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We reported for the first time the generation of titanium (Ti) nanoparticles (NPs) in different liquids (deionized (DI) water and sodium dodecyl sulfate (SDS) solution) and at a range of temperatures (5 °C, 28 °C, 60 °C, and 80 °C) using continuous-wave high-power laser ablation in liquid (CWLAL). The CWLAL technique is a convenient and cost-effective way to generate NPs. The key outcomes of our investigation are the effects of temperature and the liquid mediums on the average size, generation rate, shape, surface charges, and crystallographic structure of the NPs. Generated NPs show consistent spherical shape regardless of liquid medium changes and temperature variation. SDS solution notably impacts NP size and generation rate with higher surface charges than DI water. For instance, at temperatures of 28 °C and 80 °C, the generation rates in SDS solution are 316 mg/hr and 309 mg/hr, with average NP sizes of 33 nm and 34 nm, respectively. In contrast, the generation rates in DI water are 96 mg/hr and 302 mg/hr, with NP sizes of 13 nm and 20 nm, respectively. The weaker crystallographic structure observed in NPs generated in SDS solution, compared to the more robust crystallographic structure of NPs synthesized in DI water. Liquid temperature plays a significant role in determining surface charges, average particle size, and molecular structure of NPs. The choice of the liquid medium and temperature can be critical for tailoring NP characteristics to specific applications. Ongoing work is being conducted to explore the possibilities of further progress in this area to generate efficient and customized NPs. [ABSTRACT FROM AUTHOR]

With the increasing of renewable energy penetration rate in power source structure, the impact of its uncertainty on the stability of the power system is becoming increasingly apparent. The power system faces dual pressures of ensuring power supply and renewable energy accommodation. The way in which to accurately plan the power structure under situations with a high renewable energy penetration rate has become an urgent issue for future power infrastructure upgrading. In this paper, a rational power structure model was proposed for a provincial power grid by iteratively optimizing variables. The synergistic relationship between renewable energy, traditional power sources, and the energy storage system was considered comprehensively and calculated through the time-series production simulation method. The as-proposed model was studied using a scenario of a provincial grid plan in the year 2035. The power balance, electricity consumption, and renewable energy utilization were systematically analyzed, providing an important theoretical basis for the optimization and upgrading of provincial power systems under the rapid growth of renewable energy. [ABSTRACT FROM AUTHOR]

The effects of transient increases in UVB radiation on plants are not well known; whether cumulative damage dominates or, alternately, an increase in photoprotection and recovery periods ameliorates any negative effects. We investigated photosynthetic capacity and metabolite accumulation of grapevines (Vitis vinifera Cabernet Sauvignon) in response to UVB fluctuations under four treatments: fluctuating UVB (FUV) and steady UVB radiation (SUV) at similar total biologically effective UVB dose (2.12 and 2.23 kJ m−2 day−1), and their two respective no UVB controls. We found a greater decrease in stomatal conductance under SUV than FUV. There was no decrease in maximum yield of photosystem II (Fv/Fm) or its operational efficiency (ɸPSII) under the two UVB treatments, and Fv/Fm was higher under SUV than FUV. Photosynthetic capacity was enhanced under FUV in the light‐limited region of rapid light‐response curves but enhanced by SUV in the light‐saturated region. Flavonol content was similarly increased by both UVB treatments. We conclude that, while both FUV and SUV effectively stimulate acclimation to UVB radiation at realistic doses, FUV confers weaker acclimation than SUV. This implies that recovery periods between transient increases in UVB radiation reduce UVB acclimation, compared to an equivalent dose of UVB provided continuously. Thus, caution is needed in interpreting the findings of experiments using steady UVB radiation treatments to infer effects in natural environments, as the stimulatory effect of steady UVB is greater than that of the equivalent fluctuating UVB. [ABSTRACT FROM AUTHOR]

Background: Giant cell-rich solitary fibrous tumour (GCR-SFT), previously referred to as giant cell angiofibroma, is an uncommon soft tissue tumour that classically occurs in the orbit but very rarely presents in deep organs. Here, we present a case of GCR-SFT occurring in the urinary bladder, which is one of the unusual histological subtypes of SFT. Case presentation: A 56-year-old man was incidentally found to have a mass measuring 4.5 × 4.3 × 4.0 cm located in the left posterior wall of the bladder by computed tomography during a physical examination. The lesion was confirmed as GCR-SFT by pathological examination after laparoscopic radical surgery. Histopathologically, the tumour was a well-circumscribed, nonencapsulated lesion that was composed of bland spindle-ovoid tumour cells alternating with hypocellular and hypercellular areas, staghorn-like vasculatures and scattered large dark-stained multinucleate giant cells lining pseudovascular spaces. The spindle-ovoid cells and multinucleate giant cells showed strong and diffuse expression of CD34 and nuclear STAT6. In addition, the hallmark of the NAB2ex4-STAT6ex5 fusion gene was detected by RT‒PCR. The patient was classified as having a low risk of recurrence or metastasis according to the risk stratification criteria. The patient underwent regular follow-up for 34 months after surgery, and there was no evidence of local recurrence or metastasis. Conclusion: This is the first reported case of GCR-SFT occurring in the urinary bladder with underlying NAB2ex4-STAT6ex5 fusion. Complete surgical excision of the tumour and long-term follow-up are recommended to ensure no local recurrence or metastasis. [ABSTRACT FROM AUTHOR]

