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The original intensity value recorded by terrestrial laser scanners is influenced by multiple variables, among which incidence angle and distance play a crucial and dominant role. Further studies on incidence angle and distance effects are required to improve the accuracy of currently available methods and to implement these methods in practical applications. In this study, the effects of incidence angle and distance on intensity data of the Faro Focus3D 120 terrestrial laser scanner are investigated. A new method is proposed to eliminate the incidence angle and distance effects. The proposed method is based on the linear interpolation of the intensity values of reference targets previously scanned at various incidence angles and distances. Compared with existing methods, a significant advantage of the proposed method is that estimating the specific function forms of incidence angle versus intensity and distance versus intensity is no longer necessary; these are canceled out when the scanned and reference targets are measured at the same incidence angle and distance. Results imply that the proposed method has high accuracy and simplicity in eliminating incidence angle and distance effects and can significantly reduce the intensity variations caused by these effects on homogeneous surfaces.

People tend to be more prosocial after synchronizing behaviors with others, yet the underlying neural mechanisms are rarely known. In this study, participant dyads performed either a coordination task or an independence task, with their brain activations recorded via the functional near-infrared spectroscopy hyperscanning technique. Participant dyads in the coordination group showed higher synchronized behaviors and greater subsequent inclination to help each other than those in the independence group, indicating the prosocial effect of interpersonal synchrony. Importantly, the coordination group demonstrated the significant task-related brain coherence, namely the interbrain synchronization, at the left middle frontal area. The detected interbrain synchronization was sensitive to shared intentionality between participants and was correlated with the mutual prosocial inclination. Further, the task-related brain coherence played a mediation role in the prosocial effect of interpersonal synchrony. This study reveals the relevance of brain-to-brain synchronization among individuals with subsequent mutual prosocial inclination and suggests the neural mechanism associating with shared cognition for the facilitation of interpersonal synchrony on prosociality.

Pseudo-spin and valley degrees of freedom engineered in photonic analogues of topological insulators provide potential approaches to optical encoding and robust signal transport. Here we observe a ballistic edge state whose spin–valley indices are locked to the direction of propagation along the interface between a valley photonic crystal and a metacrystal emulating the quantum spin–Hall effect. We demonstrate the inhibition of inter-valley scattering at a Y-junction formed at the interfaces between photonic topological insulators carrying different spin–valley Chern numbers. These results open up the possibility of using the valley degree of freedom to control the flow of optical signals in 2D structures. Valleys in the photonic band structure provide an additional degree of freedom to engineer topological photonic structures and devices. Here, Kang et al. demonstrate that inter-valley scattering is inhibited at a Y-junction between three sections with different valley topology.

Fair distribution of resources matters to both individual interests and group harmony during social cooperation. Different allocation rules, including equity- and equality-based rules, have been widely discussed in reward allocation research; however, it remains unclear whether and how individuals’ cooperative manner, such as interpersonal coordination, influence their subsequent responsibility attribution and reward allocation. Here, 46 dyads conducted a time estimation task—either synergistically (the coordination group) or solely (the control group)—while their brain activities were measured using a functional near-infrared spectroscopy hyperscanning approach. Dyads in the coordination group showed higher behavioral synchrony and higher interpersonal brain synchronization (IBS) in the dorsal lateral prefrontal cortex (DLPFC) during the time estimation task than those in the control group. They also showed a more egalitarian tendency of responsibility attribution for the task outcome. More importantly, dyads in the coordination group who had higher IBS in the dorsal medial prefrontal cortex (DMPFC) were more inclined to make egalitarian reward allocations, and this effect was mediated by responsibility attribution. Our findings elucidate the influence of interpersonal coordination on reward allocation and the critical role of the prefrontal cortex in these processes.

Point cloud classification is an essential requirement for effectively utilizing point cloud data acquired by Terrestrial laser scanning (TLS). Neighborhood selection, feature selection and extraction, and classification of points based on the respective features constitute the commonly used workflow of point cloud classification. Feature selection and extraction has been the focus of many studies, and the choice of different features has had a great impact on classification results. In previous studies, geometric features were widely used for TLS point cloud classification, and only a few studies investigated the potential of both intensity and color on classification using TLS point cloud. In this paper, the geometric features, color features, and intensity features were extracted based on a supervoxel neighborhood. In addition, the original intensity was also corrected for range effect, which is why the corrected intensity features were also extracted. The different combinations of these features were tested on four real-world data sets. Experimental results demonstrate that both color and intensity features can complement the geometric features to help improve the classification results. Furthermore, the combination of geometric features, color features, and corrected intensity features together achieves the highest accuracy in our test.

•In interactive decision-making, novices benefited from equal or novice-favoring reward distribution, unlike expert-favoring allocations.•The dyads tended to compromise mutually and exhibited decreased inter-brain synchronization, suggesting a shared strategy when novices benefited. Equality is often considered fundamental for effective social interaction, while inequality seems to be counterproductive. Although interaction benefits under equal sharing are well-documented, how unequal reward allocation shapes such benefits and their neural basis remains unclear. This study examined dyads consisting of one “expert” and one “novice” (classified based on individual performance in baseline task) performing a joint dot-location estimation task during simultaneous functional near-infrared spectroscopy (fNIRS) hyperscanning. Three reward conditions were tested: equal reward distribution (ED), unequal distribution-expert advantage (EA), and unequal distribution-novice advantage (NA). Behaviorally, novices benefited from interaction in the ED and NA conditions, but not in EA, while experts showed no gains across conditions. Moreover, dyads compromised more under ED and NA, indicating reflecting greater mutual influence and cooperation. Neurally, inter-brain synchronization (IBS) was highest in EA between experts’ frontal pole (FP) and novices’ right temporoparietal junction (rTPJ) and dorsolateral prefrontal cortex (DLPFC). In contrast, both EA and NA elicited greater IBS than ED in fronto-executive pathways (expert-novice: FP–DLPFC, DLPFC–DLPFC), with NA in particular supporting novice benefit through enhanced coordination. Notably, IBS was lowest in the ED condition, despite behavioral benefits, suggesting that equal allocation may foster more streamlined or efficient neural collaboration. These findings indicate that unequal reward allocation modulates expert-novice neural coupling differently than equal allocation. Crucially, allocation favoring novices preserves behavioral interaction benefits alongside distinct fronto-executive neural synchrony patterns, revealing adaptive social and neural dynamics shaped by reward structures.

