Size Uniformity of CsPbBr3 Perovskite Quantum Dots via Manganese-Doping.

The achievement of size uniformity and monodispersity in perovskite quantum dots (QDs) requires the implementation of precise temperature control and the establishment of optimal reaction conditions. Nevertheless, the accurate control of a range of reaction variables represents a considerable challenge. This study addresses the aforementioned challenge by employing manganese (Mn) doping to achieve size uniformity in CsPbBr3 perovskite QDs without the necessity for the precise control of the reaction conditions. By optimizing the Mn:Pb ratio, it is possible to successfully dope CsPbBr3 QDs with the appropriate concentrations of Mn²âº and achieve a uniform size distribution. The spectroscopic measurements on single QDs indicate that the appropriate Mn²âº concentrations can result in a narrower spectral linewidth, a longer photoluminescence (PL) lifetime, and a reduced biexciton Auger recombination rate, thus positively affecting the PL properties. This study not only simplifies the size control of perovskite QDs but also demonstrates the potential of Mn-doped CsPbBr3 QDs for narrow-linewidth light-emitting diode applications.

Functional architecture of intracellular oscillations in hippocampal dendrites.

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions, report an advancing gradient of dendritic theta phase along the basal-tuft axis, and describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find that spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.

Depth Completion with Multiple Balanced Bases and Confidence for Dense Monocular SLAM.

Dense SLAM based on monocular cameras does indeed have immense application value in the field of AR/VR, especially when it is performed on a mobile device. In this paper, we propose a novel method that integrates a light-weight depth completion network into a sparse SLAM system using a multi-basis depth representation, so that dense mapping can be performed online even on a mobile phone. Specifically, we present a specifically optimized multi-basis depth completion network, called BBC-Net, tailored to the characteristics of traditional sparse SLAM systems. BBC-Net can predict multiple balanced bases and a confidence map from a monocular image with sparse points generated by off-the-shelf keypoint-based SLAM systems. The final depth is a linear combination of predicted depth bases that can be easily optimized by tuning the corresponding weights. To seamlessly incorporate the weights into traditional SLAM optimization and ensure efficiency and robustness, we design a set of depth weight factors, which makes our network a versatile plug-in module, facilitating easy integration into various existing sparse SLAM systems and significantly enhancing global depth consistency through bundle adjustment. To verify the portability of our method, we integrate BBC-Net into two representative SLAM systems. The experimental results on various datasets show that the proposed method achieves better performance in monocular dense mapping than the state-of-the-art methods. We provide an online demo running on a mobile phone, which verifies the efficiency and mapping quality of the proposed method in real-world scenarios.

Study on the Stability of Complex Networks in the Stock Markets of Key Industries in China.

Investigating the significant "roles" within financial complex networks and their stability is of great importance for preventing financial risks. On one hand, this paper initially constructs a complex network model of the stock market based on mutual information theory and threshold methods, combined with the closing price returns of stocks. It then analyzes the basic topological characteristics of this network and examines its stability under random and targeted attacks by varying the threshold values. On the other hand, using systemic risk entropy as a metric to quantify the stability of the stock market, this paper validates the impact of the COVID-19 pandemic as a widespread, unexpected event on network stability. The research results indicate that this complex network exhibits small-world characteristics but cannot be strictly classified as a scale-free network. In this network, key roles are played by the industrial sector, media and information services, pharmaceuticals and healthcare, transportation, and utilities. Upon reducing the threshold, the network's resilience to random attacks is correspondingly strengthened. Dynamically, from 2000 to 2022, systemic risk in significant industrial share markets significantly increased. From a static perspective, the period around 2019, affected by the COVID-19 pandemic, experienced the most drastic fluctuations. Compared to the year 2000, systemic risk entropy in 2022 increased nearly sixtyfold, further indicating an increasing instability within this complex network.

Enhanced detection limit in an exceptional surface-based fiber resonator by manipulating Fano interference.