Purpose: Material extrusion technology is considered to be an effective way to realize the accurate and integrated manufacturing of high-performance metal diamond tools with complex structures. The present work aims to report the G4 binder that can be used to create metal composite filament loading high concentrations of large diamond particles through comparative experiments. Design/methodology/approach: The quality of filaments was evaluated by surface topography observation and porosity measurement. And the printability of filaments was further studied by the tensile test, rheological test, shear analysis and printing test. Findings: The results show that the G4 binder exhibits the best capacity for loading diamonds among G1–G4. The L4 filament created with G4 has no defects such as pores, cracks and patterns on the surface and section, and has the lowest porosity, which is about 1/3 of the L1. Therefore, the diamond-containing composite filament based on G4 binder exhibits the best quality. On the other hand, the results of the tensile test of L5–L8 filaments reveal that as the diamond content increases from 10% to 30%, the tensile strength of the filament decreases by 29.52%, and the retention force coefficient decreases by 15.74%. This can be attributed to the formation of inefficient bonding areas of the clustered diamond particles inside the composite filament, which also leads to a weakening of the shear strength. Despite this, the results of the printing test show that the diamond-containing composite filament based on the G4 binder has reliable printability. Originality/value: Therefore, the G4 binder is considered to solve the most critical first challenge in the development of diamond-containing filament. [ABSTRACT FROM AUTHOR]

Objective: Hypertriglyceridemia (HTG) is one of the common causes of acute pancreatitis (AP). Hyperlipidemic acute pancreatitis (HTG-AP) is associated with higher mortality owing to its tendency for greater severity and rapid progression. The purpose of this study was to explore the mechanism of involvement of tumor necrosis factor receptor-related factor 6 (TRAF6) in pyroptosis during HTG-AP. Methods: The HTG environment was simulated with palmitic acid treatment in vitro and a high-fat diet in vivo. Cerulein was used to establish the HTG-AP model, followed by genetic and pharmacological inhibition of TRAF6. Pyroptosis activation, inflammatory reaction, and the interaction between TRAF6 and pyroptosis in HTG-AP were assessed. Results: HTG was found to aggravate the development of pancreatitis, accompanied by increased pyroptosis and enhanced inflammatory response in HTG-AP models. Mechanistically, TRAF6 downregulation decreased the activation of pyroptosis in cerulein-induced HTG-AP. Conclusion: Collectively, inhibition of TRAF6 improved HTG-AP and the associated inflammation by alleviating pyroptosis. [ABSTRACT FROM AUTHOR]

Fused deposition modeling (FDM) technique is one of the most popular additive manufacturing techniques. Infill density is a critical factor influencing the mechanical properties of 3D-printed components using the FDM technique. For irregular components with variable cross-sections, to increase their overall mechanical properties while maintaining a lightweight, it is necessary to enhance the local infill density of the thin part while decreasing the infill density of the thick part. However, most current slicing software can only generate a uniform infill throughout one model to be printed and cannot adaptively create a filling structure with a varying infill density according to the dimensional variation of the cross-section. In the present study, to improve the mechanical properties of irregular components with variable cross-sections, an adaptive-density filling structure was proposed, in which Hilbert curve with the same order was used to fill each slice, i.e., the level of the Hilbert curves in each slice is the same, but the side length of the Hilbert curve decreases with the decreasing size of each slice; hence, the infill density of the smaller cross-section is greater than that of the larger cross-section. The ultimate bearing capacity of printed specimens with the adaptive-density filling structure was evaluated by quasi-static compression, three-point bending, and dynamic compression tests, and the printed specimens with uniform filling structure and the same overall infill density were tested for comparison. The results show that the maximum flexural load, the ultimate compression load, and the maximum impact resistance of the printed specimens with the adaptive-density filling structure were increased by 140%, 47%, and 82%, respectively, compared with their counterparts using the uniform filling structure. [ABSTRACT FROM AUTHOR]

