Optimizing the Utilization of Steel Slag in Cement-Stabilized Base Layers: Insights from Freeze-Thaw and Fatigue Testing.

This paper presents a study on the mechanical properties of cement-stabilized steel-slag-based materials under freeze-thaw cycles for a highway project in Xinjiang. Using 3D scanning technology the specimen model conforming to the real steel slag shape was established. The objectives of the study are as follows: to explore the sensitivity between the macro- and micro-parameters of the specimen and to establish a non-linear regression equation; and to study the changes in mechanical properties of materials under freeze-thaw cycles, fatigue loading, and coupled freeze-thaw cycle-fatigue loading. The results show that there are three stages of compression damage of the specimen, namely, linear elasticity, peak plasticity, and post-peak decline. Maximum contact forces between cracks and particles occur mainly in the shear zone region within the specimen. The compression damage of the specimen is a mixed tensile-shear damage dominated by shear damage. When freeze-thaw cycles or fatigue loads are applied alone, the flexural strength and fatigue life of the specimens show a linear relationship of decline. The decrease in flexural modulus at low stress is divided into the following: a period of rapid decline, a relatively smooth period, and a period of fracture, with a tendency to change towards linear decay with increasing stress. In the case of freeze-thaw-fatigue coupling, the flexural modulus of the specimen decreases drastically by about 50% in the first 2 years, and then enters a period of steady decrease in flexural modulus in the 3rd-5th years.

Sleep disturbances are associated with anxiety, depression, and decreased quality of life in patients with coronary heart disease.

BACKGROUND: Studies have shown that sleep disorders are closely related to anxiety and depression, and the quality of life (QoL) of patients with sleep disorders is generally poor. AIM: To examine the occurrence of sleep disorders in people with coronary heart disease (CHD) and their relationships with QoL, depression, and anxiety. METHODS: As per the sleep condition, 240 CHD individuals were separated into two groups: non-sleep disorder group (n = 128) and sleep disorder group (n = 112). The self-rating anxiety scale (SAS), self-rating depression scale (SDS), and World Health Organization criteria for the Quality of Life Brief scale (WHOQOL-BREF) scores of the two groups were compared. Logistic regression method was used to analyze the independent risk factors of CHD patients with sleep disorders. Multivariate logistic regression analysis was employed to develop the risk prediction model. The association among the Pittsburgh Sleep Quality Index, SAS, and SDS was examined using Spearman's correlation analysis. RESULTS: The incidence of sleep disorder was 46.67% in 240 patients. The scores of SAS and SDS in the sleep disorder group were higher than those in the non-sleep disorder group, and the WHOQOL-BREF scores were lower than those in the non-sleep disorder group (P < 0.05). The risk prediction model of sleep disturbances in CHD patients was constructed using the outcomes of multivariate logistic regression analysis, P = 1/[1 + e (-2.160 + 0.989 × (female) + 0.001 × (new rural cooperative medical insurance) + 2.219 × (anxiety) + 2.157 × depression)]. The results of a Spearman's correlation study revealed that sleep quality was strongly adversely connected with the physiological field, psychological field, and social relation scores in QoL, and was considerably positively correlated with SAS and SDS (P < 0.05). CONCLUSION: A multivariate logistic regression model can better predict the occurrence of sleep disorders in CHD patients. Sleep disorders in CHD patients are significantly correlated with QoL, depression, and anxiety.

Piston Error Measurement for Segmented Telescopes Based on a Hybrid Artificial Neural Network.

To address the difficulty and complexity of detecting piston errors for segmented telescopes, this paper proposes a new piston error measurement method based on a hybrid artificial neural network. First, we use the Resnet network to learn the mapping relationship between the focal plane degradation image and signs of the piston error. Then, based on the established theoretical relationship between the modulation transfer function and the piston error, a BP neural network is used to learn the mapping relationship between the MTF and the absolute value of the piston error. After the training of the hybrid network is completed, a wide-range and high-precision detection of the piston error of the sub-mirrors can be achieved using the combined output of the two networks, where only a focal plane image of the point source with broadband illumination is used as the input. The detection range can reach the entire coherent length of the input broadband light, and the detection accuracy can reach 10 nm. The method proposed in this paper has the advantages of high detection accuracy, a wide detection range, low hardware cost, a small network scale, and low training difficulty.

