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As the international energy market pays more and more attention to the development of clean energy, wind power is gradually attracting the attention of various countries. Wind power is a sustainable and environmentally friendly resource of energy. However, it is unstable. Therefore, it is important to develop algorithms for its prediction. In this paper, we apply a recently developed algorithm that effectively combines the tensor train decomposition with the higher order dynamic mode decomposition (TT‐HODMD). The dynamic mode decomposition (DMD) is a data‐driven technique that does not need a prior mathematical model. It is based on the measurement data or time slots. As demonstrated, for prediction it is important to use the higher order DMD (HODMD). In turn, HODMD might lead to very large scale arrays that are sparse. The tensor train decomposition provides a highly efficient way to work with such arrays. It is demonstrated that the combined TT‐HODMD algorithm is capable of providing quite accurate prediction of wind power for months ahead. [ABSTRACT FROM AUTHOR]

In this paper, we propose an efficient method called the response-aided score-matching representative (RASMR) approach to facilitate massive data model selection and data analysis with generalized linear models (GLMs) and a predetermined data partition due to data localization. Similar to the original score-matching representative (SMR) approach, RASMR constructs an artificial data point, called the representative, for each data block. It then fits a GLM on the representative dataset, which provides not only an efficient approach for massive data analysis but also an ideal solution in response to privacy concerns by avoiding the transfer of sensitive data. By further splitting the data blocks according to the values of the response variables, RASMR can obtain more accurate parameter estimates than SMR. Furthermore, by theoretical justifications and simulation studies, we show that RASMR can be more efficiently utilized for model selection and variable selection for a massive dataset by approximating the Akaike information criterion (AIC) and the aggregated prediction errors for cross-validation, which are commonly used for choosing the most appropriate statistical model and drawing reliable conclusions. We also apply the proposed RASMR approach to the airline on-time performance data, which consists of 371 data files labeled by month, and show that RASMR can be successfully used for selecting the most appropriate model for real massive data analysis. [ABSTRACT FROM AUTHOR]

In this paper, we address the problem of designing an experimental plan with both discrete and continuous factors under fairly general parametric statistical models. We propose a new algorithm, named ForLion, to search for locally optimal approximate designs under the D-criterion. The algorithm performs an exhaustive search in a design space with mixed factors while keeping high efficiency and reducing the number of distinct experimental settings. Its optimality is guaranteed by the general equivalence theorem. We present the relevant theoretical results for multinomial logit models (MLM) and generalized linear models (GLM), and demonstrate the superiority of our algorithm over state-of-the-art design algorithms using real-life experiments under MLM and GLM. Our simulation studies show that the ForLion algorithm could reduce the number of experimental settings by 25% or improve the relative efficiency of the designs by 17.5% on average. Our algorithm can help the experimenters reduce the time cost, the usage of experimental devices, and thus the total cost of their experiments while preserving high efficiencies of the designs. [ABSTRACT FROM AUTHOR]

Background and aims: Hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT) has an extremely poor prognosis. A previous study proved that low-dose radiotherapy (RT) could prolong the prognosis of HCC patients with PVTT. This study aims to explore the sensitivity of PVTT to RT treatment. Methods: Patients were selected based on imaging diagnosis of HCC accompanied by PVTT and received combined treatment of radiotherapy, antiangiogenic drugs and immune checkpoint inhibitors, followed by hepatectomy or liver transplantation from January 2019 to August 2022. The efficacy was evaluated by Response Evaluation Criteria in Solid Tumors (RECIST) guidelines and pathological assessment. The sensitivity of tumor cells to the treatment was compared between the primary tumor (PT)and PVTT by analyzing their residual tumor and pathologic complete remission (PCR) incidence. Results: Data from 14 patients were collected in the study. After combined treatment, the size of PVTT decreased more significantly than that of the primary tumor in the imaging study (p < 0.05). The residual cancer was significantly more restrictive than that of primary tumor in paired patients based on pathological measurement (p = 0.008). The PCR incidence of the primary tumor (21.42%) was significantly lower (p = 0.008) than that of PVTT in the pathologic study (78.57%). Conclusion: PVTT is more sensitive to radiotherapy treatment than the primary tumor in patients with HCC. This combination therapy might be an effective option as a downstaging therapy for patients with HCC with PVTT. [ABSTRACT FROM AUTHOR]

