Nature-inspired computing has been a hot topic in scientific and engineering fields in recent years. Inspired by the shallow water wave theory, the paper presents a novel metaheuristic method, named ...water wave optimization (WWO), for global optimization problems. We show how the beautiful phenomena of water waves, such as propagation, refraction, and breaking, can be used to derive effective mechanisms for searching in a high-dimensional solution space. In general, the algorithmic framework of WWO is simple, and easy to implement with a small-size population and only a few control parameters. We have tested WWO on a diverse set of benchmark problems, and applied WWO to a real-world high-speed train scheduling problem in China. The computational results demonstrate that WWO is very competitive with state-of-the-art evolutionary algorithms including invasive weed optimization (IWO), biogeography-based optimization (BBO), bat algorithm (BA), etc. The new metaheuristic is expected to have wide applications in real-world engineering optimization problems.
Biotic resistance may influence invasion success; however, the relative roles of species richness, functional or phylogenetic distance in predicting invasion success are not fully understood. We used ...biomass fraction of Chromolaena odorata, an invasive species in tropical and subtropical areas, as a measure of ‘invasion success’ in a series of artificial communities varying in species richness. Communities were constructed using species from Mexico (native range) or China (non‐native range). We found strong evidence of biotic resistance: species richness and community biomass were negatively related with invasion success; invader biomass was greater in plant communities from China than from Mexico. Harvesting time had a greater effect on invasion success in plant communities from China than on those from Mexico. Functional and phylogenetic distances both correlated with invasion success and more functionally distant communities were more easily invaded. The effects of plant‐soil fungi and plant allelochemical interactions on invasion success were species‐specific.
Abstract
As a key component in stretchable electronics, semiconducting polymers have been widely studied. However, it remains challenging to achieve stretchable semiconducting polymers with high ...mobility and mechanical reversibility against repeated mechanical stress. Here, we report a simple and universal strategy to realize intrinsically stretchable semiconducting polymers with controlled multi-scale ordering to address this challenge. Specifically, incorporating two types of randomly distributed co-monomer units reduces overall crystallinity and longer-range orders while maintaining short-range ordered aggregates. The resulting polymers maintain high mobility while having much improved stretchability and mechanical reversibility compared with the regular polymer structure with only one type of co-monomer units. Interestingly, the crystalline microstructures are mostly retained even under strain, which may contribute to the improved robustness of our stretchable semiconductors. The proposed molecular design concept is observed to improve the mechanical properties of various p- and n-type conjugated polymers, thus showing the general applicability of our approach. Finally, fully stretchable transistors fabricated with our newly designed stretchable semiconductors exhibit the highest and most stable mobility retention capability under repeated strains of 1,000 cycles. Our general molecular engineering strategy offers a rapid way to develop high mobility stretchable semiconducting polymers.
Diabetic nephropathy (DN) is a severe end‐stage kidney disease developed from diabetes mellitus. The involvement of circular RNAs (circRNAs) in modulating DN pathogenesis has been implied, but ...underlying mechanism is still lacking. In this study, we demonstrated that the expression of circ_0080425 correlated with the DN progression, and exerted positive effect on cell proliferation and fibrosis in mesangial cells. Further assessment suggested that circ_0080425 function as sponge harboring miR‐24‐3p. Moreover, miR‐24‐3p negatively correlated with the DN progression, and showed an antagonistic effect to circ_0080425on regulating MCs cell proliferation and fibrosis. Bioinformatics analysis predicted fibroblast growth factor 11 (FGF11) acting as direct downstream target of miR‐24‐3p. Indeed, the expression of FGF11 was significantly activated by circ_0080425 while suppressed by miR‐24‐3p. Knockdown of FGF11 resulted in a significant reduced cell proliferation rate and fibrosis. In addition, miR‐24‐3p inhibitor rescued the suppression of si‐circ_0080425 on FGF11, suggesting that circ_0080425 competitive binding to miR‐24‐3p could release FGF11 from miR‐24‐3p suppression, which subsequently promoted DN progression.In conclusion, we have reported a novel circ_0080425‐miR‐24‐3p‐FGF11 axis, and explored the underlying mechanism in regulating DN pathogenesis.
