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The modernization of the Global Navigation Satellite Systems (GNSS) has brought many new features and capabilities, one of which is programmable power output capability, also known as flex power. Flex power capability allows for an increase in the signal strength of the individual signals to better fulfil operational constraints, but it may also cause biases in the pseudorange and carrier phase observations. This study focuses on the flex power capability characteristics of the second-generation Beidou Navigation and Positioning System (Beidou-2). We summarized the Beidou-2 flex power activation periods from January 2021 to April 2024 and analyzed the impact of flex power on phase biases and precise point positioning with ambiguity resolution (PPP-AR). The results show that Beidou-2 flex power would affect both pseudorange and phase observations on the B3I signals simultaneously. In addition, Hatch–Melbourne–Wübbena (HMW) combinations with single-epoch exhibit obvious discontinuities due to this mode of Beidou-2 flex power. Furthermore, the differences in estimated wide-lane (WL) biases can reach up to approximately 0.4 cycles when the Beidou-2 flex power is switched on or off. During this time, regarding the WL biases estimation with the daily constant strategy, the WL ambiguity residuals of Beidou-2 PPP-AR users are only approximately 70% within ± 0.25 cycles. In contrast, with the piecewise constant strategy, the WL ambiguity residuals above the threshold can reach approximately 90%. Considering flex power in kinematic PPP-AR, the position biases root mean square (RMS) values of 0.8, 0.8 and 2.5 cm can be achieved for the east, north and up components, respectively, while the corresponding position biases RMS without careful consideration of flex power are 1.0, 0.9 and 2.8 cm. Therefore, to achieve more reliable positioning results, it is advisable to incorporate flex power into high-precision GNSS data processing, especially for bias products of PPP-AR. [ABSTRACT FROM AUTHOR]

The realistic security of quantum key distribution (QKD) systems is currently a hot research topic in the field of quantum communications. There are always defects in practical devices, and eavesdroppers can make use of the security risk points of various devices to obtain key information. To date, current types of security analysis tend to analyze each security risk point individually, thereby posing great challenges for the overall security evaluation of QKD systems. In this paper, for the first time, we employ machine learning algorithms to identify the defects of different devices and certain attacks in real time, with an accuracy of 98%. It provides a novel solution for the practical security evaluation of QKD systems, thereby addressing the bottleneck problem of multiple risk points being difficult to address simultaneously in QKD systems, thus paving the way for the future large-scale application of quantum communication networks. [ABSTRACT FROM AUTHOR]

In Underwater Wireless Sensor Networks, ensuring precise localization of sensor nodes is crucial. Existing localization algorithms heavily rely on pre-deployed and known anchor nodes to compute and determine the positions of other nodes. However, anchor nodes may be compromised or misled in practical scenarios, resulting in localization inaccuracies. To address this challenge, a proficient iterative localization algorithm is proposed in Garg and Varna (IEEE Trans Inf Forensics Secur 7: 717–730, 2012), which selects known nodes as reference anchors to locate unknown nodes and analyzes their performance under non-collaborative attacks. Therefore, a novel localization algorithm is introduced to counter collaborative attacks, utilizing time difference of arrival ranging mapping and selective minimum gradient principles from the AdaDelta Gradient Descent (AGD) algorithm to iteratively eliminate deceptive information transmitted by interfering nodes, thereby enhancing localization accuracy. Validations demonstrate its efficacy in combating collaborative network attacks under certain conditions and significantly improving localization performance. Simulation experiments confirm its robustness even under network attacks, ensuring the reliable operation of UWSNs. [ABSTRACT FROM AUTHOR]

Chaetomium globosum can inhibit the growth of fusarium by means of their extracellular proteins. Two novel β-glucanases, designated Cgglu17A and Cgglu16B, were separated from the supernatant of C. globosum W7 and verified to have the ability to hydrolyze cell walls of Fusarium sporotrichioides MLS-19. Cgglu17A (397 amino acids) was classified as glycoside hydrolase family 17 while Cgglu16B belongs to the family16 (284 amino acids). Recombinant protein Cgglu17A was successfully expressed in Escherichia coli, and the enzymes were purified by affinity chromatography. Maximum activity of Cgglu17A appeared at the pH 5.5 and temperature 50 °C, but Cgglu16B shows the maximum activity at the pH 5.0 and temperature 50 °C. Most of heavy metal ions had inhibition effect on the two enzymes, but Cgglu17A and Cgglu16B were respectively activated by Ba2+ and Mn2+. Cgglu17A exhibited high substrate specificity, almost only catalyzing the cleavage of β-1,3-glycosidic bond, in various polysaccharose, to liberate glucose. However, Cgglu16B showed high catalytic activities to both β-1,3-glycosidic and β-1,3-1,4-glycosidic bonds. Cgglu17A was an exo-glucanase, but Cgglu16B was an endo-glucanase based on hydrolytic properties assay. Both of two enzymes showed potential antifungal activity, and the synergistic effect was observed in the germination experiment of pathogenic fungus. In conclusion, Cgglu17A (exo-1,3-β-glucanase) and Cgglu16B (endo-1,3(4)-β-glucanase) were confirmed to play a key role in the process of C. globosum controlling fusarium and have potential application value on industry and agriculture for the first time. [ABSTRACT FROM AUTHOR]