For next generation wireless communication systems, high throughput, low latency, and large user accommodation are popular and important required characteristics. To achieve these requirements for next generation wireless communication systems, an in-band full-duplex (IBFD) communication system is one of the possible candidate technologies. However, to realize IBFD systems, there is an essential problem that there exists a large self-interference (SI) due to the simultaneous signal transmission and reception in the IBFD systems. Therefore, to implement the IBFD system, it is necessary to realize a series of effective SI cancellation processes. In this study, we implemented a prototype of SI cancellation processes with our designed antenna, analog circuit, and digital cancellation function using an adaptive filter. For system implementation, we introduce software-defined radio (SDR) devices in this study. By using SDR devices, which can be customized by users, the evaluations of complicated wireless access systems like IBFD can be realized easily. Besides the validation stage of system practicality, the system development can be more effective by using SDR devices. Therefore, we utilize SDR devices to implement the proposed IBFD system and conduct experiments to evaluate its performance. The results show that the SI cancellation effect can reach nearly 100 dB with  10 − 3  order bit error rate (BER) after signal demodulation. From the experiment results, it can be seen obviously that the implemented prototype can effectively cancel the large amount of SI and obtain satisfied digital demodulation results, which validates the effectiveness of the developed system. [ABSTRACT FROM AUTHOR]

Higher-order dynamic mode decomposition (HODMD) has proved to be an efficient tool for the analysis and prediction of complex dynamical systems described by data-driven models. In the present paper, we propose a realization of HODMD that is based on the low-rank tensor decomposition of potentially high-dimensional datasets. It is used to compute the HODMD modes and eigenvalues to effectively reduce the computational complexity of the problem. The proposed extension also provides a more efficient realization of the ordinary dynamic mode decomposition with the use of the tensor-train decomposition. The high efficiency of the tensor-train-based HODMD (TT-HODMD) is illustrated by a few examples, including forecasting the load of a power system, which provides comparisons between TT-HODMD and HODMD with respect to the computing time and accuracy. The developed algorithm can be effectively used for the prediction of high-dimensional dynamical systems. [ABSTRACT FROM AUTHOR]

Although oxaliplatin-based chemotherapy has been effective in the treatment of hepatocellular carcinoma (HCC), primary or acquired resistance to oxaliplatin remains a major challenge in the clinic. Through functional screening using CRISPR/Cas9 activation library, transcriptomic profiling of clinical samples, and functional validation in vitro and in vivo, we identify PRMT3 as a key driver of oxaliplatin resistance. Mechanistically, PRMT3-mediated oxaliplatin-resistance is in part dependent on the methylation of IGF2BP1 at R452, which is critical for the function of IGF2BP1 in stabilizing the mRNA of HEG1, an effector of PRMT3-IGF2BP1 axis. Also, PRMT3 overexpression may serve as a biomarker for oxaliplatin resistance in HCC patients. Collectively, our study defines the PRTM3-IGF2BP1-HEG1 axis as important regulators and therapeutic targets in oxaliplatin-resistance and suggests the potential to use PRMT3 expression level in pretreatment biopsy as a biomarker for oxaliplatin-resistance in HCC patients. Despite being an effective treatment for hepatocellular carcinoma (HCC), resistance to oxaliplatin presents a major obstacle. Here, the authors identify PRMT3-induced methylation of IGF2BP1 resulting in HEG1 stabilisation as a mechanism of oxaliplatin resistance in HCC. [ABSTRACT FROM AUTHOR]

