An evolutionary game analysis of algorithmic indirect copyright infringement from the perspective of collusion between UGC platforms and direct infringers.

User-generated content (UGC) is developing rapidly as an emerging platform form, however, the problem of indirect copyright infringement by algorithms is becoming more and more prominent, and infringement governance has become a key act in the development of UGC platforms. When infringement occurs, recommendation algorithms expand the scope and results of infringement, while platforms choose to conspire with direct infringers for their own interests, making it difficult for infringed persons to defend their rights. In order to analyse the influence of different factors in the platform ecosystem on the subject's behavioural strategies, a "platform-infringer" evolutionary game model is constructed, and numerical simulation is used to verify the correctness of the stable results. Based on the simulation results, it is concluded that the factors of uncertain revenue, punishment and reputation loss have important influence on the decision-making behaviour of the subject of infringement governance, and accordingly, the proposed measures on the publishers, platforms and the legal level of the government are conducive to the evolution of the system to the point of positive regulation and stability of rights protection, with a view to promoting the healthier and more stable development of the UGC platforms.

Set-Membership State Estimation for Multirate Nonlinear Complex Networks Under FlexRay Protocols: A Neural-Network-Based Approach.

In this article, the set-membership state estimation problem is investigated for a class of nonlinear complex networks under the FlexRay protocols (FRPs). In order to address practical engineering requirements, the multirate sampling is taken into account which allows for different sampling periods of the system state and the measurement. On the other hand, the FRP is deployed in the communication network from sensors to estimators in order to alleviate the communication burden. The underlying nonlinearity studied in this article is of a general nature, and an approach based on neural networks is employed to handle the nonlinearity. By utilizing the convex optimization technique, sufficient conditions are established in order to restrain the estimation errors within certain ellipsoidal constraints. Then, the estimator gains and the tuning scalars of the neural network are derived by solving several optimization problems. Finally, a practical simulation is conducted to verify the validity of the developed set-membership estimation scheme.

The dynamic landscape of enhancer-derived RNA during mouse early embryo development.

Enhancer-derived RNAs (eRNAs) play critical roles in diverse biological processes by facilitating their target gene expression. However, the abundance and function of eRNAs in early embryos are not clear. Here, we present a comprehensive eRNA atlas by systematically integrating publicly available datasets of mouse early embryos. We characterize the transcriptional and regulatory network of eRNAs and show that different embryo developmental stages have distinct eRNA expression and regulatory profiles. Paternal eRNAs are activated asymmetrically during zygotic genome activation (ZGA). Moreover, we identify an eRNA, MZGAe1, which plays an important function in regulating mouse ZGA and early embryo development. MZGAe1 knockdown leads to a developmental block from 2-cell embryo to blastocyst. We create an online data portal, M2ED2, to query and visualize eRNA expression and regulation. Our study thus provides a systematic landscape of eRNA and reveals the important role of eRNAs in regulating mouse early embryo development.

Joint State and Unknown Input Estimation for a Class of Artificial Neural Networks With Sensor Resolution: An Encoding-Decoding Mechanism.

This article is concerned with the joint state and unknown input (SUI) estimation for a class of artificial neural networks (ANNs) with sensor resolution (SR) under the encoding-decoding mechanisms. The consideration of SR, which is an important specification of sensors in the real world, caters to engineering practice. Furthermore, the implementation of the encoding-decoding mechanism in the communication network aims to accommodate the limited bandwidth. The objective of this study is to propose a set-membership estimation algorithm that accurately estimates the state of the ANN without being influenced by the unknown input while accounting for the SR and the encoding-decoding mechanism. First, a sufficient condition is derived to ensure an ellipsoidal constraint on the estimation error. Then, by addressing an optimization problem, the design of the estimator gains is accomplished, and the minimal ellipsoidal constraint on the state estimation error is obtained. Finally, an example is provided to confirm the validity of the proposed joint SUI estimation scheme.

Narcolepsy and psychiatric disorders: A bidirectional Mendelian randomization study.

