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The spontaneous carrier generation process was identified in the Y6 acceptor with moderate quantum yields and extremely low recombination in optimized blends, which result in high efficiency and morphology tolerance.

An interface modification layer plays an important role in improving the performance of organic solar cells (OSCs). The structure design or doping of electrode interlayer materials can effectively inhibit interfacial carrier recombination and improve ohmic contact between the active layer and the electrodes, which is desirable for realizing high power conversion efficiencies (PCEs). Poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) has been extensively used as a hole-transport layer (HTL) in OSCs. Here, a modification of PEDOT:PSS is proposed using sulfonated graphene (SG) as a secondary dopant for improving the surface morphology and conductivity. The incorporation of the SG-doped PEDOT:PSS as the HTLs in OSCs leads to the increased charge extraction and shows the best PCEs of 17.48% for PM6:Y6 devices and 18.56% for PM6:L8-BO devices. The significant improvement in device performance suggests that SG-PEDOT:PSS is a promising interfacial layer for efficient charge transport and extraction toward high-efficiency OSCs.

The introduction of solvent additives has become a general approach in optimizing the active layer morphology in organic photovoltaics (OPV) to achieve high power conversion efficiency. It is of general interest to understand the mechanism of how additives optimize the thin-film nanostructure formation such as crystallization kinetics and phase separation. In the current manuscript, state-of-the-art nonfullerene bulk heterojunction blends, PM6:IT-4F mixture, are used in a slot-die coating experiment. The 1,8-octanedithiol (DIO)-aided fabrication leads to a significant increase in the power conversion efficiency (PCE) from 10.11 to 12.67%. Exciton dissociation and carrier transport have also been improved, largely associated with morphology improvement. Time-resolved crystallization kinetics during PM6:IT-4F film formation under different processing conditions was studied by in situ grazing-incidence wide-angle X-ray scattering (GIWAXS), in which a detailed polymer fibril morphology formation was seen. The Johnson–Mehl–Avrami–Kolmogorov (JMAK) crystallization analysis affords insights that the addition of the DIO additive in a small amount would not only increase the nucleation rate during the nucleation and growth stage but also introduce secondary fibril crystal perfection via burst nucleation-mediated crystallization to a grain boundary-induced crystallization stage change. These observations can be of general interest to the OPV community in manipulating the printed solar cell morphology and efficiency toward the commercial application.

Defect passivation is one of the most important strategies to boost both the efficiency and stability of perovskite solar cells (PSCs). Here, nontoxic and sustainable forest-based biomaterial, betulin, is first introduced into perovskites. The experiments and calculations reveal that betulin can effectively passivate the uncoordinated lead ions in perovskites via sharing the lone pair electrons of hydroxyl group, promoting charge transport. As a result, the power conversion efficiencies of the p-i-n planar PSCs remarkably increase from 19.14% to 21.15%, with the improvement of other parameters. The hydrogen bonds of betulin lock methylamine and halogen ions along the grain boundaries and on the film surface and thus suppress ion migration, further stabilizing perovskite crystal structures. These positive effects enable the PSCs to maintain 90% of the initial efficiency after 30 days in ambient air with 60%±5% relative humidity, 75% after 300 h aging at 85 °C, and 55% after 250 h light soaking, respectively. This work opens a new pathway for using nontoxic and low-cost biomaterials from forest to make highly efficient and stable PSCs.

Device-free localization (DFL) techniques based on pyroelectric infrared (PIR) sensors have attracted much attention due to their advantages of low cost, low power consumption, and privacy protection. However, existing PIR-based DFL methods still have a practical limitation that they usually require a high deployment density in multi-person scenarios. In this article, we propose a new PIR-based DFL method which requires a significantly lower deployment density in the multi-person scenario. The proposed method is based on deep learning. Especially, instead of directly utilizing the commonly used neural network architectures, we proposed a task-specific network architecture that integrates the domain knowledge of PIR sensors to improve its localization performance. Specifically, following the idea of modular learning, we design the proposed network architecture to contain two modules for counting the number of existing persons and another is for predicting their locations, respectively. Moreover, we also design the modules for person counting and localization to contain two secondary modules for different sub-tasks. Besides, to further improve the localization performance, we also propose two data augmentation strategies that aim at enhancing the training data diversity from the aspects of the moving speed of existing persons and the influence of surrounding noise. Through the proposed method, we succeed to remarkably reduce the deployment density of the traditional PIR-based methods by about 76%, while maintaining the localization accuracy.