The expression of circ_0080425 correlated with the diabetic nephropathy (DN) progression, and exerted positive effect on cell proliferation and fibrosis in mesangial cells. Circ_0080425 competitive binding to miR‐24‐3p could release FGF11 from miR‐24‐3p suppression, which subsequently promoted DN progression. In conclusion, we have reported a novel circ_0080425‐miR‐24‐3p‐FGF11 axis.
Conjugation breakers (CBs) with different H-bonding chemistries and linker flexibilities are designed and incorporated into a diketopyrrolopyrrole (DPP)-based conjugated polymer backbone. The effects ...of H-bonding interactions on polymer semiconductor morphology, mechanical properties, and electrical performance are systematically investigated. We observe that CBs with an H-bonding self-association constant >0.7 or a denser packing tendency are able to induce higher polymer chain aggregation and crystallinity in as-casted thin films, resulting in a higher modulus and crack on-set strain. Additionally, the rDoC (relative degree of crystallinity) of the stretched thin film with the highest crack on-set strain only suffers a small decrease, suggesting the main energy dissipation mechanism is the breakage of H-bonding interactions. By contrast, other less stretchable polymer films dissipate strain energy through the breakage of crystalline domains, indicated by a drastic decrease in rDoC. Furthermore, we evaluate their electrical performances under mechanical strain in fully stretchable field-effect transistors. The polymer with the highest crack on-set strain has the least degradation in mobility as a function of strain. Overall, these observations suggest that we can aptly tune the mechanical properties of a polymer semiconductor by modulating intermolecular interactions, such as H-bonding chemistry and linker flexibility. Such understanding provides molecular design guidelines for future stretchable semiconductors.
Predicting flows (e.g., the traffic of vehicles, crowds, and bikes), consisting of the in-out traffic at a node and transitions between different nodes, in a spatio-temporal network plays an ...important role in transportation systems. However, this is a very challenging problem, affected by multiple complex factors, such as the spatial correlation between different locations, temporal correlation among different time intervals, and external factors (like events and weather). In addition, the flow at a node (called node flow) and transitions between nodes (edge flow) mutually influence each other. To address these issues, we propose a multitask deep-learning framework that simultaneously predicts the node flow and edge flow throughout a spatio-temporal network. Based on fully convolutional networks, our approach designs two sophisticated models for predicting node flow and edge flow, respectively. These two models are connected by coupling their latent representations of middle layers, and trained together. The external factor is also integrated into the framework through a gating fusion mechanism. In the edge flow prediction model, we employ an embedding component to deal with the sparse transitions between nodes. We evaluate our method based on the taxicab data in Beijing and New York City. Experimental results show the advantages of our method beyond 11 baselines, such as ConvLSTM, CNN, and Markov Random Field.
Purpose
To investigate the role of computed tomography (CT) radiomics for the preoperative prediction of lymph node (LN) metastasis in gastric cancer.
Materials and methods
This retrospective study ...included 247 consecutive patients (training cohort, 197 patients; test cohort, 50 patients) with surgically proven gastric cancer. Dedicated radiomics prototype software was used to segment lesions on preoperative arterial phase (AP) CT images and extract features. A radiomics model was constructed to predict the LN metastasis by using a random forest (RF) algorithm. Finally, a nomogram was built incorporating the radiomics scores and selected clinical predictors. Receiver operating characteristic (ROC) curves were used to validate the capability of the radiomics model and nomogram on both the training and test cohorts.
Results
The radiomics model showed a favorable discriminatory ability in the training cohort with an area under the curve (AUC) of 0.844 (95% CI, 0.759 to 0.909), which was confirmed in the test cohort with an AUC of 0.837 (95% CI, 0.705 to 0.926). The nomogram consisted of radiomics scores and the CT-reported LN status showed excellent discrimination in the training and test cohorts with AUCs of 0.886 (95% CI, 0.808 to 0.941) and 0.881 (95% CI, 0.759 to 0.956), respectively.
Conclusions
The CT-based radiomics nomogram holds promise for use as a noninvasive tool in the individual prediction of LN metastasis in gastric cancer.