Transarterial chemoembolization (TACE) is the major treatment for advanced hepatocellular carcinoma (HCC), but it may cause hypoxic environment, leading to rapid progression after treatment. Here, using high‐throughput sequencing on different models, S100 calcium binding protein A9 (S100A9) is identified as a key oncogene involved in post‐TACE progression. Depletion or pharmacologic inhibition of S100A9 significantly dampens the growth and metastatic ability of HCC. Mechanistically, TACE induces S100A9 via hypoxia‐inducible factor 1α (HIF1A)‐mediated pathway. S100A9 acts as a scaffold recruiting ubiquitin specific peptidase 10 and phosphoglycerate mutase family member 5 (PGAM5) to form a tripolymer, causing the deubiquitination and stabilization of PGAM5, leading to mitochondrial fission and reactive oxygen species production, thereby promoting the growth and metastasis of HCC. Higher S100A9 level in HCC tissue or in serum predicts a worse outcome for HCC patients. Collectively, this study identifies S100A9 as a key driver for post‐TACE HCC progression. Targeting S100A9 may be a promising therapeutic strategy for HCC patients. [ABSTRACT FROM AUTHOR]

We propose a new lazy learning-based cancellation approach to improve spectral efficiency for current wireless communication systems, suppress self-interference (SI) sent from base stations, and enable in-band full-duplex (IBFD) transmissions in cellular networks. Our proposed approach consists of two phases based on traditional IBFD systems: an offline phase for database generation and an online phase for data transmission. In the offline phase, the output before a 0/1 decision is premeasured without the desired signal input and recorded in a database with self-defined feature vectors (FVs). In the online phase, a suitable result is sought from the generated database with the help of a learning method and FV for the same system architecture with the desired signal input. The result is then assigned an SI cancellation value. Regular and eager learning-based cancellation approaches are employed to evaluate the proposed method and simulate the transmission output. Computer simulation results indicated that the proposed cancellation methods could achieve about 134 dB SI suppression and achieve nearly the same transmission levels as methods with no SI effect, enabling the IBFD operations in wireless communication systems better than the regular and eager learning-based techniques. [ABSTRACT FROM AUTHOR]

Extracting information from quantum devices has long been a crucial problem in the field of quantum mechanics. By performing elaborate measurements, quantum state tomography, an important and fundamental tool in quantum science and technology, can be used to determine unknown quantum states completely. In this study, methods to determine multi‐qubit pure quantum states uniquely and directly are explored. Two adaptive protocols are proposed, with their respective quantum circuits. Herein, two or three observables are sufficient, while the number of measurement outcomes are either the same as or fewer than those in existing methods. Additionally, experiments on the IBM 5‐qubit quantum computer, as well as numerical investigations, demonstrate the feasibility of the proposed protocols. [ABSTRACT FROM AUTHOR]

As a universal quantum computer requires millions of error-corrected qubits, one of the current goals is to exploit the power of noisy intermediate-scale quantum (NISQ) devices. Based on a NISQ module–layered circuit, we propose a heuristic protocol to simulate Hermitian matrix evolution, which is widely applied as the core for many quantum algorithms. The two embedded methods, with their own advantages, only require shallow circuits and basic quantum gates. Capable to being deployed in near future quantum devices, we hope it provides an experiment-friendly way, contributing to the exploitation of power of current devices. [ABSTRACT FROM AUTHOR]

Quantum optimization algorithms can outperform their classical counterpart and are key in modern technology. The second-order optimization algorithm (the Newton algorithm) is a critical optimization method, speeding up the convergence by employing the second-order derivative of loss functions in addition to their first derivative. Here, we propose a new quantum second-order optimization algorithm for general polynomials with a computational complexity of O(poly(log d)). We use this algorithm to solve the nonlinear equation and learning parameter problems in factorization machines. Numerical simulations show that our new algorithm is faster than its classical counterpart and the first-order quantum gradient descent algorithm. While existing quantum Newton optimization algorithms apply only to homogeneous polynomials, our new algorithm can be used in the case of general polynomials, which are more widely present in real applications. [ABSTRACT FROM AUTHOR]

