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Previous studies have reported that deletion of the transcription factor, early growth response protein 2 (EGR2), in normal C57BL/6 (B6) resulted in the development of lupus-like autoimmune disease. However, increased EGR2 expression has been noted in human and murine lupus, which challenges the notion of the autoimmune suppressive role of EGR2 in B6 mice. In this study, we derived both conditional EGR2-/-B6/lpr and EGR2-/-B6 mice to elucidate the immune and autoimmune regulatory roles of EGR2 in autoinflammation (B6/lpr) versus physiologically normal (B6) conditions. We found that conditional EGR2 deletion increased spleen weight, enhanced T cell activation and IFNγ production, and promoted germinal center B cells and LAG3+ regulatory T cells development in both B6/lpr and B6 mice. Nevertheless, EGR2 deletion also showed strikingly differential effects in these two strains on T lymphocyte subsets profile, Foxp3+ Tregs and plasma cell differentiation, anti-dsDNA autoantibodies and immunoglobulins production, and on the induction of IL-17 in in vitro activated splenocytes. Specifically, EGR2 deletion in B6/lpr mice significantly decreased serum levels of anti-dsDNA autoantibodies, total IgG, IgM, IgG1, and IgG2a with reduced plasma cells differentiation. Furthermore, EGR2 deletion in B6/lpr mice had no obvious effect on IgG immunocomplex deposition, medium caliber vessel, and glomeruli inflammation but increased complement C3 immunocomplex deposition and large caliber vessel inflammation in the kidneys. Importantly, we demonstrated that EGR2 deletion in B6/lpr mice significantly reduced pathogenic CD4-CD8-CD3+B220+ double negative T cells, which correlated with the reduced anti-dsDNA autoantibodies in serum and decreased IL-17 production in splenocytes of EGR2-/-B6/lpr mice. Together, our data strongly suggest that the role of EGR2 is complex. The immunoregulatory role of EGR2 varies at normal or autoinflammation conditions and should not be generalized in differential experimental settings.

A prediction method that integrated a mixture descriptor with an established mixture toxicology method was proposed for the joint toxicity of chemical pollutants. A weighted descriptor derived from the single descriptor of each component was employed to calculate a mixture descriptor, which was successfully embedded into the generalized concentration addition (GCA) model named the extended GCA (XGCA) model. To develop and validate the proposed approach, binary antibiotic mixtures (ciprofloxacin and oxytetracycline) and metal-oxide (copper oxide and zinc oxide) nanoparticle mixtures were selected to study their toxicity to freshwater green algae. The results showed that concentration-response curve (CRC) derived from the XGCA model was closer to the observed CRC than those from the GCA, Concentration Addition (CA), and Independent Action (IA) models. The difference between effect concentrations predicted by the XGCA model and observed did not exceed a factor of 1.6. The XGCA model was relatively more accurate at predicting joint toxicity (in terms of effect concentrations and effect errors) than the reference models, independent of component types and mixture ratios. The XGCA model predicts the joint toxicity through molecular structural or nanostructural characters, thus modes of toxic action are not preconditions for predicting the toxicity of the mixtures. This result demonstrates the practicability of using the XGCA method in toxicity assessments of mixture pollutants with unknown modes of action.

In a classical metasurface-based holographic display system, a clear holographic reconstruction image can be obtained only in the back-focal-plane of the lens. However, when the receiving plane deviates from the focal plane, the reconstructed holographic image suffers from degradations that limit the quality of the images. Hence, we propose a novel metasurface-based holographic display to realize clearly continuous imaging within the specified position range by superimposing the meta-axilens phase. It can effectively relieve the alignment requirements of the imaging system. Firstly, the parameters and properties of all-dielectric meta-atom is analyzed. Then we compare and demonstrate two sets of metasurface-based optical elements (meta-axicon, meta-lens, and meta-axilens), made by silicon meta-atoms working at 610 nm. Furthermore, we show that the metasurface hologram with the axilens phase can form a series of the relatively clear holographic images away from the focal plane. Our proposal suggests a method to reconstruct holographic wavefront in different planes simultaneously, and one can find their application domain, such as 3D biological imaging, spectroscopy, optical information storage, and encryption.

In order to accurately calculate the sunshine-induced temperature effect of an ultra-high bridge pylon, a refined numerical simulation model for the 3D bridge temperature field was established based on the proposed automatic sunshine shadow recognition method and pylon-height-related convection modification method. A suspension bridge H-shaped pylon with a height of 280 m was taken as an example, and the temperature field and corresponding thermal stress and deformation were calculated under typical meteorological conditions in spring, summer, autumn, and winter. The results show that the maximum temperature differences between the outer surfaces of the pylon can reach 19 °C and 16 °C for north–south walls and east–west walls, respectively, and exceed the recommended value of ±5 °C in the Chinese Specification. The maximum displacements can reach 370 mm and 110 mm at the top of the bridge pylon in the longitudinal and transverse directions of the bridge, respectively. After the modification of the convective coefficient of the outer surfaces with different wind speeds at different pylon heights, the temperature gradually decreased from the top to the bottom of the pylon, with a temperature difference of 8 °C. The significant influence of the sunshine shadow was shown on the temperature field and temperature effect of the bridge pylon. By considering the shadow effect, the maximum temperature difference can reach 12 °C between adjacent sunlit and shaded areas and can reach 14 °C between two pylon columns. A significant mutation of thermal stress existed in the shaded area, and the maximum stress could be reduced by 13 MPa compared with the adjacent sunlit area. Obvious asynchronous deformation was shown between two pylon columns, and the maximum asynchronous displacement at the top of the pylon can reach 18 mm and 45 mm in the longitudinal and transverse directions, respectively.

The assessment and prediction of the toxicity of engineered nanomaterials (NMs) present in mixtures is a challenging research issue. Herein, the toxicity of three advanced two-dimensional nanomaterials (TDNMs), in combination with an organic chemical (3,4-dichloroaniline, DCA) to two freshwater microalgae (Scenedesmus obliquus and Chlorella pyrenoidosa), was assessed and predicted not only from classical mixture theory but also from structure-activity relationships. The TDNMs included two layered double hydroxides (Mg-Al-LDH and Zn-Al-LDH) and a graphene nanoplatelet (GNP). The toxicity of DCA varied with the type and concentration of TDNMs, as well as the species. The combination of DCA and TDNMs exhibited additive, antagonistic, and synergistic effects. There is a linear relationship between the different levels (10, 50, and 90%) of effect concentrations and a Freundlich adsorption coefficient (KF) calculated by isotherm models and adsorption energy (Ea) obtained in molecular simulations, respectively. The prediction model incorporating both parameters KF and Ea had a higher predictive power for the combined toxicity than the classical mixture model. Our findings provide new insights for the development of strategies aimed at evaluating the ecotoxicological risk of NMs towards combined pollution situations.