The rapid development of deep learning has promoted the research progress in the field of visual object detection. In metal surface irregular small defect object detection, the traditional metal surface defect detection methods were not effective in detecting small and irregular defects. Therefore, how to improve the detection accuracy of small irregular defects on metal surfaces is a hot and difficult research problem. In this study, we propose a deep learning-based method for detecting small irregular defects on metal surfaces. Firstly, we make our own infrared laser diode metal base surface defect dataset to fill the gap of the dataset. Secondly, a new shallow feature extraction layer based on You Only Look Once (YOLO) v5s (an improved YOLO model) is designed for detecting irregular small object defects in the metal surface defect dataset. Thirdly, an attention mechanism was introduced into the network model to enhance the network's ability to extract features of small target defects. The improved model was trained and evaluated on the laser diode metal base surface defect detection dataset, and the results showed that the accuracy of the improved algorithm improved by 3.8% over the original detection algorithm. The detection accuracy also achieves very significant results when compared with other excellent object detection algorithms. [ABSTRACT FROM AUTHOR]

Objectives: To explore clinical and laboratory characteristics of primary Sjögren's syndrome (pSS) complicated with interstitial lung disease (ILD) and investigate the risk factors for respiratory infections in pSS-ILD. Methods: A cohort of 162 pSS-ILD patients in Peking University People's Hospital from 2015 to 2020 were included, and all medical records were completely collected. We screened 53 patients suffering from respiratory infections as study cases, compared with 109 age- and sex-matched controls. Differences between infection group and control group were compared. Univariate and multivariate binary logistic regression tests were conducted to identify potential risk factors for respiratory infections in pSS-ILD patients. Results: Among 162 pSS-ILD patients, 32.72% (53/162) suffered from respiratory infections. The most frequent type of ILD was nonspecific interstitial pneumonia (32.08%, 51/159), and the most common type of pathogen was bacteria (64.25%, 34/53). Infection group showed higher levels of ESSDAI (P < 0.001), CRP (P < 0.001), ESR (P = 0.003), and C3 (P = 0.020) but lower level of DLCO-SB (P = 0.015). Univariate logistic model revealed that PAH and the use of glucocorticoid increased infection risk in pSS-ILD patients. On multivariate logistic regression analysis, PAH (OR = 3.993, 95% CI = 1.192–13.373, P = 0.025) and severe reduction of DLCO (DLCO-SB < 40%, OR = 4.625, 95% CI = 1.281–16.702, P = 0.019) were significantly associated with increased risk of respiratory infections in pSS-ILD patients. Conclusion: Among pSS-ILD patients, the most frequent type of ILD was nonspecific interstitial pneumonia. In patients with infection, bacteria were the most common pathogen. Higher levels of ESSDAI, CRP, ESR, and C3 may be correlated with increased infection risk. PAH and reduction of DLCO were identified as independent risk factors. Key Points • ILD and infectious diseases severely affect pSS patient conditions. • Higher levels of ESSDAI, CRP, ESR, and C3 may be correlated with increased infection risks in pSS-ILD. • PAH and reduction of DLCO were identified as independent risk factors for lower respiratory infection. [ABSTRACT FROM AUTHOR]