An exceptional surface (ES) has advantages in improving sensing robustness and enhancing frequency splitting. Typically, the eigenvalue splitting must exceed the mode linewidth in order to be clearly visible in the spectrum, which limits the precision of the ES-based sensing structure. In this paper, a strategy for manipulating spectral line shape in an ES-based structure is experimentally realized. In addition, the limit of the minimum detectable displacement can be further reduced by monitoring the peak intensity of the Fano interference line shape. The demonstration of Fano interference in an ES-based system opens the way for a new class of ultrasensitive optical sensors.

Multi-view fringe projection profilometry for surfaces with intricate structures and high dynamic range.

Fringe projection profilometry plays an important role for quality control in production line. However, it is facing challenges in the measurement of objects with intricate structures and high dynamic range that involved in precision manufacturing and semiconductor packaging. In this paper, a multi-view fringe projection profilometry system, which deploys a vertical telecentric projector and four oblique tilt-shift cameras, is presented to address the "blind spots" caused by shadowing, occlusion and local specular reflection. A flexible and accurate system calibration method is proposed, in which the corrected pinhole imaging model is used to calibrate the telecentric projection, and the unified calibration is performed by bundle adjustment. Experimental results show that the 3D repeated measurement error and standard deviation are no more than 10 µm within a measurable volume of 70 × 40 × 20 mm3. Furthermore, a group of experiments prove that the developed system can achieve complete and accurate 3D measurement for high dynamic range surfaces with complex structures.

Intelligent Sensing of Thermal Error of CNC Machine Tool Spindle Based on Multi-Source Information Fusion.

Aiming at the shortcomings of single-sensor sensing information characterization ability, which is easily interfered with by external environmental factors, a method of intelligent perception is proposed in this paper. This method integrates multi-source and multi-level information, including spindle temperature field, spindle thermal deformation, operating parameters, and motor current. Firstly, the internal and external thermal-error-related signals of the spindle system are collected by sensors, and the feature parameters are extracted; then, the radial basis function (RBF) neural network is utilized to realize the preliminary integration of the feature parameters because of the advantages of the RBF neural network, which offers strong multi-dimensional solid nonlinear mapping ability and generalization ability. Thermal-error decision values are then generated by a weighted fusion of different pieces of evidence by considering uncertain information from multiple sources. The spindle thermal-error sensing experiment was based on the spindle system of the VMC850 (Yunnan Machine Tool Group Co., LTD, Yunnan, China) vertical machining center of the Yunnan Machine Tool Factory. Experiments were designed for thermal-error sensing of the spindle under constant speed (2000 r/min and 4000 r/min), standard variable speed, and stepped variable speed conditions. The experiment's results show that the prediction accuracy of the intelligent-sensing model with multi-source information fusion can reach 98.1%, 99.3%, 98.6%, and 98.8% under the above working conditions, respectively. The intelligent-perception model proposed in this paper has higher accuracy and lower residual error than the traditional BP neural network perception and wavelet neural network models. The research in this paper provides a theoretical basis for the operation, maintenance management, and performance optimization of machine tool spindle systems.

Real-time passive cavitation mapping and B-mode fusion imaging via hybrid adaptive beamformer with modified diagnostic ultrasound platform.

The implementation of real-time, convenient and high-resolution passive cavitation imaging (PCM) is crucial for ensuring the safety and effectiveness of ultrasound applications related to cavitation effects. However, the current B-mode ultrasound imaging system cannot achieve these functions. By developing a hybrid adaptive beamforming algorithm, the current work presented a real-time PCM and B-mode fusion imaging technique, using a modified diagnostic ultrasound platform enabling time-division multiplexing external triggering function. The proposed hybrid adaptive beamformer combined the advantages of delay-multiply-and-sum (DMAS) and minimum variance (MV) methods to effectively suppress the side lobe and tail-like artifacts, improving the resolution of PCM images. A high-pass filter was applied to selectively detect cavitation-specific signals while removing the interference from the tissue scatters. The system enabled synchronous visualization of tissue structure and cavitation activity under ultrasound exposure. Both numerical and experimental studies demonstrated that, compared with DAS, MV-DAS and DMAS methods, the proposed MV-DMAS algorithm performed better in both axial and lateral resolutions. This work represented a significant advancement in achieving high-quality real-time B-mode and PCM fusion imaging utilizing commercial medical ultrasound system, providing a powerful tool for synchronous monitoring and manipulating cavitation activity, which would enhance the safety and efficacy of cavitation-based applications.

