, Skermanella and Sphingomonas in soil, Pseudomonas, Acinetobacter and Kaistobacter in grape and grapes leaves, and Oenococcus in grape juice and wine. Principal coordinate analysis showed structural separation between the composition of fungi and bacteria in all samples. This is the first study to understand microbiome population in soil, grape, grapes leaves, grape juice and wine in Xinjiang through High-throughput Sequencing and identify microorganisms like Saccharomyces cerevisiae and Oenococcus spp. that may contribute to the quality and flavor of wine.
In this study, researchers describe the clinical characteristics of coronavirus disease 2019 in a selected cohort of 1099 patients with laboratory-confirmed disease throughout mainland China during ...the first 2 months of the current outbreak.
Controlling toxigenic Fusarium graminearum (FG) is challenging. A bacterial strain (S76-3, identified as Bacillus amyloliquefaciens) that was isolated from diseased wheat spikes in the field ...displayed strong antifungal activity against FG. Reverse-phase high performance liquid chromatography and electrospray ionization mass spectrometry analyses revealed that S76-3 produced three classes of cyclic lipopeptides including iturin, plipastatin and surfactin. Each class consisted of several different molecules. The iturin and plipastatin fractions strongly inhibited FG; the surfactin fractions did not. The most abundant compound that had antagonistic activity from the iturin fraction was iturin A (m/z 1043.35); the most abundant active compound from the plipastatin fraction was plipastatin A (m/z 1463.90). These compounds were analyzed with collision-induced dissociation mass spectrometry. The two purified compounds displayed strong fungicidal activity, completely killing conidial spores at the minimal inhibitory concentration range of 50 µg/ml (iturin A) and 100 µg/ml (plipastatin A). Optical and fluorescence microscopy analyses revealed severe morphological changes in conidia and substantial distortions in FG hyphae treated with iturin A or plipastatin A. Iturin A caused leakage and/or inactivation of FG cellular contents and plipastatin A caused vacuolation. Time-lapse imaging of dynamic antagonistic processes illustrated that iturin A caused distortion and conglobation along hyphae and inhibited branch formation and growth, while plipastatin A caused conglobation in young hyphae and branch tips. Transmission electron microscopy analyses demonstrated that the cell walls of conidia and hyphae of iturin A and plipastatin A treated FG had large gaps and that their plasma membranes were severely damaged and separated from cell walls.
Cartilage injury and pathological degeneration are reported in millions of patients globally. Cartilages such as articular hyaline cartilage are characterized by poor self-regeneration ability due to ...lack of vascular tissue. Current treatment methods adopt foreign cartilage analogue implants or microfracture surgery to accelerate tissue repair and regeneration. These methods are invasive and are associated with the formation of fibrocartilage, which warrants further exploration of new cartilage repair materials. The present study aims to develop an injectable modified gelatin hydrogel.
The hydrogel effectively adsorbed proteoglycans secreted by chondrocytes adjacent to the cartilage tissue in situ, and rapidly formed suitable chondrocyte survival microenvironment modified by ε-poly-L-lysine (EPL). Besides, dynamic covalent bonds were introduced between glucose and phenylboronic acids (PBA). These bonds formed reversible covalent interactions between the cis-diol groups on polyols and the ionic boronate state of PBA. PBA-modified hydrogel induced significant stress relaxation, which improved chondrocyte viability and cartilage differentiation of stem cells. Further, we explored the ability of these hydrogels to promote chondrocyte viability and cartilage differentiation of stem cells through chemical and mechanical modifications.
In vivo and in vitro results demonstrated that the hydrogels exhibited efficient biocompatibility. EPL and PBA modified GelMA hydrogel (Gel-EPL/B) showed stronger activity on chondrocytes compared to the GelMA control group. The Gel-EPL/B group induced the secretion of more extracellular matrix and improved the chondrogenic differentiation potential of stem cells. Finally, thus hydrogel promoted the tissue repair of cartilage defects.
Modified hydrogel is effective in cartilage tissue repair.
