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Magnetic reconnection occurs ubiquitously in the universe and is often invoked to explain fast energy release and particle acceleration in high-energy astrophysics. The study of relativistic magnetic reconnection in the magnetically dominated regime has surged over the past two decades, revealing the physics of fast magnetic reconnection and nonthermal particle acceleration. Here we review these recent progresses, including the magnetohydrodynamic and collisionless reconnection dynamics as well as particle energization. The insights in astrophysical reconnection strongly connect to the development of magnetic reconnection in other areas, and further communication is greatly desired. We also provide a summary and discussion of key physics processes and frontier problems, toward a better understanding of the roles of magnetic reconnection in high-energy astrophysics. [ABSTRACT FROM AUTHOR]

This study presents the design and implementation of a low-speed intrusion experiment under microgravity, with a strong motivation to support the pre-research of the Chinese asteroid exploration mission. In the experiment apparatus, we reconstructed an effective gravity of 10 - 2 g in a free-falling capsule in the drop tower. The simulant of regolith particles is processed using natural basalt and sorted using layered screens. The irregular shapes of the particles are retained to mimic the realistic regolith. A detailed description of the experimental system components and the full-cycle procedure is first presented, which gives 3.6 s of microgravity time for each trial. Repeatable controlled experiments are performed to characterize the dynamical responses of the simulant particles under centimeter-per second intrusion. The results reveal diverse responses that depend on different variables, and the mechanism of different responses is discussed based on theories of granular mechanics. This experimental study is expected to improve our understanding of the contact mechanics of regolith material, which will facilitate the operation design of future asteroid missions. [ABSTRACT FROM AUTHOR]

Background: Sleep deprivation (SD) is commonplace in modern society and there are large individual differences in the vulnerability to SD. We aim to identify the structural network differences based on diffusion tensor imaging (DTI) that contribute to the individual different vulnerability to SD. Methods: The number of psychomotor vigilance task (PVT) lapses was used to classify 49 healthy subjects on the basis of whether they were vulnerable or resistant to SD. DTI and graph theory approaches were used to investigate the topologic organization differences of the brain structural connectome between SD‐vulnerable and ‐resistant individuals. We measured the level of global efficiency and clustering in rich club and non‐rich club organizations. Results: We demonstrated that participants vulnerable to SD had less global efficiency, network strength, and local efficiency but longer shortest path length compared with participants resistant to SD. Lower efficiency was mainly distributed in the right insula, bilateral thalamus, bilateral frontal, temporal, and temporal lobes. Furthermore, a disrupted subnetwork was observed that consisted of widespread connections. Moreover, the vulnerable group showed significantly decreased strength of the rich club compared with the resistant group. The strength of rich club connectivity was found to be correlated negatively with PVT performance (r = −0.395, p = 0.005). We further tested the reliability of the results. Conclusion: The findings revealed that individual differences in resistance to SD are related to disrupted topologic efficiency connectome pattern, and our study may provide potential connectome‐based biomarkers for the early detection of the vulnerable degree to SD. [ABSTRACT FROM AUTHOR]

Background: Cervical cancer (CC) is a potential clinical application of PD-1/PD-L1 inhibitor. We aimed to study the mechanism of DNA mismatch repair (MMR) system regulating the expression of PD-L1 in CC through DNA methyltransferase (DNMTs). Methods: We collected pathological specimens from 118 cases of CC to analyze the relationship between PD-L1 expression and DNMTs in different MMR states. RNA interference (RNAi) technique was used to simulate the formation of CC cell line with MMR deficiency (dMMR) state, and subcutaneous tumor formation experiment was carried out in nude mice to verify the relationship between PD-L1 expression and DNMTs in MMR state. Results: The PD-L1 positive rate in 118 cases of CC was 58.47%, while the microsatellite instability (MSI) status accounted for 5.93%. There was a significant difference in the expression of PD-L1 between patients within the dMMR and MMR proficient (pMMR) groups (χ2 = 21.405, P < 0.001). Subcutaneous inoculation after infection of Siha cells led to successful tumorigenesis in nude mice, accompanied by a significant increase in the level of PD-L1 expression in the mouse tumors, while the expression level of MLH1 and MSH2 protein decreased significantly. We also found that PD-L1 expression was closely related to the expression of DNMTs. Conclusion: PD-L1 is universal expressed on the surface of CC cells, dMMR status enhances the expression of PD-L1 on the surface of CC cells, dMMR states of CC are related to the demethylation status of the PD-L1 gene promoter region. [ABSTRACT FROM AUTHOR]

In this paper, a new approach to visual geo‐localization for natural environments is proposed. The digital elevation model (DEM) data in virtual space is rendered and construct a panoramic skyline database is constructed. By combining the skyline database with real‐world image data (used as the "queries" to be localized), visual geo‐localization is treated as a cross‐modal image retrieval problem for panoramic skyline images, creating a unique new visual geo‐localization benchmark for the natural environment. Specifically, the semantic segmentation model named LineNet is proposed, for skyline extractions from query images, which has proven to be robust to a variety of complex natural environments. On the aforementioned benchmarks, the fully automatic method is elaborated for large‐scale cross‐modal localization using panoramic skyline images. Finally, the compound index is delicately designed to reduce the storage space of the positioning global descriptors and improve the retrieval efficiency. Moreover, the proposed method is proven to outperform most state‐of‐the‐art methods. [ABSTRACT FROM AUTHOR]

Carbon aerogels (CAs) are emerging carbon-based cellular materials with high porosity, low density, and a variety of functions. The combination of all these unique properties contributes to their wide applications in flexible sensors, energy devices, acoustic devices, and environmental applications. However, their wide applications are strictly limited by poor mechanical robustness. The existing conflicts between mechanical robustness and the sparse network of porous materials have never received due attention. Good robustness could ensure structural integrity and performance stability for practical applications of aerogels. Here, we discuss recently emerged strategies for optimizing mechanical robustness, including cell-wall strengthening, cell-wall orientation, pore topology control, and joint reinforcement. Particularly, we conclude advanced design principles to achieve stretching elasticity of CAs without introducing intrinsically stretchable elastomers. In addition, we briefly overview the recent applications of robust CAs and provide an outlook on the open questions for obtaining more mechanically robust CAs. [ABSTRACT FROM AUTHOR]