Enrichment and Evaluation of Antitumor Properties of Total Flavonoids from Juglans mandshurica Maxim.

Flavonoids are important secondary metabolites found in Juglans mandshurica Maxim., which is a precious reservoir of bioactive substances in China. To explore the antitumor actions of flavonoids (JMFs) from the waste branches of J. mandshurica, the following optimized purification parameters of JMFs by macroporous resins were first obtained. The loading concentration, flow rate, and loading volume of raw flavonoid extracts were 1.4 mg/mL, 2.4 BV/h, and 5 BV, respectively, and for desorption, 60% ethanol (4 BV) was selected to elute JMFs-loaded AB-8 resin at a flow rate of 2.4 BV/h. This adsorption behavior can be explained by the pseudo-second-order kinetic model and Langmuir isotherm model. Subsequently, JMFs were identified using Fourier transform infrared combined with high-performance liquid chromatography and tandem mass spectrometry, and a total of 156 flavonoids were identified. Furthermore, the inhibitory potential of JMFs on the proliferation, migration, and invasion of HepG2 cells was demonstrated. The results also show that exposure to JMFs induced apoptotic cell death, which might be associated with extrinsic and intrinsic pathways. Additionally, flow cytometry detection found that JMFs exposure triggered S phase arrest and the generation of reactive oxygen species in HepG2 cells. These findings suggest that the JMFs purified in this study represent great potential for the treatment of liver cancer.

Does technological innovation in National Sustainable Development Agenda Innovation Demonstration Zones promote green development?-the case from Chengde City, China.

The National Sustainable Development Agenda Innovation Demonstration Zones (NSDAIDZs) aim to spearhead green development through scientific and technological innovation, showcasing sustainable development to other regions in China and offering valuable insights for countries worldwide. Taking Chengde City, which is one of the cities in the second batch of NSDAIDZs, as a case study, we examine the quantitative impact of technological innovation on green development. Additionally, it investigates the threshold effect of Research and development investments (R&D investments) on the relationship between technological innovation and green development. The results indicate that: (1) technological innovation has a positive promoting effect on green development, with a 1.01% increase in green development for every one unit increase in technological innovation; (2) The positive effect of technological innovation on green development becomes fully realized only when R&D investments and the upgrading of industrial structure surpass a specific threshold value. We contribute to the existing research on the connection between technological innovation and green development in innovation demonstration zones. It also provides empirical insights to foster a mutually beneficial relationship between R&D investments, industrial structure upgrading, and technological innovation, ultimately maximizing the promoting role of technological innovation in green development.

Size-dependent photoluminescence blinking mechanisms and volume scaling of biexciton Auger recombination in single CsPbI3 perovskite quantum dots.

Determining the correlation between the size of a single quantum dot (QD) and its photoluminescence (PL) properties is a challenging task. In the study, we determine the size of each QD by measuring its absorption cross section, which allows for accurate investigation of size-dependent PL blinking mechanisms and volume scaling of the biexciton Auger recombination at the single-particle level. A significant correlation between the blinking mechanism and QD size is observed under low excitation conditions. When the QD size is smaller than their Bohr diameter, single CsPbI3 perovskite QDs tend to exhibit BC-blinking, whereas they tend to exhibit Auger-blinking when the QD size exceeds their Bohr diameter. In addition, by extracting bright-state photons from the PL intensity trajectories, the effects of QD charging and surface defects on the biexcitons are effectively reduced. This allows for a more accurate measurement of the volume scaling of biexciton Auger recombination in weakly confined CsPbI3 perovskite QDs at the single-dot level, revealing a superlinear volume scaling (τXX,Auger ∝ σ1.96).