The gradient descent method is central to numerical optimization and is the key ingredient in many machine learning algorithms. It promises to find a local minimum of a function by iteratively moving along the direction of the steepest descent. Since for high-dimensional problems the required computational resources can be prohibitive, it is desirable to investigate quantum versions of the gradient descent, such as the recently proposed (Rebentrost et al.1). Here, we develop this protocol and implement it on a quantum processor with limited resources. A prototypical experiment is shown with a four-qubit nuclear magnetic resonance quantum processor, which demonstrates the iterative optimization process. Experimentally, the final point converged to the local minimum with a fidelity >94%, quantified via full-state tomography. Moreover, our method can be employed to a multidimensional scaling problem, showing the potential to outperform its classical counterparts. Considering the ongoing efforts in quantum information and data science, our work may provide a faster approach to solving high-dimensional optimization problems and a subroutine for future practical quantum computers. [ABSTRACT FROM AUTHOR]

Understanding the transport of carbon nanotubes in porous media is essential to their applications in subsurface reservoirs, e.g., delivering catalysts or chemicals to targeted formations. In this study, a series of laboratory experiments are conducted to explore the transport of surfactant‐dispersed multiwalled nanotubes (MWNT) in different porous media in flow‐through columns at elevated electrolyte levels. Noncovalent bonding of ethoxylated alcohols adsorbed on the MWNT surface provides them with outstanding dispersion stability and excellent transport properties in a crushed‐limestone sand pack. Superior transport performance in silica sand is obtained with binary nonionic–anionic surfactant formulations, which provide both steric repulsion and electrostatic repulsion between nanoparticle–nanoparticle and nanoparticle–sand surface. The mobility of MWNT suspensions are further investigated in the exposure to multiphase flow, e.g., with residual oil present, or coinjected with air into the sand pack. Coinjecting surfactant‐dispersed MWNT suspensions with air (i.e., MWNT‐stabilized foams) has hardly any impact on their propagation; retention in the sand pack remains quite low. With the presence of oil in the sand pack, the transport of MWNT suspensions is highly dependent on the type of surfactants used as the dispersant. For surfactants that achieved modest interfacial tension (IFT) reduction, the injected MWNT suspension bypasses the oil phase, and little impact on retention is observed. When the dispersant surfactant is also adjusted for an ultralow IFT condition, greater MWNT retention in the porous medium is observed because surfactants detach from the MWNT surface and aggressively partition to the oil/water interface, allowing the MWNT to flocculate and become deposited in the porous medium. [ABSTRACT FROM AUTHOR]

Tools designed to predict patient satisfaction following total knee arthroplasty (TKA) have the potential to guide patient selection. Our study aimed to validate a model that predicts patient satisfaction following TKA. Phone surveys were administered to 203 patients who underwent TKA between 2009 and 2016 at the University of Illinois. We utilized health records to document age, gender, body mass index (BMI), and comorbidities. First, we compared the descriptive variables between the satisfied and dissatisfied groups. We then performed multivariate linear regression and multiple logistic regression to assess the predictive value of the questions in the Van Onsem et al. model. The true satisfaction rate in our study was 65%. The Van Onsem et al. model predicted a satisfaction rate of 70%. The scatter plot of predicted satisfaction score versus observed satisfaction score showed poor agreement between actual satisfaction and predicted satisfaction. Comparing satisfied and dissatisfied groups, there was a significant difference with respect to pain prior to surgery and BMI. The validity of the Van Onsem et al. prediction tool was not supported. While the predicted satisfaction rate was near the measured satisfaction rate, the model misidentified which patients were likely to be satisfied. Preoperative variables including pain, anxiety/depression, and a patient's ability to control pain symptoms showed potential for inclusion in future prediction models. Level of evidence: Level III, developing a decision model. [ABSTRACT FROM AUTHOR]