The performance of classic radar geometry based on the line-of-sight (LOS) signal transmitted from radar to the target in the free space is affected by multipath echoes in urban areas, where non-line-of-sight (NLOS) signals reflected by obstacles are received by the radar. Based on prior information of the urban situation, this article proposes a novel two-stage localization algorithm with multipath exploitation in a dense clutter environment. In the offline stage, multipath propagation parameters of uniformly distributed samples in the radar field of view are predicted by the ray-tracing technique. In the online stage, a rough location of the target is estimated by the maximum similarity between measurements and the predicted parameters of reference samples at different locations. The similarity is described by the likelihood between measurements and the predicted multipath parameters with respect to all possible associated hypotheses. A gating threshold is derived to exclude less likely hypotheses and reduce the computational burden. The accurate target location is acquired by a non-linear least squares (NLS) optimization of the associated multipath components. Simulation results in various noise conditions show that the proposed method provides robust and accurate target localization results under dense clutter conditions, and the offline pre-calculation of ray-tracing ensures the real-time performance of the proposed localization algorithm. The root mean square error (RMSE) of simulation results shows the advantage of the proposed method over the existing method. The presented results suggest that the proposed method can be applied to NLOS target localization applications in complex environments.

Humans have long been fascinated by the opportunities afforded through motor augmentation provided by the supernumerary robotic fingers (SRFs) and limbs (SRLs). However, the neuroplasticity mechanism induced by the motor augmentation equipment still needs further investigation. This study focused on the resting-state brain functional reorganization during longitudinal brain–computer interface (BCI)-controlled SRF training in using the fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and degree centrality (DC) metrics. Ten right-handed subjects were enrolled for 4 weeks of BCI-controlled SRF training. The behavioral data and the neurological changes were recorded at baseline, training for 2 weeks, training for 4 weeks immediately after, and 2 weeks after the end of training. One-way repeated-measure ANOVA was used to investigate long-term motor improvement [F(2.805,25.24) = 43.94, p < 0.0001] and neurological changes. The fALFF values were significantly modulated in Cerebelum_6_R and correlated with motor function improvement (r = 0.6887, p < 0.0402) from t0 to t2. Besides, Cerebelum_9_R and Vermis_3 were also significantly modulated and showed different trends in longitudinal SRF training in using ReHo metric. At the same time, ReHo values that changed from t0 to t1 in Vermis_3 was significantly correlated with motor function improvement (r = 0.7038, p < 0.0344). We conclude that the compensation and suppression mechanism of the cerebellum existed during BCI-controlled SRF training, and this current result provided evidence to the neuroplasticity mechanism brought by the BCI-controlled motor-augmentation devices.

To improve the cross-range resolution of three-dimensional (3-D) images obtained along the direction of movement by Multiple-Input Mmultiple-Output (MIMO) radar, a novel MIMO-ISAR 3-D imaging method that combines multi-snapshot images is proposed. This method integrates multiple single-snapshot 3-D images acquired by a planar antenna array during a specific period of observation and extracts the peak slice along the linear fitting direction of the scatterers to construct a new 3-D image. The simulation results demonstrated that the proposed method significantly improves the cross-range resolution of the imaging results along the direction of movement compared with other methods based on single-snapshot 3-D images. Additionally, compared with the classical MIMO-ISAR method based on rearrangement and interpolation, this method is suitable for both fast-moving and slow-moving targets. Moreover, the imaging results are well focused and the side lobes along the direction of movement are effectively suppressed.

Abstract An optical 32QAM-OFDM-PON system with different numbers of sub-carriers using discrete multitone (DMT) modulation and demodulation is designed and demonstrated by experiment. Electron-optic generation, directly photoelectric detection, and electrical self-mixing reception of 32QAM-OFDM downstream signals are achieved. 5Gb/s 32QAM-OFDM downlink signals with different numbers of sub-carriers are successfully transmitted over 42 km SMF-28. Peak-to average power ratio (PAPR) characteristic, computational complexity and bit error rate (BER) performance are analyzed. The results show that the sub-carriers numbers of 32QAM-OFDM downlink signals should be carefully selected according to the actual requirements, if spectral efficiency, PAPR characteristic, computational complexity and receiver sensitivity are considered.

Cross-range scaling of sequential inverse synthetic aperture radar (ISAR) images is a vital problem for the three-dimensional (3D) reconstruction of spatial targets. Specifically, since the angular velocity of spatial targets cannot be accurately estimated due to their non-cooperative nature, the obtained cross-range coordinates of the scattering points often have non-negligible errors. The errors may result in a serious distortion of the reconstructed geometry of the targets, which makes consequent target recognition and classification unreliable. To tackle this problem, via geometrical analysis, the relationship between the cross-range projection vector and the range projection vector is revealed for the first time, based on which a novel algorithm is proposed to iteratively scale the cross-range coordinates with no need for estimating the angular velocity of the spatial targets. Experimental simulations show that the proposed algorithm not only provides a higher accuracy of 3D reconstruction, but also has a lower computational complexity compared with conventional algorithm.

Enantiodivergent methods, which to access both enantiomers of the same compound, are of importance in drug synthesis. Here, the authors show that by simply changing a NiBu- to a NMe-group in readily available amine organocatalysts, high stereocontrol and broad scope are achieved in eight asymmetric reactions.

Poly(I:C) is a kind of chemosynthetic double-stranded RNA (dsRNA) analogue which could act as TLR3 agonist and induce IFN production. It is widely applied in anti-virus treatment and immunoregulation, as well as vaccine adjuvant in farmed animals. However, whether poly(I:C) could activate innate immune response to defense against bacterial infection remains unclear. In this study, we established a feeding trial model with different dose of poly(I:C) in turbot larvae, then challenged with Edwardsiella piscicida after 3–7 weeks resting period. The results show that feeding turbot with poly(I:C) exhibited a stronger inflammatory response and antioxidant stress ability, and significantly elevated the survival rate within the decreased bacterial loads. Importantly, the bacterial infection-induced white feces in hindgut of turbot were significantly alleviated after poly(I:C) feeding, and this administration induced protection could last for about 7 weeks. Taken together, these findings indicate that feeding turbot with poly(I:C) could enhance a long-term intestinal mucosal immunity in response to bacterial infection, suggesting that poly(I:C) might be a promising immunostimulant in aquaculture.