Pediatric incarcerated inguinal hernia: Traditional open or laparoscopic-assisted approach?

The objective of this study was to compare the safety and efficacy of laparoscopic-assisted surgery and traditional open surgery for pediatric incarcerated inguinal hernia. A total of 58 pediatric patients with indirect incarcerated inguinal hernia between January 2014 and January 2020 were included in this study. The patients were divided into 2 groups; observational group who underwent laparoscopic-assisted surgery (n = 36), and a control group who underwent traditional open surgery (n = 22). The overall operation time, intraoperative blood loss, postoperative recovery time, length of hospital stay, occurrence of postoperative scrotal or vulvar hematomas, incidence of postoperative surgical site infection, and hernia recurrence were analyzed and compared between the 2 groups. Compared with the control group, the operation time (38.28 ±â€…5.90) minutes, intraoperative blood loss (1.15 ±â€…0.54 mL), postoperative recovery time (8.39 ±â€…1.42 h), and length of hospital stay (1.64 ±â€…0.59) were significantly lower in the observational group (P < .05). There was no incidence of scrotal or vulvar hematoma or surgical site infection in the observation group, which was significantly lower than that in the control group (P < .05). However, no statistically significant difference was found in the rate of postoperative hernia recurrence between the 2 groups (P > .05). In conclusion, laparoscopic-assisted surgery appears to be a safe and effective alternative approach to traditional open surgery for the treatment of pediatric incarcerated inguinal hernia. Its advantages include reduced trauma, faster recovery, shorter hospital stays, and fewer complications.

A lung disease diagnosis algorithm based on 2D spectral features of ultrasound RF signals.

Lung diseases are commonly diagnosed based on clinical pathological indications criteria and radiological imaging tools (e.g., X-rays and CT). During a pandemic like COVID-19, the use of ultrasound imaging devices has broadened for emergency examinations by taking their unique advantages such as portability, real-time detection, easy operation and no radiation. This provides a rapid, safe, and cost-effective imaging modality for screening lung diseases. However, the current pulmonary ultrasound diagnosis mainly relies on the subjective assessments of sonographers, which has high requirements for the operator's professional ability and clinical experience. In this study, we proposed an objective and quantifiable algorithm for the diagnosis of lung diseases that utilizes two-dimensional (2D) spectral features of ultrasound radiofrequency (RF) signals. The ultrasound data samples consisted of a set of RF signal frames, which were collected by professional sonographers. In each case, a region of interest of uniform size was delineated along the pleural line. The standard deviation curve of the 2D spatial spectrum was calculated and smoothed. A linear fit was applied to the high-frequency segment of the processed data curve, and the slope of the fitted line was defined as the frequency spectrum standard deviation slope (FSSDS). Based on the current data, the method exhibited a superior diagnostic sensitivity of 98% and an accuracy of 91% for the identification of lung diseases. The area under the curve obtained by the current method exceeded the results obtained that interpreted by professional sonographers, which indicated that the current method could provide strong support for the clinical ultrasound diagnosis of lung diseases.

Optimizing glutamine concentration enhances ex vivo expansion of natural killer cells through improved redox status.