Summary Perovskite solar cells (PSCs) suffer from significant nonradiative recombination, limiting their power conversion efficiencies. Here, for the first time, we directly observe a complete transformation of perovskite MAPbI3 surface region energetics from p- to n-type during defect passivation caused by natural additive capsaicin, attributed to the spontaneous formation of a p-n homojunction in perovskite active layer. We demonstrate that the p-n homojunction locates at ∼100 nm below perovskite surface. The energetics transformation and defect passivation promote charge transport in bulk perovskite layer and at perovskite/PCBM interface, suppressing both defect-assisted recombination and interface carrier recombination. As a result, an efficiency of 21.88% and a fill factor of 83.81% with excellent device stability are achieved, both values are the highest records for polycrystalline MAPbI3 based p-i-n PSCs reported to date. The proposed new concept of synergetic defect passivation and energetic modification via additive provides a huge potential for further improvement of PSC performance.

Pyroelectric infrared (PIR) sensors are much promising for device-free localization (DFL) due to their advantages of lower cost, low power consumption, and privacy protection. Most PIR-based localization methods usually assume some geometric models according to the detection principle of PIR sensors, which are however not accurate or robust due to the various cases of infrared radiation from human body, especially the case of multiple persons. Recently, deep learning is utilized in the PIR-based localization method (i.e. PIRNet Yang et al.) and well handles the complex infrared radiation even in the multi-person case. However, this method requires a high training cost, and has very weak generalization ability as it assumes the PIR sensors’ deployment in the testing environment is same to the deployment in training environment. To reduce the training cost and achieve high generalization ability, in this paper, we propose a robust method DeepPIRATES, which can be directly utilized in various deployment scenarios without retraining. DeepPIRATES combines deep learning and a geometric model. Specifically, DeepPIRATES divides the localization task into two steps. The first step utilizes a neural network to estimate the azimuth changes of multiple persons to a PIR sensor. Then, DeepPIRATES utilizes the persons’ azimuth changes to infer their locations based on a geometric model. Extensive experimental results show that DeepPIRATES can achieve similar localization accuracy as PIRNet, while does not require to be retrained when the sensor deployment changes.

Non-fullerene acceptor (NFA) based organic solar cells (OSCs) are of high efficiency and low energy loss and low recombination features, which is owing to the advantage of non-fullerene acceptors. The photophysics investigation of non-fullerene solar cells, in comparing to fullerene based analogue as well as mixed acceptor ternary blends could help to understand the working mechanism of NFA functioning mechanism. We choose PBDB-T donor, the fullerene derivative PC71BM acceptor, and the non-fullerene acceptor ITIC as the model system, to construct binary and ternary solar cells, which then subject to ultrafast spectroscopy investigation. The charge transfer pathway in binary and ternary blends is revealed. And it is seen that ITIC leads to a faster exciton separation and exciton diffusion. ITIC in blends suppresses the geminate recombination and shows smaller amount of charge transfer states, which is beneficial for the device performance. And the addition of ITIC enhances the crystallinity for both donor and acceptor leads to a morphology change of forming bicontinuous crystalline networks and phase separation. In a consequence, fill factor and JSC, increase dramatically for the related OSC.