Image dehazing is always a hot topic in the field of computer vision since haze has significant impact on the imaging quality of camera. Therefore, many image dehazing methods have been proposed for the past decades. To help researchers who are new to this field quickly figure out the development history as well as the current status of image dehazing, this review analyzes some representative dehazing methods, evaluates their advantages and disadvantages, and most importantly, points out the best dehazing method from different viewpoints. A large quantity of experiments show that AECR-Net can be generally considered to be the best dehazing algorithm and Tarel method can be regarded as the best real-time dehazing method. Besides, the mainstream benchmark, metrics, challenges and opportunities for image dehazing are also discussed in this review. [ABSTRACT FROM AUTHOR]

Magnetic reconnection in the relativistic regime has been proposed as an important process for the efficient production of nonthermal particles and high-energy emission. Using fully kinetic particle-in-cell simulations, we investigate how the guide-field strength and domain size affect the characteristic spectral features and acceleration processes. We study two stages of acceleration: energization up until the injection energy γ inj and further acceleration that generates a power-law spectrum. Stronger guide fields increase the power-law index and γ inj, which suppresses acceleration efficiency. These quantities seemingly converge with increasing domain size, suggesting that our findings can be extended to large-scale systems. We find that three distinct mechanisms contribute to acceleration during injection: particle streaming along the parallel electric field, Fermi reflection, and the pickup process. The Fermi and pickup processes, related to the electric field perpendicular to the magnetic field, govern the injection for weak guide fields and larger domains. Meanwhile, parallel electric fields are important for injection in the strong guide-field regime. In the post-injection stage, we find that perpendicular electric fields dominate particle acceleration in the weak guide-field regime, whereas parallel electric fields control acceleration for strong guide fields. These findings will help explain the nonthermal acceleration and emission in high-energy astrophysics, including black hole jets and pulsar wind nebulae. [ABSTRACT FROM AUTHOR]

Rational engineering active sites and vantage defects of catalysts are promising but grand challenging task to enhance photoreduction CO2 to high value‐added C2 products. In this study, we designed an N,S‐codoped Fe‐based MIL‐88B catalyst with well‐defined bipyramidal hexagonal prism morphology via a facile and effective process, which was synthesized by addition of appropriate 1,2‐benzisothiazolin‐3‐one (BIT) and acetic acid to the reaction solution. Under simulated solar irradiation, the designed catalyst exhibits high C2H4 evolution yield of 17.7 μmol g−1⋅h, which has been rarely achieved in photocatalytic CO2 reduction process. The synergistic effect of Fe‐N coordinated sites and reasonable defects in the N,S‐codoped photocatalyst can accelerate the migration of photogenerated carriers, resulting in high electron density, and this in turn helps to facilitate the formation and dimerization of C−C coupling intermediates for C2H4 effectively. [ABSTRACT FROM AUTHOR]

Rational engineering active sites and vantage defects of catalysts are promising but grand challenging task to enhance photoreduction CO2 to high value‐added C2 products. In this study, we designed an N,S‐codoped Fe‐based MIL‐88B catalyst with well‐defined bipyramidal hexagonal prism morphology via a facile and effective process, which was synthesized by addition of appropriate 1,2‐benzisothiazolin‐3‐one (BIT) and acetic acid to the reaction solution. Under simulated solar irradiation, the designed catalyst exhibits high C2H4 evolution yield of 17.7 μmol g−1⋅h, which has been rarely achieved in photocatalytic CO2 reduction process. The synergistic effect of Fe‐N coordinated sites and reasonable defects in the N,S‐codoped photocatalyst can accelerate the migration of photogenerated carriers, resulting in high electron density, and this in turn helps to facilitate the formation and dimerization of C−C coupling intermediates for C2H4 effectively. [ABSTRACT FROM AUTHOR]

PiGF (Phosphor-in-glass film) with high color rendering was successfully prepared at a low sintering temperature. The influence of sintering temperature, the mass ratio of glass and phosphor, and different fluorescent layers on the luminescence properties of PiGF was systematically studied. It is of note that the "cyan cavity" is significantly reduced due to the addition of "cyan phosphor" (BaSi 2 O 2 N 2 :Eu2+). Under 455 nm blue light laser excitation, PiGF has the highest luminous efficiency of 94.55 lm/W and a white light composite PiGF with a correlated color temperature of 5500 K and a color rendering index of 95 can be obtained. In short, this work shows that the PiGF has great potential application in white light laser lighting. • The PiGF has a very high color rendering index, which can reach 95. • While maintaining a high color rendering index, the correlated color temperature is low, only about 5500 K. • First application of cyan phosphor (BaSi 2 O 2 N 2 :Eu2+) to laser lighting to fill in cyan glow. [ABSTRACT FROM AUTHOR]

The consequence of exposure to the dual environment of seawater sea sand concrete (SWSSC) on the inner surface and seawater (SW) on the outer surface on the durability of fibre reinforced plastic (FRP) confining tubes has received very limited research attention. The durability of FRPs fabricated with different fibre types was investigated for the application of SWSSC filled tubes and SWSSC-filled double-skin tubes exposed to the external environment of SW. The colour and shininess of carbon-fibre-reinforced polymer (CFRP) surfaces generally stayed unchanged even after 6 months of exposure to the dual environment, whereas basalt-fibre-reinforced polymer (BFRP) and glass-fibre-reinforced polymer (GFRP) tubes suffered degradation. The degradation led to a ~20–30% increase in pH; however, the pH increase in the external SW was more pronounced when the internal solution was SWSSC. The extent of degradation was greater in BFRP that in GFRP. The investigation also included a specialised investigation of the degradation at the fibre–matrix interface by fracturing specimens in liquid nitrogen. [ABSTRACT FROM AUTHOR]

An identification method is proposed for errors-in-variables (EIV) ARX model with input time-varying time-delays. A Markov chain is used to model varying time delays whose parameters are also estimated. The EIV system accounts for noises in both input and output. To estimate noise-free input, a linear state space model is used to describe input generation process and a Kalman smoother is adopted for its estimation. An expectation maximization algorithm is used to estimate ARX model parameters. A spinning process of polyester fiber and a continuous stirred tank reactor process are used to verify the effectiveness of the proposed approach. • Time-varying time-delays are considered for Errors-in-variables (EIV) system. • Kalman smoother is used to estimation the noise-free input. • The EM algorithm is used to estimate the EIV-TD system parameters and update the noise variance of the input data. • Two simulations are provided for performance evaluation. [ABSTRACT FROM AUTHOR]