Mitigating end-to-end nonlinearity in LED-based VLC transceivers via optical intensity feedback: erratum.

We present an erratum to our Letter [Opt. Lett.47, 3688 (2022)10.1364/OL.463637]. This erratum corrects subscript errors in Eq. (1), H1 and H2. These errors could confuse readers when they perform the derivation processes, but the errors do not affect our experimental results. Therefore, these corrections do not affect the results and conclusions of the original Letter.

Mitigating end-to-end nonlinearity in LED-based VLC transceivers via an optical intensity feedback.

This Letter proposes a novel, to the best of our knowledge, intensity-modulation transmitter equipped with an optical intensity feedback (OIF) loop, which mitigates the holistic nonlinearity on both sides of intensity modulation and direct detection (IM/DD) transceivers from solely the transmitter side. In contrast to the recent effort on pre-distortion, we construct a negative feedback loop bridging the optical intensity of light-emitting diodes (LEDs) toward a sensor for nonlinearity perception to suppress the nonlinearity among all physical devices. In the meantime, we propose an analytical model for the feedback loop and an implementation scheme. The experimental results demonstrate a significant linearity improvement in the total harmonic distortion (THD) and the power gain flatness. More specifically, the average THD of the bipolar junction transistor (BJT)-based OIF transceiver is -49.4 dB (0.37%) and the minimum power gain variance is 0.0005, 0.0025% of the control group. As for the transceiver using a metal-oxide-semiconductor field-effect transistor (MOSFET), its average THD is -52.42 dB (0.25%) and the minimum power gain variance can reach 0.0026. Not only that, since the method only takes advantage of the negative feedback feature and dose not rely on any particular module, it has lower complexity and better applicability.

The Shortest Duration Constrained Hidden Markov Model: Data denoise and forecast optimization on the country-product matrix for the Fitness-Complexity Algorithm.

The Economic Fitness Index describes industrial completeness and comprehensively reflects product diversification with competitiveness and product complexity in production globalization. The Fitness-Complexity Algorithm offers a scientific approach to predicting GDP and obtains fruitful results. As a recursion algorithm, the non-linear iteration processes give novel insights into product complexity and country fitness without noise data. However, the Country-Product Matrix and Revealed Comparative Advantage data have abnormal noises which contradict the relative stability of product diversity and the transformation of global production. The data noise entering the iteration algorithm, combined with positively related Fitness and Complexity, will be amplified in each recursion step. We introduce the Shortest Duration Constrained Hidden Markov Model (SDC-HMM) to denoise the Country-Product Matrix for the first time. After the country-product matrix test, the country case test, the noise estimation test and the panel regression test of national economic fitness indicators to predict GDP growth, we show that the SDC-HMM could reduce abnormal noise by about 25% and identify change points. This article provides intra-sample predictions that theoretically confirm that the SDC-HMM can improve the effectiveness of economic fitness indicators in interpreting economic growth.

Transcription Factor p53 Suppresses Tumor Growth by Prompting Pyroptosis in Non-Small-Cell Lung Cancer.

OBJECTIVE: To evaluate the effect of p53 on pyroptosis and its inhibitory role on tumor growth in non-small-cell lung cancer (NSCLC). METHODS: The correlation of p53 and pyroptosis was determined in tumor tissues of NSCLC patients. The pyroptotic level was detected in A549 cells to clarify the effect of p53 on pyroptosis. p53 overexpression A549 tumor-bearing mice were used to clarify the therapeutic target of p53 in NSCLC treatment. RESULTS: p53 expression level was positively related to pyroptosis in NSCLC tissues. In in vitro assays, p53 directly regulated pyroptosis in A549 cells. p53-specific knockdown blocked lipopolysaccharide- (LPS-) induced pyroptosis. In in vivo assays, p53 overexpression in A549 markedly decreased tumor growth and death rate by increasing the pyroptotic level. CONCLUSIONS: Upregulation of p53 prompts pyroptosis to produce anti-NSCLC effects suggesting the potential of p53 on suppressing tumor growth in NSCLC patients.