Since the introduction of the concept of narcolepsy, there has been a proliferation of discussions about its association with psychiatry. To elucidate the causal role of narcolepsy in the three psychiatric disorders [i.e., schizophrenia (SCZ), major depressive disorder (MDD), and attention-deficit hyperactivity disorder (ADHD)], we applied a bidirectional Mendelian randomization study using two stages (discovery stage and validation stage) and data from three different genome-wide association studies of narcolepsy. The estimates from different stages were combined using fixed-effects meta-analysis. Our findings suggest that narcolepsy is associated with an increased risk of SCZ. Conversely, MDD may be causally related to narcolepsy. A causal relationship between narcolepsy and ADHD was excluded.

Attenuating RNA Viruses with Expanded Genetic Codes to Evoke Adjustable Immune Response in PylRS-tRNACUAPyl Transgenic Mice.

Ribonucleic acid (RNA) viruses pose heavy burdens on public-health systems. Synthetic biology holds great potential for artificially controlling their replication, a strategy that could be used to attenuate infectious viruses but is still in the exploratory stage. Herein, we used the genetic-code expansion technique to convert Enterovirus 71 (EV71), a prototypical RNA virus, into a controllable EV71 strain carrying the unnatural amino acid (UAA) Nε-2-azidoethyloxycarbonyl-L-lysine (NAEK), which we termed an EV71-NAEK virus. After NAEK supplementation, EV71-NAEK could recapitulate an authentic NAEK time- and dose-dependent infection in vitro, which could serve as a novel method to manipulate virulent viruses in conventional laboratories. We further validated the prophylactic effect of EV71-NAEK in two mouse models. In susceptible parent mice, vaccination with EV71-NAEK elicited a strong immune response and protected their neonatal offspring from lethal challenges similar to that of commercial vaccines. Meanwhile, in transgenic mice harboring a PylRS-tRNACUAPyl pair, substantial elements of genetic-code expansion technology, EV71-NAEK evoked an adjustable neutralizing-antibody response in a strictly external NAEK dose-dependent manner. These findings suggested that EV71-NAEK could be the basis of a feasible immunization program for populations with different levels of immunity. Moreover, we expanded the strategy to generate controllable coxsackieviruses for conceptual verification. In combination, these results could underlie a competent strategy for attenuating viruses and priming the immune system via artificial control, which might be a promising direction for the development of amenable vaccine candidates and be broadly applied to other RNA viruses.

Association Between Omega-3 Fatty Acid Intake and Dyslipidemia: A Continuous Dose-Response Meta-Analysis of Randomized Controlled Trials.

Background Previous results provide supportive but not conclusive evidence for the use of omega-3 fatty acids to reduce blood lipids and prevent events of atherosclerotic cardiovascular disease, but the strength and shape of dose-response relationships remain elusive. Methods and Results This study included 90 randomized controlled trials, reported an overall sample size of 72 598 participants, and examined the association between omega-3 fatty acid (docosahexaenoic acid, eicosapentaenoic acid, or both) intake and blood lipid changes. Random-effects 1-stage cubic spline regression models were used to study the mean dose-response association between daily omega-3 fatty acid intake and changes in blood lipids. Nonlinear associations were found in general and in most subgroups, depicted as J-shaped dose-response curves for low-/high-density lipoprotein cholesterol. However, we found evidence of an approximately linear dose-response relationship for triglyceride and non-high-density lipoprotein cholesterol among the general population and more evidently in populations with hyperlipidemia and overweight/obesity who were given medium to high doses (>2 g/d). Conclusions This dose-response meta-analysis demonstrates that combined intake of omega-3 fatty acids near linearly lowers triglyceride and non-high-density lipoprotein cholesterol. Triglyceride-lowering effects might provide supportive evidence for omega-3 fatty acid intake to prevent cardiovascular events.

Mortality rates for mental disorders by gender in urban and rural areas in China from 2006 to 2020: An age-period-cohort analysis.

This study was to explore the trends of mortality rates for mental disorders by gender in urban and rural areas in China (2006-2020) and estimate the independent effects of age, period, and cohort on the mortality of mental disorders. This study employs data from the China Health Statistical Yearbook. The data were analysed using joinpoint regression analysis as well as age-period-cohort analysis. Results revealed the age-standardized mortality rates of mental disorders in China showed a downward trend, and women had a faster rate of decline than men over the years 2006-2020. Age, period, and birth cohort effects were statistically significant in the trend analysis of mental disorder mortality, and compared with period and cohort effects, age effects were the leading correlate of mental disorder mortality. The risk of death increased with advancing age. Our findings suggest that the mortality of mental disorders showed a downward trend, but some effective measures, especially regarding mental disorders, need to be taken to protect people with these disorders and prevent their occurrence in the setting of an ageing population.