With the increasing demands for more flexibility, lighter weight, and larger working space of industrial robotic systems in many fields, the rigid–flexible coupled robotic systems attract more attention. In this work, the desired angular tracking and vibration suppression issues are investigated for the rigid–flexible coupled robotic systems (RFCRSs) in the presence of input quantization. The vibrating displacement is coupled nonlinear due to the coupling between two joints' angular positions and flexible displacements. Using the assumed mode principle, the nonlinear infinite-dimension dynamics of rigid–flexible coupled robotic systems are reduced by ordinary differential equations. With the backstepping-based Lyapunov method, robust adaptive flexible prescribed performance control (FPPC) law is developed to track the given angular positions and to reduce the vibration oscillations. Besides, the robust adaptive update law is incorporated into the quantized FPPC for estimating the unknown parameters of logarithmic quantizers in the face of input quantization. In terms of the above robust adaptive FPPC control, the tracking errors of the RFCRSs eventually converge to a compact set in face of input quantization. At last, three comparison cases are implemented to verify the efficacy of the proposed robust adaptive FPPC strategy in comparison with the PD feedback law. [ABSTRACT FROM AUTHOR]

The low-temperature thick film paste serves as the fundamental material in the electronic printing industry. Currently there is a growing trend towards integration and miniaturization in electronic printing, making high-precision printing increasingly demanded. However, due to the process limitations of screen printing, how to further improve the printing accuracy at a low cost is still a problem to be solved. In this paper, a selection method of low-temperature paste additives was proposed, enabling self-shrinking during the drying process post-printing, thereby achieving enhanced printing accuracy without necessitating equipment modifications. The organic medium with good dispersibility and stable performance was obtained by mixing resin binder, solvent and additive. The constitutive fitting was used to understand its characteristics. The rheological properties of the low-temperature paste were analyzed to comprehend their behavior and structural characteristics under varying conditions, as well as validate their printing performance. Through the screen printing process, it was found that the width of the printed line after sintering decreased to only 80.8% of its original size after sintering. This study provides theoretical guidance for low-temperature electronic paste research. [ABSTRACT FROM AUTHOR]

The mining process involves many complex problems, which are easy to cause environmental pollution and safety. The comprehensive geophysical exploration method combined with drilling method is used to carry out fine exploration of goaf. Firstly, the high density resistivity method was carried out, the data was collected by Wenner device, and the sudden change characteristics of apparent resistivity presented in the profile map of the goaf were summarized. The first-order derivative method was proposed to process the data, which was easier to distinguish the goaf boundary and scope. Transient electromagnetic method and microtremor detection were used to deduce the goaf by high-density electrical method for measurement. The transmitting current of 15A was used in TEM, the fretting detection was a linear acquisition method, and the dispersion curve was extracted by ESPAC method. Through the comprehensive detection of multiple methods, the apparent resistivity mutation area and wave velocity change area are the mined-out range. The acceptance of goaf has been carried out by several borehole verification, and good practical results have been obtained. The research results show that the high density resistivity method, transient electromagnetic method, microtremor detection and other comprehensive geophysical exploration methods can be used to identify the goaf abnormal area, which can be efficient, economical and accurate detection of goaf. [ABSTRACT FROM AUTHOR]

Gels formed by combining gelatin and agar are often used to develop food products such as pudding and gummy bears. Sensory evaluation experiments, bionic chewing experiments, correlation analysis, and regression analysis were performed on four gel samples with varying gelatin contents to explore a method for texture detection of such gels. Results showed a remarkable increase in the scores of hardness, springiness, and chewiness in the sensory evaluation experiment with increasing gelatin content. The fracture force, peak chewing force, and accumulated chewing energy in the bionic chewing experiment also showed a remarkable increase. Correlation analysis of the bionic chewing and sensory evaluation results showed that sensory hardness was highly correlated with maximum chewing force, with a correlation coefficient of 0.996, and chewiness was highly correlated with accumulated chewing energy, with a correlation coefficient of 0.993. The regression models of the four sensory evaluation parameters based on the critical parameters of bionic chewing were all significantly less than 0.001 with a fit of 0.8. The proposed bionic chewing robot and texture detection method can be applied to texture detection of gelatin foods and are consistent with the sensory evaluation results. [ABSTRACT FROM AUTHOR]

Effective production of natural gas from hydrate-bearing sediments by using various strategies (such as depressurization) is an important way to solve the current global energy crisis. Nevertheless, hydrate dissociation during gas production can weaken sediment strength, influencing reservoir stability and subsequent gas production. Previous studies focused mainly on the analysis of production behavior of natural gas from hydrates, but few on reservoir stability. In this work, evolution of gas production, reservoir characteristics and sediment deformation were analyzed thoroughly with ABAQUS platform. Investigation on gas production revealed that the average production rate was 5.57 × 104 m3/day, indicating that development strategies mentioned herein can achieve the goal of commercial development of gas hydrates. Although the changes of hydrate saturation and effective stress both affected the characteristics of hydrate reservoir throughout hydrate development operation, hydrate saturation was the main influencing factor. The contour of the distribution nephogram of reservoir characteristics basically coincided with that of the hydrate saturation distribution nephogram. Meanwhile, the yield area around wellbore appearing in the early stage of development operation corresponded to the area prone to sand production. However, the yield area near the seabed appearing in the late stage of development operation corresponded to the area prone to submarine landslide. Finally, investigation on sediment deformation indicated, except for the dissociation area, which experienced significant compaction, the sediments in other areas in the confined space experienced continuous subsidence. This study is expected to lay a theoretical foundation for proposing engineering measures to avoid uncontrollable geological disasters in the process of hydrate development. [ABSTRACT FROM AUTHOR]

