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Glioblastoma represents the predominant and a highly aggressive primary neoplasm of the central nervous system that has an abnormal metabolism. Our previous study showed that chrysomycin A (Chr-A) curbed glioblastoma progression in vitro and in vivo. However, whether Chr-A could inhibit orthotopic glioblastoma and how it reshapes metabolism are still unclear. In this study, Chr-A markedly suppressed the development of intracranial U87 gliomas. The results from airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) indicated that Chr-A improved the abnormal metabolism of mice with glioblastoma. Key enzymes including glutaminase (GLS), glutamate dehydrogenases 1 (GDH1), hexokinase 2 (HK2) and glucose-6-phosphate dehydrogenase (G6PD) were regulated by Chr-A. Chr-A further altered the level of nicotinamide adenine dinucleotide phosphate (NADPH), thus causing oxidative stress with the downregulation of Nrf-2 to inhibit glioblastoma. Our study offers a novel perspective for comprehending the anti-glioma mechanism of Chr-A, highlighting its potential as a promising chemotherapeutic agent for glioblastoma. [ABSTRACT FROM AUTHOR]

As a new programming paradigm, deep neural networks (DNNs) have been increasingly deployed in practice, but the lack of robustness hinders their applications in safety-critical domains. While there are techniques for verifying DNNs with formal guarantees, they are limited in scalability and accuracy. In this article, we present a novel counterexample-guided abstraction refinement (CEGAR) approach for scalable and exact verification of DNNs. Specifically, we propose a novel abstraction to break down the size of DNNs by over-approximation. The result of verifying the abstract DNN is conclusive if no spurious counterexample is reported. To eliminate each spurious counterexample introduced by abstraction, we propose a novel counterexample-guided refinement that refines the abstract DNN to exclude the spurious counterexample while still over-approximating the original one, leading to a sound, complete yet efficient CEGAR approach. Our approach is orthogonal to and can be integrated with many existing verification techniques. For demonstration, we implement our approach using two promising tools, Marabou and Planet, as the underlying verification engines, and evaluate on widely used benchmarks for three datasets ACAS, Xu, MNIST, and CIFAR-10. The results show that our approach can boost their performance by solving more problems in the same time limit, reducing on average 13.4%–86.3% verification time of Marabou on almost all the verification tasks, and reducing on average 8.3%–78.0% verification time of Planet on all the verification tasks. Compared to the most relevant CEGAR-based approach, our approach is 11.6–26.6 times faster. [ABSTRACT FROM AUTHOR]

Predicting protein function is crucial for understanding biological life processes, preventing diseases and developing new drug targets. In recent years, methods based on sequence, structure and biological networks for protein function annotation have been extensively researched. Although obtaining a protein in three-dimensional structure through experimental or computational methods enhances the accuracy of function prediction, the sheer volume of proteins sequenced by high-throughput technologies presents a significant challenge. To address this issue, we introduce a deep neural network model DeepSS2GO (Secondary Structure to Gene Ontology). It is a predictor incorporating secondary structure features along with primary sequence and homology information. The algorithm expertly combines the speed of sequence-based information with the accuracy of structure-based features while streamlining the redundant data in primary sequences and bypassing the time-consuming challenges of tertiary structure analysis. The results show that the prediction performance surpasses state-of-the-art algorithms. It has the ability to predict key functions by effectively utilizing secondary structure information, rather than broadly predicting general Gene Ontology terms. Additionally, DeepSS2GO predicts five times faster than advanced algorithms, making it highly applicable to massive sequencing data. The source code and trained models are available at https://github.com/orca233/DeepSS2GO. [ABSTRACT FROM AUTHOR]

Whistler mode waves are a common type of electromagnetic waves in the Martian induced magnetosphere. Using high-resolution magnetic field data from the Magnetometer (MAG) instrument onboard Mars Atmosphere and Volatile Evolution (MAVEN) from October 2014 to November 2022, we perform a detailed analysis of the statistical distribution of the occurrence rate, averaged amplitude, peak frequency, wave normal angle and ellipticity of left-hand and right-hand polarized whistler mode waves in the Martian induced magnetosphere. Our results show that whistler mode waves are mainly observed in the subsolar and magnetic pileup region, with the occurrence rate of right-hand mode waves higher than that of left-hand mode waves. The averaged wave amplitude ranges from 0.02 to 0.13 nT and peak wave frequency ranges from 2 to 9 Hz. We also find that the wave normal angles for both left-hand and right-hand polarized whistler waves are relatively larger in the subsolar region and magnetic pileup region where the corresponding wave ellipticity is closer to the linear polarization. Our results are valuable to in-depth understanding of the generation mechanism of whistler mode waves as well as their contributions to the electron dynamics in the Martian induced magnetosphere. [ABSTRACT FROM AUTHOR]

Mg‐catalyzed [4+2] cycloaddition reactions between 2‐aminobenzaldehydes and ynones offered an array of 2‐arylquinoline motifs merged with a CF3‐acyl group. Furthermore, with Mg‐catalyzed [4+2] annulation as the key step, DDD107498, DDD102542, and Hit analogues were assembled. Finally, a computational study of the reaction mechanism was conducted. [ABSTRACT FROM AUTHOR]

Power side-channel attacks allow an adversary to efficiently and effectively steal secret information (e.g., keys) by exploiting the correlation between secret data and runtime power consumption, hence posing a serious threat to software security, particularly cryptographic implementations. Masking is a commonly used countermeasure against such attacks, which breaks the statistical dependence between secret data and side-channel leaks via randomization. In a nutshell, a variable is represented by a vector of shares armed with random variables, called masking encoding, on which cryptographic computations are performed. While compositional verification for the security of masked cryptographic implementations has received much attention because of its high efficiency, existing compositional approaches either use implicitly fixed pre-conditions that may not be fulfilled by state-of-the-art efficient implementations, or require user-provided hard-coded pre-conditions that are time consuming and highly non-trivial, even for an expert. In this article, we tackle the compositional verification problem of first-order masking countermeasures, where first-order means that the adversary is allowed to access only one intermediate computation result. Following the literature, we consider countermeasures given as gadgets, which are special procedures whose inputs are masking encodings of variables. We introduce a new security notion parameterized by an explicit pre-condition for each gadget, as well as composition rules for reasoning about masking countermeasures against power side-channel attacks. We propose accompanying efficient algorithms to automatically infer proper pre-conditions, based on which our new compositional approach can efficiently and automatically prove security for masked implementations. We implement our approaches as a tool MaskCV and conduct experiments on publicly available masked cryptographic implementations including 10 different full AES implementations. The experimental results confirm the effectiveness and efficiency of our approach. [ABSTRACT FROM AUTHOR]

