An effective heuristic for project scheduling with resource availability cost

[EN] The resource constrained project scheduling problem (RCPSP) is widely studied in the literature and has a host of applications in practice. As a variant of the RCPSP, the resource availability cost problem (RACP), which has the aim of minimizing the availability costs of renewable resources in order to complete a project subject to a given deadline, is considered in this paper. We divide the RACP into two sub-problems: the sequencing problem and the resource decision problem, and propose a multi-start iterative search heuristic (MSIS) to solve it. For the sequencing problem, an iterative search framework is constructed to effectively search the activity sequences. A two stage resource adjustment procedure and a backward peak elimination procedure is developed for solving the resource decision problem. MSIS is compared with three existing algorithms on both PSPLib and RanGen data sets involving 1380 instances. A complete calibration of the different parameters and operators of MSIS by means of a design of experiments approach is given. Experimental and statistical results show that MSIS outperforms the other three algorithms in both effectiveness and efficiency by a significant margin. (C) 2016 Published by Elsevier B.V.This work is supported by the National Natural Science Foundation of China (Nos. 61572127, 61272377), the Key Research & Development program in Jiangsu Province (No. BE2015728) and the Collaborative Innovation Center of Wireless Communications Technology. Rubén Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project SCHEYARD - Optimization of Scheduling Problems in Container Yards with reference DPI2015-65895-R co-financed with FEDER funds.Zhu, X.; Ruiz García, R.; Li, S.; Li, X. (2017). An effective heuristic for project scheduling with resource availability cost. European Journal of Operational Research. 257(3):746-762. https://doi.org/10.1016/j.ejor.2016.08.049S746762257

Perceptual Image Compression with Cooperative Cross-Modal Side Information

The explosion of data has resulted in more and more associated text being transmitted along with images. Inspired by from distributed source coding, many works utilize image side information to enhance image compression. However, existing methods generally do not consider using text as side information to enhance perceptual compression of images, even though the benefits of multimodal synergy have been widely demonstrated in research. This begs the following question: How can we effectively transfer text-level semantic dependencies to help image compression, which is only available to the decoder? In this work, we propose a novel deep image compression method with text-guided side information to achieve a better rate-perception-distortion tradeoff. Specifically, we employ the CLIP text encoder and an effective Semantic-Spatial Aware block to fuse the text and image features. This is done by predicting a semantic mask to guide the learned text-adaptive affine transformation at the pixel level. Furthermore, we design a text-conditional generative adversarial networks to improve the perceptual quality of reconstructed images. Extensive experiments involving four datasets and ten image quality assessment metrics demonstrate that the proposed approach achieves superior results in terms of rate-perception trade-off and semantic distortion

Model-free adaptive iterative learning control of melt pool width in wire arc additive manufacturing

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Wire arc additive manufacturing (WAAM) is a Direct Energy Deposition (DED) technology, which utilize electrical arc as heat source to deposit metal material bead by bead to make up the final component. However, issues like the lack of assurance in accuracy, repeatability and stability hinder the further application in industry. Therefore, a Model Free Adaptive Iterative Learning Control (MFAILC) algorithm was developed to be applied in WAAM process in this study. The dynamic process of WAAM is modelled by adaptive neuro fuzzy inference system (ANFIS). Based on this ANFIS model, simulations are performed to demonstrate the effectiveness of MFAILC algorithm. Furthermore, experiments are conducted to investigate the tracking performance and robustness of the MFAILC controller. This work will help to improve the forming accuracy and automatic level of WAAM

Experimental and Theoretical Advances on Single Atom and Atomic Cluster-Decorated Low-Dimensional Platforms towards Superior Electrocatalysts

The fundamental relationship between structure and properties, which is called “structure-property”, plays a vital role in the rational designing of high-performance catalysts for diverse electrocatalytic applications. Low-dimensional (LD) nanomaterials, including 0D, 1D, 2D materials, combined with low-nuclearity metal atoms, ranging from single atoms to subnanometer clusters, are currently emerging as rising star nanoarchitectures for heterogeneous catalysis due to their well-defined active sites and unbeatable metal utilization efficiencies. In this work, a comprehensive experimental and theoretical review is provided on the recent development of single atom and atomic cluster-decorated LD platforms towards some typical clean energy reactions, such as water-splitting, nitrogen fixation, and carbon dioxide reduction reactions. The upmost attractive structural properties, advanced characterization techniques, and theoretical principles of these low-nuclearity electrocatalysts as well as their applications in key electrochemical energy devices are also elegantly discussed

Progressive Learning with Visual Prompt Tuning for Variable-Rate Image Compression

In this paper, we propose a progressive learning paradigm for transformer-based variable-rate image compression. Our approach covers a wide range of compression rates with the assistance of the Layer-adaptive Prompt Module (LPM). Inspired by visual prompt tuning, we use LPM to extract prompts for input images and hidden features at the encoder side and decoder side, respectively, which are fed as additional information into the Swin Transformer layer of a pre-trained transformer-based image compression model to affect the allocation of attention region and the bits, which in turn changes the target compression ratio of the model. To ensure the network is more lightweight, we involves the integration of prompt networks with less convolutional layers. Exhaustive experiments show that compared to methods based on multiple models, which are optimized separately for different target rates, the proposed method arrives at the same performance with 80% savings in parameter storage and 90% savings in datasets. Meanwhile, our model outperforms all current variable bitrate image methods in terms of rate-distortion performance and approaches the state-of-the-art fixed bitrate image compression methods trained from scratch