Multiagent reinforcement learning holds considerable promise to deal with cooperative multiagent tasks. Unfortunately, the only global reward shared by all agents in the cooperative tasks may lead to the lazy agent problem. To cope with such a problem, we propose a generating individual intrinsic reward algorithm, which introduces an intrinsic reward encoder to generate an individual intrinsic reward for each agent and utilizes the hypernetworks as the decoder to help to estimate the individual action values of the decomposition methods based on the generated individual intrinsic reward. Experimental results in the StarCraft II micromanagement benchmark prove that the proposed algorithm can increase learning efficiency and improve policy performance.

Images captured in bad weather are not conducive to visual tasks. Rain streaks in rainy images will significantly affect the regular operation of imaging equipment; to solve this problem, using multiple neural networks is a trend. The ingenious integration of network structures allows for full use of the powerful representation and fitting abilities of deep learning to complete low-level visual tasks. In this study, we propose a generative adversarial network (GAN) with multiple attention mechanisms for image rain removal tasks. Firstly, to the best of our knowledge, we propose a pretrained vision transformer (ViT) as the discriminator in GAN for single-image rain removal for the first time. Secondly, we propose a neural network training method that can use a small amount of data for training while maintaining promising results and reliable visual quality. A large number of experiments prove the correctness and effectiveness of our method. Our proposed method achieves better results on synthetic and real image datasets than multiple state-of-the-art methods, even when using less training data.

Artificial intelligence for aircraft guidance is a hot research topic, and deep reinforcement learning is one of the promising methods. However, due to the different movement patterns of destinations in different guidance tasks, it is inefficient to train agents from scratch. In this article, a policy-reuse algorithm based on destination position prediction is proposed to solve this problem. First, the reward function is optimized to improve flight trajectory quality and training efficiency. Then, by predicting the possible termination position of the destinations in different moving patterns, the problem is transformed into a fixed-position destination aircraft guidance problem. Last, taking the agent in the fixed-position destination scenario as the baseline agent, a new guidance agent can be trained efficiently. Simulation results show that this method can significantly improve the training efficiency of agents in new tasks, and its performance is stable in tasks with different similarities. This research broadens the application scope of the policy-reuse approach and also enlightens the research in other fields.

Studying the characteristics of new particle formation (NPF) is conducive to exploring the impact of atmospheric particulate matter on the climate, environment, and human health. The particle number size distributions (5.6–560 nm) of aerosols were measured using a fast mobility particle sizer (FMPS) from 1 to 11 May 2019. The clean atmosphere was one of the basic conditions for the occurrence of this continuous new particle formation events. It started between 9:00 and 12:00, and it mainly ended after 20:00. The growth rate (GR) and condensation sink (CS) values in Hefei were 2.98 ± 0.97 nm·h−1 and (3.0 ± 0.4) × 10−2 s−1, respectively. Back trajectory clustering analysis revealed that the mass concentration of the air masses from the southeastern part of Henan Province and the southern part of Anhui Province surrounding the study area were relatively high. The analysis results of the potential source contribution function (PSCF) and the concentration weighted trajectory (CWT) methods show that in addition to local pollution, the long-distance transport of pollutants in the Yangtze River Delta (YRD) greatly contributed to the accumulation modal particulate concentration in Hefei. Moreover, the population affected by PM2.5 during the observation period reached 8.19 × 104, accounting for 1.08% to the total population in Hefei. The premature death cases associated with PM2.5 reached 8.35 × 102. This study is helpful to understand the main influencing factors of consecutive NPF events and the health risks of fine particles.

In recent years, with the rapid rise of social networks, such as Weibo and Twitter, multimodal social network rumors have also spread. Unlike traditional unimodal rumor detection, the main difficulty of multimodal rumor detection is in avoiding the generation of noise information while using the complementarity of different modal features. In this article, we propose a multimodal online social network rumor detection model based on the multilevel attention residual neural network (MARN). First, the features of text and image are extracted by Bert and ResNet-18, respectively, and the cross-attention residual mechanism is used to enhance the representation of images with a text vector. Second, the enhanced image vector and text vector are concatenated and fused by the self-attention residual mechanism. Finally, the fused image–text vectors are classified into two categories. Among them, the attention mechanism can effectively enhance the image representation and further improve the fusion effect between the image and the text, while the residual mechanism retains the unique attributes of each original modal feature while using different modal features. To assess the performance of the MARN model, we conduct experiments on the Weibo dataset, and the results show that the MARN model outperforms the state-of-the-art models in terms of accuracy and F1 value.

The coronavirus disease-19 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is rampant in the world and is a serious threat to global health. The SARS-CoV-2 RNA has been detected in various environmental media, which speeds up the pace of the virus becoming a global biological pollutant. Because many engineered nanomaterials (ENMs) are capable of inducing anti-microbial activity, ENMs provide excellent solutions to overcome the virus pandemic, for instance by application as protective coatings, biosensors, or nano-agents. To tackle some mechanistic issues related to the impact of ENMs on SARS-CoV-2, we investigated the molecular interactions between carbon nanoparticles (CNPs) and a SARS-CoV-2 RNA fragment (i.e., a model molecule of frameshift stimulation element from the SARS-CoV-2 RNA genome) using molecular mechanics simulations. The interaction affinity between the CNPs and the SARS-CoV-2 RNA fragment increased in the order of fullerenes < graphenes < carbon nanotubes. Furthermore, we developed quantitative structure–activity relationship (QSAR) models to describe the interactions of 17 different types of CNPs from three dimensions with the SARS-CoV-2 RNA fragment. The QSAR models on the interaction energies of CNPs with the SARS-CoV-2 RNA fragment show high goodness-of-fit and robustness. Molecular weight, surface area, and the sum of degrees of every carbon atom were found to be the primary structural descriptors of CNPs determining the interactions. Our research not only offers a theoretical insight into the adsorption/separation and inactivation of SARS-CoV-2, but also allows to design novel ENMs which act efficiently on the genetic material RNA of SARS-CoV-2. This contributes to minimizing the challenge of time-consuming and labor-intensive virus experiments under high risk of infection, whilst meeting our precautionary demand for options to handle any new versions of the coronavirus that might emerge in the future.