Amino acids are vital components of the serum-free medium that influence the expansion and function of NK cells. This study aimed to clarify the relationship between amino acid metabolism and expansion and cytotoxicity of NK cells. Based on analyzing the mino acid metabolism of NK-92 cells and Design of Experiments (DOE), we optimized the combinations and concentrations of amino acids in NK-92 cells culture medium. The results demonstrated that NK-92 cells showed a pronounced demand for glutamine, serine, leucine, and arginine, in which glutamine played a central role. Significantly, at a glutamine concentration of 13 mM, NK-92 cells expansion reached 161.9 folds, which was significantly higher than 55.5 folds at 2.5 mM. Additionally, under higher glutamine concentrations, NK-92 cells expressed elevated levels of cytotoxic molecules, the level of cytotoxic molecules expressed by NK-92 cells was increased and the cytotoxic rate was 68.42%, significantly higher than that of 58.08% under low concentration. In view of the close relationship between glutamine metabolism and intracellular redox state, we investigated the redox status within the cells. This study demonstrated that intracellular ROS levels in higher glutamine concentrations were significantly lower than those under lower concentration cultures with decreased intracellular GSH/GSSG ratio, NADPH/NADP+ ratio, and apoptosis rate. These findings indicate that NK-92 cells exhibit improved redox status when cultured at higher glutamine concentrations. Overall, our research provides valuable insights into the development of serum-free culture medium for ex vivo expansion of NK-92 cells.

Anomalous layer-dependent photoluminescence spectra of supertwisted spiral WS2.

Twisted stacking of two-dimensional materials with broken inversion symmetry, such as spiral MoTe2 nanopyramids and supertwisted spiral WS2, emerge extremely strong second- and third-harmonic generation. Unlike well-studied nonlinear optical effects in these newly synthesized layered materials, photoluminescence (PL) spectra and exciton information involving their optoelectronic applications remain unknown. Here, we report layer- and power-dependent PL spectra of the supertwisted spiral WS2. The anomalous layer-dependent PL evolutions that PL intensity almost linearly increases with the rise of layer thickness have been determined. Furthermore, from the power-dependent spectra, we find the power exponents of the supertwisted spiral WS2 are smaller than 1, while those of the conventional multilayer WS2 are bigger than 1. These two abnormal phenomena indicate the enlarged interlayer spacing and the decoupling interlayer interaction in the supertwisted spiral WS2. These observations provide insight into PL features in the supertwisted spiral materials and may pave the way for further optoelectronic devices based on the twisted stacking materials.

Neural 3D Scene Reconstruction With Indoor Planar Priors.

This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view images. Many previous works have shown impressive reconstruction results on textured objects, but they still have difficulty in handling low-textured planar regions, which are common in indoor scenes. An approach to solving this issue is to incorporate planar constraints into the depth map estimation in multi-view stereo-based methods, but the per-view plane estimation and depth optimization lack both efficiency and multi-view consistency. In this work, we show that the planar constraints can be conveniently integrated into the recent implicit neural representation-based reconstruction methods. Specifically, we use an MLP network to represent the signed distance function as the scene geometry. Based on the Manhattan-world assumption and the Atlanta-world assumption, planar constraints are employed to regularize the geometry in floor and wall regions predicted by a 2D semantic segmentation network. To resolve the inaccurate segmentation, we encode the semantics of 3D points with another MLP and design a novel loss that jointly optimizes the scene geometry and semantics in 3D space. Experiments on ScanNet and 7-Scenes datasets show that the proposed method outperforms previous methods by a large margin on 3D reconstruction quality.

Three-dimensional quantum imaging of dynamic targets using quantum compressed sensing.

Quantum imaging based on entangled light sources exhibits enhanced background resistance compared to conventional imaging techniques in low-light conditions. However, direct imaging of dynamic targets remains challenging due to the limited count rate of entangled photons. In this paper, we propose a quantum imaging method based on quantum compressed sensing that leverages the strong correlation characteristics of entangled photons and the randomness inherent in photon pair generation and detection. This approach enables the construction of a compressed sensing system capable of directly imaging high-speed dynamic targets. The results demonstrate that our system successfully achieves imaging of a target rotating at a frequency of 10 kHz, while maintaining an impressive data compression rate of 10-6. This proposed method introduces a pioneering approach for the practical implementation of quantum imaging in real-world scenarios.