As a new programming paradigm, deep learning (DL) has achieved impressive performance in areas such as image processing and speech recognition, and has expanded its application to solve many real-world problems. However, neural networks and DL are normally black-box systems; even worse, DL-based software are vulnerable to threats from abnormal examples, such as adversarial and backdoored examples constructed by attackers with malicious intentions as well as unintentionally mislabeled samples. Therefore, it is important and urgent to detect such abnormal examples. Although various detection approaches have been proposed respectively addressing some specific types of abnormal examples, they suffer from some limitations; until today, this problem is still of considerable interest. In this work, we first propose a novel characterization to distinguish abnormal examples from normal ones based on the observation that abnormal examples have significantly different (adversarial) robustness from normal ones. We systemically analyze those three different types of abnormal samples in terms of robustness and find that they have different characteristics from normal ones. As robustness measurement is computationally expensive and hence can be challenging to scale to large networks, we then propose to effectively and efficiently measure robustness of an input sample using the cost of adversarially attacking the input, which was originally proposed to test robustness of neural networks against adversarial examples. Next, we propose a novel detection method, named attack as detection (A2D for short), which uses the cost of adversarially attacking an input instead of robustness to check if it is abnormal. Our detection method is generic, and various adversarial attack methods could be leveraged. Extensive experiments show that A2D is more effective than recent promising approaches that were proposed to detect only one specific type of abnormal examples. We also thoroughly discuss possible adaptive attack methods to our adversarial example detection method and show that A2D is still effective in defending carefully designed adaptive adversarial attack methods—for example, the attack success rate drops to 0% on CIFAR10. [ABSTRACT FROM AUTHOR]

With the spread and persistence of COVID-19, pharyngeal swab sampling, is an important link in nucleic acid testing, which is characterized by a high workload and susceptibility to infection. Therefore, it is necessary for medical workers to use medical robots instead of manual site sampling for collaborative sampling. However, the traditional teleoperation has difficulty ensuring the closed-loop performance due to the delay of the actual process, along with the weak control performance; Moreover, a robot cannot accurately plan and track sampling paths due to sensor accuracy and the changes in patient pharyngeal posture. The paper proposes a human-robot shared control strategy based on intention estimation, introducing the human intention as a reference, and the operator and robot work together to solve various significant problems during sampling. The human-robot negotiation based on the method includes the human judgement and perception and the robot into the invasion task. Through, the shared control based on the operator intention estimation, the robot can operate the obstacle avoidance and approach the target contact point remotely. Finally, two kinds of experiments of invasion process of throat swab sampling are implemented: a static target invasive experiment and a dynamic target invasive experiment, aiming at two different sampling conditions. Compared with the robotic independent control sampling, the time consumption in the two experiments is reduced by 34.8% and 41.6%, respectively, and the ultimate target position is basically within the scope of sampling field (where the range of the posterior pharynx wall < 20 mm). Thus, the sampling rate can reach 100%. Compared with independent control sampling by humans, the time consumption of the two experiments is respectively reduced by 15.9% and 42.3% on average, and the target position accuracy and sampling rate are quite close. Experimental results show that the control strategy improves the speed, flexibility, and intelligence of task execution compared to common sampling methods, laying the foundation for low-cost human-robot collaborative sampling. [ABSTRACT FROM AUTHOR]

The development of facile luminescent sensors for detecting nitrophenols in aqueous media is of great necessity for the safety of the environment and human health, as they are a class of widespread toxic organic pollutants that cause serious adverse effects upon consumption. Based on a new multidentate asymmetric ligand (H2L) in which salicylamide and 4-nitryl-salicylaldimine are spaced by 1,2-bis(2-ethoxy)ethyl, a new hydrostable lanthanide intercycle, [Tb2L2(NO3)2]·CH3CN (Tb-[2]c), was prepared to act as a new luminescent sensor for 4-NP in water media. Structural analysis indicated that two fully deprotonated L2− ligands in cis-configuration and μ2-L-κ2O1:κO2:κO4:κN2:κO5 coordination mode were interlocked by two TbIII ions to render the emitted TbIII encapsulated by L2− for lessening non-radiative transitions. The excellent sensitizing capability of the ligand L2− to TbIII was ascertained by both experimental methods and theoretical calculations. The sensing exploration indicated that Tb-[2]c exhibited highly sensitive and selective recognition of 4-NP against other nitroaromatics in aqueous media. The recognition mechanism could be attributed to the internal filtration effect (IFE) mechanism when DFT calculations and accumulating experimental evidence were combined. [ABSTRACT FROM AUTHOR]

CO2 mineralization via aqueous Mg/Ca/Na-carbonate (MgCO3/CaCO3/Na2CO3) formation represents a huge opportunity for the utilization of captured CO2. However, large-scale mineralization is hindered by slow kinetics due to the highly hydrated character of the cations in aqueous solutions (Mg2+ in particular). Reaction conditions can be optimized to accelerate carbonation kinetics, for example, by the inclusion of additives that promote competitive dehydration of Mg2+ and subsequent agglomeration, nucleation, and crystallization. For tracking mineralization and these reaction steps, neutron scattering presents unprecedented advantages over traditional techniques for time-resolved in situ measurements. However, a setup providing continuous solution circulation to ensure reactant system homogeneity for industrially relevant CO2-mineralization is currently not available for use on neutron beamlines. We, therefore, undertook the design, construction, testing and implementation of such a self-contained reactor rig for use on selected neutron beamlines at the ISIS Neutron and Muon Source (Harwell, UK). The design ensured robust attachment via suspension from the covering Tomkinson flange to stabilize the reactor assembly and all fittings (~25 kg), as well as facilitating precise alignment of the entire reactor and sample (test) cell with respect to beam dimension and direction. The assembly successfully accomplished the principal tasks of providing a continuous flow of the reaction mixture (~500 mL) for homogeneity, quantitative control of CO2 flux into the mixture, and temperature and pressure regulation throughout the reaction and measurements. The design is discussed, with emphasis placed on the reactor, including its geometry, components, and all technical specifications. Descriptions of the off-beamline bench tests, safety, and functionality, as well as the installation on beamlines and trial experimental procedure, are provided, together with representative raw neutron scattering results. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is a major type of primary brain tumor without ideal prognosis and it is therefore necessary to develop a novel compound possessing therapeutic effects. Chrysomycin A (Chr-A) has been reported to inhibit the proliferation, migration and invasion of U251 and U87-MG cells through the Akt/GSK-3β signaling pathway, but the mechanism of Chr-A against glioblastoma in vivo and whether Chr-A modulates the apoptosis of neuroglioma cells is unclear. The present study aims to elucidate the potential of Chr-A against glioblastoma in vivo and how Chr-A modulates the apoptosis of neuroglioma cells. Briefly, the anti-glioblastoma activity was assessed in human glioma U87 xenografted hairless mice. Chr-A-related targets were identified via RNA-sequencing. Apoptotic ratio and caspase 3/7 activity of U251 and U87-MG cells were assayed via flow cytometry. Apoptosis-related proteins and possible molecular mechanisms were validated via Western blotting. The results showed that Chr-A treatment significantly inhibits glioblastoma progression in xenografted hairless mice, and enrichment analysis suggested that apoptosis, PI3K-Akt and Wnt signaling pathways were involved in the possible mechanisms. Chr-A increased the apoptotic ratio and the activity of caspase 3/7 in U251 and U87-MG cells. Western blotting revealed that Chr-A disturbed the balance between Bax and Bcl-2, activating a caspase cascade reaction and downregulating the expression of p-Akt and p-GSK-3β, suggesting that Chr-A may contribute to glioblastoma regression modulating in the Akt/GSK-3β signaling pathway to promote apoptosis of neuroglioma cells in vivo and in vitro. Therefore, Chr-A may hold therapeutic promise for glioblastoma. [ABSTRACT FROM AUTHOR]