Rational incorporation of any unnatural amino acid into proteins by machine learning on existing experimental proofs.

The unnatural amino acid (UAA) incorporation technique through genetic code expansion has been extensively used in protein engineering for the last two decades. Mutations into UAAs offer more dimensions to tune protein structures and functions. However, the huge library of optional UAAs and various circumstances of mutation sites on different proteins urge rational UAA incorporations guided by artificial intelligence. Here we collected existing experimental proofs of UAA-incorporated proteins in literature and established a database of known UAA substitution sites. By program designing and machine learning on the database, we showed that UAA incorporations into proteins are predictable by the observed evolutional, steric and physiochemical factors. Based on the predicted probability of successful UAA substitutions, we tested the model performance using literature-reported and freshly-designed experimental proofs, and demonstrated its potential in screening UAA-incorporated proteins. This work expands structure-based computational biology and virtual screening to UAA-incorporated proteins, and offers a useful tool to automate the rational design of proteins with any UAA.

Optimizing eRF1 to Enable the Genetic Encoding of Three Distinct Noncanonical Amino Acids in Mammalian Cells.

Site-specific incorporation of distinct noncanonical amino acids (ncAAs) into proteins via genetic code expansion in mammalian cells represents a new avenue for protein engineering. Reassigning three TAGs with the same ncAA in mammalian cells has previously been achieved using translational machinery. However, simultaneous recoding of three nonsense codons with distinct ncAAs in mammalian cells remains a challenge due to low incorporation efficiencies. Here, three optimized aaRS/tRNA pairs (i.e., the E. coli-derived tyrosyl (EcTyr)/tRNAUUA , E. coli-derived leucyl (EcLeu)/tRNACUA , and Methanosarcina mazei pyrrolysyl (MmPyl)/tRNAUCA pairs) are screened for ncAA incorporation. Furthermore, introduced combinations of eukaryotic release factor 1 (eRF1) mutants (E55R, E55D, N129D, and Y125F) significantly improve the encoding efficiency of the three premature stop codons' sites from 0.78% to 11.6%. Thus, site-specific incorporation of three distinct ncAAs into a single protein is achieved in this study. This work markedly expands the potential for multiple site-specific protein modifications within mammalian cells, thereby facilitating new in vivo applications.

Encoding-decoding strategy based resilient state estimation for bias-corrupted stochastic nonlinear systems.

This paper is concerned with the resilient state estimation problem for a type of stochastic nonlinear systems, in which the possible dynamical bias is considered that is depicted by a dynamical equation. In pursuit of enhancing the robustness of the propagated data, a binary encoding strategy (BES) is exploited in the binary symmetric channel (BSC). While the random bit errors caused by the channel noise may take place during the propagation of the binary bit string via the memoryless BSC. To characterize the occurrence of the bit errors, a series of Bernoulli distributed random variables is adopted. More specifically, in order to deal with the possible gain fluctuation of the estimator in the execution process, a resilient state estimator is employed. This paper intends to put forward a novel resilient estimation scheme under the BES, which can assure that the estimation error dynamics is exponentially ultimately bounded in mean square. A sufficient criterion is first acquired for the existence of the expected resilient estimator and the estimator parameter is achieved by solving a convex optimization problem. Finally, an illustrative simulation example is provided to verify the validity of the theoretical results.

Recursive State Estimation for Networked Multirate Multisensor Systems With Distributed Time-Delays Under Round-Robin Protocol.

This article is concerned with the problem of recursive state estimation for a class of multirate multisensor systems with distributed time delays under the round-robin (R-R) protocol. The state updating period of the system and the sampling period of the sensors are allowed to be different so as to reflect the engineering practice. An iterative method is presented to transform the multirate system into a single-rate one, thereby facilitating the system analysis. The R-R protocol is introduced to determine the transmission sequence of sensors with the aim to alleviate undesirable data collisions. Under the R-R protocol scheduling, only one sensor can get access to transmit its measurement at each sampling time instant. The main purpose of this article is to develop a recursive state estimation scheme such that an upper bound on the estimation error covariance is guaranteed and then locally minimized through adequately designing the estimator parameter. Finally, simulation examples are provided to show the effectiveness of the proposed estimator design scheme.