[Health Effects of PM2.5 Based on Bacterial Toxicity Test and Transcriptional Analysis in Lungs of Mice].

Although epidemiology and toxicology studies have demonstrated that exposure to ambient air particles could result in a variety of lung diseases, but the pulmonary toxicological mechanism remains obscure. In this study, the toxicity of PM2.5 particles in different concentrations was investigated by toxicological methods, including the luminescent bacteria acute toxicity test and genotoxicity performed by SOS chromogenic reaction. The results indicated that, the acute toxicity and genotoxicity were low and negative, respectively. In addition, rats were treated with PM2.5 suspension through intratracheal instillation, and the pathologic changes and expression of different genes in their lungs were carried out. We found that PM2.5 exposure resulted in fibrotic changes and inflammation in the lung with the increase in PM2.5 concentration. Pathway analysis indicated that PM2.5 can induce pulmonary toxicity through disturbing the function of ribosomal protein, fatty acids, and cholesterol metabolism, suggesting an inflammatory reaction in the lung is caused by genetic damage and is irreversible. A gene ontology analysis revealed that abnormal expression of related genes in the immune response could be the specific pathway of lung inflammation. These findings improve our understanding of the toxicological pathway and mechanism of PM2.5 exposure.

Cordycepin inhibits LPS-induced acute lung injury by inhibiting inflammation and oxidative stress.

Acute lung injury (ALI) is a common severe clinical syndrome in intensive care unit. Inflammation has been reported to play a critical role in the development of ALI. Cordycepin, an active component isolated from Cordyceps militaris, has been reported to have anti-inflammatory effects. However, the anti-inflammatory effects of cordycepin on LPS-induced ALI remain unclear. Therefore, in the present study, we assessed whether cordycepin could attenuate ALI induced by LPS. The mice were conditioned with cordycepin 1h before intranasal instillation of LPS. Lung wet/dry (W/D) ratio, MPO activity, MDA content, and inflammatory cytokines production were detected. The expression of NF-κB p65, I-κB, Nrf2, and HO-1 were detected by western blot analysis. We found that LPS significantly increased lung wet/dry (W/D) ratio, MPO activity, MDA content, and inflammatory cytokines production. However, the increases were significantly inhibited by treatment of cordycepin. LPS-induced NF-κB activation was also suppressed by cordycepin. In addition, cordycepin was found to up-regulate the expression of Nrf2 and HO-1 in a dose-dependent manner. In conclusion, our results demonstrated that cordycepin could attenuate LPS-induced ALI effectively, probably due to inhibition of inflammation and oxidative stress.

Transcriptome Profiling of the Lungs Reveals Molecular Clock Genes Expression Changes after Chronic Exposure to Ambient Air Particles.

The symptoms of asthma, breathlessness, insomnia, etc. all have relevance to pulmonary rhythmic disturbances. Epidemiology and toxicology studies have demonstrated that exposure to ambient air particles can result in pulmonary dysfunction. However, there are no data directly supporting a link between air pollution and circadian rhythm disorder. In the present study, we found that breathing highly polluted air resulted in changes of the molecular clock genes expression in lung by transcriptome profiling analyses in a rodent model. Compared to those exposed to filtered air, in both pregnant and offspring rats in the unfiltered group, key clock genes (Per1, Per2, Per3, Rev-erbα and Dbp) expression level decreased and Bmal1 expression level increased. In both rat dams and their offspring, after continuous exposure to unfiltered air, we observed significant histologic evidence for both perivascular and peribronchial inflammation, increased tissue and systemic oxidative stress in the lungs. Our results suggest that chronic exposure to particulate matter can induce alterations of clock genes expression, which could be another important pathway for explaining the feedbacks of ambient particle exposure in addition to oxidative stress and inflammation.

Electric-Field-Induced Reversible Phase Transitions in Two-Dimensional Colloidal Crystals.