Purpose: In this investigation, a linear encoder system based on the ultrasonic transducer has been proposed. Ultrasonic transducers are usually designed for distance measurements, such as the time of flight method and sonar system. These applications are defined as discrete-length measurement technologies. The purpose of this study is to develop a continuous displacement measurement system using ultrasonic transducers. Design/methodology/approach: A modified signal processing based on heterodyne signaling is implemented in this system. In the proposed signal processing, there is an automatic gain control module, a phase-shifting module, a phase detection module, an interpolation module and especially a frequency multiplication module, which can enhance the resolution and reduce the interpolation error simultaneously. Findings: The proposed system can generate the encoding signals and is compatible with most motion control systems. For the experimental result, the maximum measurement error and standard deviation are about −0.027 and 0.048 mm, respectively. It shows that the proposed encoder system has the potential for displacement measurement tasks. Originality/value: This study reveals an ultrasonic linear encoder that is capable of generating an incremental encoding signal, accompanied by a corresponding signal processing methodology. In contrast to the conventional heterodyne signal processing approach, the proposed multiplication method effectively reduces the interpolation error that arises because of multiple reflections. [ABSTRACT FROM AUTHOR]

The aims of this study were to evaluate metabolic profiles obtained at -14, 14, and 28 days in milk (DIM), and to identify potential predictive biomarkers of Holstein dairy cows with purulent vaginal discharge (PVD) at 28 DIM. The body condition score (BCS) and hematocrit (Hct) were evaluated, and a metabolic profile test (MPT) was performed at -14, 14, and 28 DIM using serum samples. Cows at 28 DIM were classified using a vaginoscopy and divided into groups of healthy cows (n=89) and cows with PVD (n=31). Albumin (Alb), total cholesterol (TCho), calcium (Ca) and, magnesium (Mg) levels were lower in cows with PVD than in healthy cows at 14 DIM. At 28 DIM, levels of Alb, TCho, Ca, blood urea nitrogen (BUN), Mg, and Hct were lower in cows with PVD. A multivariate stepwise logistic regression analysis showed that higher non-esterified fatty acids (NEFA; odds ratios; OR=4.47; P<0.01), lower Alb (OR=0.07; P<0.01) and lower TCho (OR=0.99; P=0.08) at 14 DIM, and lower Hct (OR=0.83; P=0.05), lower Alb (OR=0.12; P<0.01), and lower BUN (OR=0.74; P=0.02) at 28 DIM were significantly associated with PVD. In conclusion, serum Alb levels was a potential indicator associated with PVD, reflecting dietary protein deficiency preceding disease. Our findings suggest that MPT should be considered to monitor health status during the postpartum period for early diagnosis of PVD. [ABSTRACT FROM AUTHOR]

Activity hijacking is one of the most powerful attacks in Android. Though promising, all the prior activity hijacking attacks suffer from some limitations and have limited attack capabilities. They no longer pose security threats in recent Android due to the presence of effective defense mechanisms. In this work, we propose the first automated and adaptive activity hijacking attack, named VenomAttack, enabling a spectrum of customized attacks (e.g., phishing, spoofing, and DoS) on a large scale in recent Android, even the state-of-the-art defense mechanisms are deployed. Specifically, we propose to use hotpatch techniques to identify vulnerable devices and update attack payload without re-installation and re-distribution, hence bypassing offline detection. We present a newly-discovered flaw in Android and a bug in derivatives of Android, each of which allows us to check if a target app is running in the background or not, by which we can determine the right attack timing via a designed transparent activity. We also propose an automated fake activity generation approach, allowing large-scale attacks. Requiring only the common permission INTERNET, we can hijack activities at the right timing without destroying the GUI integrity of the foreground app. We conduct proof-of-concept attacks, showing that VenomAttack poses severe security risks on recent Android versions. The user study demonstrates the effectiveness of VenomAttack in real-world scenarios, achieving a high success rate (95%) without users’ awareness. That would call more attention to the stakeholders like Google. [ABSTRACT FROM AUTHOR]

Sparse unmixing is a semisupervised unmixing method based on the linear mixture model, in which the spectral library is known a prior, and has received considerable attention recently. It has been confirmed that the spatial information in hyperspectral images plays a crucial role in improving the performance of sparse unmixing algorithms. However, the spatial information extracted or captured in most unmixing algorithms is inaccurate and robust enough, which leads to artificial block noise or outliers in the estimated abundance maps, especially as the noise level increases. To address these problems and more efficiently utilize the spatial information, this paper proposes a graph learning and denoising-based weighted sparse mixing (GLDWSU) algorithm, which includes three stages in the unmixing procedure: graph learning, denoising and unmixing. In the first stage, the graph Laplacian matrix is adaptively learned to capture the spatial structure of HSI with the relative total variation (RTV) regularization. In the next stage, HSI is denoised with the learned Laplacian matrix by using Laplacian smoothing. In the final stage, the denoised HSI is unmixed with the reweighted-norm regularization based on the alternating direction method of multipliers (ADMM) framework. The experimental results on both simulated and real data sets show that the proposed GLDWSU algorithm can more accurately capture and utilize the spatial structure information of HSI with a low computational cost and outperforms all the compared methods. [ABSTRACT FROM AUTHOR]

Tillering onion is a herbaceous plant belonging to the Liliaceae family. We cloned the cDNAs of the actin gene (AcACT, GenBank: MF919598) of tillering onion using rapid amplification of the cDNA ends. The fulllength cDNA of AcACT was 1,357 bp long with an open reading frame of 1,131 bp encoding 376 amino acids. The amino acid sequence of AcACT shared > 96% similarity with the amino acid sequences of other ACTs and was found (by means of phylogenetic tree analysis) to be closely related to those of Ananas comosus and Papaver somniferum. AcACT expressions showed no significant differences (p > 0.01) in two cultivars L-SH and L-SY over three growth periods and under suitable conditions, low temperature, and short-day conditions. In addition, AcACT was used as an internal reference gene to analyse the expression of the alliinase gene (AcALL). AcALL expression trends in the roots, stems and leaves were consistent with those of diallyl disulphide and diallyl trisulphide. Thus, AcACT is highly conserved and can be used as a suitable internal reference gene when analysing gene expression in tillering onion. [ABSTRACT FROM AUTHOR]