Peripheral Administration of a Cell-Penetrating MOTS-c Analogue Enhances Memory and Attenuates Aß1-42- or LPS-Induced Memory Impairment through Inhibiting Neuroinflammation.

MOTS-c is a 16-amino acid mitochondrial derivative peptide reported to be involved in regulating insulin and metabolic homeostasis via the AMP activated protein kinase (AMPK). AMPK agonist AICAR has been reported to improve cognition. Previous reports also pointed out that MOTS-c may be effective as a therapeutic option toward the prevention of the aging processes. Therefore, we investigated the roles of MOTS-c in the memory recognition process. The results showed that central MOTS-c not only enhanced object and location recognition memory formation and consolidation but also ameliorated the memory deficit induced by Aß1-42 or LPS. The memory-ameliorating effects of MOTS-c could be blocked by AMPK inhibitor dorsomorphin. Moreover, MOTS-c treatment significantly increased the phosphorylation of AMPK but not ERK, JNK, and p38 in the hippocampus. The underlying mechanism of MOTS-c neuroprotection may involve inhibiting the activation of astrocytes and microglia and production of proinflammatory cytokines. In addition, we found that peripheral administration of MOTS-c does not cross the blood-brain barrier (BBB) and plays an effect. In order to improve the brain intake of MOTS-c, we screen out (PRR)5, a cell penetrating peptides, as a carrier for MOTS-c into the brain. Then in the NOR task, intranasal or intravenous MP (cell-penetrating MOTS-c analogue) showed good memory performance on memory formation, memory consolidation, and memory impairment. Near-infrared fluorescent experiments showed the real-time biodistribution in brain after intranasal or intravenous infusion of MP. These results suggested that MOTS-c might be a new potential target for treatment of cognitive decline in AD.

Event-Triggering State and Fault Estimation for a Class of Nonlinear Systems Subject to Sensor Saturations.

This paper is concerned with the state and fault estimation issue for nonlinear systems with sensor saturations and fault signals. For the sake of avoiding the communication burden, an event-triggering protocol is utilized to govern the transmission frequency of the measurements from the sensor to its corresponding recursive estimator. Under the event-triggering mechanism (ETM), the current transmission is released only when the relative error of measurements is bigger than a prescribed threshold. The objective of this paper is to design an event-triggering recursive state and fault estimator such that the estimation error covariances for the state and fault are both guaranteed with upper bounds and subsequently derive the gain matrices minimizing such upper bounds, relying on the solutions to a set of difference equations. Finally, two experimental examples are given to validate the effectiveness of the designed algorithm.

Outlier-Resistant Recursive Filtering for Multisensor Multirate Networked Systems Under Weighted Try-Once-Discard Protocol.

In this article, a new outlier-resistant recursive filtering problem (RF) is studied for a class of multisensor multirate networked systems under the weighted try-once-discard (WTOD) protocol. The sensors are sampled with a period that is different from the state updating period of the system. In order to lighten the communication burden and alleviate the network congestions, the WTOD protocol is implemented in the sensor-to-filter channel to schedule the order of the data transmission of the sensors. In the case of the measurement outliers, a saturation function is employed in the filter structure to constrain the innovations contaminated by the measurement outliers, thereby maintaining satisfactory filtering performance. By resorting to the solution to a matrix difference equation, an upper bound is first obtained on the covariance of the filtering error, and the gain matrix of the filter is then characterized to minimize the derived upper bound. Furthermore, the exponential boundedness of the filtering error dynamics is analyzed in the mean square sense. Finally, the usefulness of the proposed outlier-resistant RF scheme is verified by simulation examples.

Visible-Light-Promoted C(sp3 )-H Alkylation by Intermolecular Charge Transfer: Preparation of Unnatural α-Amino Acids and Late-Stage Modification of Peptides.

Disclosed herein is the visible-light-promoted deaminative C(sp3 )-H alkylation of glycine and peptides using Katritzky salts as electrophiles. Simple reaction conditions and excellent functional-group tolerance provide a general strategy for the efficient preparation of unnatural α-amino acids and precise modification of peptides with unnatural α-amino-acid residues. Mechanistic studies suggest that visible-light-promoted intermolecular charge transfer within a glycine-Katritzky salt electron donor-acceptor (EDA) complex induces a single-electron transfer process without the assistance of photocatalyst.

l2-l∞ state estimation for delayed artificial neural networks under high-rate communication channels with Round-Robin protocol.