100-Phones: A Large VI-SLAM Dataset for Augmented Reality Towards Mass Deployment on Mobile Phones.

Visual-inertial SLAM (VI-SLAM) is a key technology for Augmented Reality (AR), which allows the AR device to recover its 6-DoF motion in real-time in order to render the virtual content with the corresponding pose. Nowadays, smartphones are still the mainstream devices for ordinary users to experience AR. However the current VI-SLAM methods, although performing well on high-end phones, still face robustness challenges when deployed on a larger stock of mid- and low-end phones. Existing VI-SLAM datasets use either very ideal sensors or only a limited number of devices for data collection, which cannot reflect the capability gaps that VI-SLAM methods need to solve when deployed on a large variety of phone models. This work proposes 100-Phones. the first VI-SLAM dataset covering a wide range of mainstream phones in the market. The dataset consists of 350 sequences collected by 100 different models of phones. Through analysis and experiments on the collected data, we conclude that the quality of visual-inertial data vary greatly among the mainstream phones, and the current open source VI-SLAM methods still have serious robustness issues when it comes to mass deployment on mobile phones. We release the dataset to facilitate the robustness improvement of VI-SLAM and to promote the mass popularization of AR. Project page: https://github.com/zju3dv/100-Phones.

Functional architecture of intracellular oscillations in hippocampal dendrites.

Fast electrical signaling in dendrites is central to neural computations that support adaptive behaviors. Conventional techniques lack temporal and spatial resolution and the ability to track underlying membrane potential dynamics present across the complex three-dimensional dendritic arbor in vivo. Here, we perform fast two-photon imaging of dendritic and somatic membrane potential dynamics in single pyramidal cells in the CA1 region of the mouse hippocampus during awake behavior. We study the dynamics of subthreshold membrane potential and suprathreshold dendritic events throughout the dendritic arbor in vivo by combining voltage imaging with simultaneous local field potential recording, post hoc morphological reconstruction, and a spatial navigation task. We systematically quantify the modulation of local event rates by locomotion in distinct dendritic regions and report an advancing gradient of dendritic theta phase along the basal-tuft axis, then describe a predominant hyperpolarization of the dendritic arbor during sharp-wave ripples. Finally, we find spatial tuning of dendritic representations dynamically reorganizes following place field formation. Our data reveal how the organization of electrical signaling in dendrites maps onto the anatomy of the dendritic tree across behavior, oscillatory network, and functional cell states.

Basiliximab Induction and Postoperative Steroid-free Immunosuppression With Tacrolimus in Pediatric Liver Transplantation: A Randomized Clinical Trial.

BACKGROUND: Optimizing the immunosuppressive regimen is essential to improve the long-term outcomes of pediatric liver transplant recipients. METHODS: We conducted a prospective, randomized, open-label study to compare the safety and efficacy of 2 treatment approaches during pediatric liver transplantation: tacrolimus monotherapy following basiliximab induction (the study group) and a dual regimen of tacrolimus plus steroids (the control group). A total of 150 patients were enrolled, with 75 patients allocated to each group. RESULTS: In both groups, recipients achieved graft and recipient overall survival rates exceeding 93%, with no statistically significant differences between them. However, the study group exhibited a significantly lower incidence of acute cellular rejection (ACR), delayed occurrence of ACR, and an improved ACR-free survival rate at 2 y compared with the control group. Notably, the study group also showed a significant reduction in the incidence of de novo donor-specific antibodies at 3-mo and 2-y posttransplant. Furthermore, 6 mo after the transplant, the study group demonstrated significant improvements in weight-for-age Z score and height-for-age Z score. No notable differences were observed in postoperative complications or the incidence of liver fibrosis between the 2 groups. CONCLUSIONS: Basiliximab induction combine with tacrolimus (TAC) monotherapy is a safe and effective immunosuppressive regimen to reduce the episodes of ACR without influencing the development of liver fibrosis and graft and recipient survival rate after pediatric liver transplantation.