This article, titled "[Retracted] Brain cell apoptosis inhibition by butylphthalide in Alzheimer's disease model in rats," was published in the journal Experimental & Therapeutic Medicine in 2017. However, it has since been retracted due to concerns raised by a reader. The TUNEL assay data presented in Figure 1A were found to be strikingly similar to data from other articles published by different authors at different research institutes. The authors were asked for an explanation but did not respond. The editor of the journal apologizes for any inconvenience caused. [Extracted from the article]

Chrysomycin A (Chr-A), an antibiotic from Streptomyces, is reported to have anti-tumor and anti-tuberculous activities, but its anti-glioblastoma activity and possible mechanism are not clear. Therefore, the current study was to investigate the mechanism of Chr-A against glioblastoma using U251 and U87-MG human cells. CCK8 assays, EdU-DNA synthesis assays and LDH assays were carried out to detect cell viability, proliferation and cytotoxicity of U251 and U87-MG cells, respectively. Transwell assays were performed to detect the invasion and migration abilities of glioblastoma cells. Western blot was used to validate the potential proteins. Chr-A treatment significantly inhibited the growth of glioblastoma cells and weakened the ability of cell migration and invasion by down regulating the expression of slug, MMP2 and MMP9. Furthermore, Chr-A also down regulated Akt, p-Akt, GSK-3β, p-GSK-3β and their downstream proteins, such as β-catenin and c-Myc in human glioblastoma cells. In conclusion, Chr-A may inhibit the proliferation, migration and invasion of glioblastoma cells through the Akt/GSK-3β/β-catenin signaling pathway. [ABSTRACT FROM AUTHOR]

A series of 51 novel sulfonylurea compounds with ortho‐alkoxy substituent at phenyl ring were chemically synthesized and spectroscopically characterized. The biological activities of the target compounds were evaluated using the enzyme inhibition against acetohydroxyacid synthase (AHAS; EC 2.2.1.6) from fungal or plant source, as well as cell‐based antifungal assay and greenhouse pot herbicidal assay. Among the target compounds, 6e showed desirable antifungal activity against Candida albicans standard isolate sc5314 with minimum inhibition concentration (MIC) of 0.39 mg/L (0.98 μM) after 24 h, and 6a demonstrated promising pre‐emergence herbicidal activity against Echinochloacrus‐galli at 30 g/ha dosage. Representative compounds 6a, 6e, and 6i showed no cell cytotoxicity even at 40 mg/L concentration. Theoretical DFT calculations indicated HOMO maps should be considered to understand the structure–activity relationships. The present study has hence provided useful information for further discovery of novel antifungal agents or selective herbicides. [ABSTRACT FROM AUTHOR]

Aircraft with a blunt-nosed slender body configuration exhibit free-to-roll motion during maneuvering flight. The separation vortex on the forebody and the wing parameters are the two key factors affecting this motion. A blunt-nosed slender body configuration normally includes multiple sets of wings, which enhances the complexity of the roll motion. The strips, narrow wings, and tail rudders are installed at different axial locations on the blunt-nosed body to study the influence of wings on the roll motion. Wind tunnel experiments are conducted to investigate the motion at Reynolds number ReD = 1.54 x 105, which is based on the coming freestream velocity and diameter of the blunt-nosed body. Free-to-roll motion and aerodynamic forces are measured by the free-to-roll sting support and force balance, respectively. The free-toroll motion is first described and divided into six regions based on the motion characteristics at 0° ≤ α ≤ 55°. The strips, narrow wings, and tail rudders are removed to investigate the effect of the wings on the roll motion. The major control performance of strips, narrow wings, and tail rudders on motion in each angle-of-attack (AOA) region are discussed in detail. The experimental results indicate that the coupling between asymmetric flow and tail rudders leads to different characteristics of free-to-roll motion at different AOAs. The asymmetric flow is closely related to the strips, narrow wings and AOA. [ABSTRACT FROM AUTHOR]

The cross-flow (CF) vortex-induced vibration (VIV) of a deepwater steep wave riser (SWR) subjected to uniform or shear flow loads is investigated numerically. The model is based on a three-dimensional (3D) nonlinear elastic rod theory coupled with a wake oscillator model. In this numerical simulation, the nonlinear motion equations of the riser with large deformation features are established in a global coordinate system to avoid the transformation between global and local coordinate systems, and are discretized with the time-domain finite element method (FEM). A wake-oscillator model is employed to study the vortex shedding, and the lift force generated by the wake flow is described in a van der Pol equation. A Newmark-β iterative scheme is used to solve their coupling equation for the VIV response of the SWR. The developed model is validated against the existing experimental results for the VIV response of the top-tension riser (TTR). Then, the numerical simulations are executed to determine VIV characteristics of the SWR. The effects of both flow velocity and the spanwise length of the flow field on the drag coefficient in the inline (IL) direction and the lift coefficient in the CF direction are investigated systematically. The results indicate that compared with TTR, the low frequency and multi-modal vibration are the main components of the SWR due to the large deformation and flexible characteristics. For shear flow, the multi-frequency resonance dominates the VIV response of the SWR, especially at the hang-off segment. [ABSTRACT FROM AUTHOR]

JavaScript has become one of the most widely used languages for Web development. Its dynamic and event-driven features make it challenging to ensure the correctness of Web applications written in JavaScript. A variety of dynamic analysis techniques have been proposed which are, however, limited in either coverage or scalability. In this paper, we propose a simple, yet effective, model-based automated testing approach to achieve a high code-coverage within the time budget via testing with longer event sequences. We implement our approach as an open-source tool LJS, and perform extensive experiments on 21 publicly available benchmarks. On average, LJS is able to achieve 86.5% line coverage in 10 minutes. Compared with JSDEP, a state-of-the-art breadth-first search based automated testing tool enriched with partial order reduction, the coverage of LJS is 11%–19% higher than that of JSDEP on real-world large Web applications. Our empirical findings support that proper longer test sequences can achieve a higher code coverage in JavaScript Web application testing. [ABSTRACT FROM AUTHOR]

Background: Maternal smoking during pregnancy may be associated with low birth weight (LBW) in offspring and global risk estimates have not been summarized previously. We aimed to systematically explore evidence regarding maternal smoking and the LBW risk in offspring globally and examine possible causes of heterogeneity across relevant studies. Methods: Comprehensive search of PubMed, Ovid Embase, Ovid Medline (R), and Web of science from inception until October 2021 was carried out. A random-effects meta-analysis was used to estimate the pooled odds ratio (OR) and corresponding 95% confidence interval (CI). Restricted cubic spline analysis with three knots was used to further examine the dose–response relationship. Results: Literature searches yielded 4940 articles, of which 53 met inclusion criteria (comprising 55 independent studies). Maternal smoking during pregnancy was significantly associated with the risk of LBW in offspring (OR = 1.89, 95% CI = 1.80–1.98). Furthermore, an obvious dose–response relationship between the amount of cigarettes daily smoked in pregnancy and the risk of LBW in offspring was observed. The results of subgroup analyses indicated that the risk of maternal smoking on LBW was larger in more recently conducted studies (P = 0.020) and longer period of active smoking during pregnancy (P = 0.002). No evidence of publication bias was found. Conclusions: In summary, maternal smoking in pregnancy was significantly associated with a higher risk of LBW in offspring on a global scale. The risk of maternal smoking on infant LBW seems to be increasing over time, and was higher with longer smoking duration throughout pregnancy and more cigarettes smoked daily. [ABSTRACT FROM AUTHOR]

