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2022 ◽  
Vol 119 ◽  
pp. 104213
Peng Zhao ◽  
Xiaozhao Li ◽  
Wei Zhang ◽  
Zhiyong Xiong ◽  
Wentao Xu ◽  

2021 ◽  
Michael LoCascio ◽  
Christopher Bay ◽  
Majid Bastankhah ◽  
Garrett Barter ◽  
Paul Fleming ◽  

Abstract. Annual energy production (AEP) is often the objective function in wind plant layout optimization studies. The conventional method to compute AEP for a wind farm is to first evaluate power production for each wind direction and speed using either computational fluid dynamics simulations or engineering wake models. The AEP is then calculated by weighted-averaging (based on the wind rose at the wind farm site) the power produced across all wind directions. We propose a novel formulation for time-averaged wake velocity that incorporates an analytical integral of a wake deficit model across every wind direction. This approach computes the average flow field more efficiently, and layout optimization is an obvious application to exploit this benefit. The clear advantage of this new approach is that the layout optimization produces solutions with comparable AEP performance yet is completed about 700 times faster. The analytical integral and the use of a Fourier expansion to express the wind speed and wind direction frequency create a more smooth solution space for the gradient-based optimizer to excel compared with the discrete nature of the existing weighted-averaging power calculation.

2021 ◽  
Nadya Abbood ◽  
Tien Duy Vo ◽  
Jonas Watzel ◽  
Kenan A. J. Bozhueyuek ◽  
Helge B. Bode

Bacterial natural products in general, and non-ribosomally synthesized peptides in particular, are structurally diverse and provide us with a broad range of pharmaceutically relevant bioactivities. Yet, traditional natural product research suffers from rediscovering the same scaffolds and has been stigmatised as inefficient, time-, labour-, and cost-intensive. Combinatorial chemistry, on the other hand, can produce new molecules in greater numbers, cheaper and in less time than traditional natural product discovery, but also fails to meet current medical needs due to the limited biologically relevant chemical space that can be addressed. Consequently, methods for the high throughput generation of new-to-nature natural products would offer a new approach to identifying novel bioactive chemical entities for the hit to lead phase of drug discovery programms. As a follow-up to our previously published proof-of-principle study on generating bipartite type S non-ribosomal peptide synthetases (NRPSs), we now envisaged the de novo generation of non-ribosomal peptides (NRPs) on an unreached scale. Using synthetic zippers, we split NRPS in up to three subunits and rapidly generated different bi- and tripartite NRPS libraries to produce 49 peptides, peptide derivatives, and de novo peptides at good titres up to 145 mgL-1. A further advantage of type S NRPSs not only is the possibility to easily expand the created libraries by re-using previously created type S NRPS, but that functions of individual domains as well as domain-domain interactions can be studied and assigned rapidly.

2021 ◽  
Fabian Jirasek ◽  
Robert Bamler ◽  
Stephan Mandt

We present a generic way to hybridize physical and data-driven methods for predicting physicochemical properties. The approach ‘distills’ the physical method's predictions into a prior model and combines it with sparse experimental data using Bayesian inference. We apply the new approach to predict activity coefficients at infinite dilution and obtain significant improvements compared to the physical and data-driven baselines and established ensemble methods from the machine learning literature.

Molecules ◽  
2021 ◽  
Vol 26 (21) ◽  
pp. 6428
Shmuel Zilberg ◽  
Michael Zinigrad

The coordination of the B2 fragment by two σ-donor ligands L: could lead to a diboryne compound with a formal triple bond L:→B≡B←:L. σ-Type coordination L:→B leads to an excess of electrons around the B2 central fragment, whereas π-back-donation from the B≡B moiety to ligand L has a compensation effect. Coordination of the σ-donor and π-acceptor ligand is accompanied by the lowering of the BB bond order. Here, we propose a new approach to obtain the perfect triple BB bond through the incorporation of the BB unit into a rigid molecular capsule. The idea is the replacement of π-back-donation, as the principal stabilization factor in the linear NBBN structure, with the mechanical stabilization of the BB fragment in the inert molecular capsule, thus preserving the perfect B≡B triple bond. Quantum-chemical calculations show that the rigid molecular capsule provided a linear NBBN structure and an unusually short BB bond of 1.36 Å. Quantum-chemical calculations of the proposed diboryne adducts show a perfect triple bond B≡B without π-back-donation from the B2 unit to the host molecule. Two mechanisms were tested for the molecular design of a diboryne adduct with a perfect B≡B triple bond: the elimination of π-back-donation and the construction of a suitable molecular trap for the encapsulation of the B2 unit. The second factor that could lead to the strengthening or stretching of a selected chemical bond is molecular strain produced by the rigid molecular host capsule, as was shown for B≡B and for C≡C triple bonds. Different derivatives of icosane host molecules exhibited variation in BB bond length and the corresponding frequency of the BB stretch. On the other hand, this group of molecules shows a perfect triple BB bond character and they all possess a similar level of HOMO.