Triboelectric nanogenerator (TENG) is a promising technology for harvesting energy from various sources, such as human motion, wind and vibration. At the same time, a matching backend management circuit is essential to improve the energy utilization efficiency of TENG. Therefore, this work proposes a power regulation circuit (PRC) suitable for TENG, which is composed of a valley-filling circuit and a switching step-down circuit. The experimental results indicate that after incorporating a PRC, the conduction time of each cycle of the rectifier circuit doubles, increasing the number of current pulses in the TENG output and resulting in an output charge that is 1.6 fold that of the original circuit. Compared with the initial output signal, the charging rate of the output capacitor increased significantly by 75% with a PRC at a rotational speed of 120 rpm, significantly improving the utilization efficiency of the TENG’s output energy. At the same time, when the TENG powers LEDs, the flickering frequency of LEDs is reduced after adding a PRC, and the light emission is more stable, which further verifies the test results. The PRC proposed in this study can enable the energy harvested by the TENG to be utilized more efficiently, which has a certain promoting effect on the development and application of TENG technology.

Trust can be a dynamic social process, during which the social identity of the interacting agents (e.g., an investor and a trustee) can bias trust outcomes. Here, we investigated how social status modulates trust and the neural mechanisms underlying this process. An investor and a trustee performed a 10-round repeated trust game while their brain activity was being simultaneously recorded using functional near-infrared spectroscopy. The social status (either high or low) of both investors and trustees was manipulated via a math competition task. The behavioral results showed that in the initial round, individuals invested more in low-status partners. However, the investment ratio increased faster as the number of rounds increased during trust interaction when individuals were paired with a high-status partner. This increasing trend was particularly prominent in the low (investor)-high (trustee) status group. Moreover, the low-high group showed increased investor-trustee brain synchronization in the right temporoparietal junction as the number of rounds increased, while brain activation in the right dorsolateral prefrontal cortex of the investor decreased as the number of rounds increased. Both interpersonal brain synchronization and brain activation predicted investment performance at the early stage; furthermore, two-brain data provided earlier predictions than did single-brain data. These effects were detectable in the investment phase in the low-high group only; no comparable effects were observed in the repayment phase or other groups. Overall, this study demonstrated a multi-brain mechanism for the integration of social status and trust.

The intensity value recorded by terrestrial laser scanning (TLS) systems is significantly influenced by the incidence angle. The incidence angle effect is an object property, which is mainly related to target scattering properties, surface structures, and even some instrumental effects. Most existing models focus on diffuse reflections of rough surfaces and ignore specular reflections, despite that both reflections simultaneously exist in all natural surfaces. Due to the coincidence of the emitter and receiver in TLS, specular reflections can be ignored at large incidence angles. On the contrary, at small incidence angles, TLS detectors can receive a portion of specular reflections. The received specular reflections can trigger highlight phenomenon (hot-spot effects) in the intensity data of the scanned targets, particularly those with a relatively smooth or highly-reflective surface. In this study, a new method that takes diffuse and specular reflections, as well as the instrumental effects into consideration, is proposed to eliminate the specular reflection effects in TLS intensity data. Diffuse reflections and instrumental effects are modeled by a polynomial based on Lambertian reference targets, whereas specular reflections are modeled by the Phong model. The proposed method is tested and validated on different targets scanned by the Faro Focus3D 120 terrestrial scanner. Results imply that the coefficient of variation of the intensity data from a homogeneous surface is reduced by approximately 38% when specular reflections are considered. Compared with existing methods, the proposed method exhibits good feasibility and high accuracy in eliminating the specular reflection effects for intensity image interpretation and 3D point cloud representation by intensity.

Owing to the complex forest structure and large variation in crown size, individual tree detection in subtropical mixed broadleaf forests in urban scenes is a great challenge. Unmanned aerial vehicle (UAV) light detection and ranging (LiDAR) is a powerful tool for individual tree detection due to its ability to acquire high density point cloud that can reveal three-dimensional crown structure. Tree detection based on a local maximum (LM) filter, which is applied on a canopy height model (CHM) generated from LiDAR data, is a popular method due to its simplicity. However, it is difficult to determine the optimal LM filter window size and prior knowledge is usually needed to estimate the window size. In this paper, a novel tree detection approach based on crown morphology information is proposed. In the approach, LMs are firstly extracted using a LM filter whose window size is determined by the minimum crown size and then the crown morphology is identified based on local Gi* statistics to filter out LMs caused by surface irregularities contained in CHM. The LMs retained in the final results represent treetops. The approach was applied on two test sites characterized by different forest structures using UAV LiDAR data. The sensitivity of the approach to parameter setting was analyzed and rules for parameter setting were proposed. On the first test site characterized by irregular tree distribution and large variation in crown size, the detection rate and F-score derived by using the optimal combination of parameter values were 72.9% and 73.7%, respectively. On the second test site characterized by regular tree distribution and relatively small variation in crown size, the detection rate and F-score were 87.2% and 93.2%, respectively. In comparison with a variable-size window tree detection algorithm, both detection rates and F-score values of the proposed approach were higher.