As an important medium of human-computer interaction, flexible tactile sensors have a vital influence on the intelligence and safety of a system by accurately identifying the contact position and force. For now, most of the existing flexible capacitive pressure sensors adopt an array structure, which still cannot meet the requirements including simple manufacturing, simple wiring, and low cost. This paper innovatively proposes a flexible array-less capacitive tactile sensor, a 30 mm $\times30$ mm sensor prototype, consisting of flexible electrodes and a dielectric layer of a polydimethylsiloxane (PDMS) and multiwalled carbon nanotube (MWCNT) composite. Under the action of a contact force, the contact area is deformed, resulting in a capacitance change in the flexible sensor. First, Poisson’s equation is used to determine the relationship between the electric potential and position. Then, elastic contact mechanics is adopted to describe the relationship between the electric charges and force. Finally, the contact position and force are recognized by measuring the change in capacitance in real time, based on the classical principle of capacitance. Simulation and experimental results verified the effectiveness of the proposed recognition method, showing that the recognition resolution of contact position can reach $500\,\,\mu \text{m}\,\,\times 100\,\,\mu \text{m}$ , and the accuracy of contact force is 95.85%. Theoretically, the proposed flexible array-less sensor in this paper has infinite spatial resolution, and most importantly, it does not rely on complex manufacturing, redundant circuits, or sensor cell arrays. Therefore, it has broad application prospects in related fields such as electronic skin and wearable electronic devices. [ABSTRACT FROM AUTHOR]

Using over-5-year EMFISIS wave measurements from Van Allen Probes, we present a detailed survey to identify the controlling factors among the geomagnetic indices and solar wind parameters for the 1-min root mean square amplitudes of lower band chorus (LBC) and upper band chorus (UBC). A set of important features are automatically determined by feature selection techniques, namely, Random Forest and Maximum Relevancy Minimum Redundancy. Our analysis results indicate the AE index with zero-time-delay dominates the intensity evolution of LBC and UBC, consistent with the evidence that chorus waves prefer to occur and amplify during enhanced substorm periods. Regarding solar wind parameters, solar wind speed and IMF Bz are identified as the controlling factors for chorus wave intensity. Using the combination of all these important features, a predictive neural network model of chorus wave intensity is established to reconstruct the temporal variations of chorus wave intensity, for which application of Random Forest produces the overall best performance. Plain Language Summary Whistler mode chorus waves are electromagnetic waves observed in the low-density region near the geomagnetic equator outside the plasmapause. The dynamics of Earth's radiation belts are largely influenced by chorus waves owing to their dual contributions to both radiation belt electron acceleration and loss. In this study, we use feature selection techniques to identify the controlling geomagnetic and solar wind factors for magnetospheric chorus waves. Feature selection techniques implement the processes which can select the features most influential to the output. In this study, the inputs are geomagnetic indices and solar wind parameters and the output is the chorus wave intensity. The results indicate that AE index with zerotime delay dominates the chorus wave intensity. Furthermore, solar wind speed and IMF Bz are identified as the most important solar wind drivers for chorus wave intensity. On basis of the combination of all these important geomagnetic and solar wind controlling factors, we develop a neural network model of chorus wave intensity, and find that the model with the inputs identified using the Random Forest method produces the overall best performance. [ABSTRACT FROM AUTHOR]

Recent studies have reported the simultaneous observation of Magnetosonic (MS) waves and Electromagnetic ion cyclotron (EMIC) waves. In this study, a detailed survey of the concurrent EMIC waves and MS waves is performed using the Van Allen Probes observations from 2012 to 2017. The results suggest that most of the concurrent EMIC waves and MS waves are H+ band EMIC waves and MS waves. The favorable geomagnetic conditions for the concurrent EMIC waves and MS waves are AE* = 500 nT inside the plasmapause and AE* = 100 nT outside the plasmapause. Although EMIC waves are generally stronger than MS waves, stronger MS waves than EMIC waves are more likely to occur during moderate and active geomagnetic times. Our study is consistent with the most recent research, and provides more detailed information that helps us to deepen our understanding of the concurrent EMIC waves and MS waves. Plain Language Summary Electromagnetic ions cyclotron (EMIC) waves and magnetosonic (MS) waves are two common wave mode in the Earth radiation belts and play important roles in radiation belt dynamics. Recent studies have reported observations of concurrent EMIC waves and MS waves and conducted a brief statistic survey. To deepen our understanding of the concurrent EMIC waves and MS waves, this study aims to comprehensively analyze the statistical occurrence pattern and associated global distribution of concurrent EMIC waves and MS waves. Our study demonstrated that most of the concurrent EMIC waves and MS waves are H+ band EMIC waves and MS waves, which reveals the deep relationship between MS waves and the concurrent H+ band EMIC waves. Our study also demonstrated that the concurrent EMIC waves are generally stronger than MS waves, while the wave amplitudes of MS waves can exceed EMIC waves during geomagnetically turbulent times. This result indicates that the combined scattering effect of the concurrent EMIC waves and MS waves could vary significantly under different geomagnetic conditions. [ABSTRACT FROM AUTHOR]

From the perspective of human health and environmental safety, the development of hydrostable fluorescent sensors for the detection of heavy metal ions and nitroaromatics is an important but a challenging issue. To this end, a water-stable Zn2+ coordination polymer formulated as {[Zn(H2L)]·2DMF·3H2O}n (ZnCP) was prepared elaborately by a solvothermal method using a multidentate ligand (H4L) with 2,6-pyridine-dicarboxylic acid spaced by para-substituted benzene. Single-crystal analysis shows that the new ZnCP exhibits one-dimensional chain structural features, which further promoted to afford a wrinkled two-dimensional network structure via inter-chain hydrogen bonding. Powder X-ray diffraction and fluorescence measurements show that it can maintain crystallinity and structural integrity under harsh acidic and alkaline conditions with the pH ranging from 4 to 11. Notably, the bright blue–emissive ZnCP showed selective fluorescence quenching effects for Fe3+ and picric acid (PA), which makes it an excellent chemical sensor for Fe3+ and picric acid (PA) with low detection limits of 0.41 and 0.26 μM in water. The recognition mechanism of Fe3+ could be attributed to UV absorption competition and resonance energy transfer in the aid of weak electrostatic interactions, while the recognition mechanism of PA is considered to be a multi-quenching mechanism dominated by absorption competition and PET effects with the assistance of hydrogen bonding. In addition, poly(methyl methacrylate) (PMMA) films doped with ZnCP (ZnCP@PMMA) were developed to provide better sensing performance and portability for practical applications. [ABSTRACT FROM AUTHOR]