Optical solitons in ultrafast fiber lasers, as a result of dual balances between dispersion and nonlinearity as well as gain and loss, enable various soliton interactions. Soliton collisions are among the most intriguing soliton interactions, which fuel the understanding for particle-like properties of solitons. Here, we experimentally investigate the transient dynamics of collisions between a two-soliton molecule and a soliton singlet in a mode-locked fiber laser. By means of the dispersive Fourier transform technique, the evolving spectral interferograms of different collision scenarios are measured in real time. In particular, the “quasi-elastic” collision is observed, which shows that the soliton-molecule state remains unaltered after the collision and the group-velocity difference between the soliton molecule and the singlet is changed. It is directly demonstrated that a bond exchange occurs between the colliding solitons. By tuning the intra-cavity polarization controller, the dynamic processes of other collision outcomes, including the annihilation of a soliton in the soliton molecule as well as the formation of a stable unequally spaced soliton triplet, are also revealed. Our work facilitates a deeper understanding of soliton collision dynamics in ultrafast fiber lasers.

The vector nature of dissipative-soliton-resonance (DSR) pulses is numerically investigated in an all-normal-dispersion Yb-doped fiber laser mode-locked by the nonlinear polarization rotation technique. We calculate the polarization ellipses of the DSR pulse throughout the cavity, which shows that the polarization state varies during the propagation. The features of pulse polarization are also displayed on the Poincaré sphere. The impact of nonlinear birefringence on the polarization evolution is analyzed. Furthermore, we find that the polarization state is not uniform across a DSR pulse at a fixed intracavity position. The flat-top part of the pulse has a nearly fixed polarization, while its leading and trailing edges feature polarization states that vary with time. The peak power ratio of the two orthogonal polarization components in the pulse is limited in the range from 4 to 31. Our simulation results offer insight into the polarization properties of DSR pulses in mode-locked fiber lasers containing polarization discrimination devices.

Flaviviruses, represented by Zika and dengue virus (ZIKV and DENV), are widely present around the world and cause various diseases with serious consequences. However, no antiviral drugs have been clinically approved for use against them. Azelnidipine (ALP) is a dihydropyridine calcium channel blocker and has been approved for use as an antihypertensive drug. In the present study, ALP was found to show potent anti-flavivirus activities in vitro and in vivo. ALP effectively prevented the cytopathic effect induced by ZIKV and DENV and inhibited the production of viral RNA and viral protein in a dose-dependent manner. Moreover, treatment with 0.3 mg/kg of ALP protected 88.89% of mice from lethal challenge. Furthermore, using the time-of-drug-addition assay, the enzymatic inhibition assay, the molecular docking, and the surface plasmon resonance assay, we revealed that ALP acted at the replication stage of the viral infection cycle by targeting the viral RNA-dependent RNA polymerase. These findings highlight the potential for the use of ALP as an antiviral agent to combat flavivirus infections.

Enterovirus infections can cause hand, foot, and mouth disease (HFDM), aseptic meningitis, encephalitis, myocarditis, and acute flaccid myelitis, leading to death of infants and young children. However, no specific antiviral drug is currently available for the treatment of this type of infection. The Unites States and United Kingdom health authorities recently approved a new antiviral drug, molnupiravir, for the treatment of COVID-19. In this study, we reported that molnupiravir (EIDD-2801) and its active form, EIDD-1931, have broad-spectrum anti-enterovirus potential. Our data showed that EIDD-1931 could significantly reduce the production of EV-A71 progeny virus and the expression of EV-A71 viral protein at non-cytotoxic concentrations. The results of the time-of-addition assay suggest that EIDD-1931 acts at the post-entry step, which is in accordance with its antiviral mechanism. The intraperitoneal administration of EIDD-1931 and EIDD-2801 protected 1-day-old ICR suckling mice from lethal EV-A71 challenge by reducing the viral load in various tissues of the infected mice. The pharmacokinetics analysis indicated that the plasma drug concentration overwhelmed the EC50 for enteroviruses, suggesting the clinical potential of molnupiravir against enteroviruses. Thus, molnupiravir along with its active form, EIDD-1931, may be a promising drug candidate against enterovirus infections.

Deep reinforcement learning (DRL) has been widely adopted recently for its ability to solve decision-making problems that were previously out of reach due to a combination of nonlinear and high dimensionality. In the last few years, it has spread in the field of air traffic control (ATC), particularly in conflict resolution. In this work, we conduct a detailed review of existing DRL applications for conflict resolution problems. This survey offered a comprehensive review based on segments as (1) fundamentals of conflict resolution, (2) development of DRL, and (3) various applications of DRL in conflict resolution classified according to environment, model, algorithm, and evaluating indicator. Finally, an open discussion is provided that potentially raises a range of future research directions in conflict resolution using DRL. The objective of this review is to present a guidance point for future research in a more meaningful direction.

The goal of this research is to offer an effective intelligent model for forecasting college students’ career decisions in order to give a useful reference for career decisions and policy formation by relevant departments. The suggested prediction model is mainly based on a support vector machine (SVM) that has been modified using an enhanced butterfly optimization approach with a communication mechanism and Gaussian bare-bones mechanism (CBBOA). To get a better set of parameters and feature subsets, first, we added a communication mechanism to BOA to improve its global search capability and balance exploration and exploitation trends. Then, Gaussian bare-bones was added to increase the population diversity of BOA and its ability to jump out of the local optimum. The optimal SVM model (CBBOA-SVM) was then developed to predict the career decisions of college students based on the obtained parameters and feature subsets that are already optimized by CBBOA. In order to verify the effectiveness of CBBOA, we compared it with some advanced algorithms on all benchmark functions of CEC2014. Simulation results demonstrated that the performance of CBBOA is indeed more comprehensive. Meanwhile, comparisons between CBBOA-SVM and other machine learning approaches for career decision prediction were carried out, and the findings demonstrate that the provided CBBOA-SVM has better classification and more stable performance. As a result, it is plausible to conclude that the CBBOA-SVM is capable of being an effective tool for predicting college student career decisions.