The sustainability of biogas production from straws is limited by the collection, transportation, storage, and pretreatment of feedstocks. To address these constraints, this study investigated briquetting as a pretreatment strategy for rice straw (RS) to increase bioenergy generation. The results indicated that briquetted RS yielded 205.4 mL/g VS of methane, which was 11.7% higher compared to that produced by the untreated RS. The economic analysis revealed that the briquetting process had positive effects with a payback time of 3.4 y and an internal rate of return of 23.4%. It also reduced feedstock transportation and storage costs by 42.6%. Adding a NaOH treatment to the briquetting process increased methane production by 26.4% compared to untreated RS. However, the integration of briquetting with NaOH treatment might be an unprofitable method for processing RS. This became apparent when examining the production cost, which stood at 1.13 $/kg biomethane with an internal rate of return of 16.2%, representing an 8.7% increase and a 7.2% decrease, respectively, compared to the mono briquetting method. These results revealed that briquetting as a source pretreatment strategy can improve the productivity of straw biogas plants, thereby advancing the industry towards cleaner production. [Display omitted] • Briquetting, a source pretreatment strategy, improved straw biogas production. • The briquetting strategy integrates the collection and pretreatment of rice straw. • The proposed strategy reduced straw transportation and storage costs by 42.6%. • Adding an NaOH treatment reduced the profitability of a straw biogas plant. [ABSTRACT FROM AUTHOR]

The regulation of γ-aminobutyric acid (GABA) on plant anti-oxygenation and programmed cell death (PCD) in fresh-cut pumpkins was investigated. Exogenous GABA positively promoted GABA accumulation and alleviated oxidant damage in pumpkins tissue. Pumpkins treated with GABA showed lower electrolyte leakage, reactive oxygen species (ROS) and MDA content, while higher activities of superoxide dismutase (SOD), catalase (CAT), peroxidase (POD), and ascorbate peroxidase (APX) as compared to the non-treated tissues. Our results also found that GABA treatment retarded DNA degradation and cytochrome c release and delayed the apoptosis of pumpkin cells. On the other hand, the inhibitor of GABA generation, 3-mercaptopropionic acid (3-MP) treatment not only accelerated oxidant damage, but also induced cell death involving chromatin condensation, DNA ladder and cytochrome c releasing. Taken together, our present research indicated that exogenous GABA could alleviate the wound-induced oxidative stress and PCD occurrence in fresh-cut pumpkins. [Display omitted] • Exogenous GABA alleviated oxidant damage in fresh-cut pumpkins. • 3-Mercaptopropionic acid treatment accelerated oxidant damage and induced PCD. • GABA involved the PCD event and delayed PCD process in fresh-cut pumpkins. [ABSTRACT FROM AUTHOR]

Phosphor-in-glass (PiG) is one of the most important spectral converters to overcome thermal effect in high-power white light-emitting diodes (LEDs). The Al 2 O 3 –SiO 2 –B 2 O 3 –ZnO–Na 2 O–Li 2 O glass was designed and sintered with Y 3 Al 5 O 12 :Ce3+ (YAG: Ce) phosphors at the low temperature of 650 °C to obtain YAG: Ce-PiG. The optimized YAG: Ce-PiG shows the white light of the luminous efficiency (LE), correlated color temperature (CCT) and chromaticity coordinate (CIE) of 177.5 lm/W, 6410 K and (0.31,0.34), respectively. The white LEDs (WLED) were fabricated by coupling the YAG: Ce-PiG with a blue light emitting chip, and the correlation between the luminescence properties, the thickness of PiG and the ratio of phosphors was investigated. More importantly, the WLEDs of a maximum luminous efficiency can reach up to 199.5 lm/W with the thickness of 0.35 mm. In addition, a structure with vacuum packaging technique based on the WLEDs lighting combined with sapphire as substrate was fabricated, which can effectively reduce the heat accumulation during the working process of WLEDs. Compared with normal non-vacuum packaging, the working temperature of WLEDs was reduced by about 35%, from 359.2 to 232.2 °C, with the novel vacuum packaging technique under 30W high-power chip and the luminous performance can still be maintained at 94.7%. In a word, the prepared YAG: Ce-PiG exhibits a great potential for application in high-power solid-state WLEDs. • The new glass matrix of Al 2 O 3 –SiO 2 –B 2 O 3 –ZnO–Na 2 O–Li 2 O was designed and the thermal quenching effect of PiG was alleviated. • The white LEDs fabricated using PiG with high thermal stability and luminous efficiency reach up to 199.5 lm/W. • The vacuum packaging technique can significantly reduce heat accumulation in high-power white light-emitting diodes by 35%. [ABSTRACT FROM AUTHOR]

In the contribution, magnesium hydroxides and graphene oxide were synergistically combined to prepare the chip-in-flakes nanohybrid (Mg(OH)2/GO, MGO) via one-step hydrothermal approach for improving fire retardancy of polypropylene. Various characterizations confirmed its composition, structure and morphology. The fire-retardant evaluations illustrated that limiting oxygen index (LOI) of PP composite with 50 wt.% MGO was improved to 27.8% with UL-94 V-0 rating compared with virgin PP (17.4%, no rating). In parallel, the peak heat release rate, total heat release and smoke production rate of PP/MGO (PMG) were reduced by 80.5%, 30.8% and 79.4% respectively. The mechanism investigation uncovered that the conspicuous fire retardancy and smoke suppression were credited to the synergistic effect between GO and Mg(OH)2 toward the optimized physical barrier. Furthermore, dynamic mechanical analysis (DMA) disclosed the highest modulus (8043 MPa) at -71 °C relative to 3236 MPa of pure PP. In viewpoint, hierarchical nano-flakes with synergistic effect offered an effective approach for the fire-safe polymer. [ABSTRACT FROM AUTHOR]

In strongly magnetized astrophysical plasma systems, magnetic reconnection is believed to be the primary process during which explosive energy release and particle acceleration occur, leading to significant high-energy emission. Past years have witnessed active development of kinetic modeling of relativistic magnetic reconnection, supporting this magnetically dominated scenario. A much less explored issue in studies of relativistic reconnection is the consequence of three-dimensional dynamics, where turbulent structures are naturally generated as various types of instabilities develop. This paper presents a series of three-dimensional, fully kinetic simulations of relativistic turbulent magnetic reconnection (RTMR) in positronâ€"electron plasmas with system domains much larger than kinetic scales. Our simulations start from a force-free current sheet with several different modes of long-wavelength magnetic field perturbations, which drive additional turbulence in the reconnection region. Because of this, the current layer breaks up and the reconnection region quickly evolves into a turbulent layer filled with coherent structures such as flux ropes and current sheets. We find that plasma dynamics in RTMR is vastly different from its 2D counterpart in many aspects. The flux ropes evolve rapidly after their generation, and can be completely disrupted by the secondary kink instability. This turbulent evolution leads to superdiffusive behavior of magnetic field lines as seen in MHD studies of turbulent reconnection. Meanwhile, nonthermal particle acceleration and the timescale for energy release can be very fast and do not depend strongly on the turbulence amplitude. The main acceleration mechanism is a Fermi-like acceleration process supported by the motional electric field, whereas the nonideal electric field acceleration plays a subdominant role. We also discuss possible observational implications of three-dimensional RTMR in high-energy astrophysics. [ABSTRACT FROM AUTHOR]