Machine learning (ML) based classifiers are vulnerable to evasion attacks, as shown by recent attacks. However, there is a lack of systematic study of evasion attacks on ML‐based anti‐phishing detection. In this study, we show that evasion attacks are not only effective on practical ML‐based classifiers, but can also be efficiently launched without destructing the functionalities and appearance. For this purpose, we propose three mutation‐based attacks, differing in the knowledge of the target classifier, addressing a key technical challenge: automatically crafting an adversarial sample from a known phishing website in a way that can mislead classifiers. To launch attacks in the white‐ and gray‐box scenarios, we also propose a sample‐based collision attack to gain the knowledge of the target classifier. We demonstrate the efficacy of our evasion attacks on the state‐of‐the‐art, Google's phishing page filter, achieved 100% attack success rate in less than one second per website. Moreover, the transferability attack on BitDefender's industrial phishing page classifier, TrafficLight, achieved up to 81.25% attack success rate. We further propose a similarity‐based method to mitigate such evasion attacks, Pelican, which compares the similarity of an unknown website with recently detected phishing websites. We demonstrate that Pelican can effectively detect evasion attacks, hence could be integrated into ML‐based classifiers. We also highlight two strategies of classification rule selection to enhance the robustness of classifiers. Our findings contribute to design more robust phishing website classifiers in practice. [ABSTRACT FROM AUTHOR]

Simulations of hydrated Mg2+, in the absence and presence of several solution additive anions, show that in pure liquid water Mg(H2O)62+ is the only stable coordination state; yet anions may stabilise undercoordinated five-hydration configurations. Solution composition can lower the barrier to Mg2+ dehydration and subsequent incorporation into the lattice of Mg-carbonates, promoting low-temperature crystallisation. [ABSTRACT FROM AUTHOR]

This study performs global stability/receptivity analyses of hypersonic flows over a swept blunt body with infinite span. For the first time, we obtain the characteristics of the leading attachment-line mode to the variation of sweep angles from 20◦ to 70◦. The global eigenfunctions exhibit the characteristics of the attachment-line instability at the leading edge. At the same time, cross-flow (at small sweep angles) or second Mack mode (at larger sweep angles) dominates further downstream. We establish an adjoint-based bi-orthogonal eigenfunction system to address the receptivity problem of such flows to any external forces and boundary perturbations. The receptivity analyses indicate that the global modes are the most responsive to external forces and surface perturbations applied in the vicinity of the attachment line, regardless of the sweep angles. It is also proven that the present global extension of the bi-orthogonal eigenfunction system can be successfully applied to complex hypersonic flows. [ABSTRACT FROM AUTHOR]

This study aims to shed light on hypersonic attachment-line instabilities with large sweep Mach numbers. Highly swept flows over a cold cylinder that give rise to large sweep Mach numbers are studied. High-fidelity basic flows are obtained by solving full Navier-Stokes equations with a high-order shock-fitting method. Using local and global stability theories, an attachment-line mode is found to be dominant for the laminar-turbulent transition along the leading edge that agrees qualitatively with the experimental observations (Gaillard et al., Exp. Fluids, vol. 26, 1999, pp. 169-176). The behaviour of this mode explains the reason for the transition occurring earlier as the sweep Mach number is above 5. In addition, this attachment-line mode is absent if the basic flow is calculated with boundary layer assumptions, indicating that the influence of inviscid flow outside the boundary layer cannot be ignored as is normally done. It is clearly demonstrated that the global modes display the features of both attachment-line modes, as in sweep Hiemenz flow, and the second Mack modes further downstream along the surface. In the large sweep Mach number regime, the attachment-line mode is inviscid in nature and its growth rate increases with the sweep angle. In contrast, in the lower sweep Mach number regime, the attachment-line instability exhibits the features of viscous Tollmien-Schlichting waves, and the sweep angle first increases but then decreases the maximum growth rate. [ABSTRACT FROM AUTHOR]

As a common boundary layer that distinctly separates the regions of high-density plasmasphere and low-density plasmatrough, the plasmapause is essential to comprehend the dynamics and variability of the inner magnetosphere. Using the machine learning framework PyTorch and high- quality Van Allen Probes data set, we develop a neural network model to predict the global dynamic variation of the plasmapause location, along with the identification of 6,537 plasmapause crossing events during the period from 2012 to 2017. To avoid the overfitting and optimize the model generalization, 5,493 events during the period from September 2012 to December 2015 are adopted for division into the training set and validation set in terms of the 10-fold cross-validation method, and the remaining 1,044 events are used as the test set. The model parameterized by only AE or Kp index can reproduce the plasmapause locations similar to those modeled using all five considered solar wind and geomagnetic parameters. Model evaluation on the test set indicates that our neural network model is capable of predicting the plasmapause location with the lowest RMSE. Our model can also produce a smooth magnetic local time variation of the plasmapause location with good accuracy, which can be incorporated into global radiation belt simulations and space weather forecasts under a variety of geomagnetic conditions. [ABSTRACT FROM AUTHOR]

This article analyzes the eigenvalues of financial graphs and discusses different types of graphs using random graph theory. We found that the energy-based Rényi index is an effective tool for studying the spectrum of financial graphs. The entropy of financial graphs is usually different from the theoretical predictions of random graph theory, which implies the existence of rich structures. This article also constructed some benchmark graphs for comparative analysis through the classic financial models. The calculations show that the geometric Brownian motion and the one factor model correspond to completely different entropy values based on eigenvalues, thus providing two extreme cases for characterizing real graph entropy. In particular, we find a high correlation between the degree-based Rényi index and the eigenvalue-based Rényi index based on real market data. This article shows the analysis of the structure and complexity of financial graphs from the perspective of graph entropy, thus providing a new way to analyze different types of financial graphs. [ABSTRACT FROM AUTHOR]

We here present a planarized solid-state chemical reaction that can produce transition metal monochalcogenide (TMMC) 2D crystals with large lateral extent and finely controllable thickness down to individual layers. The enhanced lateral diffusion of a gaseous reactant at the interface between a solid precursor and graphene was found to provide a universal route towards layered TMMCs of different compositions. A unique layer-by-layer growth mechanism yields atomically abrupt crystal interfaces and kinetically controllable thickness down to a single TMMC layer. Our approach stabilizes 2D crystals with commonly unattainable thermodynamic phases, such as β-Cu2S and γ-CuSe, and spectroscopic characterization reveals ultra-large phase transition depression and interesting electronic properties. The presented ability to produce large-scale 2D crystals with high environmental stability was applied to highly sensitive and fast optoelectronic sensors. Our approach extends the morphological, compositional, and thermodynamic complexity of 2D materials. [ABSTRACT FROM AUTHOR]