To enhance the performance of guiding an aircraft to a moving destination in a certain direction in three-dimensional continuous space, it is essential to develop an efficient intelligent algorithm. In this article, a pretrained proximal policy optimization (PPO) with reward shaping algorithm, which does not require an accurate model, is proposed to solve the guidance problem of manned aircraft and unmanned aerial vehicles. Continuous action reward function and position reward function are presented, by which the training speed is increased and the performance of the generated trajectory is improved. Using pretrained PPO, a new agent can be trained efficiently for a new task. A reinforcement learning framework is built, in which an agent can be trained to generate a reference trajectory or a series of guidance instructions. General simulation results show that the proposed method can significantly improve the training efficiency and trajectory performance. The carrier-based aircraft approach simulation is carried out to prove the application value of the proposed approach.

Monitoring the consumption of pharmaceuticals and licit drugs is important for assessing the needs of public health owing to the impact on individuals as well as society. The present work applied wastewater-based epidemiology to profile the spatial patterns of metformin, nicotine, and caffeine use and their correlations. Influent wastewater samples were collected from 27 wastewater treatment plants in 22 typical Chinese cities that covered all geographic regions of the country. The consumption of metformin ranged from 0.02 g/d/1000 inh to 8.92 g/d/1000 inh, whereas caffeine and nicotine consumption ranged from 4.33 g/d/1000 inh to 394 g/d/1000 inh and 0.17 g/d/1000 inh to 1.88 g/d/1000 inh, respectively. There were significant regional differences in the consumption of caffeine, with the highest consumption in East China and the lowest consumption in Northeast China. The consumption and concentration of caffeine were related to the gross domestic product and per capita disposable income of urban residents, respectively. There was a correlation between the concentrations of caffeine and cotinine (a nicotine metabolite), thereby indicating that individuals that use one of these substances are likely to use the other substance. A significant relationship was found between the concentration of metformin and cotinine, thereby implying that the use of tobacco may be correlated with type 2 diabetes. Co-analysis of these substances in wastewater may provide a more accurate picture of substance use situations within different communities and provide more information on human health, human behavior, and the economy. This report describes the newest study related to the consumption of metformin among the general population in China.

In this study, the physiological response of the annual branches of three varieties of pitaya (Xianmi, Fulong, and Zihonglong) in cold stress was investigated using a multivariate statistical method. Physiological change results showed that cold stress could decrease the moisture and chlorophyll contents, on the contrary, increase the relative electric conductivity, the contents of malonadehyde, soluble protein, soluble sugar, and free proline, and enhance the enzyme activities of peroxidase, superoxide dismutase, and catalase. Meanwhile, a comparative proteomic approach was also conducted to clarify the cold resistance-related proteins and pathways in annual pitaya branches. Proteomics results concluded that the cold tolerance of annual pitaya branches could be improved by modulating autophagy. Therefore, we hypothesized that an increased autophagy ability may be an important characteristic of the annual pitaya branches in response to cold stress conditions. Our results provide a good understanding of the physiological responses and molecular mechanisms of the annual pitaya branches in response to cold stress.

Mild traumatic brain injury (mTBI) without skull fracturing is the most common occurrence of all TBIs and is considered as a serious public health concern. Animal models of mTBI are essential to investigation of TBI and its effects. In the current study, we developed and characterized a reproducible mouse model of mild TBI, meanwhile, the effects of this mTBI model, as well as repetitive mTBIs (rmTBIs), on the endothelial function of mouse aortas were also studied. In variety of closed-head models of mTBI, impact velocity, weight, and dwell time are the main parameters that affect the severities of injury. Here, we used a device, converting parameters of velocity, tip weight, and dwell time into impact force, to develop a mouse model of close-head mTBI. Mice were subjected to a mild TBI induced by the impact forces of 500, 600, 700 and 800 kdyn, respectively. Later, brain injuries were assessed histologically and molecularly. Systemic and brain inflammation were measured by plasma cytokine assay and glial fibrillary acidic protein (GFAP) staining. The composite neurobehavioral test revealed significant acute functional deficits in mice after mTBI, corresponding to the degree of injury. Mice brain undergoing mTBI had significant elevated GFAP staining. Plasma cytokines interleukin-1β (IL-1β) and superoxide dismutase (SOD) were significantly increased within 2 h after mTBI. Taken together, these data suggest that the mTBI mouse model introduce within our study exhibits good repeatability and comparable pathological characters. Moreover, we used this mTBI mouse model to determine the effect of single or rmTBIs on systemic vasoconstriction and relaxation. The isometric-tension results indicate that rmTBIs induce a pronounced and long-lasting endothelial dysfunction in mouse aorta.

Pitayas (Hylocereus spp.) is an attractive, highly nutritious and commercially valuable tropical fruit. However, low-temperature damage limits crop production. Genome of pitaya has not been sequenced yet. In this study, we sequenced the transcriptome of pitaya as the reference and further investigated the proteome under low temperature. By RNAseq technique, approximately 25.3 million reads were obtained, and further trimmed and assembled into 81,252 unigene sequences. The unigenes were searched against UniProt, NR and COGs at NCBI, Pfam, InterPro and Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and 57,905 unigenes were retrieved annotations. Among them, 44,337 coding sequences were predicted by Trandecoder (v2.0.1), which served as the reference database for label-free proteomic analysis study of pitaya. Here, we identified 116 Differentially Abundant Proteins (DAPs) associated with the cold stress in pitaya, of which 18 proteins were up-regulated and 98 proteins were down-regulated. KEGG analysis and other results showed that these DAPs mainly related to chloroplasts and mitochondria metabolism. In summary, chloroplasts and mitochondria metabolism-related proteins may play an important role in response to cold stress in pitayas.

Prolactinomas are the most frequently observed pituitary adenomas. Prolactinomas invasion is a key risk factor associated with operation results, and it is highly correlated with clinical prognosis. Nuclear receptor subfamily 2 group C member 2 (NR2C2) first cloned from testis is involved in the invasion and metastasis of several human tumors. In 46 patients with prolactinamas, the expression levels of CCNB1, Notch2, and NR2C2 was determined with tissue micro-array (TMA). The association between NR2C2 levels and clinical parameters was established with univariate analysis. The levels of Notch2 and CCNB1 were analyzed by RT-PCR and western blot techniques.The average methylation levels of the NR2C2 promoter were 0.505 and 0.825 in invasive prolactinomas (IPA) and non-IPA groups, respectively (p = 0.013). Univariate analysis also showed that there is a significant relationship between high NR2C2 expression and invasion (x2 = 7.043, p = 0.008), prolactin granules (x2 = 8.712, p = 0.003), and tumor size (x2 = 4.261, p = 0.039.) With the knockdown of NR2C2, cell proliferation was inhibited. Genes related to epithelial-mesenchymal transition (EMT) induced the apoptosis in MMQ cells. In addition, the level of Notch2 and CCNB1 were down-regulated with the knockdown of NR2C2. Moreover, miR-129-5p reduced mRNA levels of NR2C2, and they inhibited cell proliferation by inducing apoptosis levels of MMQ cells. Our findings proved NR2C2 played the important role in tumorigenesis tumor invasion of prolactinomas; moreover, NR2C2 is identified as a potential target.