A new image dehazing algorithm based on adaptive sky region is proposed in this paper, which shows good fidelity in sky region and satisfying visual effect in non‐sky region. For robust sky segmentation, we propose a rough‐to‐fine method that can make a balance between efficiency and accuracy. Considering distribution of haze is inconsistent, we divide the input image into three parts and calculate their atmospheric lights respectively. To solve the problem of invalid dark channel prior, we make an improvement for the transmission estimation. Finally, image fusion is taken as a post processing that can solve the problem of partial darkness and ensure a visual pleasing result. The experimental results for both synthetic and natural hazy images demonstrate that our algorithm performs comparable or even better results than the state‐of‐the‐art methods in terms of various measurement indexes, such as the PSNR, SSIM, and so forth. Besides, the proposed algorithm can be also applied in FPGA platform due to the optimized performance. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Middle East respiratory syndrome (MERS) is caused by MERS‐CoV that infects both human and camel. Camel is supposed to be the natural reservoir for human infection while the sources for most of the primary human infection cases are still not known. We identified two conserved pyrimidine nucleotides that flank UAAU element in MERS‐CoV 5'‐UTR. These conserved pyrimidine nucleotides distinguish MERS‐CoVs into 3 types, that is, UUAAUU, CUAAUU and CUAAUC (referred to as U‐‐‐‐U, C‐‐‐‐U, and C‐‐‐‐C types, respectively). Human MERS‐CoV displays a genetic drift from U‐‐‐‐U, C‐‐‐‐U, to C‐‐‐‐C from 2012 to 2019. Camel virus displays a genetic drift from U‐‐‐‐U to C‐‐‐‐U with a time lag when compared with human virus. The discrepancy in genetic drift seems not to support the notion that camel serves as the only natural reservoir for human infection. [ABSTRACT FROM AUTHOR]

Objective: The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients.Methods: We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS).Results: We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS.Conclusions: Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia. [ABSTRACT FROM AUTHOR]

Summary: Rh catalyst shows promising performance for coke resistance in the CH4/CO2 reforming reaction. In this study, a single atom Rh was added to the surface of Ni(111) by doping and adsorbing ways, and the performance of these surfaces was compared with the pure Ni(111) through density functional theory (DFT) calculation. The reactions related to the carbon formation were studied to obtain the favored adsorption site and dominant reaction paths on three surfaces. A good linear relationship between the charge difference and the reaction barrier was proposed. On the Ni(111) surface, the highest energy barrier of CH* oxidation and decomposition is 1.24 and 1.30 eV, respectively, thus these two reaction paths are dominant. The most favorable pathway for the Rh/Ni(111) is CH* + O* → CHO* → CO* + H*, with the highest energy barrier of 1.34 eV. However, C* is more likely to be converted into C‐C (C2) than oxidized on all three catalyst surfaces. As a result, Rh/Ni(111) surface shows better catalytic activity thermodynamically and more superior carbon deposition resistance. In general, compared with pure Ni catalyst, the modification of Rh could manipulate the reaction path of CH* consumption, which could inhibit the direct decomposition of CH*, and finally suppress the carbon deposition. [ABSTRACT FROM AUTHOR]

N × N filter operations are frequently used in various image processing algorithms in display driver circuits. The implementation of the N × N filter requires a storage element to temporarily retain N or N-1 lines of display data. The traditional approach for this temporary storage element for N × N image filter is either by using N blocks of memory to store N lines of display data with single-port six-transistor (6T) SRAM bit-cells or by using N-1 blocks of memory to store N-1 lines of display data with dual-port eight-transistor (8T) SRAM bit-cells. In this paper, a pseudo multi-port SRAM circuit is proposed for N × N filter in image processing in a display driver integrated circuit (IC). By using pre-read mechanism and word-line/column selection signal forwarding technique, the proposed approach only stores N-1 lines of display 3 × 3 filter application, the proposed approach reduces the overall layout area by 50.3% and 30.2% compared to the traditional dual-port 8T and single-port 6T memory implementations, respectively, in an industrial 0.18-μm CMOS technology. Furthermore, the power used to perform a 3 × 3 filter operation is reduced by 47% and 30.8% with the proposed approach as compared to the traditional dual-port 8T and signal-port 6T memory circuits, respectively, with slight degradation of the access speed. [ABSTRACT FROM AUTHOR]

Magnetic reconnection is a primary driver of particle acceleration processes in space and astrophysical plasmas. Understanding how particles are accelerated and the resulting particle energy spectra are among the central topics in reconnection studies. We review recent advances in addressing this problem in nonrelativistic reconnection that is relevant to space and solar plasmas and beyond. We focus on particle acceleration mechanisms, particle transport due to 3D reconnection physics, and their roles in forming power-law particle energy spectra. We conclude by pointing out the challenges in studying particle acceleration and transport in a large-scale reconnection layer and the relevant issues to be addressed in the future. [ABSTRACT FROM AUTHOR]

An oblique-rotating pulsar generates a relativistic striped wind in a pulsar wind nebula (PWN). The termination shock of the PWN compresses the Poynting-flux-dominated flow and drives magnetic reconnection. By carrying out particle-in-cell simulations of the termination shock of the PWN, we study the shock structure as well as the energy conversion processes and particle acceleration mechanisms. With the recent advances in the numerical methods, we extend the simulations to the ultrarelativistic regime with a bulk Lorentz factor of up to γ0 = 106. Magnetic reconnection at the termination shock is highly efficient at converting magnetic energy to particle kinetic energy and accelerating particles to high energies. Similar to earlier studies, we find that the resulting energy spectra crucially depend on λ/de (λ is the wavelength of the striped wind and de is the relativistic plasma skin depth). When λ/de is large (λ ≳ 40de), the downstream particle spectra form a power-law distribution in the magnetically dominated relativistic wind regime. By analyzing particle trajectories and statistical quantities relevant to particle energization, we find that Fermi-type mechanism dominates the particle acceleration and power-law formation. We find that the results for particle acceleration are scalable as γ0 and σ0 increase to large values. The maximum energy for electrons and positrons can reach hundreds of TeV if the wind has a bulk Lorentz factor of γ0 ≈ 106 and a magnetization parameter of σ0 = 10, which can explain the recent observations of high-energy gamma rays from PWNe. [ABSTRACT FROM AUTHOR]