The oxygen reduction reaction (ORR) is one of the most important reactions in life processes and energy conversion systems. To alleviate global warming and the energy crisis, the development of ...high‐performance electrocatalysts for the ORR for application in energy conversion and storage devices such as metal–air batteries and fuel cells is highly desirable. Inspired by the biological oxygen activation/reduction process associated with heme‐ and multicopper‐containing metalloenzymes, iron and copper‐based transition‐metal complexes have been extensively explored as ORR electrocatalysts. Herein, an outline into recent progress on non‐precious‐metal electrocatalysts for the ORR is provided; these electrocatalysts do not require pyrolysis treatment, which is regarded as desirable from the viewpoint of bioinspired molecular catalyst design, focusing on iron/cobalt macrocycles (porphyrins, phthalocyanines, and corroles) and copper complexes in which the ORR activity is tuned by ligand variation/substitution, the method of catalyst immobilization, and the underlying supporting materials. Current challenges and exciting imminent developments in bioinspired ORR electrocatalysts are summarized and proposed.
An outline of recent progress on non‐precious‐metal electrocatalysts for the oxygen reduction reaction (ORR) is presented from the viewpoint of bioinspired molecular catalyst design, with a focus on iron/cobalt macrocycles and copper complexes in which the ORR activity is tuned by ligand modification, the method of catalyst immobilization, and the underlying supporting materials (see scheme).
Niching techniques have been widely incorporated into evolutionary algorithms (EAs) for solving multimodal optimization problems (MMOPs). However, most of the existing niching techniques are either ...sensitive to the niching parameters or require extra fitness evaluations (FEs) to maintain the niche detection accuracy. In this paper, we propose a new automatic niching technique based on the affinity propagation clustering (APC) and design a novel niching differential evolution (DE) algorithm, termed as automatic niching DE (ANDE), for solving MMOPs. In the proposed ANDE algorithm, APC acts as a parameter-free automatic niching method that does not need to predefine the number of clusters or the cluster size. Also, it can facilitate locating multiple peaks without extra FEs. Furthermore, the ANDE algorithm is enhanced by a contour prediction approach (CPA) and a two-level local search (TLLS) strategy. First, the CPA is a predictive search strategy. It exploits the individual distribution information in each niche to estimate the contour landscape, and then predicts the rough position of the potential peak to help accelerate the convergence speed. Second, the TLLS is a solution refine strategy to further increase the solution accuracy after the CPA roughly predicting the peaks. Compared with the other state-of-the-art DE and non-DE multimodal algorithms, even the winner of competition on multimodal optimization, the experimental results on 20 widely used benchmark functions illustrate the superiority of the proposed ANDE algorithm.
Since the outbreak in late December 2019 in Wuhan, China, coronavirus disease-2019 (COVID-19) has become a global pandemic. We analyzed and compared the clinical, laboratory, and radiological ...characteristics between survivors and non-survivors and identify risk factors for mortality.
Clinical and laboratory variables, radiological features, treatment approach, and complications were retrospectively collected in two centers of Hubei province, China. Cox regression analysis was conducted to identify the risk factors for mortality.
A total of 432 patients were enrolled, and the median patient age was 54 years. The overall mortality rate was 5.09% (22/432). As compared with the survivor group (n = 410), those in the non-survivor group (n = 22) were older, and they had a higher frequency of comorbidities and were more prone to suffer from dyspnea. Several abnormal laboratory variables indicated that acute cardiac injury, hepatic damage, and acute renal insufficiency were detected in the non-survivor group. Non-surviving patients also had a high computed tomography (CT) score and higher rate of consolidation. The most common complication causing death was acute respiratory distress syndrome (ARDS) (18/22, 81.8%). Multivariate Cox regression analysis revealed that hemoglobin (Hb) <90 g/L (hazard ratio, 10.776; 95% confidence interval, 3.075-37.766; p<0.0001), creatine kinase (CK-MB) >8 U/L (9.155; 2.424-34.584; p = 0.001), lactate dehydrogenase (LDH) >245 U/L (5.963; 2.029-17.529; p = 0.001), procalcitonin (PCT) >0.5 ng/ml (7.080; 1.671-29.992; p = 0.008), and CT score >10 (39.503; 12.430-125.539; p<0.0001) were independent risk factors for the mortality of COVID-19.
Low Hb, high LDH, PCT, and CT score on admission were the predictors for mortality and could assist clinicians in early identification of poor prognosis among COVID-19 patients.
During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in ...other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences.
Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined.
At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7
44.9 years), had more cases with comorbidity (32.9%
19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7
4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0%
11.1%, death rate 7.3%
0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4
4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)).
There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.
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