Microbial-induced calcium carbonate precipitation (MICP) treatment of consolidated loess has the advantages of high efficiency and environmental protection. In this study, changes in the microscopic pore structure of loess before and after MICP treatment were compared and quantified, combined with test results at different scales, to better understand the mechanisms of MICP-consolidated loess. The unconfined compressive strength (UCS) of MICP-consolidated loess is significantly increased, and the stress–strain curve indicates improved strength and stability of the loess. X-ray diffraction (XRD) test results show that the signal strength of calcium carbonate crystals is significantly enhanced after loess consolidation. The microstructure of the loess was determined by scanning electron microscopy (SEM). The loess SEM microstructure images are quantitatively analyzed using comprehensive image processing methods (including gamma adjustment, grayscale threshold selection, median processing). The changes in microscopic pore area and average pore sizes (Feret diameter) of the loess before and after consolidation are described. More than 95% of the pores consist of pores with a pore area of less than 100 μm2 and an average pore size of less than 20 μm. The total percentage of pore numbers with pore areas of 100–200 and 200–1000 μm2 decreased by 1.15% after MICP consolidation, while those with 0–1 and 1–100 μm2 increased. The percentage of pore numbers with an average pore size greater than 20 μm decreased by 0.93%, while the 0–1, 1–10, and 10–20 μm increased. Particle size distributions revealed a significant increase in particle size after MICP consolidation, with an increase of 89 μm in D50. [ABSTRACT FROM AUTHOR]

To improve the detection ability for small defects on the surface of the metal base of an infrared laser sensor, master the fluctuation and distribution of product quality, and form closed-loop control of production and quality improvement, the advanced You Only Look Once (YOLO) v5s (an improved YOLO model) object detection algorithm was further improved in this study. Specifically, the same-scale feature fusion part that is easily ignored in the structure was strengthened to enhance the network detection performance. In deep learning object detection, the propagation of information between features in the neural network is important. It was often represented by the pyramid features in the neck part of the model to enhance feature fusion. First, this study proposed a cross-convolution feature strengthening connection method combining the backbone and neck, which shortened the path of information propagation and improved the semantic information between feature pyramids. Then, the concat module of the original network was improved, and a new enhanced feature concat module was proposed to enhance the fusion of features at the same scale. The attention modules implemented by combining the convolutional block attention module were integrated into the concat module to enable the network to learn the weights of each channel independently, enhance the information transmission between features, and improve the detection performance of deep learning small objects. Lastly, the K-means + + algorithm was used to optimize the self-made Metal Base dataset of Infrared Laser Sensor (ILS-MB) and generate a new anchor box suitable for small objects in this dataset to improve the matching degree of target objects. With a small increase in computational cost, the improved YOLO v5s algorithm enhanced the accuracy by 3.8% on the ILS-MB dataset and achieved a very significant effect compared with other state-of-the-art detection methods. [ABSTRACT FROM AUTHOR]

Neural network state observer-based robust adaptive iterative learning output feedback control (NNSO-RAILOFC) is considered for the rigid-flexible coupled robotic systems (RFCRSs) with unknown delays and backlash-like hysteresis. To cope with the unknown backlash-like hysteresis and delays, a new type of the robust adaptive ILOFC laws, based only on available system output data, is firstly developed. Then the robust adaptive ILOFC laws combined with the neural network state observer are designed to follow the two given angular positions and suppress the flexible vibration simultaneously. Meanwhile, the uncertainties related to system dynamic are considered during the controller design of the controlled RFCRSs. It is proved that the NNSO-RAILOFC scheme would converges to a predefined small compact set and stick to it after a finite number of iterations. Moreover, the system signal sequences are also proved to be bounded under the unknown delays and backlash-like hysteresis case. At last, numerical example is carried out to demonstrate the effectiveness of the proposed NNSO-RAILOFC strategy. [ABSTRACT FROM AUTHOR]