In humans, caspase-5 is an LPS sensor that can induce gasdermin D cleavage and pyroptosis. Here, the authors show that zebrafish caspy2 is a functional homolog as it also senses cytosolic LPS to activate the noncanonical inflammasome and to protect against bacterial infection, but it does so via pyrin death domain interactions.

Constructing the mapping between the geometric object and its corresponding 3D scattering response is a fundamental but challenging task in the domain of electromagnetic scattering, which is crucial for radar target recognition and the 3D structure interpretation. In recent years, the analytic physical optics, as a typical analytic solution, has been successfully utilized to produce the parsimonious, physically relevant 3D bistatic scattering models for standard dihedral and obtuse dihedral. In this paper, the scattering mechanism of separated dihedral, as a canonical structure that often appears in the actual targets, is investigated and its corresponding bistatic 3D scattering model is derived and established by the combination of geometric optics and physical optics method. First, the single and double-bounce reflection, as well as the occlusion occurred under different incident wave angles for the separated dihedral are analyzed in detail. Consecutively, the bistatic 3D scattering responses for different reflection cases are derived by the physical optical integration. Finally, the closed-form solution to bistatic 3D scattering model of separated dihedral is presented. The experiments with the two state-of-the-art electromagnetic calculation methods, shooting and bouncing rays and method of moments, validate the effectiveness of the proposed model. Especially, the experimental results also manifest that the standard dihedral is the specific case of the proposed model.

Abstract Background Toxoplasma gondii can invade and replicate in all nucleated cells in a wide range of host species, and infection induces IL-1β production. IL-1β plays central roles in the stimulation of the innate immune system and inflammation. However, little is known of the innate immune responses in human fetal small intestinal epithelial cells (FHs 74 Int cells) after T. gondii infection. Methods FHs 74 Int cells were infected with the T. gondii GFP-RH strain. Then, IL-1β production and its mechanisms of action were evaluated using ELISA, MTT cell viability assays, Western blotting, immunofluorescence, quantitative real-time polymerase chain reaction (qRT-PCR), and gene-specific small interfering RNA (siRNA) transfection. Results Infection of FHs 74 Int cells by T. gondii triggered significant time- and dose-dependent IL-1β production. Although T. gondii activated NLRP1, NLRP3, NLRC4 and AIM2 inflammasomes in FHs 74 Int cells, NLRP3 levels were consistently and significantly time-dependently increased, while the other inflammasomes were not. Transfection with siRNA targeting NLRP3, cleaved caspase-1 (Casp-1) or ASC significantly reduced T. gondii-induced IL-1β production, whereas T. gondii proliferation was markedly increased. Toxoplasma gondii infection activated P2X7 receptor (P2X7R) levels in FHs 74 Int cells in a time-dependent manner; however, transfection with siRNA targeting P2X7R significantly reduced T. gondii-induced IL-1β secretion and substantially increased T. gondii proliferation, which is mediated by decreased protein expression levels of NLRP3, cleaved Casp-1 and ASC. Collectively, NLRP3-dependent IL-1β secretion is mediated by P2X7R in small intestinal epithelial cells in response to T. gondii infection, thereby controlling parasite proliferation. Conclusions This study revealed that the P2X7R/NLRP3 pathway plays important roles in IL-1β secretion and inhibition of T. gondii proliferation in small intestinal epithelial cells. These results not only contribute to our understanding of the mucosal immune mechanisms of T. gondii infection but also offer new insight into the identification of innate resistance in the gut epithelium.

The polarization–Raman Lidar combined sun photometer is a powerful method for separating dust and urban haze backscatter, extinction, and mass concentrations. The observation was performed in Beijing during the 2019 National Day parade, the particle depolarization ratio at 532 nm and Lidar ratio at 355 nm are 0.13 ± 0.05 and 52 ± 9 sr, respectively. It is the typical value of a mixture of dust and urban haze. Here we quantify the contributions of cross-regional transported natural dust and urban haze mass concentrations to Beijing’s air quality. There is a significant correlation between urban haze mass concentrations and surface PM2.5 (R = 0.74, p < 0.01). The contributions of local emissions to air pollution during the 2019 National Day parade were insignificant, mainly affected by regional transport, including urban haze in North China plain and Guanzhong Plain (Hebei, Tianjin, Shandong, and Shanxi), and dust aerosol in Mongolia regions and Xinjiang. Moreover, the trans-regional transmission of natural dust dominated the air pollution during the 2019 National Day parade, with a relative contribution to particulate matter mass concentrations exceeding 74% below 4 km. Our results highlight that controlling anthropogenic emissions over regional scales and focusing on the effects of natural dust is crucial and effective to improve Beijing’s air quality.

Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease that afflicts multiple organs, especially kidneys and joints. In addition to genetic predisposition, it is now evident that DNA methylation and microRNAs (miRNAs), the two major epigenetic modifications, are critically involved in the pathogenesis of SLE. DNA methylation regulates promoter accessibility and gene expression at the transcriptional level by adding a methyl group to 5′ cytosine within a CpG dinucleotide. Extensive evidence now supports the importance of DNA hypomethylation in SLE etiology. miRNAs are small, non-protein coding RNAs that play a critical role in the regulation of genome expression. Various studies have identified the signature lupus-related miRNAs and their functional contribution to lupus incidence and progression. In this review, the mutual interaction between DNA methylation and miRNAs regulation in SLE is discussed. Some lupus-associated miRNAs regulate DNA methylation status by targeting the DNA methylation enzymes or methylation pathway-related proteins. On the other hand, DNA hyper- and hypo-methylation are linked with dysregulated miRNAs expression in lupus. Further, we specifically discuss the genetic imprinting Dlk1-Dio3 miRNAs that are subjected to DNA methylation regulation and are dysregulated in several autoimmune diseases, including SLE.