Facial micro‐expression recognition is a natural mechanism of facial behavior with subtle muscle movements and short duration, which is widely considered to be hard to recognize. In this paper, we propose the temporal sampling deformation (TSD) to normalize the temporal lengths and conserve time domain information for micro‐expression sequences. A three‐stream combining 2D and 3D convolutional neural network (TSNN) is also proposed to capture the features of micro‐expressions and classify the expressions as well. The proposed network has two variants TSNN‐IF and TSNN‐LF, which can automatically learn spatial and temporal features at the same time. Single domain experiments and cross‐domain experiments are also performed in the three benchmark datasets (chinese academy of sciences micro‐expression II (CASME II), spontaneous micro‐expression database (SMIC), and spontaneous micro‐facial movement dataset (SAMM)) to verify the effectiveness and validity of the proposed framework. Comprehensive results and ablation studies show that the proposed method can achieve comparable or even better results compared with other state‐of‐the‐art methods for micro‐expression recognition. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

In this paper, a (2+1)-dimensional extended higher-order Broer–Kaup system is introduced and its bilinear form is presented from the truncated Painlevé expansion. By taking the auxiliary function as the ansatzs including quadratic, exponential, and trigonometric functions, lump, mixed lump-soliton, and periodic lump solutions are derived. The mixed lump-soliton solutions are classified into two cases: the first one describes the non-elastic collision between one lump and one line soliton, which exhibits fission and fusion phenomena. The second one depicts the interaction consisting of one lump and two line soliton, which generates a rogue wave excited from two resonant line solitons. [ABSTRACT FROM AUTHOR]

Dry reforming of methane (DRM) is a promising reaction, it could convert two greenhouse gases CO 2 and CH 4 into syngas (CO and H 2) which could provide a mixed fuel for daily life or chemical feedstock for industrial application. Transition metals were widely applied in this process, however, single component of transition metal catalysts could not meet the stability, selectivity and activity demands simultaneously. And the coke formation on the catalysts is the major barrier to the commercialization of DRM. This review presents a systematic discussion and analysis of methane dry reforming to syngas in the catalytic process from both experimental study and density functional theory (DFT) calculation based on recent research. It includes catalytic performance test of activity, selectivity and stability in DRM on monometallic and bimetallic systems, and also gives the discussion of carbon formation in the former parts. The later parts focus on CH 4 and CO 2 activation over monometal and bimetal surface using DFT simulation. The rate determining step and reaction mechanisms involved in DRM are obtained based on thermodynamic analysis and microkinetic model. In the end, we give our outlook to the design and preparation of good performance catalysts as well as further theoretical simulation and analysis in DRM. This review could provide some useful information for going into methane dry reforming from both experimental application and atomic scale. Image 1 • Dry reforming of methane could provide a mixed fuel or chemical feedstock. • Coke formation on the catalysts is the major barrier. • It includes catalytic performance test of activity, selectivity and stability. • The rate determining step and reaction mechanisms involved are obtained. [ABSTRACT FROM AUTHOR]

Automatic detection of the skyline plays an important role in several applications, such as visual geo-localization, flight control, port security, and mountain peak recognition. Existing skyline detection methods are mostly used under common weather conditions; however, they do not consider bad weather situations, such as rain, which limits their application in real scenes. In this paper, we propose a multi-stream-stage DenseNet to detect skyline automatically under different weather conditions. This model fully considers the adverse factors influencing the skyline and outputs a probability graph of the skyline. Finally, a dynamic programming algorithm is implemented to detect the skyline in images accurately. A comparison with the existing state-of-the-art methods proves that the proposed model shows a good performance under rainy or common weather conditions and exhibits the best detection precision for the public database. [ABSTRACT FROM AUTHOR]

Glaucoma is a chronic disease that threatens eye health and can cause permanent blindness. Since there is no cure for glaucoma, early screening and detection are crucial for the prevention of glaucoma. Therefore, a novel method for automatic glaucoma screening that combines clinical measurement features with image-based features is proposed in this paper. To accurately extract clinical measurement features, an improved UNet++ neural network is proposed to segment the optic disc and optic cup based on region of interest (ROI) simultaneously. Some important clinical measurement features, such as optic cup to disc ratio, are extracted from the segmentation results. Then, the increasing field of view (IFOV) feature model is proposed to fully extract texture features, statistical features, and other hidden image-based features. Next, we select the best feature combination from all the features and use the adaptive synthetic sampling approach to alleviate the uneven distribution of training data. Finally, a gradient boosting decision tree (GBDT) classifier for glaucoma screening is trained. Experimental results based on the ORIGA dataset show that the proposed algorithm achieves excellent glaucoma screening performance with sensitivity of 0.894, accuracy of 0.843, and AUC of 0.901, which is superior to other existing methods. Graphical abstract [ABSTRACT FROM AUTHOR]

Aims: The brain function impairment induced by sleep deprivation (SD) is temporary and can be fully reversed with sufficient sleep. However, in many cases, long‐duration recovery sleep is not feasible. Thus, this study aimed to investigate whether a short nap after SD is sufficient to restore brain function. Methods: The data of 38 subjects, including resting state functional magnetic resonance imaging data collected at three timepoints (before SD, after 30 h of SD, and after a short nap following SD) and psychomotor vigilance task (PVT) data, were collected. Dynamic functional connectivity (DFC) analysis was used to evaluate changes in brain states among three timepoints, and four DFC states were distinguished across the three timepoints. Results: Before SD, state 2 (a resting‐like FC matrix) was dominant (48.26%). However, after 30 h SD, the proportion of state 2 dramatically decreased, and state 3 (still resting‐like, but FCs were weakened) became dominant (40.92%). The increased proportion of state 3 positively correlated with a larger PVT "lapse" time. After a nap, the proportions of states 2 and 3 significantly increased and decreased, respectively, and the change in proportion of state 2 negatively correlated with the change in PVT "lapse" time. Conclusions: Taken together, the results indicated that, after a nap, the cognitive function impairment caused by SD may be reversed to some extent. Additionally, DFC differed among timepoints, which was also associated with the extent of cognitive function impairment after SD (state 3) and the extent of recovery therefrom after a nap (state 2). [ABSTRACT FROM AUTHOR]