Ambiguity resolution (AR) is an effective approach to improve the orbit accuracy of the low Earth orbit satellites using the Global Navigation Satellite System (GNSS). The most commonly used single-difference (SD) AR requires prior knowledge of the GNSS hardware biases, while the potential unavailability of the bias products may hinder the AR process for users. The track-to-track (T2T) AR can work as an alternative without the GNSS bias products, but the performance may be degraded by the receiver hardware biases. To provide a better alternative in this condition, a new AR method called SD T2T (SDT2T) is proposed in this study, where the GNSS and receiver biases can be greatly eliminated without external knowledge. The performance of the SD AR, SDT2T AR, and T2T AR methods are assessed based on the gravity recovery and climate experiment follow on and SWARM data. The results show that the improvements contributed by the SDT2T AR are comparable to the SD AR. The multiple iterations required by the T2T AR can be avoided by the SDT2T AR, and the accuracy of the T2T AR can be further improved with the preprocessed ambiguities of the SDT2T AR. Considering the efficiency and stable performance, the SDT2T AR is recommended as the preferred alternative single-receiver AR method in the absence of the GNSS hardware bias products. [ABSTRACT FROM AUTHOR]

The Yishu fault zone in Shandong Province, China, exhibits favorable conditions for medium- and high-temperature geothermal storage. However, its geothermal occurrence patterns and heat storage model remain unclear. Recognizing the importance of deep heat sources and heat channels in unraveling the formation mechanisms of medium- and high-temperature geothermal systems, we conducted a magnetotelluric survey along the Yishu fault zone, which contained 10 survey lines and 119 usable points. Using two-dimensional and three-dimensional nonlinear conjugate gradient inversion, the deep electrical structure was obtained, and the three-dimensional geothermal reservoir model in the study area was constructed for the first time. The results show that the deep low-resistance anomaly in the Yishu fault zone moves upward through the channel with slightly higher resistivity, forming a relatively low-resistance layer and a low-resistance layer in the shallow part, corresponding to the heat source, thermal conduction fault, heat reservoir, and overburden layer, respectively. The fault structure primarily controls regional geothermal anomalies, influencing atmospheric precipitation, surface water infiltration, and geothermal water migration pathways. The results of this study have a certain guiding significance for the study of the formation mechanism and distribution law of geothermal resources in the middle and deep strata of the Yishu fault zone. Additionally, the results provide valuable insights for the exploration and assessment of geothermal resources in the area. [ABSTRACT FROM AUTHOR]

Satellite attitudes that relate to the satellite antenna phase center and wind-up are essential to high-precision Global Navigation Satellite System (GNSS) data processing. However, during eclipse seasons, various attitude strategies are adopted in the different Multi-GNSS Experiment Analysis Centers (MGEX ACs), which may cause inconsistent yaw attitude errors between the network and user ends. Thus, exchanging satellite attitude quaternions are provided by the Centre National d'Etudes Spatiales and Collecte Localisation Satellites (CNES/CLS) to match the corresponding orbit and clock products. In this research, the yaw angle computation method that uses attitude quaternions is given, and the characteristic of the CNES/CLS attitude model is also described in the eclipse seasons. Experiments with CNES/CLS final orbit and clock products are processed to investigate the benefit of attitude quaternions on satellite clock estimation and precise point positioning (PPP). The results demonstrate that the differences between nominal and quaternion yaw angles can reach 360°. Compared with the nominal attitude, the statistic standard deviation (STD) of the clock difference can be reduced by approximately 70% with the attitude quaternions. Regarding kinematic PPP with nominal attitude, a large impact of approximately 20 cm can be found in the position biases. When applying the attitude quaternions, the root mean square (RMS) of the position biases can be significantly reduced and shows an approximately 29% improvement in the up (U) component. Furthermore, if the specific MGEX AC does not provide the attitude quaternions, deleting the eclipsing satellite can obtain a similar position accuracy to that of attitude quaternions strategy when the satellite geometry is strong. However, under the condition of few redundant observations, such as Galileo-only PPP, position performance of attitude quaternions strategy outperforms that of deleting strategy. Therefore, it is hoped that more ACs can provide attitude quaternions to match with corresponding orbit and clock products. [ABSTRACT FROM AUTHOR]