We propose a millimeter-wave antenna to serve as an element antenna for a multi-sector switched-beam antenna, which can be fed by a post-wall waveguide. Several tapered slot antennas are connected to an aperture of an H-plane sectoral post-wall horn antenna whose radiation pattern is narrowed in the H-plane to further narrow the pattern in the E-plane. Moreover, the aperture of each tapered slot antenna is loaded with a dielectric to increase the gain. We designed an antenna whose gain is over 16 dBi in the frequency band of 57–66 GHz. The wideband property is experimentally examined. [ABSTRACT FROM PUBLISHER]

We present results of the dynamics of a single polymer, anchored at both ends and subjected to a periodic oscillatory force at a middle segment. Via Brownian dynamics simulations, the influences of the periodicity of the forcing on the shape of the orbit in the position-force plane have been investigated for flexible and semiflexible polymer. The shape of the orbit exhibits in the form of hysteresis cycle or a single curve. [ABSTRACT FROM AUTHOR]

This article presents a novel tunable sharp notch filter using open stub structure with varactor for implementing detect-and-avoid method into ultrawideband radio system. On the basis of the experimental results on the open stub structure with lumped capacitor, we introduced two techniques in this work to realize a tunable sharp notch filter using open stub structure with varactor to perform narrow stopband and using resistors to build a DC bias circuit, so that no influence to the tunable notch filter over a wide band. The developed tunable notch filter has excellent performance: wide tuning range from 3.65 to 4.35 GHz with low tuning voltage from 0 to 6 V, narrow bandwidth less than 270 MHz of the notch filter (at 10 dB insertion loss at 0 V), and compact size of the developed filter: about 2.0 cm × 4.0 cm. © 2008 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 2712–2715, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23773 [ABSTRACT FROM AUTHOR]

This paper presents a systematic technique to improve the convergence of the Green's function for multilayered medium structure by introducing a three-layered model into the multilayered system. The technique uses a combination of Fourier series expansion and method of images. Numerical analysis demonstrates dramatic improvements of the convergence of Green's function and its boundary integrals. © 1998 John Wiley & Sons, Inc. Int J RF and Microwave CAE 8: 474–483, 1998 [ABSTRACT FROM AUTHOR]

As monolithic integration of the microwave circuits progresses, the microstrip line used as a fundamental transmission medium becomes extremely small in size. As the transmission line is miniaturized, it becomes necessary to consider the effect of the shape of the edges of the strip conductor in addition to the thickness. in this paper, an integral equation is derived for the charge density distribution on the strip conductor surface as the unknown. The transmission line characteristics are obtained by discretizing the integration range. Further, the effect of the trapezoidal cross section of the strip conductor formed by etching and plating on the characteristic parameters is specifically studied. [ABSTRACT FROM AUTHOR]

Discusses the general analytical solutions of the static Green's functions for shielded and open arbitrarily multilayered media. Analytical Green's functions for an arbitrarily multilayered media with shielded conductor walls; Derivation of the analytical Green's functions for the shielded multilayered media; Analytical Green's functions for an open multilayered media; Green's functions for a three-layered dielectric structure; Conclusion.

Quantum simulation has shown its irreplaceable role in many fields, where it is difficult for classical computers to do much. On a four-qubit Nuclear Magnetic Resonance (NMR) quantum simulator, we experimentally simulate the spin-network states by simulating quantum spacetime tetrahedra. The fidelities of our experimentally prepared quantum tetrahedra are all above 95%. We then use the quantum tetradedra prepared by the Nuclear Magnetic Resonance to simulate a spinfoam vertex amplitude, which displays the local dynamics of quantum spacetime. By measuring the geometric properties on the corresponding quantum tetrahedra and simulating their interaction, our experiment serves as a basic module that represents the Feynman diagram vertex in the spinfoam formulation of Loop Quantum Gravity(LQG). This is an initial attempt to study LQG by quantum information processing. Quantum simulation is a crucial tool in areas where classical computers are inefficient. In this work, the authors use a Nuclear Magnetic Resonance quantum simulator to simulate the local dynamics of quantum spacetime as an attempt to exploit quantum information to study loop quantum gravity. [ABSTRACT FROM AUTHOR]

