Abstract
As evolutionary algorithms (EAs) are general-purpose optimization algorithms, recent theoretical studies have tried to analyze their performance for solving general problem classes, with the ...goal of providing a general theoretical explanation of the behavior of EAs. Particularly, a simple multiobjective EA, that is, GSEMO, has been shown to be able to achieve good polynomial-time approximation guarantees for submodular optimization, where the objective function is only required to satisfy some properties and its explicit formulation is not needed. Submodular optimization has wide applications in diverse areas, and previous studies have considered the cases where the objective functions are monotone submodular, monotone non-submodular, or non-monotone submodular. To complement this line of research, this article studies the problem class of maximizing monotone approximately submodular minus modular functions (i.e., g-c) with a size constraint, where g is a so-called non-negative monotone approximately submodular function and c is a so-called non-negative modular function, resulting in the objective function (g-c) being non-monotone non-submodular in general. Different from previous analyses, we prove that by optimizing the original objective function (g-c) and the size simultaneously, the GSEMO fails to achieve a good polynomial-time approximation guarantee. However, we also prove that by optimizing a distorted objective function and the size simultaneously, the GSEMO can still achieve the best-known polynomial-time approximation guarantee. Empirical studies on the applications of Bayesian experimental design and directed vertex cover show the excellent performance of the GSEMO.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Metastasis is the major cause of treatment failure in cancer patients and of cancer-related deaths. This editorial discusses how cancer metastasis may be better perceived and controlled. Based on ...big-data analyses, a collection of 150 important pro-metastatic genes was studied. Using The Cancer Genome Atlas datasets to re-analyze the effect of some previously reported metastatic genes-e.g., JAM2, PPARGC1A, SIK2, and TRAF6-on overall survival of patients with renal and liver cancers, we found that these genes are actually protective factors for patients with cancer. The role of epithelial-mesenchymal transition (EMT) in single-cell metastasis has been well-documented. However, in metastasis caused by cancer cell clusters, EMT may not be necessary. A novel role of epithelial marker E-cadherin, as a sensitizer for chemoresistant prostate cancer cells by inhibiting Notch signaling, has been found. This editorial also discusses the obstacles for developing anti-metastatic drugs, including the lack of high-throughput technologies for identifying metastasis inhibitors, less application of animal models in the pre-clinical evaluation of the leading compounds,and the need for adjustments in clinical trial design to better reflect the anti-metastatic efficacy of new drugs.We are confident that by developing more effective high-throughput technologies to identify metastasis inhibitors,we can better predict, prevent, and treat cancer metastasis.
Becoming invisible at will has fascinated humanity for centuries and in the past decade it has attracted a great deal of attention owing to the advent of metamaterials. However, state-of-the-art ...invisibility cloaks typically work in a deterministic system or in conjunction with outside help to achieve active cloaking. Here, we propose the concept of an intelligent (that is, self-adaptive) cloak driven by deep learning and present a metasurface cloak as an example implementation. In the experiment, the metasurface cloak exhibits a millisecond response time to an ever-changing incident wave and the surrounding environment, without any human intervention. Our work brings the available cloaking strategies closer to a wide range of real-time, in situ applications, such as moving stealth vehicles. The approach opens the way to facilitating other intelligent metadevices in the microwave regime and across the wider electromagnetic spectrum and, more generally, enables automatic solutions of electromagnetic inverse design problems.A deep-learning-enabled metasurface cloak actively self-adapts to take into account changing microwave illumination and varying physical surroundings.
Topology optimization (TO) is a common technique used in free-form designs. However, conventional TO-based design approaches suffer from high computational cost due to the need for repetitive forward ...calculations and/or sensitivity analysis, which are typically done using high-dimensional simulations such as finite element analysis (FEA). In this work, artificial neural networks are used as efficient surrogate models for forward and sensitivity calculations in order to greatly accelerate the design process of topology optimization. To improve the accuracy of sensitivity analyses, dual-model artificial neural networks that are trained with both forward and sensitivity data are constructed and are integrated into the Solid Isotropic Material with Penalization (SIMP) method to replace the FEA. The performance of the accelerated SIMP method is demonstrated on two benchmark design problems namely minimum compliance design and metamaterial design. The efficiency gained in the problem with size of 64 × 64 is 137 times in forward calculation and 74 times in sensitivity analysis. In addition, effective data generation methods suitable for TO designs are investigated and developed, which lead to a great saving in training time. In both benchmark design problems, a design accuracy of 95% can be achieved with only around 2000 training data.
Optical logic operations lie at the heart of optical computing, and they enable many applications such as ultrahigh-speed information processing. However, the reported optical logic gates rely ...heavily on the precise control of input light signals, including their phase difference, polarization, and intensity and the size of the incident beams. Due to the complexity and difficulty in these precise controls, the two output optical logic states may suffer from an inherent instability and a low contrast ratio of intensity. Moreover, the miniaturization of optical logic gates becomes difficult if the extra bulky apparatus for these controls is considered. As such, it is desirable to get rid of these complicated controls and to achieve full logic functionality in a compact photonic system. Such a goal remains challenging. Here, we introduce a simple yet universal design strategy, capable of using plane waves as the incident signal, to perform optical logic operations via a diffractive neural network. Physically, the incident plane wave is first spatially encoded by a specific logic operation at the input layer and further decoded through the hidden layers, namely, a compound Huygens' metasurface. That is, the judiciously designed metasurface scatters the encoded light into one of two small designated areas at the output layer, which provides the information of output logic states. Importantly, after training of the diffractive neural network,
basic types of optical logic operations can be realized by the same metasurface. As a conceptual illustration, three logic operations (NOT, OR, and AND) are experimentally demonstrated at microwave frequencies.