AimsTo study the clinical characteristics of 2000 patients with uveitis admitted to the ophthalmology centre of the Second Hospital of Jilin University.MethodsWe retrospectively analysed 2000 patients with uveitis who were admitted to the uveitis clinic of the Second Hospital of Jilin University from July 2010 to June 2019 and analysed data on sex, onset age, onset season, anatomical classification, visual acuity and compared the results with those of other investigation studies.ResultsAmong 2000 uveitis patients, the mean age of onset was 39.9±14.9 years. There were 946 male patients (47.3%) and 1054 female patients (52.7%). By anatomical classification, panuveitis was the most common (986 cases, 49.3%), followed by anterior uveitis (786 cases, 39.3%), posterior uveitis (119 cases, 6.0%) and intermediate uveitis (109 cases, 5.5%). Among anterior uveitis cases, ankylose spondylitis (207 cases, 26.34%), Fuchs syndrome (74 cases, 9.41%) and viral uveitis (71 cases, 9.03%) were the most common. Among panuveitis cases, Vogt-Koyanagi-Harada syndrome (372 cases, 37.73%), Behcet’s disease (142 cases, 14.40%) and sympathetic ophthalmitis (33 cases, 3.35%) were the most common. Uveitis often occurs during the autumn–winter transition period. The prevalence of anterior uveitis is highest in November, and statistical analysis shows that the incidence of uveitis has a significant correlation with the month. Panuveitis has the most significant effect on vision.ConclusionPanuveitis and anterior uveitis are the most common anatomical classifications of uveitis, which has a significant impact on vision, and their incidence is related to seasonal changes.

The success of nonfullerene acceptor (NFA) solar cells lies in their unique physical properties beyond the extended absorption and suitable energy levels. The current study investigates the morphology and photophysical behavior of PBDB-T donor blending with ITIC, 4TIC, and 6TIC acceptors. Single-crystal study shows that the π-π stacking and side-chain interaction dictate molecular assembly, which can be carried to blended films, forming a multi-length-scale morphology. Spontaneous carrier generation is seen in ITIC, 4TIC, and 6TIC neat films and their blended thin films using the PBDB-T donor, providing a new avenue of zero-energy-loss carrier formation. The molecular packing associated with specific contacts and geometry is key in influencing the photophysics, as demonstrated by the charge transfer and carrier lifetime results. The 2D layer of 6TIC facilitates the exciton-to-polaron conversion, and the largest photogenerated polaron yield is obtained. The new mechanism, together with the highly efficient blending region carrier generation, has the prospect of the fundamental advantage for NFA solar cells, from molecular assembly to thin-film morphology.

The donor/acceptor interaction in non-fullerene organic photovoltaics leads to the mixing domain that dictates the morphology and electronic structure of the blended thin film. Initiative effort is paid to understand how these domain properties affect the device performances on high-efficiency PM6:Y6 blends. Different fullerenes acceptors are used to manipulate the feature of mixing domain. It is seen that a tight packing in the mixing region is critical, which could effectively enhance the hole transfer and lead to the enlarged and narrow electron density of state (DOS). As a result, short-circuit current (J

Precise estimation of optical flow, stereo depth and camera motion are important for the real-world 3D scene understanding and visual perception. Since the three tasks are tightly coupled with the inherent 3D geometric constraints, current studies have demonstrated that the three tasks can be improved through jointly optimizing geometric loss functions of several individual networks. In this paper, we show that effective feature-level collaboration of the networks for the three respective tasks could achieve much greater performance improvement for all three tasks than only loss-level joint optimization. Specifically, we propose a single network to combine and improve the three tasks. The network extracts the features of two consecutive stereo images, and simultaneously estimates optical flow, stereo depth and camera motion. The whole network mainly contains four parts: (I) a feature-sharing encoder to extract features of input images, which can enhance features’ representation ability; (II) a pooled decoder to estimate both optical flow and stereo depth; (III) a camera pose estimation module which fuses optical flow and stereo depth information; (IV) a cost volume complement module to improve the performance of optical flow in static and occluded regions. Our method achieves state-of-the-art performance among the joint unsupervised methods, including optical flow and stereo depth estimation on KITTI 2012 and 2015 benchmarks, and camera motion estimation on KITTI VO dataset.