Single-difference (SD) ambiguity resolution (AR) and track-to-track (T2T) AR are two typical AR methods in precise orbit determination (POD) for Low Earth Orbit (LEO) satellites, which could improve the accuracy of orbits greatly. In this study, SD AR and T2T AR methods are introduced and analyzed. The performance of these two methods is assessed by three months of GPS observations from the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) twin satellites. Results show that T2T AR is highly dependent on the stability of receiver hardware delays, while SD AR requires Fractional Cycle Bias (FCB) or Integer Recovery Clock (IRC) products. We find that these two methods have comparable performance in Reduced Dynamic Precise Orbit Determination (RDPOD), while SD AR slightly outperforms T2T AR in Kinematic Precise Orbit Determination (KPOD). We also find that SD AR has a higher AR success rate than T2T AR. Therefore, we recommend SD AR as the top choice in LEO orbit determination, and T2T AR can be a good alternative when FCB or IRC products are not available. [ABSTRACT FROM AUTHOR]

This paper deals with reliable, robust fuzzy filtering problem with random time delays characterized by uncertain Takagi–Sugeno (T–S) fuzzy singular systems. The singular systems are presented as T–S fuzzy singular systems, which gives a more realistic representation for a variety of nonlinear dynamical systems than usual state-space models.The proposed scheme is designed for uncertain T–S fuzzy singular systems with linear fractional parametric uncertainties. The delay in the filtering system is supposed to be random. The interim and parameter uncertainties are measured with a linear fractional transformation structure. Furthermore, another intention of this article is to establish the filters containing network communication delays with uncertainties under the sensor fault. To construct the fuzzy singular filters with these considerations, a new version of fuzzy Lyapunov–Krasovskii functional is implemented for the performance and stability analysis of the resultant error. Linear matrix inequalities characterize original stability conditions. The effectiveness of the proposed algorithm is validated by an example of the DC motor application. [ABSTRACT FROM AUTHOR]

This paper investigates the quantized iterative learning consensus tracking problem for singular nonlinear multi-agent systems (MASs) in the presence of state time-delay and initial state error. The unified D-type quantized learning control protocols based on the initial state learning with index gain is proposed and employed for singular nonlinear MASs with state time-delay in both continuous-time domain and discrete-time domain. Based on the operator theory, the convergence condition of the consensus tracking errors between each follower agent and the leader is manifested and analyzed over a fixed time interval. Furthermore, the closed-loop D-type learning protocols are introduced to track the leader's trajectory in order to compare the convergent rate with the variable index gain learning protocols. Finally, simulation results are applied to confirm the validity of the proposed protocols. [ABSTRACT FROM AUTHOR]

The hierarchical microspindle-like Fe–Mn oxalates were fabricated by solvothermal method. After the following calcination, the as-derived Fe2−xMnxO3 composite oxides still maintain the hierarchical morphology of micro spindle which consisted of nanoparticles as the primary building blocks and secondary layered structure. As the calcination temperature elevated from 400 to 1000 °C, the average size of primary nanoparticles dramatically increased from 5 to 300 nm and the phase composition changed from γ-Fe2O3 to FeMnO3 and α-Fe2O3 mixture. Moreover, the magnetic property transformed superparamagnetic into antiferromagnetic nature. The exotic structure displays superior electrochemical performances as Li-ion battery anode materials. The reversible capacity of material calcined at 800 °C is up to 620.0 mAh/g at 2 A/g and coulombic efficiency is maintained around 99.0% besides initial charge–discharge efficiency after 500 cycles. The excellent lithium storage performance emerges from the distinctive hierarchical structure, phase compositions, and highly homogenous distribution of Fe and Mn which endow materials with more Li+ insertion/extraction channels, oxygen vacancies, feebly magnetic property, and structural stability. [ABSTRACT FROM AUTHOR]

Premature ovarian insufficiency (POI) is a highly heterogeneous ovarian disorder. Genetic factors account for the cause of POI. We aimed to analyze the genetic alterations in two affected sisters diagnosed with POI and their parents from a highly consanguineous Chinese Han family. Whole-exome sequencing was performed, and bioinformatics analysis was used to determine the potential genetic cause of POI in this family. A SYCE1 deletion was verified by Sanger sequencing. A homozygous deletion in SYCE1 was harbored by the proband and her affected sister, whereas both parents had heterozygous deletions. There were distinct differences in the amino acid sequences between wild-type and SYCE1 deletion. Domain analysis and 3D structural analysis of the SYCE1 deletion was also performed to evaluate the potential impact and pathogenicity of POI. The SYCE1 domain structure was truncated. Additionally, the 3D structure showed that the SYCE1 deletion changed the shape of the protein compared with that of wild-type SYCE1. This study revealed a novel SYCE1 deletion. This SYCE1 deletion may be the cause of POI. Genetic counseling for POI is helpful for researchers and clinicians to identify the mode of genetic inheritance for SYCE1 deletion in POI pathology. [ABSTRACT FROM AUTHOR]