Matrix computation, as a fundamental building block of information processing in science and technology, contributes most of the computational overheads in modern signal processing and artificial ...intelligence algorithms. Photonic accelerators are designed to accelerate specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for computing resources and capacity. Photonic matrix multiplication has much potential to expand the domain of telecommunication, and artificial intelligence benefiting from its superior performance. Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors. In this review, we first introduce the methods of photonic matrix multiplication, mainly including the plane light conversion method, Mach-Zehnder interferometer method and wavelength division multiplexing method. We also summarize the developmental milestones of photonic matrix multiplication and the related applications. Then, we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years. Finally, we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration.
Breakthroughs in the field of object recognition facilitate ubiquitous applications in the modern world, ranging from security and surveillance equipment to accessibility devices for the visually ...impaired. Recently-emerged optical computing provides a fundamentally new computing modality to accelerate its solution with photons; however, it still necessitates digital processing for in situ application, inextricably tied to Moore's law. Here, from an entirely optical perspective, we introduce the concept of neuro-metamaterials that can be applied to realize a dynamic object- recognition system. The neuro-metamaterials are fabricated from inhomogeneous metamaterials or transmission metasurfaces, and optimized using, such as topology optimization and deep learning. We demonstrate the concept in experiments where living rabbits play freely in front of the neuro-metamaterials, which enable to perceive in light speed the rabbits' representative postures. Furthermore, we show how this capability enables a new physical mechanism for creating dynamic optical mirages, through which a sequence of rabbit movements is converted into a holographic video of a different animal. Our work provides deep insight into how metamaterials could facilitate a myriad of in situ applications, such as illusive cloaking and speed-of-light information display, processing, and encryption, possibly ushering in an "Optical Internet of Things" era.
Optical analog computing has recently sparked growing interest due to the appealing characteristics of low energy consumption parallel processing and ultrafast speed, spawning it complementary to ...conventional electronic computing. As the basic computing unit, optical logic operation plays a pivotal role for integrated photonics. However, the reported optical logic operations are volumetric and single-functional, which considerably hinders the practical cascadability and complex computing requirement. Here, we propose an on-chip combinational optical logic circuit using inverse design. By precisely engineering the scattering matrix of each small-footprint logic gate, all basic optical logic gates (OR, XOR, NOT, AND, XNOR, NAND, and NOR) are realized. On this foundation, we explore the assembly of these basic logic gates for general purpose combinational logic circuits, including optical half-adder and code converter. Our work provides a path for the development of integrated, miniaturized, and cascadable photonic processor for future optical computing technologies.
Objective Bariatric surgery is recommended for patients with obesity and type 2 diabetes. Recent evidence suggested a strong connection between gut microbiota and bariatric surgery. Design Systematic ...review. Methods The PubMed and OVID EMBASE were used, and articles concerning bariatric surgery and gut microbiota were screened. The main outcome measures were alterations of gut microbiota after bariatric surgery and correlations between gut microbiota and host metabolism. We applied the system of evidence level to evaluate the alteration of microbiota. Modulation of short-chain fatty acid and gut genetic content was also investigated. Results Totally 12 animal experiments and 9 clinical studies were included. Based on strong evidence, 4 phyla (Bacteroidetes, Fusobacteria, Verrucomicrobia and Proteobacteria) increased after surgery; within the phylum Firmicutes, Lactobacillales and Enterococcus increased; and within the phylum Proteobacteria, Gammaproteobacteria, Enterobacteriales Enterobacteriaceae and several genera and species increased. Decreased microbial groups were Firmicutes, Clostridiales, Clostridiaceae, Blautia and Dorea. However, the change in microbial diversity is still under debate. Faecalibacterium prausnitzii, Lactobacillus and Coprococcus comes are implicated in many of the outcomes, including body composition and glucose homeostasis. Conclusions There is strong evidence to support a considerable alteration of the gut microbiome after bariatric surgery. Deeper investigations are required to confirm the mechanisms that link the gut microbiome and metabolic alterations in human metabolism.
Metformin, an inexpensive and well-tolerated oral agent commonly used in the first-line treatment of type 2 diabetes,has become the focus of intense research as a candidate anticancer agent. Here, we ...discuss the potential of metformin in cancer therapeutics, particularly its functions in multiple signaling pathways, including AMP-activated protein kinase, mammalian target of rapamycin, insulin-like growth factor, c-Jun N-terminal kinase/mitogen-activated protein kinase (p38 MAPK), human epidermal growth factor receptor-2, and nuclear factor kappaB pathways. In addition, cutting-edge targeting of cancer stem cells by metformin is summarized.
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