Pterostilbene (PTB) is a derivative of resveratrol present in grapes and blueberries. PTB is structurally similar to resveratrol, possessing properties such as being analgesic, anti-aging, antidiabetic, anti-inflammatory, anti-obesity, anti-oxidation, cholesterol-reductive, and neuroprotective. However, there have not been reports on the effect of PTB on macrophage-myofibroblast transition (MMT) induced fibrosis in kidney. In this study, we investigated the antifibrotic effects of PTB on the in vivo mouse unilateral ureteral obstruction (UUO) model and in vitro MMT cells. Kidneys subjected to UUO with PTB treatment were collected for the investigation of PTB mediating MMT derived renal interstitial fibrosis. We conducted kidney RNA-seq transcriptomes and TGF- β 1-induced bone marrow-derived macrophages assays to determine the mechanisms of PTB. We found that PTB treatment suppressed the interstitial fibrosis in UUO mice. PTB also attenuated the number of MMT cells in vivo and in vitro. The transcriptomic analysis showed that CXCL10 may play a central role in the process of PTB-treated renal fibrosis. The siRNA-mediated CXCL10 knockdown decreased the number of MMT cells in TGF- β 1-induced bone marrow-derived macrophages. Our results suggested that PTB attenuated renal interstitial fibrosis by mediating MMT by regulating transcriptional activity of CXCL10. [ABSTRACT FROM AUTHOR]

Main challenges for developing data-based models lie in the existence of high-dimensional and possibly missing observations that exist in stored data from industry process. Variational autoencoder (VAE) as one of the deep learning methods has been applied for extracting useful information or features from high-dimensional dataset. Considering that existing VAE is unsupervised, an output-relevant VAE is proposed for extracting output-relevant features in this work. By using correlation between process variables, different weight is correspondingly assigned to each input variable. With symmetric Kullback–Leibler (SKL) divergence, the similarity is evaluated between the stored samples and a query sample. According to the values of the SKL divergence, data relevant for modeling are selected. Subsequently, Gaussian process regression (GPR) is utilized to establish a model between the input and the corresponding output at the query sample. In addition, owing to the common existence of missing data in output data set, the parameters and missing data in the GPR are estimated simultaneously. A practical debutanizer industrial process is utilized to illustrate the effectiveness of the proposed method. • An output-relevant VAE is proposed for extracting output-relevant features by using correlation between process variables. • With symmetric Kullback–Leibler divergence, the similarity is evaluated between the stored samples and a query sample. According to the values of the SKL divergence, data relevant for modeling are selected. • Owing to the common existence of missing data in output data set, the parameters and missing data in the GPR are estimated simultaneously. • A practical debutanizer industrial process is utilized to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

For nanosecond pulsed gas discharge under hundreds of kV/cm in sulfur hexafluoride (SF6), the electric field emission (EFE) effect may be the mechanism of the initial electrons. Electrode surface micro-protrusions (ESMPs) generated after discharging, would affect the discharge process under a high electric field. To investigate the effect of ESMPs on the breakdown time delay and jitter, the breakdown characteristics of different electrode materials and surface roughness are determined in this paper. Three types of electrode materials include stainless 304L, EDM-AF5 graphite, and CuW70 W-Cu alloy. The influences of stainless 304L electrodes with surface roughness coefficients of 1.6 and 0.8 on the breakdown delay and jitter are compared. After 700 discharge shots, the morphology characteristics and distributions of ESMPs are observed by a contourgraph. Based on the statistical results of ESMPs and EFE theory, the relationship between the electric field of EFE and ESMPs can be calculated. In addition, the effective electron rates of negative ion detachment (NID) are estimated. The experimental and calculation results indicate that the initial electrons are mainly produced by the EFE effect. When the pressure is below 0.5 MPa, the NID effect is limited and the breakdown time delay and jitter are dependent on the height to radius ratio and distributions of ESMPs. Once the pressure exceeds 0.5 MPa, the NID effect will be significant and the influence of ESMPs can be neglected. [ABSTRACT FROM AUTHOR]

Magnetic reconnection in strongly magnetized astrophysical plasma environments is believed to be the primary process for fast energy release and particle energization. Currently, there is strong interest in relativistic magnetic reconnection in that it may provide a new explanation for high-energy particle acceleration and radiation in strongly magnetized astrophysical systems. We review recent advances in particle acceleration and reconnection physics in the magnetically dominated regime. Much discussion is focused on the physics of particle acceleration and power-law formation as well as the reconnection rate problem. In addition, we provide an outlook for studying reconnection acceleration mechanisms and kinetic physics in the next step. [ABSTRACT FROM AUTHOR]

Background: Nowadays, the latent power of technology, which can offer innovative resolutions to disease diagnosis, has awakened high-level anticipation in the community of patients as well as professionals. An easy-to-use mobile app is developed by us, which is purposefully intended for those patients with glaucoma.Methods: A mobile App has been invented for smartphones for the convenient use wherever and whenever. The corresponding experiments carried out by public retinal image database and real captured clinical data reveal the ideal classification accuracy of the App. Also, user feedback evaluation is also carried out in terms of performance test as well as and users' experience.Results: For clinical test using Yanbao App, we found 274 patients for the identification with 648 retinal images to be evaluated by glaucoma classification. Of the 243 glaucoma patients, 191 were screened out with an accuracy of 0.7860 (sensitivity); the number of non-glaucoma patients was 310 of 405, and the accuracy reached 0.7654 (specificity).` The total Accuracy amounted to 0.7731, and the result is close to the test performance obtained on public dataset ORIGA and DRISHTI-GS1.Conclusions: Yanbao App can be applied as an innovative approach exploiting mobile technology to enhance the clinicians' efficiency and a balanced medical resources as well as a provided better tiered medical service system. [ABSTRACT FROM AUTHOR]

In this paper, we propose a deep convolutional network for single image dehazing based on derived image fusion strategy. Instead of estimating the transmission map and atmospheric light as previously performed, we directly generate a haze-free image by the proposed end-to-end trainable neural network. We derive five maps from the original hazy image based on the characteristics of the hazy scene to improve the dehazing performance. First, the exposure map (EM) and saliency map (SM) complement each other to focus on details in far-away and near-region scenes. Second, the white balance map (BM) and gamma correction map (GM) are employed to recover the latent colour and intensity components of the scene. Finally, the haze veil map (VM) is introduced to enhance the global image contrast. To efficiently blend the five derived maps, we propose a U-shaped deep convolutional network consisting of encoder and decoder layers to generate a haze-free image. The convolutional layers transferred from the pretrained ResNet50 are used as encoder layers for hierarchical feature extraction. Two efficient blocks, named the cascaded residual block and the channel compression block, are proposed in the network for better dehazing performance. The final dehazed result is generated by combining the significant features of the different derived maps. Additionally, perceptual loss is introduced for better visual quality. The experimental results for both synthetic and natural hazy images demonstrate that our algorithm performs comparably or even better than state-of-the-art methods in terms of the peak signal-to-noise ratio (PSNR), structure similarity (SSIM) and visual quality. [ABSTRACT FROM AUTHOR]