It is challenging to develop highly stable lanthanide luminescent sensors for detecting heavy metal ions and nitroaromatics in view of the human health and environmental security. To this end, two water stable Ln-MOFs with the chemical constitution of {[Ln(HL)]·3DMF·3H2O}n (Ln = Eu, LZG-Eu and Ln = Tb, LZG-Tb) have been developed solvothermally using a multidentate ligand (H4L) with the central phenyl backbone bisubstituted by 2,6-pyridine-dicarboxylic acid at the para-position, H4L = 1,4-bis(2′,2′′,6′,6′′-tetracarboxy-1,4′:4,4′′-pyridyl)benzene. Single crystal analysis demonstrates that two novel Ln-MOFs feature 4,4,4-connected nets with an unprecedented topology symbol of {42·6·83}2{42·62·82}{42·84} and contain two kinds of one-dimensional channels. Powder X-ray diffraction as well as the luminescence determination results indicate that they retain their crystallinity and structural integrity in harsh acidic and basic conditions with pH in the range of 4–11. Moreover, they are highly luminescent, which makes them excellent chemical sensors for detecting Cu2+ and 4-NP (4-nitrophenol) with high selectivity and sensitivity in aqueous media such as deionized water, tap water, and river water based on distinct quenching effects. To the best of our knowledge, their detection limits are lower than those documented so far. In addition, the quenching efficiency of 4-NP was retained in the presence of interfering ions even after the compounds were used for five cycles, which makes them attractive, reliable, visual, and recyclable luminescent Ln-MOF sensor materials for 4-NP. The recognition mechanism for Cu2+ could be attributed to the dissociation of the main framework induced by Cu2+ and the subsequent formation of a Cu2+ coordination species and that for 4-NP is considered to be multi-quenching mechanisms dominated by competition absorption. [ABSTRACT FROM AUTHOR]

Recently, by tuning the coordination behavior of a new asymmetric multidentate ligand, H3L, containing two nitrogen and six oxygen donors by both metal centres and anions, H3L = 1-(2-hydroxy-3-methoxy-benzamido)-2-(2-hydroxy-3-methoxy-benzylideneamino)-2-hydroxy propane, three types of heterometallic compounds with the chemical composition of [Zn8Ln2L2(OH)4(OAc)12]·xCH3OH·yCH3CN·zH2O (Zn8Ln2, where Ln = Nd, Tb, Dy and Er), [Ni3Tb2(HL)2(OH)4(OAc)6]·3CH3CN·H2O (Ni3Tb2), and [Ni2Tb2(HL)2(OAc)4(NO3)2(H2O)2]·4CH3CN·3H2O (Ni2Tb2) were developed. Structural analysis revealed that four ellipsoidal decanuclear ZnII–LnIII clusters resulted from the assembly of H3L with Zn(OAc)2·2H2O and Ln(OAc)3·6H2O. Replacement of Zn(OAc)2·2H2O with Ni(OAc)2·4H2O rendered a butterfly pentanuclear NiII–LnIII cluster, and upon further using Tb(NO3)3·6H2O to replace Tb(OAc)3·6H2O, a tetranuclear NiII–LnIII metallocycle was obtained. The luminescence studies on these compounds indicated that the ZnII-containing chromophore is a good antenna for sensitizing the characteristic emission of Ln3+ effectively from the visible to near-infrared region as a result of its energy match, perfect shielding and less concentration quenching compared to its NiII analogues, where the d → d transitions characteristic of Ni2+ were observed in the excitation spectra when irradiated. Notably, weak emission bands characteristic of Tb3+ were observed in the spectrum of Ni2Tb2 but not in that of Ni3Tb2 when excited by the d→d transition, which may be attributed to the difference in crystal field. Furthermore, the magnetic susceptibility studies indicate that the magnetic exchange for the TbIII ions in Zn8Tb2, Ni3Tb2 and Ni2Tb2 is ferromagnetic, whereas that for the DyIII ions in Zn8Dy2 is antiferromagnetic. Our results are of great significance for the rational design and synthesis of novel heterometallic supramolecular structures with interesting luminescence and magnetic properties. [ABSTRACT FROM AUTHOR]

Qing-Mai-Yin (QMY) is a clinically used herbal formula for treating arteriosclerosis obliterans (ASO). To evaluate the chemical constituents and effects of QMY on ASO rabbit model. Forty-eight New Zealand rabbits were divided into six groups (n = 8): normal (normal rabbits treated with 0.5% CMC-Na), vehicle (ASO rabbits treated with 0.5% CMC-Na), positive (simvastatin, 1.53 mg/kg), and QMY treatment (300, 600, and 1200 mg/kg). ASO rabbit model was prepared by high fatty feeding, roundly shortening artery, and bovine serum albumin immune injury. QMY (300, 600 and 1200 mg/kg) was orally administered for 8 weeks. The effects and possible mechanisms of QMY on ASO rabbits were evaluated by pathological examination, biochemical assays, and immunohistochemical assays. The compositions of QMY were analysed using HPLC-Q-TOF-MS/MS analysis. Compared to the vehicle rabbit, QMY treatment suppressed plaque formation and intima thickness in aorta, and decreased intima thickness, whereas increased lumen area of femoral artery. Additionally, QMY treatment decreased TC, TG and LDL, decreased CRP and ET, and increased NO and 6-K-PGF1α in serum. Furthermore, the potential mechanisms studied revealed that QMY treatment could suppress expression of TNF-α, IL-6, ICAM-1 and NF-κB in endothelial tissues, and increase IκB. In addition, HPLC analysis showed QMY had abundant anthraquinones, stilbenes, and flavonoids. QMY has ameliorative effects on ASO rabbit, and the potential mechanisms are correlated to reducing inflammation and down-regulating NF-κB. Our study provides a scientific basis for the future application and investigation of QMY. [ABSTRACT FROM AUTHOR]

Neural networks, as an important computing model, have a wide application in artificial intelligence (AI) domain. From the perspective of computer science, such a computing model requires a formal description of its behaviors, particularly the relation between input and output. In addition, such specifications ought to be verified automatically. ReLU (rectified linear unit) neural networks are intensively used in practice. In this paper, we present ReLU Temporal Logic (ReTL), whose semantics is defined with respect to ReLU neural networks, which could specify value-related properties about the network. We show that the model checking algorithm for the Σ2 ∪ Π2 fragment of ReTL, which can express properties such as output reachability, is decidable in EXPSPACE. We have also implemented our algorithm with a prototype tool, and experimental results demonstrate the feasibility of the presented model checking approach. [ABSTRACT FROM AUTHOR]