Key Points
• CT radiomics showed a favorable performance for the prediction of LN metastasis in gastric cancer.
• Radiomics model outperformed the routine CT in predicting LN metastasis in gastric cancer.
• The radiomics nomogram holds potential in the individualized prediction of LN metastasis in gastric cancer.
Chiral amino acids are extensively applied in the pharmaceutical, food, cosmetic, agricultural, and feedstuff industries. The development of synthetic methodologies for optically pure amino acids has ...been driven by their significant applications. Among the various synthesis methods for the production of chiral amino acids, enzymatic asymmetric synthesis is a unique preparation strategy that shows great potential. This review provides an overview of the reported methods for enzymatic asymmetric synthesis of chiral amino acids, including asymmetric reductive amination of keto acids, asymmetric transfer of an amino group to keto acids, enantioselective addition of ammonia to α,β-unsaturated acids, and aldol condensation of an amino acid to aldehydes.
This review summarizes the progress achieved in the enzymatic asymmetric synthesis of chiral amino acids from prochiral substrates.
Real-Time City-Scale Taxi Ridesharing Shuo Ma; Yu Zheng; Wolfson, Ouri
IEEE transactions on knowledge and data engineering,
2015-July-1, 2015-7-1, Volume:
27, Issue:
7
Journal Article
Peer reviewed
Open access
We proposed and developed a taxi-sharing system that accepts taxi passengers' real-time ride requests sent from smart phones and schedules proper taxis to pick up them via ride sharing, subject to ...time, capacity, and monetary constraints. The monetary constraints provide incentives for both passengers and taxi drivers: passengers will not pay more compared with no ride sharing and get compensated if their travel time is lengthened due to ride sharing; taxi drivers will make money for all the detour distance due to ride sharing. While such a system is of significant social and environmental benefit, e.g., saving energy consumption and satisfying people's commute, real-time taxi-sharing has not been well studied yet. To this end, we devise a mobile-cloud architecture based taxi-sharing system. Taxi riders and taxi drivers use the taxi-sharing service provided by the system via a smart phone App. The Cloud first finds candidate taxis quickly for a taxi ride request using a taxi searching algorithm supported by a spatio-temporal index. A scheduling process is then performed in the cloud to select a taxi that satisfies the request with minimum increase in travel distance. We built an experimental platform using the GPS trajectories generated by over 33,000 taxis over a period of three months. A ride request generator is developed (available at http://cs.uic.edu/~sma/ridesharing) in terms of the stochastic process modelling real ride requests learned from the data set. Tested on this platform with extensive experiments, our proposed system demonstrated its efficiency, effectiveness and scalability. For example, when the ratio of the number of ride requests to the number of taxis is 6, our proposed system serves three times as many taxi riders as that when no ridesharing is performed while saving 11 percent in total travel distance and 7 percent taxi fare per rider.
The Keap1–Nrf2–ARE ((Kelch‐like ECH‐Associating protein 1) nuclear factor erythroid 2 related factor 2‐antioxidant response element) pathway is one of the most important defense mechanisms against ...oxidative and/or electrophilic stresses, and it is closely associated with inflammatory diseases, including cancer, neurodegenerative diseases, cardiovascular diseases, and aging. In recent years, progress has been made in strategies aimed at modulating the Keap1–Nrf2–ARE pathway. The Nrf2 activator DMF (Dimethylfumarates) has been approved by the FDA as a new first‐line oral drug to treat patients with relapsing forms of multiple sclerosis, while a phase 3 study of another promising candidate, CDDO‐Me, was terminated for safety reasons. Directly inhibiting Keap1–Nrf2 protein–protein interactions as a novel Nrf2‐modulating strategy has many advantages over using electrophilic Nrf2 activators. The development of Keap1–Nrf2 protein–protein interaction inhibitors has become a topic of intense research, and potent inhibitors of this target have been identified. In addition, inhibiting Nrf2 activity has attracted an increasing amount of attention because it may provide an alternative cancer therapy. This review summarizes the molecular mechanisms and biological functions of the Keap1–Nrf2–ARE system. The main focus of this review is on recent progress in studies of agents that target the Keap1–Nrf2–ARE pathway and the therapeutic applications of such agents.
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