Background. Patients with liver cirrhosis have a high risk of sepsis and a poor prognosis. Recently, a new standard for sepsis (Sepsis-3) has been proposed in the general population. The Coulter Lh 750 hematology analyzer can evaluate mean volume, conductivity, scatter, and distribution width of leukocyte. We tried to use Sepsis-3 criteria to study the diagnostic value of volume, conductivity, and scattering (VCS) parameters in sepsis and infection in patients with liver cirrhosis compared with traditional infection markers (PCT, IL-6, sCDl63). Methods. A blinded, cohort study was conducted in three different ED populations within three affiliated hospitals. A total of 249 patients with liver cirrhosis were enrolled in the study. According to the "Sepsis-3" consensus criteria, clinical history, and laboratory examination, the subjects were divided into sepsis (n=54), patients with infections (n=95), and patients without systemic infections (n=100). The blood samples of the patients were collected at the time of ED admission and were evaluated for the detection of sepsis. Results. The differences of MNV, MNS, MMV, MMS, MLV, NDW, and MDW in the three groups were statistically significant. In the diagnosis of sepsis in patients with liver cirrhosis, the sensitivity of combined detection of MMV and MDW was 88.89%; the specificity was 74%. This sensitivity was significantly better than the 83.3% achieved using 0.97 mg/L as the cutoff for sCD163. In the diagnosis of infection in cirrhosis, the sensitivity of combination of MNV and MMS was increased to 86.32%; the specificity was 92%. The sensitivity was the same as that achieved by using 0.31 ng/mL as the cutoff value of PCT, but the specificity increased. Conclusion. The leukocyte VCS parameter could be potential parameters for indicating sepsis and infection in patients with liver cirrhosis. The combined detection of MMV and MDW seemed to be helpful for the diagnosis of sepsis in these patients, and the combination of MNV and MMS could better indicate infection for them. [ABSTRACT FROM AUTHOR]

The fiber stretching process plays the key role in the process of fiber production and its effects is measured by the stretching ratio. The stretching ratio is determined by the relative speed of the winding roller. The stretching ratio has impact on the performance of the final fiber filament and production directly. Focused on the importance of the stretching ratio, the support vector regression (SVR) predictive model, called nonlinear auto-regressive exogenous model, for the fiber stretching rate based on existing industry data is proposed. Furthermore, the fruit fly optimization algorithm inspired by immune mechanism and cooperation functional (IFOA) is presented, and then is used to optimize the parameters in SVR. Furthermore, taking into account the high cost and accurate precision of the fiber stretching process, a time series autoregressive moving average (ARMA) model is introduced to reduce the prediction error of the IFOA–SVR model. Simulations results demonstrate that the proposed IFOA–SVR method can increase the prediction accuracy than the traditional FOA and the SVR method, and the ARMA model is essential to modify the prediction error of the IFOA–SVR model. [ABSTRACT FROM AUTHOR]

Objective: Intravascular ultrasound (IVUS) is not routinely performed in the real-world practice, and the benefits of IVUS-guided drug-eluting stent (DES) implantation in patients with complex coronary lesions remains unclear. This updated meta-analysis attempts to evaluate the clinical outcomes of the IVUS guidance in these patients. Methods: We searched potential eligible citations from the PubMed, EMBASE, Medline, and other internet sources. The primary endpoint were major adverse cardiovascular events (MACE), including cardiac death, myocardial infarction (MI), and target vessel revascularization (TVR). The risk of definite/probable stent thrombosis (ST) was chosen as the safety endpoint. Results: Nine randomized trials including a total of 3,612 patients with complex coronary lesions were finally analyzed. Compared to angiography guidance, IVUS-guided DES implantation was associated with significantly lower incidence of MACE [odds ratios (OR) 0.57, 95% confidence intervals (CI): 0.45-0.72, p<0.001; I2=0.0%, p=0.674], cardiac death (OR 0.42, 95% CI: 0.21-0.82, p=0.010; I2=0.0%, p=0.961), MI (OR 0.65, 95% CI: 0.44-0.95, p=0.027; I2=41.8%, p=0.089), TVR (OR 0.55, 95% CI: 0.38-0.79, p=0.001; I2=0.0%, p=0.916), target lesion revascularization (TLR) (OR 0.58, 95% CI: 0.41-0.82, p=0.002; I2=0.0%, p=0.888), and ST (OR 0.48, 95% CI: 0.24-0.93, p=0.029; I2=0.0%, p=0.733). Conclusion: The updated meta-analysis demonstrates that DES implantation under IVUS guidance leads to a significant reduction in MACE, cardiac death, MI, TVR, TLR, and ST among patients with complex coronary lesions. [ABSTRACT FROM AUTHOR]

Glaucoma refers to a chronic disease of the eye that leads to vision loss that is irreversible, which is called 'silent theft of sight'. Thus, an automatic glaucoma screening pipeline from optic disc (OD) localisation to glaucoma risk prediction is proposed in this study. The proposed pipeline consists of three main phases. Firstly, the OD is localised by morphological processing and sliding window methods. Secondly, a novel neural network which is in U‐shape and convolutional introduces concatenating path and fusion loss function is developed to split OD and optic cup (OC) at the same time. Thirdly, both clinical measurements including optic cup‐to‐disc ratio (CDR), neuroretinal rim related features, and hidden features including statistical moments, entropy and energy are combined to train glaucoma classifiers. According to the results of the experiment, the proposed segmentation network achieves the best performance on both OD and OC segmentation and the proposed CDR calculation method is capable of achieving the performance similar to that of ophthalmologist on CDR measurement. Besides, the authors' glaucoma classification model can obtain the best performance on sensitivity and area under the curve score in comparison with the existing methods. [ABSTRACT FROM AUTHOR]

The characteristics, breakdown probability, and statistical distribution of breakdown time delay under different du/dt in hundreds of nanoseconds pulse for millimeter gaps have been investigated by employing the statistical experimental method in this paper. The experimental results indicate that both the breakdown time delay and jitter are essentially decreased as the slope of the pulse voltage- du/dt is increased for 1-, 2-, and 4-mm gaps; in particular, increasing the value of du/dt is useful to obtain the smaller relative deviation of breakdown time delay under the same breakdown electric field. The breakdown probabilities for different gaps have been analyzed and a method of utilizing the Gaussian distribution function has been proposed which can be used for evaluating the statistical distribution of breakdown time delay. When the experimental condition is 100% breakdown probability, the breakdown time delay follows a Gaussian distribution. However, it is unsuitable for the fitting of breakdown time delay utilizing a Gaussian function for 2- and 4-mm gaps from the cumulative probability distributions of breakdown time delay because of the lower du/dt values and breakdown probabilities. [ABSTRACT FROM AUTHOR]