Two-dimensional colloidal crystals confined within electric field traps on the surface of a dielectrophoretic cell undergo reversible phase transitions that depend on the strength of the applied AC electric field. At low field strengths, the particles adopt a two-dimensional hexagonal close-packed lattice with p6m plane group symmetry and the maximum achievable packing fraction of φ = 0.91. Higher electric field strengths induce dipoles in the particles that provoke a phase transition to structures that depend on the number of particles confined in the trap. Whereas traps containing N = 24 particles transform to a square-packed lattice with p4m symmetry and φ = 0.79 is observed, traps of the same size containing N = 23 particles can also pack in a lattice with p2 symmetry and φ = 0.66. Traps with N = 21, 22, and 25 particles exhibit a mixture of packing structures, revealing the influence of lateral compressive forces, in addition to induced dipole interactions, in stabilizing loosely packed arrangements. These observations permit construction of a phase diagram based on adjustable parameters of electric field strength (0-750 V/cm) and particle number (N = 21-25).

Patchy particle packing under electric fields.

Colloidal particles equipped with two, three, or four negatively charged patches, which endow the particles with 2-fold, 3-fold, or tetrahedral symmetries, form 1D chains, 2D layers, and 3D packings when polarized by an AC electric field. Two-patch particles, with two patches on opposite sides of the particle (2-fold symmetry) pack into the cmm plane group and 3D packings with I4mm space group symmetry, in contrast to uncharged spherical or ellipsoidal colloids that typically crystallize into a face-centered ABC layer packing. Three-patch particles (3-fold symmetry) form chains having a 21 screw axis symmetry, but these chains pair in a manner such that each individual chain has one-fold symmetry but the pair has 21 screw axis symmetry, in an arrangement that aligns the patches that would favor Coulombic interactions along the chain. Surprisingly, some chain pairs form unanticipated double-helix regions that result from mutual twisting of the chains about each other, illustrating a kind of polymorphism that may be associated with nucleation from short chain pairs. Larger 2D domains of the three-patch particles crystallize in the p6m plane group with alignment (with respect to the field) and packing densities that suggest random disorder in the domains, whereas four-patch particles form 2D domains in which close-packed rows are aligned with the field.

Illusory spirals and loops in crystal growth.

The theory of dislocation-controlled crystal growth identifies a continuous spiral step with an emergent lattice displacement on a crystal surface; a mechanistic corollary is that closely spaced, oppositely winding spirals merge to form concentric loops. In situ atomic force microscopy of step propagation on pathological L-cystine crystals did indeed show spirals and islands with step heights of one lattice displacement. We show by analysis of the rates of growth of smaller steps only one molecule high that the major morphological spirals and loops are actually consequences of the bunching of the smaller steps. The morphology of the bunched steps actually inverts the predictions of the theory: Spirals arise from pairs of dislocations, loops from single dislocations. Only through numerical simulation of the growth is it revealed how normal growth of anisotropic layers of molecules within the highly symmetrical crystals can conspire to create features in apparent violation of the classic theory.

Crystallization of micrometer-sized particles with molecular contours.

The crystallization of micrometer-sized particles with shapes mimicking those of tetrabenzoheptacene (TBH) and 1,2:5,6-dibenzanthracene (DBT), both flat polyacenes, in an electric field results in the formation of ordered 2D packings that mimic the plane group symmetries in their respective molecular crystal equivalents. Whereas the particles packed in low-density disordered arrangements under a gravitational gradient, dielectrophoresis (under an ac electric field) produced ordered high-density packings with readily identifiable plane group symmetry. The ordered colloidal assemblies were stable for hours, with the packing density decreasing slowly but with recognizable symmetry for up to 12 h for the TBH-shaped particles and up to 4 h for the DBT-shaped particles. This unexpected stability is attributed to jamming behavior associated with interlocking of the dogbone-shaped (TBH) and Z-block (DBT) particles, contrasting with the more rapid reduction of packing density and loss of hexagonal symmetry for disk-shaped particles upon removal of the electric field. The TBH-shaped and DBT-shaped particles assemble into the p2 plane group, which corresponds to the densest particle packing among the possible close-packed plane groups for these particle symmetries. The p2 symmetry observed for the TBH-shaped and DBT-shaped colloid crystal emulates the p2 symmetry of the (010) layers in their respective molecular crystals, which crystallize in monoclinic lattices. Notably, DBT-shaped particles also form ordered domains with pgg symmetry, replicating the plane group symmetry of the (100) layer in the orthorhombic polymorph of DBT. These observations illustrate that the 2D ordering of colloid particles can mimic the packing of molecules with similar shapes, demonstrating that packing can transcend length scales from the molecular to the colloidal.