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Monsef Boughrous ◽  
Hanan El Bakkali

Workflow management systems are very important for any organization to manage and model complex business processes. However, significant work is needed to keep a workflow resilient and secure. Therefore, organizations apply a strict security policy and enforce access control constraints. As a result, the number of available and authorized users for the workflow execution decreases drastically. Thus, in many cases, such a situation leads to a workflow deadlock situation, where there no available authorized user-task assignments for critical tasks to accomplish the workflow execution. In the literature, this problem has gained interest of security researchers in the recent years, and is known as the workflow satisfiability problem (WSP). In this paper, we propose a new approach to bypass the WSP and to ensure workflow resiliency and security. For this purpose, we define workflow criticality, which can be used as a metric during run-time to prevent WSP. We believe that the workflow criticality value will help workflow managers to make decisions and start a mitigation solution in case of a critical workflow. Moreover, we propose a delegation process algorithm (DP) as a mitigation solution that uses workflow instance criticality, delegation, and priority concepts to find authorized and suitable users to perform the critical task with low-security risks.

2021 ◽  
Haobin Chen ◽  
Lisa Gesumaria ◽  
Young-Kwon Park ◽  
Trudy G Oliver ◽  
Dinah S. Singer ◽  

SCLC is a recalcitrant malignancy with a dismal prognosis. Four molecular subtypes of SCLC have been named, each associated with one master transcription factor (ASCL1, NEUROD1, POU2F3, or YAP1). Much is still unknown about the function and transactivation of NEUROD1 in this malignancy. Herein we report that knockout of NEUROD1 triggered SCLC to evolve into a YAP1 subtype. Through an integrated analysis of RNA-seq and ChIP-seq, we found NEUROD1 regulates neural-related genes by binding to gene promoters and distal enhancers. NEUROD1 physically interacts with BET bromodomain proteins and recruits them to actively transcribed genes. Inhibition of BET bromodomain proteins blocks NEUROD1 transactivation and suppresses SCLC growth. We identified LSAMP as one of the NEUROD1-target genes that mediate SCLC sensitivity to BET bromodomain inhibitors. Our findings suggest that targeting transcriptional coactivators could be a new approach to block master transcription factors in SCLC to enable precision therapy.

Yi-Feng Chen ◽  
Yi-Feng Chen ◽  
Shou-Zen Fan ◽  
Maysam F Abbod ◽  
Jiann-Shing Shieh ◽  

Abstract In this paper, a new approach of extracting and measuring the variability in electroencephalogram (EEG) was proposed to assess the depth of anesthesia (DOA) under general anesthesia. The EEG variability (EEGV) was extracted as a fluctuation in time interval that occurs between two local maxima of EEG. Eight parameters related to EEGV were measured in time and frequency domains, and compared with state-of-the-art DOA estimation parameters, including sample entropy, permutation entropy, median frequency and spectral edge frequency of EEG. The area under the receiver-operator characteristics curve (AUC) and Pearson correlation coefficient were used to validate its performance on 56 patients. Our proposed EEGV-derived parameters yield significant difference for discriminating between awake and anesthesia stages at a significance level of 0.05, as well as improvement in AUC and correlation coefficient on average, which surpasses the conventional features of EEG in detection accuracy of unconscious state and tracking the level of consciousness. To sum up, EEGV analysis provides a new perspective in quantifying EEG and corresponding parameters are powerful and promising for monitoring DOA under clinical situations.

Geofluids ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Guannan Liu ◽  
Xiaopeng Pei ◽  
Dayu Ye ◽  
Feng Gao ◽  
Zongqing Zhou ◽  

As one of the most prevalent porous media, rock contains a large number of pore throats of varying size and shape. It is essential to analyze the complex pore network structure and to define the network structural features to reveal the microscopic mechanism of the rock permeability. In this paper, based on the complex network theory and CT scanning technology, sandstone is used as an example to study the structural characteristics of the rock network with different porosities. The results show that the structural characteristics of the sandstone seepage network are consistent with BA scale-free network, whose average path length increases with the size of the network. At the same time, the porosity of the sandstone is strongly influenced by the number of throat in the rock pore network. Furthermore, our analysis concludes that a few pores with a large number of connections contribute significantly to the overall connectivity of the sandstone seepage network. Removing the ‘hub’ pores increased the average path length of the entire network by 27.63-37.26%, which could not be achieved by randomly removing method. While the sandstone seepage network has better fault tolerance and robustness to external random attacks, this study provides a new approach to study the mechanisms of fluid storage and migration in porous media.

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