Bioinspired electronics are rapidly promoting advances in artificial intelligence. Emerging AI applications, e.g., autopilot and robotics, increasingly spur the development of power devices with new forms. Here, we present a strain-controlled power device that can directly modulate the output power responses to external strain at a rapid speed, as inspired by human reflex. By using the cantilever-structured AlGaN/AlN/GaN-based high electron mobility transistor, the device can control significant output power modulation (2.30–2.72 × 103 W cm−2) with weak mechanical stimuli (0–16 mN) at a gate bias of 1 V. We further demonstrate the acceleration-feedback-controlled power application, and prove that the output power can be effectively adjusted at real-time in response to acceleration changes, i.e., ▵P of 72.78–132.89 W cm−2 at an acceleration of 1–5 G at a supply voltage of 15 V. Looking forward, the device will have great significance in a wide range of AI applications, including autopilot, robotics, and human-machine interfaces. Designing intelligent power devices that can directly control the output power modulation responses to external stimuli at a rapid speed remains a challenge. Here, the authors report a strain-controlled power device by using the cantilever-structured AlGaN/AlN/GaN HEMT to emulate human reflex process. [ABSTRACT FROM AUTHOR]

Currently, there is a growing concern regarding the safety of assisted reproductive technology (ART) due to increased risk of spontaneous abortion (SA) and imprinting disorders in ART-conceived offspring. Early investigations suggested that aberrant genetic imprinting may be related to pregnancy loss; however, few studies have used human tissue specimens. Here the DNA methylation patterns of 3 imprinted genes, including maternally inherited GRB10 and the paternally inherited IGF2 and PEG3 genes, were evaluated in human chorionic villus samples by pyrosequencing and bisulfite sequencing polymerase chain reaction. The samples were divided into 4 groups: (1) SA of natural conception (NC; n = 84), (2) induced abortion of NC (n = 94), (3) SA after ART (n = 73), and (4) fetal reduction after ART (n = 86). The methylation levels and the percentages of abnormal methylation of the IGF2, GRB10, and PEG3 genes between the ART group and the NC group showed no significant difference. Both IGF2 and GRB10 genes showed higher methylation levels in the SA group compared to the non-SA group. Additionally, determining the single-nucleotide polymorphisms of 4 loci, including IGF2 rs3741205, rs3741206, rs3741211, and GRB10 rs2237457, showed that the TC+CC genotype of IGF2 rs3741211 had a 1.91-fold increased risk of SA after ART. However, there was no association between the mutant genotype of IGF2 rs3741211 and the methylation levels of IGF2 and H19, and ART might not affect the distribution of the abovementioned genotypes. It provides support for the opinion that genetic imprinting defects may be associated with SA, which might not be due to ART treatments. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to explore the association of the DNA-methyltransferase (DNMT)-3A and DNMT3B promoter polymorphisms with the risk of human spontaneous abortion after assisted reproduction techniques (ARTs) and natural conception. Methods: We collected tissues from women who underwent abortion procedures: (a) chorionic villus samples (CVS) and muscle samples (MS) from spontaneous abortions conceived by ART and natural cycle (study group), n = 152; and (b) CVS and MS from normal early pregnancy and second trimester (control group), n = 155. The single-nucleotide polymorphism (SNP) −448A > G in the DNMT3A promoter region and −149C/T polymorphism of DNMT3B were determined by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) and confirmed by sequencing. Results: The allele frequency of −448A among pregnancy loss group and control group was 34.2 % vs. 16.5 %, respectively. Compared with GG carriers, the DNMT3A −448AA homozygotes had an about 16-fold increased risk of spontaneous abortion [odds ratio (OR) = 16.130, 95 % confidence interval (CI), 3.665-70.984], and AG heterozygotes had an OR of 2.027 (95 % CI, 1.247-3.293). However, the distribution of −448A > G in individuals derived from ART pregnancies was not statistically significantly compared with those derived from spontaneous pregnancies ( P = 0.661). For DNMT3B, we observed genotype frequencies of 100 % (TT) in the study group and the control group. Conclusions: The DNMT3A −448A > G polymorphism may be a novel functional SNP and contribute to its genetic susceptibility to spontaneous abortion in Chinese women, and ART may not affect the distribution of −448A > G in pregnancy loss and normal pregnancy. The observed TT genotype of DMNT3B suggests that this is the predominant genotype of this population. The findings provide new insights into the etiology of human spontaneous abortion. [ABSTRACT FROM AUTHOR]