Persistent heavy haze episodes have repeatedly shrouded North China in recent years. Besides anthropogenic emissions, natural dust also contributes to the aerosols in this region. Through continuous observation by a dual-wavelength Raman lidar, the primary aerosol types and their contributions to air pollution in North China were determined. The following three aerosol types can be classified: natural dust, anthropogenic aerosols, and the mixture of anthropogenic aerosols and dust (polluted dust). The classification results are basically consistent with the classification results from the cloud–aerosol lidar and infrared pathfinder satellite observations (CALIPSO) satellite measurements. The relative bias of the lidar ratio between the Raman lidar and CALIPSO is less than 25% over 90% of the cases, indicating that the CALIPSO lidar ratio selection algorithm is reasonable. The classification results show that approximately 45% of aerosols below 1.8 km are contributed by polluted dust during our one year observations. The contribution of dust increased with height, from 6% at 500 m to 28% at 1,800 m, while the contribution of anthropogenic aerosols decreased from 49% to 25%. In addition, polluted dust is the major aerosol subtype below 1.0 km in spring (over 60%) and autumn (over 70%). Anthropogenic aerosols contribute more than 75% of air pollution in summer. In winter, anthropogenic aerosols prevailed (over 80%) in the lower layer, while polluted dust (around 60%) dominated the upper layer. Our results identified the primarily aerosol types to assess the contributions of anthropogenic and natural sources to air pollution in North China, and highlight that natural dust plays a crucial role in lower-layer air pollution in spring and autumn, while controlling anthropogenic aerosols will significantly improve air quality in winter.

Abstract Nanoporous anatase TiO2 films were fabricated by a screen-printing method, and CuxO quantum dots (QDs) were deposited on the TiO2 films through successive ionic layer adsorption and reaction (SILAR). The amount of CuxO QDs on the TiO2 films are controlled by changing the number of SILAR cycles. The morphology, microstructure, optical, and photoelectrochemical properties of different CuxO sensitized TiO2 films (CuxO/TiO2) were investigated in detail. The nanoporous TiO2 film offers a large surface area for anchoring QDs. QD deposited samples exhibited a significant improvement in photoelectrochemical performance than the bare of TiO2. CuxO/TiO2, prepared with 7 SILAR cycles, showed the best photoelectrochemical properties, where the photocurrent density was enhanced to 500.01 μA/cm2 compared with 168.88 μA/cm2 of bare TiO2 under visible light. These results indicate that the designed CuxO/TiO2 structure possesses superior charge separation efficiency and photoelectrochemical properties.

It is important that bacterium can coordinately deliver several effectors into host cells to disturb the cellular progress during infection, however, the precise role of effectors in host cell cytosol remains to be resolved. In this study, we identified a new bacterial virulence effector from pathogenic Edwardsiella piscicida, which presents conserved crystal structure to thioredoxin family members and is defined as a thioredoxin-like protein (Trxlp). Unlike the classical bacterial thioredoxins, Trxlp can be translocated into host cells, mimicking endogenous thioredoxin to abrogate ASK1 homophilic interaction and phosphorylation, then suppressing the phosphorylation of downstream Erk1/2- and p38-MAPK signaling cascades. Moreover, Trxlp-mediated inhibition of ASK1-Erk/p38-MAPK axis promotes the pathogenesis of E. piscicida in zebrafish larvae infection model. Taken together, these data provide insights into the mechanism underlying the bacterial thioredoxin as a virulence effector in downmodulating the innate immune responses during E. piscicida infection.

The joint activity of multiple engineered nanoparticles (ENPs) has attracted much attention in recent years. Many previous studies have focused on the combined toxicity of different ENPs with nanostructures of the same dimension. However, the mixture toxicity of multiple ENPs with different dimensions is much less understood. Herein, we investigated the toxicity of the binary mixture of TiO2 nanospherical particles (NPs) and TiO2 nanotubes (NTs) to two freshwater algae with different morphology, namely, Scenedesmus obliquus and Chlorella pyrenoidosa. The physicochemical properties, dispersion stability, and the generation of reactive oxygen species (ROS) were determined in the single and binary systems. Classical approaches to assessing mixture toxicity were applied to evaluate and predict the toxicity of the binary mixtures. The results show that the combined toxicity of TiO2 NPs and NTs to S. obliquus was between the single toxicity of TiO2 NTs and NPs, while the combined toxicity to C. pyrenoidosa was higher than their single toxicity. Moreover, the toxicity of the binary mixtures to C. pyrenoidosa was higher than that to S. obliquus. A toxic unit assessment showed that the effects of TiO2 NPs and NTs were additive to the algae. The combined toxicity to S. obliquus and C. pyrenoidosa can be effectively predicted by the concentration addition model and the independent action model, respectively. The mechanism of the toxicity caused by the binary mixtures of TiO2 NPs and NTs may be associated with the dispersion stability of the nanoparticles in aquatic media and the ROS-induced oxidative stress effects. Our results may offer a new insight into evaluating and predicting the combined toxicological effects of ENPs with different dimensions and of probing the mechanisms involved in their joint toxicity.

Water vapor vertical profiles are important in numerical weather prediction, moisture transport, and vertical flux calculation. This study presents the Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) retrieval algorithm for water vapor vertical profiles and the retrieved results are validated with corresponding independent datasets under clear sky. The retrieved Vertical Column Densities (VCDs) and surface concentrations are validated with the Aerosol Robotic Network (AERONET) and National Climatic Data Centre (NCDC) datasets, achieving good correlation coefficients (R) of 0.922 and 0.876, respectively. The retrieved vertical profiles agree well with weekly balloon-borne radiosonde measurements. Furthermore, the retrieved water vapor concentrations at different altitudes (100–2000 m) are validated with the corresponding European Centre for Medium-range Weather Forecasts (ECMWF) ERA-interim datasets, achieving a correlation coefficient (R) varying from 0.695 to 0.857. The total error budgets for the surface concentrations and VCDs are 31% and 38%, respectively. Finally, the retrieval performance of the MAX-DOAS algorithm under different aerosol loads is evaluated. High aerosol loads obstruct the retrieval of surface concentrations and VCDs, with surface concentrations more liable to severe interference from such aerosol loads. To summarize, the feasibility of detecting water vapor profiles using MAX-DOAS under clear sky is confirmed in this work.