Despite evidence of structural brain abnormalities in schizophrenia, the current study aimed to explore the effects of antipsychotic treatment on gray matter (GM) volume using structural magnetic resonance imaging (MRI) and investigate the relationship between brain structure and treatment response. The GM volumes of 33 patients with first-episode schizophrenia were calculated with voxel-based morphometry (VBM), with 33 matched healthy controls. Longitudinal volume changes within subjects after 4-month antipsychotic treatment were also evaluated. Correlation between volumetric changes and clinical symptoms derived from the Positive and Negative Syndrome Scale (PANSS) were further investigated. Compared with healthy controls, decreased GM volumes in the frontal gyrus were observed in schizophrenia patients. After 4-month treatment, patients showed significantly decreased GM volume primarily in the bilateral frontal, temporal and left parietal brain regions. In addition, the GM volume changes of the left postcentral gyrus was positively correlated with negative symptoms improvement, and the correlation analysis revealed the total PANSS scores changes were associated with GM volume changes in the right inferior frontal gyrus and the right superior temporal gyrus. Besides, non-responders had reduced GM volume in the bilateral middle frontal gyrus and the right superior frontal gyrus compared with responders and healthy controls. Our results suggest that the abnormality in the right frontal gyrus exists in the early stage of schizophrenia. Moreover, the relationship between antipsychotics and structural changes was identified. The GM volume might have the potential to reflect the symptom improvement in schizophrenia patients. And MRI may assist in predicting the antipsychotic treatment response in first-episode schizophrenia patients. [ABSTRACT FROM AUTHOR]

Chemically modified graphene is commonly used as a desensitizer and combustion catalyst for energetic composites. However, the interaction between polar functional groups on chemically modified graphene and energetic ionic materials has not been explored systematically. Herein, we use graphene oxide (GO) with different oxidation degrees and dihydroxylammonium 5,5′-bistetrazole-1,1′-diolate (TKX-50) as experimental systems to investigate the effect of oxygen-containing functional groups of GO on the pyrolysis mechanism of energetic ionic materials. The experimental results show that the thermal decomposition of TKX-50 is affected by different oxidation degrees of GO, among which the highly oxidized GO (HGO) has the greatest effect. The thermal decomposition temperature of GO/TKX-50 composites decrease with the increase of oxygen-containing group content. The decomposition products of GO/TKX-50 composites are consistent with those of TKX-50, but the content of gas products changed. We argue that the interaction between the oxygen-containing groups of GO and TKX-50 controls the pyrolysis mechanism by promoting the transfer of protons in hydroxyl, (NH3OH)+, and (NH4)+, at least in the context of oxygen-containing functional groups. This work provides a route to manipulate the thermal decomposition temperature and gaseous product of the final compound through functional group content, which is helpful to study the polar functional group of chemically modified graphene for the modification of energetic materials. [ABSTRACT FROM AUTHOR]

Objective: We aimed to evaluate the functional network properties in first-episode schizophrenia (SZ) patients at baseline and after 4-months treatment with second-generation antipsychotic drugs.Methods: Resting-state functional magnetic resonance imaging and graph theory approaches were utilized to evaluate the functional integration and segregation of brain networks in 36 first-episode patients (20 male/16 female) with SZ and 36 age and sex matched healthy controls (20 male/16 female).Results: Compared with healthy controls, SZ at baseline showed lower clustering coefficient (Cp) and local network efficiency (Eloc), and this abnormal pattern was modulated with treatment of antipsychotic drugs at follow-up. Longitudinally, the increase of Cp was associated with the improvement of negative symptom. We found that the strength of functional connectivity between brain regions were significantly increased in three connections after treatment, mainly involving the frontal, parietal and occipital lobes.Conclusion: The current study suggested that antipsychotic drugs could modulate the faulty local clustering of the functional connectome in SZ. Furthermore, Cp, the parameter that reflects local clustering of topological organization, demonstrated the potential to be a connectome-based biomarker of treatment response to second-generation antipsychotics in patients with SZ. [ABSTRACT FROM AUTHOR]

This paper proposes an augmented model approach for identification of nonlinear errors-in-variables (EIVs) systems. An EIV model accounts for uncertainties in the observations of both inputs and outputs. As the direct identification of nonlinear functions is difficult, we propose to approximate the nonlinear EIV model using multiple ARX models. To estimate the noise-free input signal, we use a collection of particle filters which run in parallel corresponding to each of the multiple ARX models. The parameters of local models are estimated by applying expectation maximization algorithm, under a maximum likelihood framework, using the input-output data of the nonlinear EIV system. Simulated numerical examples and an experiment study on a multitank system are used to illustrate the efficacy of the proposed approach. [ABSTRACT FROM AUTHOR]

Morpholine- and bis(2-methoxyethyl)amine-substituted 1,3,5-triazine derivatives containing an alkoxy-o-carborane in the 6-position of the triazine ring were successfully synthesized. The molecular structures of the methoxy- and ethoxy-o-carboranyl-1,3,5-triazines were established by X-ray crystallography. In vitro studies showed that the methylene bridged morpholine- and bis(2-methoxyethyl)amine-substituted o-carboranyl-1,3,5-triazines accumulated to high levels in B16 melanoma cells and exhibited higher cytotoxicity than p-boronophenylalanine. [ABSTRACT FROM AUTHOR]

Biomass chars (bio-chars) prepared under two pyrolysis modes and with four particle size ranges were investigated. The pyrolysis modes included isothermal pyrolysis and non-isothermal pyrolysis with three heating rates (5 °C/min, 10 °C/min, and 15 °C/min). The particle size ranges were 58- 75 μm, 75-106 μm, 106-150 μm, and 150-270 μm. The pyrolysis characteristics, pore structures, surface morphologies, and functional groups of the bio-chars were characterized by TGA, specific surface area and porosity analyses, SEM, and FTIR. The mercury adsorption was further explored by the adsorption kinetics. The results established the optimum pyrolysis conditions for mercury adsorption: pyrolysis temperature of 600 °C, heating rate of 10 °C/min, and particle size of 58- 75 μm. In addition, the mercury adsorption processes were affected by both physical adsorption and chemical adsorption. Furthermore, the rate constants of the pseudo-first-order and pseudo-second-order models gradually increased with decreasing particle size. [ABSTRACT FROM AUTHOR]