The chemical structure of donors and acceptors limit the power conversion efficiencies achievable with active layers of binary donor-acceptor mixtures. Here, using quaternary blends, double cascading energy level alignment in bulk heterojunction organic photovoltaic active layers are realized, enabling efficient carrier splitting and transport. Numerous avenues to optimize light absorption, carrier transport, and charge-transfer state energy levels are opened by the chemical constitution of the components. Record-breaking PCEs of 18.07% are achieved where, by electronic structure and morphology optimization, simultaneous improvements of the open-circuit voltage, short-circuit current and fill factor occur. The donor and acceptor chemical structures afford control over electronic structure and charge-transfer state energy levels, enabling manipulation of hole-transfer rates, carrier transport, and non-radiative recombination losses., Efficiency of organic solar cells is determined by the physical properties of donors and acceptors in bulk heterojunction film. The authors optimise quaternary blends to realize a double cascading energy level alignment enabling efficient carrier dissociation and transport, achieving 18% efficiency.

Double cascading energy level alignment is achieved in bulk heterojunction organic solar cells ensuring efficient carrier splitting and transport. This affords unique advantages in optimizing light absorption, exciton splitting, carrier transport, and charge transfer state energy levels in quaternary blends. Solar cell device power conversion efficiency up to 17.40%, the highest in single layered devices, was achieved. The optimization of the electronic structure and morphology resulted in a simultaneous improvement of the open circuit voltage, short circuit current and fill factor. The proper ancillary donor/acceptor material choice provides useful handles in thin film. Control of the electronic structure and charge transfer state energy level is achieved with the choice of donor and acceptor materials, allowing the manipulation of the hole-transfer rates, carrier transport, and non-radiative recombination losses. A detailed structure-property relationship that best manifests the impo

The chemical structure of donors (Ds) and acceptors (As) limit the power conversion efficiencies (PCEs) achievable with bulk heterojunction (BHJ) active layers of binary D-A mixtures. However, using quaternary D-A blends, double cascading energy level alignment in BHJ organic photovoltaic active layers are realized, enabling efficient carrier splitting and transport. Numerous avenues to optimize light absorption, carrier transport, and charge transfer state energy levels are opened by the chemical constitution of the components. Record-breaking PCEs of 18.07% are achieved where, by electronic structure and morphology optimization, simultaneous improvements of the open-circuit voltage, short-circuit current and fill factor occur. The D and A chemical structures afford control over electronic structure and charge transfer state energy levels, enabling manipulation of hole-transfer rates, carrier transport, and non-radiative recombination losses.

The rapid and continuous progress made in perovskite solar cell (PSC) technology has drawn considerable attention from the photovoltaic research community, and the application of perovskites in other electronic devices (such as photodetectors, light-emitting diodes, and batteries) has become imminent. Because of the diversity in device configurations, optimization of film deposition, and exploration of material systems, the power conversion efficiency (PCE) of PSCs has been certified to be as high as 25.2%, making this type of solar cells the fastest advancing technology until now. As demonstrated by researchers worldwide, controlling the morphology and defects in perovskite films is essential for attaining high-performance PSCs. In this regard, interface engineering has proven to be a very efficient way to address these issues, obtaining better charge collection efficiency, and reducing recombination losses. In this review, the interfacial modification between perovskite films and charge-transport layers (CTLs) as well as CTLs and electrodes of PSCs has been widely summarized. Grain boundary (GB) engineering and stress engineering are also included since they are closely related to the improvement in device performance and stability.

Generalizing certain network interdiction games communicated to us by Andrew Liu and his collaborators, this paper studies a bilevel, non-cooperative game wherein the objective function of each player’s optimization problem contains a value function of a second-level linear program parameterized by the first-level variables in a non-convex manner. In the applied network interdiction games, this parameterization is through a piecewise linear function that upper bounds the second-level decision variable. In order to give a unified treatment to the overall two-level game where the second-level problems may be minimization or maximization, we formulate it as a one-level game of a particular kind. Namely, each player’s objective function is the sum of a first-level objective function ± a value function of a second-level maximization problem whose objective function involves a difference-of-convex (dc), specifically piecewise affine, parameterization by the first-level variables. This non-convex parameterization is a major difference from the family of games with min-max objectives discussed in Facchinei et al. (Comput Optim Appl 59(1):85–112, 2014) wherein the convexity of the overall games is preserved. In contrast, the piecewise affine (dc) parameterization of the second-level objective functions to be maximized renders the players’ combined first-level objective functions non-convex and non-differentiable. We investigate the existence of a first-order stationary solution of such a game, which we call a quasi-Nash equilibrium, and study the computation of such a solution in the linear-quadratic case by Lemke’s method using a linear complementarity formulation.