Carbon nanotubes have attracted increasing attention attributable to their widespread application. To evaluate the joint toxicity of multi-walled carbon nanotubes (MWCNTs) and nonylphenol (NP), we investigated the toxicological effects of NP, pristine MWCNTs, and MWCNTs combined with NP in male mice. After exposing male mice by gavage for 5 days, intracellular superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activity, as well as malondialdehyde (MDA) and glutathione (GSH) levels in tissues were determined to evaluate in vivo oxidative stress. In addition, genotoxicity was assessed by examining DNA damage in mouse liver and sperm via the comet assay, and transmission electron microscopy (TEM) was used for direct visual observations of mitochondrial damage in the liver. Results from the oxidative damage and DNA damage experiments indicate that after adsorbing NP, MWCNTs at a high dose induce oxidative lesions in the liver and cause DNA damage in mouse sperm; these data offer new insights regarding the toxicological assessment of MWCNTs.

The objectives of the current study were to isolate and identify the pathogen responsible for citrus canker and investigate the efficacy of sulfone derivatives containing 1,3,4-oxadiazole moiety on controlling citrus canker caused by Xanthomonas citri subsp. citri (Xcc) under in vitro and field conditions. In an in vitro study, we tested eight sulfone derivatives against Xcc and the results demonstrated that compound 3 exhibited the best antibacterial activity against Xcc, with a half-maximal effective concentration (EC50) value of 1.23 μg/mL, which was even better than those of commercial bactericides Kocide 3000 (58.21 μg/mL) and Thiodiazole copper (77.04 μg/mL), respectively. Meanwhile, under field experiments, compound 3 treatments demonstrated the highest ability to reduce the disease of citrus canker in leaves and fruits in two different places relative to an untreated control as well as the commercial bactericides Kocide 3000 and Thiodiazole copper. Meanwhile, compound 3 could stimulate the increase in peroxidase (POD), polyphenol oxidase (PPO), and phenylalanine ammonia lyase (PAL) activities in the navel orange leaves, causing marked enhancement of plant resistance against citrus canker. Moreover, compound 3 could damage the cell membranes, destruct the biofilm formation, inhibit the production of extracellular polysaccharide (EPS), and affect the cell membrane permeability to restrain the growth of the bacteria.

In citrus color mutants, the levels of carotenoid constituents and other secondary metabolites are different in their corresponding wild types. Terpenoids are closely related to coloration, bitterness, and flavor. In this study, terpenoid profiles and hormones in citrus fruits of two red-flesh mutants—Red Anliu orange and Red-flesh Guanxi pummelo—and their corresponding wild types were investigated using GC/MS, HPLC, and LC-MS/MS. Results showed that Red Anliu orange (high in carotenoids) and Anliu orange (low in carotenoids) accumulated low levels of limonoid aglycones but high levels of monoterpenoids; conversely, Red-flesh Guanxi pummelo (high in carotenoids) and Guanxi pummelo (deficient in carotenoids) accumulated high levels of limonoid aglycones but low levels of monoterpenoids. However, isopentenyl diphosphate was present at similar levels. A correlation analysis indicated that jasmonic and salicylic acids might play important roles in regulating terpenoid biosynthesis. Additionally, the similarities of carotenoid and volatile profiles between each mutant and its corresponding wild type were greater than those between the two mutants or the two wild types. The flux balance of terpenoid metabolism in citrus fruit tends toward stability among various citrus genera that have different terpenoid profiles. Bud mutations could influence metabolite profiles of citrus fruit to a limited extent.

Outbreaks of pine wilt disease (PWD, caused by the pinewood nematode Bursaphelenchus xylophilus), have caused mass mortality of the genus Pinus in Eurasia. Climate change may greatly influence the distribution and population dynamics of longhorn beetles of the genus Monochamus (the main vector of B. xylophilus), the survival and development of B. xylophilus, and the resistance of pines. The aim of this study was to investigate the effect of climatic variables associated with extensive PWD outbreaks in Masson pine (Pinus massoniana Lamb.) forest across the eastern part of the Three Gorges Reservoir region. Since its discovery in 2006, the most serious PWD outbreak occurred from 2014 to 2018; the most striking characteristic of this outbreak is the consistent increase in Masson pine mortality and extent of the affected areas. Moreover, 28 out of 46 PWD biological relevant climatic variables were selected and used for redundancy analysis. The ordination biplots reflect the complicated quantitative relationship between the PWD epidemic variables and the biologically relevant climatic variables of temperature, precipitation, relative humidity, and wind speed. The results will be useful for understanding the role climatic variables play in PWD outbreaks, for predicting the spread and pattern of PWD outbreaks, and for the advance preparation of management strategies with the purpose of preventing future PWD outbreaks.

Joint biomarker responses, oxidative stress and membrane systems, were determined for nano-metal-oxides (nMeO, i.e., nCeO2, nMgO, and nFe3O4) and sulfadiazine (SDZ) exposed at relevant low concentrations to two freshwater microalgae Scenedesmus obliquus and Chlorella pyrenoidosa. The impacts of dissolved organic matter (DOM) on the joint biomarker responses were also investigated. Results indicated that the presence of SDZ significantly decreased the level of intercellular reactive oxygen species (ROS) in the algal cells exposed to each nMeO. Reduction of cell membrane permeability (CMP) and mitochondrial membrane potential (MMP) in the algal cells was observed when the algae were exposed to the mixture of SDZ and the nMeO. The degree of reduction of the ROS level, CMP, and MMP significantly went down with the addition of DOM to a certain extent. Changes in cellular oxidative stress and membrane function depended on the types of both nMeO and algal species. This contribution provides an insight into the hazard assessment of a mixture consisting of emerging contaminants and DOM, as they can coexist in the aquatic environment.

Solar radiation intensity significantly influences the cooling loads of building, and the two are correlated and accorded to a certain extent. This study proposes a double effect LiBr–H2O absorption cooling system based on the parabolic trough collector (PTC) of solar heat energy. Thermodynamic models including PTC and absorption chiller are constructed, and their accuracy is verified by comparing the simulation results and the experimental data. Subsequently, the impact of variable design parameters on the thermodynamic performance is analyzed and discussed. The analysis of a solar cooling system in a hotel case study is related to its operation in a typical day, the average coefficient of performance of the absorption chiller is approximately 1.195, and the whole solar cooling system achieves 61.98% solar energy utilization efficiency. Furthermore, the performance comparison of a solar cooling system in different types of building indicates that higher matching and a higher correlation coefficient between the transient solar direct normal irradiance and cooling load is helpful in decreasing the heat loss and improving systemic performance. The solar cooling system in the office building exhibits a correlation coefficient of approximately 0.81 and achieves 69.47% systemic thermal efficiency.