Exploratory Factor Analysis for Validating Traditional Chinese Syndrome Patterns of Chronic Atrophic Gastritis

Background. Traditional Chinese medicine (TCM) has long been used to treat chronic atrophic gastritis (CAG). The aim of the present study was to evaluate the TCM syndrome characteristics of CAG and its core pathogenesis so as to promote optimization of treatment strategies. Methods. This study was based on a participant survey conducted in 4 hospitals in China. Patients diagnosed with CAG were recruited by simple random sampling. Exploratory factor analysis (EFA) was conducted on syndrome extraction. Results. Common factors extracted were assigned to six syndrome patterns: qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, and yang deficiency. Distribution frequency of all syndrome patterns showed that qi deficiency, qi stagnation, blood stasis, phlegm turbidity, and heat excess were higher (76.7%–84.2%) compared with yang deficiency (42.5%). Distribution of main syndrome patterns showed that frequencies of qi deficiency, qi stagnation, phlegm turbidity, heat, and yang deficiency were higher (15.8%–20.8%) compared with blood stasis (8.3%). Conclusions. The core pathogenesis of CAG is combination of qi deficiency, qi stagnation, blood stasis, phlegm turbidity, heat, and yang deficiency. Therefore, treatment strategy of herbal prescriptions for CAG should include herbs that regulate qi, activate blood, resolve turbidity, clear heat, remove toxin, and warm yang

Diploid mycelia of Ustilago esculenta fails to maintain sustainable proliferation in host plant

Smut fungi display a uniform life cycle including two phases: a saprophytic phase in vitro and a parasitic phase in host plants. Several apathogenic smut fungi are found, lacking suitable hosts in their habitat. Interestingly, MT-type Ustilago esculenta was found to maintain a parasitic life, lacking the saprophytic phase. Its long period of asexual proliferation in plant tissue results in severe defects in certain functions. In this study, the growth dynamics of U. esculenta in plant tissues were carefully observed. The mycelia of T- and MT-type U. esculenta exhibit rapid growth after karyogamy and aggregate between cells. While T-type U. esculenta successfully forms teliospores after aggregation, the aggregated mycelia of MT-type U. esculenta gradually disappeared after a short period of massive proliferation. It may be resulted by the lack of nutrition such as glucose and sucrose. After overwintering, infected Zizania latifolia plants no longer contained diploid mycelia resulting from karyogamy. This indicated that diploid mycelia failed to survive in plant tissues. It seems that diploid mycelium only serves to generate teliospores. Notably, MT-type U. esculenta keeps the normal function of karyogamy, though it is not necessary for its asexual life in plant tissue. Further investigations are required to uncover the underlying mechanism, which would improve our understanding of the life cycle of smut fungi and help the breeding of Z. latifolia

The feasibility and safety of his-purkinje conduction system pacing in patients with heart failure with severely reduced ejection fraction

ObjectiveThe purpose of this study was to evaluate the feasibility and outcomes of conduction system pacing (CSP) in patients with heart failure (HF) who had a severely reduced left ventricular ejection fraction (LVEF) of less than 30% (HFsrEF).MethodsBetween January 2018 and December 2020, all consecutive HF patients with LVEF < 30% who underwent CSP at our center were evaluated. Clinical outcomes and echocardiographic data [LVEF and left ventricular end-systolic volume (LVESV)], and complications were all recorded. In addition, clinical and echocardiographic (≥5% improvement in LVEF or ≥15% decrease in LVESV) responses were assessed. The patients were classified into a complete left bundle branch block (CLBBB) morphology group and a non-CLBBB morphology group according to the baseline QRS configuration.ResultsSeventy patients (66 ± 8.84 years; 55.7% male) with a mean LVEF of 23.2 ± 3.23%, LVEDd of 67.33 ± 7.47 mm and LVESV of 212.08 ± 39.74 ml were included. QRS configuration at baseline was CLBBB in 67.1% (47/70) of patients and non-CLBBB in 32.9%. At implantation, the CSP threshold was 0.6 ± 0.3 V @ 0.4 ms and remained stable during a mean follow-up of 23.43 ± 11.44 months. CSP resulted in significant LVEF improvement from 23.2 ± 3.23% to 34.93 ± 10.34% (P < 0.001) and significant QRS narrowing from 154.99 ± 34.42 to 130.81 ± 25.18 ms (P < 0.001). Clinical and echocardiographic responses were observed in 91.4% (64/70) and 77.1% (54/70) of patients. Super-response to CSP (≥15% improvement in LVEF or ≥30% decrease in LVESV) was observed in 52.9% (37/70) of patients. One patient died due to acute HF and following severe metabolic disorders. Baseline BNP (odds ratio: 0.969; 95% confidence interval: 0.939–0.989; P = 0.045) was associated with echocardiographic response. The proportions of clinical and echocardiographic responses in the CLBBB group were higher than those in the non-CLBBB group but without significant statistical differences.ConclusionsCSP is feasible and safe in patients with HFsrEF. CSP is associated with a significant improvement in clinical and echocardiographic outcomes, even for patients with non-CLBBB widened QRS