In this paper, the l2-l∞ state estimation problem is addressed for a class of delayed artificial neural networks under high-rate communication channels with Round-Robin (RR) protocol. To estimate the state of the artificial neural networks, numerous sensors are deployed to measure the artificial neural networks. The sensors communicate with the remote state estimator through a shared high-rate communication channel. In the high-rate communication channel, the RR protocol is utilized to schedule the transmission sequence of the numerous sensors. The aim of this paper is to design an estimator such that, under the high-rate communication channel and the RR protocol, the exponential stability of the estimation error dynamics as well as the l2-l∞ performance constraint are ensured. First, sufficient conditions are given which guarantee the existence of the desired l2-l∞ state estimator. Then, the estimator gains are obtained by solving two sets of matrix inequalities. Finally, numerical examples are provided to verify the effectiveness of the developed l2-l∞ state estimation scheme.

The mesoscopic collective motion of self-propelling active particle suspension confined in two-dimensional micro-channel.

The mesoscopic collective motion of self-propelling active particle suspension confined in high aspect ratio two-dimensional micro-channel is numerically studied through coupled [Formula: see text] equation by considering background thermal fluctuation, inter-particle interaction, self-propulsion and micro-channel confinement. Both the self-propulsion and micro-channel confinement are the factors driving the system away from equilibrium and sustaining heterogeneous motion. In such system, the propulsion induced particle accumulation around the channel walls is a universal phenomenon with spatial heterogeneity, where large fraction of particles are caged inside the accumulated cluster with local oscillation coexisting with few fast propelling particles in the center region. Although the formation mechanism of the induced accumulation is well studied, post the cluster formation, how the cluster evolves and its dynamical properties is rarely discussed. Based on the merits of [Formula: see text] equation, the dynamical evolution of induced accumulation is revealed by particle trajectories. It is found that the induced accumulation can be dissociated through the slow re-orientation process of few jammed particles. By using the idea of force chain network, how the transverse confinement couples the transverse displacement with the longitudinal displacement is evidenced. It is further verified by the statistical measurement of correlation probability between transverse and longitudinal displacements. The suppressed displacements in both directions is the origin leading to the slow dynamics of cluster evolution. Temporally, within the orientational relaxation time, this system exhibits non-trivial anomalous diffusion under the competition between the counter effects of self-propulsion (enhanced diffusion) and micro-channel confinement (suppressed diffusion). Additionally, by considering the orientational coupling, the deep hysteresis of accumulation has been found even for very weak orientational coupling strength.

[Variation of atmospheric pollutants in Qinhuangdao City].

To illuminate the air pollution situation of the tourist city of Qinhuangdao, the atmospheric pollutants were measured from autumn 2009 to summer 2010. The results showed that the mean average concentration of NO, NO2, SO2, O3 and PM10 during the observation period reached (18 +/- 18), (45 +/- 18), (42 +/- 46), (44 +/- 25) and (128 +/- 77) microg x m(-3), respectively. The particulate matter pollution was serious, and the rate of the annual mean value exceeded the National Ambient Air Quality Standard II by 28%. The average daily concentration and average max hourly O3 concentration were (64 +/- 21)microg x m(-3) and (126 +/- 42) microg x m(-3) in summer, and the air masses from the southern ocean aggravated the O3 pollution. The concentrations of NO(x) SO2 and PM10 in the heating period were 1.5, 4.9 and 1.5 times more than those in the period without heating and the daily average concentration of SO2 and PM10 exceeded the National Ambient Air Quality Standard II by 53% and 11% in the heating period, respectively. The superimposition effect of regional transport in the Beijing-Tianjin-Hebei region and industrial area surrounding the Bohai Bay and local harbor emission led to an increase of 17% (NO(x)), 27% (SO2) and 12% (PM10), resulting in average concentrations of up to (100 +/- 49), (110 +/- 84) and (215 +/- 108) microg x m(-3) in winter. The winds from northern inland and southern ocean can effectively remove the air pollutants.