Highly oriented carbon nanotube papers made of aligned carbon nanotubes.

Paper-like carbon nanotube (CNT) materials have many important applications such as in catalysts, in filtration, actuators, capacitor or battery electrodes, and so on. Up to now, the most popular way of preparing buckypapers has involved the procedures of dispersion and filtration of a suspension of CNTs. In this work, we present a simple and effective macroscopic manipulation of aligned CNT arrays called 'domino pushing' in the preparation of the aligned thick buckypapers with large areas. This simple method can efficiently ensure that most of the CNTs are well aligned tightly in the buckypaper. The initial measurements indicate that these buckypapers have better performance on thermal and electrical conductance. These buckypapers with controllable structure also have many potential applications, including supercapacitor electrodes.

Machining carbon nanotubes into uniform slices.

Shearing the carbon nanotubes (CNTs) to desired size or trimming the CNT tips conveniently is usually necessary for many applications. CNTs are normally believed possessing very high strength and toughness. In this paper we present a simple and novel method to actualize this process. In this method, aligned CNT arrays were embedded in paraffin matrix, and then the materials were carefully sliced up along the direction normal to the CNTs with a microtome. These slices consisted of vertically aligned CNTs with desired and uniform length. The experiments proved that there were enough interaction forces between the CNTs and the paraffin matrix to prevent the CNTs from being pulled out during the machining process. These sheared CNTs have shown better performance for thermal interface materials and field emission applications. This process may redound to unlocking the great potential of CNT applications.

Angular path integration by moving "hill of activity": a spiking neuron model without recurrent excitation of the head-direction system.

During spatial navigation, the head orientation of an animal is encoded internally by neural persistent activity in the head-direction (HD) system. In computational models, such a bell-shaped "hill of activity" is commonly assumed to be generated by recurrent excitation in a continuous attractor network. Recent experimental evidence, however, indicates that HD signal in rodents originates in a reciprocal loop between the lateral mammillary nucleus (LMN) and the dorsal tegmental nucleus (DTN), which is characterized by a paucity of local excitatory axonal collaterals. Moreover, when the animal turns its head to a new direction, the heading information is updated by a time integration of angular head velocity (AHV) signals; the underlying mechanism remains unresolved. To investigate these issues, we built and investigated an LMN-DTN network model that consists of three populations of noisy and spiking neurons coupled by biophysically realistic synapses. We found that a combination of uniform external excitation and recurrent cross-inhibition can give rise to direction-selective persistent activity. The model reproduces the experimentally observed three types of HD tuning curves differentially modulated by AHV and anticipatory firing activity in LMN HD cells. Time integration is assessed by using constant or sinusoidal angular velocity stimuli, as well as naturalistic AHV inputs (from rodent recordings). Furthermore, the internal representation of head direction is shown to be calibrated or reset by strong external cues. We identify microcircuit properties that determine the ability of our model network to subserve time integration function.

Robust spatial working memory through homeostatic synaptic scaling in heterogeneous cortical networks.

The concept of bell-shaped persistent neural activity represents a cornerstone of the theory for the internal representation of analog quantities, such as spatial location or head direction. Previous models, however, relied on the unrealistic assumption of network homogeneity. We investigate this issue in a network model where fine tuning of parameters is destroyed by heterogeneities in cellular and synaptic properties. Heterogeneities result in the loss of stored spatial information in a few seconds. Accurate encoding is recovered when a homeostatic mechanism scales the excitatory synapses to each cell to compensate for the heterogeneity in cellular excitability and synaptic inputs. Moreover, the more realistic model produces a wide diversity of tuning curves, as commonly observed in recordings from prefrontal neurons. We conclude that recurrent attractor networks in conjunction with appropriate homeostatic mechanisms provide a robust, biologically plausible theoretical framework for understanding the neural circuit basis of spatial working memory.