Objective: Diabetic retinopathy (DR) is one of the most severe and common complications of diabetes mellitus. The present study aimed to investigate the molecular mechanism of MEG3, miR-19b and SOCS6 in human retinal microvascular endothelial cells (hRMECs) under high glucose conditions. Methods: HRMECs were cultured in 5 or 30 mM D-glucose medium. qRT-PCR and Western blotting were used to determine the mRNA expression and protein levels. MTT assay and flow cytometry analysis were performed to detect the viability and apoptosis of hRMECs, respectively. TNF--, IL-6 and IL-11 levels in cell supernatants were detected by ELISA. The activity of caspase-3/7 was also determined. A luciferase reporter assay was performed to confirm the targeting relationship between miR-19b and SOCS6, as well as MEG3 and miR-19b. Results: Our study demonstrated that miR-19b was increased and SOCS6 was decreased in HG-induced hRMECs. Knockdown of SOCS6 inhibited cell viability and reversed the promotion of cell viability induced by knockdown of miR-19b. Additionally, miR-19b directly targeted and negatively regulated SOCS6. Moreover, miR-19b promoted the cell apoptosis rate and caspase-3/7 activity and increased inflammatory factors through the SOCS6-mediated JAK2/STAT3 signalling pathway. In addition, MEG3 attenuated HG-induced apoptosis of hRMECs by targeting the miR-19b/SOCS6 axis. Conclusion: These findings indicate that MEG3 inhibited HG-induced apoptosis and inflammation by regulating the miR-19b/SOCS6 axis through the JAK2/STAT3 signalling pathway in hRMECs. Thus, these findings might provide a new target for the treatment of DR. [ABSTRACT FROM AUTHOR]

It is common knowledge that the spatial structure of substrates is the major influencing factor in DNA binding. To tune the binding affinity of DNA, a new 4-acylpyrazolone derivative ligand, (2-hydroxy-N′-((5-hydroxy-3-methyl-1-(4-nitrophenyl)-4,5-dihydro-1H-pyrazol-4-yl)(phenyl)methylene)benzohydrazide) (H2L) and its three complexes have been prepared and well characterized. Reaction of H2L with CuCl2 resulted in a mononuclear compound with tetra-coordinated quadrilateral plane, [Cu(HL)Cl] (1). When H2L was coordinated to Cu(OAc)2, a dinuclear Cu(II) compound with chemical formula of [Cu2L2(CH3OH)2]·CH3OH (2) was obtained, and the coordination geometry of Cu(II) is a square pyramid. Upon assembly of H2L with Mn(OAc)2, a quite different dinuclear compound with chemical composition of [Mn2L2(O CH3)2(H2O)2]·CH3OH (3) was afforded, where Mn(III) displayed distorted octahedral configurations. DNA binding studies were performed on H2L and its three complexes by means of electron absorption titration and EB–DNA competition experiments, and the results indicate they all bind DNA in an intercalation mode, and their binding affinity follows the order of 1 > 2 > 3 > H2L. In addition, time-dependent density functional theory (TD-DFT) calculations were performed for H2L and its three complexes to better clarify the electronic transitions in the UV-vis spectra. [ABSTRACT FROM AUTHOR]

Organic matter application was one of the suitable ways to improve soil nitrogen availability in saline soils. In this study, two soils of different levels of total soluble salts, 2.45 g kg−1 (LS) and 4.03 g kg−1 (HS), were used in a pot experiment with eight treatments: bio-organic fertilizer (prepared with cow dung) and farmyard manure (fowl manure) each at three dosages (3350, 6700, and 13,400 kg ha−1), chemical fertilizer control (DAP: 1675 kg ha−1), no fertilizer blank. At the same time, an indoor nitrogen mineralization incubation experiment with the same treatments without alfalfa planting was carried out. We aimed to explore the effects of the types and application amounts of organic fertilizers on soil nitrogen mineralization in saline soils and to improve its quality and finally realize its sustainable utilization. The main conclusions are as follows: the biomass of alfalfa treated with medium dose of organic fertilizer was higher than that of alfalfa treated with low or high dose of organic fertilizer. Compared with farmyard manure, bio-organic manure was more effective in increasing the biomass of alfalfa. The nitrogen uptake of alfalfa in high-dose treatment was significantly higher than that in low-dose treatment. The effects of the fertilizer treatments on soil nitrogen availability were in the increasing order of: medium dose, high or low dose of fertilizer treatment, single chemical fertilizer, and fertilizer free treatments by principal component analysis. For possible potential application, medium dosage of bio-organic fertilizer was recommended to apply in the region with saline fluvo-aquic soil. [ABSTRACT FROM AUTHOR]

Three D–A π-conjugated copolymers PnTIF (where n = 2, 4, or 6), composed of isoindigo electron acceptor units and difluorinated bithiophene (BTF) electron donor units, were synthesized and characterized. The HOMO and LUMO energy levels, solubility (and miscibility with PCBM), crystallinity (and crystalline orientation) and PnTIF:PCBM thin film morphology (nano-fibrillar network and phase separation) of the copolymers could be adjusted by the number (0 for P2TIF, 1 for P4TIF, 2 for P6TIF) of flexible 3-dodecylthiophene spacers between the isoindigo and BTF units. From the tested polymer solar cells fabricated with PnTIF:PCBM bulk heterojunctions, P4TIF:PC61BM solar cells exhibited a remarkably high short-circuit current density of ∼22 mA cm−2 together with a fill factor of ∼61% and an open-circuit voltage >0.80 volt, resulting in a power conversion efficiency of 10.7%, making it one of the highest among PC61BM-based polymer solar cells. [ABSTRACT FROM AUTHOR]

In this study, a linear reduced-order model of flow fields around a NACA0015 is constructed based on time-resolved particle image velocimetry (PIV) data. The PIV data were obtained at the chord Reynolds number of 6.4 © 104, and angles of attack from 11° to 20°. Proper orthogonal decomposition (POD) analysis is employed for the PIV data and the degrees of freedom are reduced by truncating the POD modes. Next, a linear model of the POD modes is constructed using the least-squares method based on the POD-mode time histories. Although the estimated POD modes initially reproduce original data, they gradually attenuate and converge to zero. This behavior is also supported by the eigenvalue analysis results of the model's coefficient matrices. In addition, the behavior of the low-order (more energetic) POD modes was reproduced better than that of the high-order (less energetic) POD modes. These results imply that the temporal fluctuation of large vortex structures has strong linearity and is not significantly affected by noise included in data. The former insight is also supported by the fact that the behaviors of POD modes were reproduced well in the case of high angle of attack. [ABSTRACT FROM AUTHOR]

The computational study on finite/infinite-state systems, probabilistic systems, and finite-state fuzzy systems, has received much attention recently. In contrast, there are very few results for algorithmic analysis of infinite-state fuzzy systems. In this paper, we introduce fuzzy pushdown termination games (FPDTGs), which are an extension of fuzzy pushdown automata with a game feature and can serve as a formal model of infinite-state fuzzy systems. We investigate some computational issues of the games under termination objectives for two players: the goal of player-1 is to maximize the truth value of eventually terminating at some given configurations with the empty stack, while player-2 aims at the opposite. Some interesting results are obtained. For example, we show that both players have optimal memoryless strategies and the same value. The problem of computing the value can be solved in exponential time when the triangular norm is chosen as the minimum one. Furthermore, we present efficient algorithms for computing the values of two special subclasses of FPDTGs. The potential for practical use of our model is demonstrated by a case study on a manufacturing system. [ABSTRACT FROM AUTHOR]