Quantum simulation promises to have wide applications in many fields where problems are hard to model with classical computers. Various quantum devices of different platforms have been built to tackle the problems in, say, quantum chemistry, condensed matter physics, and high-energy physics. Here, we report an experiment towards the simulation of quantum gravity by simulating the holographic entanglement entropy. On a six-qubit nuclear magnetic resonance quantum simulator, we demonstrate a key result of Anti-de Sitter/conformal field theory (AdS/CFT) correspondence—the Ryu-Takayanagi formula is demonstrated by measuring the relevant entanglement entropies on the perfect tensor state. The fidelity of our experimentally prepared the six-qubit state is 85.0% via full state tomography and reaches 93.7% if the signal-decay due to decoherence is taken into account. Our experiment serves as the basic module of simulating more complex tensor network states that exploring AdS/CFT correspondence. As the initial experimental attempt to study AdS/CFT via quantum information processing, our work opens up new avenues exploring quantum gravity phenomena on quantum simulators. [ABSTRACT FROM AUTHOR]

Quantum clock synchronization (QCS) is a kind of method to measure the time difference among spatially separated clocks with the principle of quantum mechanics. The first QCS algorithm proposed by Chuang and Jozsa is merely based on two parties, which is further extended and generalized to multiparty situation by Krco and Paul. They present a multiparty QCS protocol based upon W-state, utilizing shared prior entanglement and broadcasting the classical information to synchronize spatially separated clocks. Shortly afterward, Ben-Av and Exman came up with an optimized multiparty QCS based on Z-state. In this work, we firstly report the demonstrations of these two multiparty QCS protocols in a four-qubit liquid-state nuclear magnetic resonance system. The experimental results show a great agreement with the theoretical predictions and also prove that Ben-AV’s multiparty QCS algorithm is more accurate than Krco’s. [ABSTRACT FROM AUTHOR]

Accurate and efficient control of quantum systems is one of the central challenges for quantum information processing. Current state-of-the-art experiments rarely go beyond 10 qubits and in most cases demonstrate only limited control. Here we demonstrate control of a 12-qubit system, and show that the system can be employed as a quantum processor to optimize its own control sequence by using measurement-based feedback control (MQFC). The final product is a control sequence for a complex 12-qubit task: preparation of a 12-coherent state. The control sequence is about 10% more accurate than the one generated by the standard (classical) technique, showing that MQFC can correct for unknown imperfections. Apart from demonstrating a high level of control over a relatively large system, our results show that even at the 12-qubit level, a quantum processor can be a useful lab instrument. As an extension of our work, we propose a method for combining the MQFC technique with a twirling protocol, to optimize the control sequence that produces a desired Clifford gate. Headline: Bootstrapping a 12-qubit quantum processor Realizing high accuracy control of quantum systems represents a crucial ingredient in building large-scaled quantum computers. An international team of researchers led by Raymond Laflamme at Canada's Institute for Quantum Computing has succeeded in manipulating a 12-qubit nuclear magnetic resonance quantum processor with unprecedented precision. The researchers build a closed-loop pulse auto-tunning setup which employs the controlled system itself to optimize its own pulses. This gives to the benefits of more efficient pulse optimization and more robustness to system uncertainties. Because that the experiment achieves high level of individual controls over all of the qubits, it is at the cutting edge of experimental quantum computing. The experimental techniques are ready to be transferred to other quantum technologies, such as nitrogen-vacancy centers, trapped ions or superconducting circuits. [ABSTRACT FROM AUTHOR]