Mixtures of nonfullerene acceptors (NFAs) are prepared to fine‐tune bulk heterojunction (BHJ) thin‐film morphologies. The acceptor phase resulting from these mixtures has unique physical properties with excellent optoelectronic processes that dictate the output of organic photovoltaic (OPV) devices. Remarkable short‐circuit current densities (JSC) and fill factors (FFs) are achieved due to the formation of better crystalline fibrils that suppress geminate recombination, leading to improved charge transport with enhanced crystallinity and aligned cascading energy levels confirm efficient exciton diffusion and dissociation, yielding more effective exciton recycling. The decreased Urbach energy and suppressed energetic disorder account for the improvement in the open‐circuit voltage (VOC). A maximum power conversion efficiency of 17.86% is obtained, underscoring the importance of using specific material interactions to produce a suitable morphology and manage energy loss, resulting in ideal organic solar cell (OSC) devices.

Summary Appropriate energy-level alignment in non-fullerene ternary organic solar cells (OSCs) can enhance the power conversion efficiencies (PCEs), due to the simultaneous improvement in charge generation/transportation and reduction in voltage loss. Seven machine-learning (ML) algorithms were used to build the regression and classification models based on energy-level parameters to predict PCE and capture high-performance material combinations, and random forest showed the best predictive capability. Furthermore, two sets of verification experiments were designed to compare the experimental and predicted results. The outcome elucidated that a deep lowest unoccupied molecular orbital (LUMO) of the non-fullerene acceptors can slightly reduce the open-circuit voltage (VOC) but significantly improve short-circuit current density (JSC), and, to a certain extent, the VOC could be optimized by the slightly up-shifted LUMO of the third component in non-fullerene ternary OSCs. Consequently, random forest can provide an effective global optimization scheme and capture multi-component combinations for high-efficiency ternary OSCs., Highlights • ML assists in analyzing energy-level alignment of non-fullerene ternary blends • Random forest approach provides the best predictive capability • The effective global optimization scheme in material selection is provided, The bigger picture Introducing a third component into a binary blend to fabricate the ternary organic solar cells (OSCs) is a common practice to enhance light harvest and reduce energy loss of the photoactive blends, especially the non-fullerene ternary OSCs, which showed thrilling power conversion efficiencies improvement. A proper energy-level alignment in ternary blends, promoting the device charge generation, transport, and extraction, is of importance to maximize the short-circuit current and open-circuit voltage simultaneously. The machine-learning (ML) technique is a powerful tool for processing complex data from previous research to find the underlying mechanisms. In this work, we built regression and classification models, aiming to find the relationship between molecular energy levels and device performances. The results demonstrated that random forest is an effective method to assess the energy-level alignment, providing guidelines for the design of high-performance non-fullerene ternary OSCs., We built the dataset based on non-fullerene ternary organic solar cells (OSCs), and used machine-learning (ML) technology to evaluate the energy-level alignment, predict devices performance, and capture the high-performance non-fullerene ternary combinations. Important understanding regarding the relationship between molecular energy-level alignment and device performance in non-fullerene ternary OSCs was quantified by the scale of Gini importance of random forest model, guiding an effective global optimization scheme and direction of primary efforts.

Uterine leiomyomas are common clinical gynecological tumors, which are a major health concern for many women. In the current study, we aimed to investigate the effect of paclitaxel (PTX) on uterine leiomyomas. A mouse model of uterine leiomyomas was established by estradiol benzoate, followed by treatment with increasing doses of PTX. PTX showed no dose-limiting toxicity that affected the survival of mice, and was able to restore the apoptosis level of uterus tissues of the model mice to normal levels. In this study, we discovered that PTX played a critical role in promoting apoptosis in the mouse model of uterine leiomyomas, which provides a new insight into the therapy of uterine leiomyomas.