Drought is a stochastic natural hazard that is caused by intense and persistent shortage of precipitation. Spatial and temporal patterns of drought have been analyzed by several methods, ranging from satellite images to historical records; however, drought is generally identified by climate elements. Drought indices are quantitative measures that characterize drought levels by assimilating data from one or several variables (indicators). A number of different indices have been developed to quantify droughts, each with its own strengths and weaknesses. In this paper, using the remote sensing image to acquire the vegetation cover data, and combined with meteorological data and the Geographic Information System (GIS) technology to discuss the spatial and temporal characteristics of the drought. Based on precipitation observations Pu'er City, Yunnan Province, ten counties (districts) ten meteorological observation stations from 1961 to 2010 monthly for 50 years, mainly in ArcGIS10.1 analysis platform, using Mann-Kendall nonparametric trend test method for time-series trends in precipitation was tested, using ArcGIS in inverse distance weighting interpolation tool were precipitation the amount and distribution of precipitation anomaly percentage. Finally, precipitation anomaly percentage grading standards drought intensity distribution of drought The results showed that: Pu'er City under the effect of temperature, altitude, vegetation cover, and many other factors, forming the situation that the rainfall is a little more in north-south and less in east-west, the drought incidence appears more in northwest and less in southeast, more in spring and winter and less in summer and fall. [ABSTRACT FROM AUTHOR]

The three lowest-lying Υ states, i.e., Υ(1S), Υ(2S), and Υ(3S), composed of b b ¯ pairs and below the B B ¯ threshold, provide a ood platform for the researches of hadronic physics and physics beyond the Standard Model. They can be produced directly in e+e− colliding experiments, such as CLEO, Babar, and Belle, with low continuum backgrounds. In these experiments, many measurements of the exclusive Υ(1S) and Υ(2S) decays into light hadrons, which shed light on the "80% rule" for the Okubo-Zweig-Iizuka suppressed decays in the bottomonium sector, were carried out. Meanwhile, many studies of the charmonium and bottomonium productions in Υ(1S, 2S, 3S) decays were performed, to distinguish different Quantum Chromodynamics (QCD) models. Besides, exotic states and new physics were also extensively explored in Υ(1S, 2S, 3S) decays at CLEO, BaBar, and Belle. The Υ(1S, 2S, 3S) states can also be produced in pp collisions and in collisions involving heavy ions. The precision measurements of their cross sections and polarizations at the large hadron collider (LHC), especially in the CMS, ATLAS, and LHCb experiments, help to understand Υ production mechanisms in pp collisions. The observation of the sequential Υ suppression in heavy ion collisions at CMS, LHCb, and ALICE is of great importance for verifying the quark—gluon plasma predicted by QCD. In this article, we review the experimental results on Υ(1S, 2S, 3S) at e+e− colliders and the LHC, and summarize their prospects at Belle II and the LHC. [ABSTRACT FROM AUTHOR]

In this paper, the iterative learning control (ILC) technique is extended to multi-input multi-output (MIMO) systems governed by parabolic partial difference equations with time delay. Two types of ILC algorithm are presented for the system with state delay and input delay, respectively. The sufficient conditions for tracking error convergence are established under suitable assumptions. Detailed convergence analysis is given based on discrete Gronwall’s inequality and discrete Green’s formula for the systems with time-varying uncertainty coefficients. Numerical results show the effectiveness of the proposed ILC algorithms. [ABSTRACT FROM AUTHOR]

Differentiation of myoblasts is essential in the development and regeneration of skeletal muscles to form multinucleated, contractile muscle fibers. However, the process of myoblast differentiation in mammals is complicated and requires to be further investigated. In this study, we found Palmdelphin (Palmd), a cytosolic protein, promotes myoblast differentiation. Palmd is predominantly expressed in the cytosol of myoblasts and is gradually up-regulated after differentiation. Knockdown of Palmd by small interfering RNA (siRNA) in C2C12 markedly inhibits myogenic differentiation, suggesting a specific role of Palmd in the morphological changes of myoblast differentiation program. Overexpression of Palmd in C2C12 enhances myogenic differentiation. Remarkably, inhibition of Palmd results in impaired myotube formation during muscle regeneration after injury. These findings reveal a new cytosolic protein that promotes mammalian myoblast differentiation and provide new insights into the molecular regulation of muscle formation. [ABSTRACT FROM AUTHOR]