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Benzo[a]pyrene (BaP) stimulates male reproductive toxicity. In this study, we want to examine the ameliorative potential of Lycopene (LYC) on BaP-induced testicular toxicity. Adult male Wistar rats were segregated into 5 groups: Control, LYC, BaP, BaP + LYC and BaP + PQ7. Sperm parameters, testosterone level, oxidant and antioxidant parameters were determined. MRNA and protein abundances of key genes were analyzed. Cell death and apoptosis were assessed by trypan blue exclusion and Annexin V-FITC staining assay, respectively. LYC inhibited BaP-caused decrease in sperm motility and epididymal sperm concentration, and increase in head, tail and total abnormal sperm rate. LYC inhibited BaP-caused decrease in testosterone level in serum and intratesticular fluids. LYC protected germ cells from BaP-caused oxidative stress. LYC also prevented BaP-caused germ cell death and apoptosis by inhibiting apoptotic pathway. Besides, LYC ameliorated BaP-mediated gap-junction dysfunction of sertoli cells, as shown by the inhibited sertoli cell death and apoptosis, the upregulation of Bcl2 and Cx43, the downregulation of Cleaved Caspase 3, Bax and CaM, and the decrease in Ca2+ level. LYC ameliorated BaP-caused testicular damage via inhibiting oxidative stress and apoptosis, and relieving the gap-junction dysfunction of sertoli cells.

The intrinsic electronic properties of donor (D) and acceptor (A) materials in coupling with morphological features dictate the output in organic solar cells (OSCs). New physical properties of intimate eutectic mixing are used in nonfullerene-acceptor-based D-A1 -A2 ternary blends to fine-tune the bulk heterojunction thin film morphology as well as their electronic properties. With enhanced thin film crystallinity and improved carrier transport, a significant JSC amplification is achieved due to the formation of eutectic fibrillar lamellae and reduced defects state density. Material wise, aligned cascading energy levels with much larger driving force, and suppressed recombination channels confirm efficient charge transfer and transport, enabling an improved power conversion efficiency (PCE) of 17.84%. These results reveal the importance of utilizing specific material interactions to control the crystalline habit in blended films to form a well-suited morphology in guiding superior performances, which is of high demand in the next episode of OSC fabrication toward 20% PCE.

Background Enzyme matrix metalloproteinase-9 is a member of the matrix metalloproteinase family, which is critical to normal tissue remodelling during embryogenesis and wound healing. In patients with endometriosis, increased expression and activity of matrix metalloproteinase-9 have been observed in ectopic endometrium, but the plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 in patients with endometriosis and their relation to disease severity have not been clear. The aim of the study was to investigate the concentrations of matrix metalloproteinase-9 in plasma and peritoneal fluid of patients with endometriosis. Methods A prospective case–control study was conducted in Jinan Military General Hospital between January 2010 and December 2013. Fifty patients with proven endometriosis and 26 endometriosis-free controls were enrolled in this study. Patients with endometriosis were evaluated and divided into moderate/severe endometriosis group (stage I–II, n = 26) and minimal/mild endometriosis group (stage III–IV, n = 24) according to the revised criteria of the American Society for Reproductive Medicine. Blood samples and peritoneal fluid were obtained from both patients and controls. Matrix metalloproteinase-9 was measured using enzyme-linked immunosorbent assay in plasma and peritoneal fluid. The concentration of matrix metalloproteinase-9 between different groups was compared and its correlation to disease severity was analysed. Results Plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 in patients with endometriosis were higher than that in controls. In addition, those patients with moderate/severe endometriosis had significantly higher plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 compared to those with minimal/mild endometriosis. Matrix metalloproteinase-9 concentrations in plasma and peritoneal fluid were both positively correlated with severity of endometriosis and plasma matrix metalloproteinase-9 concentrations had a positive correlation with peritoneal fluid matrix metalloproteinase-9 concentrations in patients with endometriosis. Conclusions Increased concentrations of plasma and peritoneal fluid concentrations of matrix metalloproteinase-9 appear to be associated with disease severity of endometriosis and may serve as an alternative biomarker to determine disease severity of endometriosis.