Vehicular networks which are paralyzed by natural disasters is faced with communication dilemma. Through building a decentralized communication network, unmanned aerial vehicles (UAVs) with high mobility and flexibility are expected to be the solution to the post-disaster vehicular networks. The blockchain technology has been widely used in UAV networks to provision the prompt security of distributed communications. However, existing works ignore the dynamics of the network in that due to high mobility, distributed UAVs cannot timely connect to the backbone to synchronize blockchain transactions. The delay of synchronization can result in severe security issues. On addressing the issues, this paper proposes UAVs-aided blockchain offline transactions to ensure the security and effectiveness of delay-tolerant blockchain transactions when UAVs are offline. In specific, we consider vehicle-to-vehicle (V2V) charging transactions in post-disaster vehicular networks. By establishing offline channel between charging and discharging electric vehicles (EVs) by hashed time locked contract (HTLC), we design a UAVs aided penalty algorithm with accountable assertions to prevent deposit forging attacks and double-spending attacks. In addition, considering the selfishness of EVs, a Stackelberg game based incentive scheme is developed to encourage EVs to participate the offline transactions and to improve their trust values. By suing the mechanisms above, our proposal addresses the security of offline EV charging, as well as the selfishness of participant. Using extensive simulations, we demonstrate that the proposed scheme can realize secure transactions among EVs and can effectively improve the utilities of EVs through the comparison with conventional schemes. [ABSTRACT FROM AUTHOR]

Acute pancreatitis (AP) is mainly caused by acinar cells releasing various inflammatory factors, causing inflammatory storms and leading to severe pancreatitis. Detection methods and treatment targets for pancreatitis are lacking, raising the urgency of identifying diagnostic markers and therapeutic targets for AP. MicroRNAs (miRNAs) have recently been identified as molecular markers for various biological processes such as tumors, immunity, and metabolism, and the involvement of miRNAs in inflammatory responses has been increasingly studied. To explore the role of miRNAs in AP is the primary objective of this study. By using qPCR on our cerulein-induced pancreatitis cell model, it is worth noting that the change of miR-146a-5p expression in inflammation-related miRNAs in AP was predominant. Next, ELISA, CCK8, and flow cytometry were used to inspect the impact of miR-146a-5p on pancreatitis. BiBiServ bioinformatics anticipated binding ability of miR-146a-5p and 3 ′ -untranslated region (3 ′ UTR) of TNF receptor-associated factor 6 (TRAF6), and the dual-luciferase assay verified the combination of the two. TRAF6 knockdown verified the effect of TRAF6 on the progression of pancreatitis. Finally, rescue experiments verified the capability of miR-146a-5p and TRAF6 interaction on the Toll-like receptor 9 (TLR9)/NOD-like receptor protein 3 (NLRP3) signaling pathway and cell function. The expression of miR-146a-5p decreased in cerulein-induced AR42J pancreatic acinar cells. Functional experiments verified that miR-146a-5p facilitated the proliferation of AR42J pancreatic acinar cells and inhibited their apoptosis. Bioinformatic predictions and dual-luciferase experiments verified the actual binding efficiency between miR-146a-5p and 3 ′ UTR of TRAF6. Our study confirmed that knockdown of TRAF6 restrained the progression of pancreatitis, and knockdown of TRAF6 rescued pancreatitis caused by miR-146a-5p downregulation by the TLR9/NLRP3 signaling pathway. Therefore, downregulation of miR-146a-5p in the induced pancreatitis cell model promotes the progression of pancreatitis via the TLR9/TRAF6/NLRP3 signaling pathway. There is potential for miR-146a-5p to serve as a diagnostic marker and therapeutic nucleic acid drug for AP. [ABSTRACT FROM AUTHOR]

Background: Pisa syndrome (PS) is rarely reported in Dementia with Lewy bodies (DLB). The aim of this article is to investigate the prevalence rate of PS and the correlation with clinical features evaluated in patients with DLB.Methods: A total of 209 DLB patients were consecutively recruited and underwent standardized clinical evaluation in our multicenter study. The associations between PS and clinical factors were evaluated.Results: The prevalence rate of PS in patients with DLB was 15.3%, which was higher in the moderate and severe stages than mild cognitive impairment and mild stages (81.2% vs. 18.8%). Patients with PS had a longer duration of disease (P = 0.020) and parkinsonism (P = 0.003), higher scores of NPI (P = 0.028), ADL (P = 0.002) and UPDRS part III (P < 0.001), lower scores of clock drawing test (P = 0.009), visuospatial/executive abilities (P = 0.018), attention (P = 0.020), language and praxis (P = 0.020), registration (P = 0.012), greater H&Y stage (P < 0.001), and higher proportion of cholinesterase inhibitors used (P = 0.044) than those without PS. Longer disease duration (OR = 1.166, P = 0.023), presence of parkinsonism (OR = 7.971, P = 0.007), moderate and severe dementia (OR = 3.215, P = 0.021) were associated with the presence of PS. Patients had a longer duration of PS (P = 0.014) and lower mean age of onset (P = 0.040) in the group with severe lateral trunk flexion.Conclusion: The development of PS may be associated with longer disease duration, the presence of parkinsonism and severe stages of dementia in DLB. Cholinesterase inhibitors may have a correlation with PS. The severity of lateral flexion is related to the duration of PS and mean age of onset. [ABSTRACT FROM AUTHOR]

The sixth-generation (6G) mobile communication network is expected to provide world-connected smart and autonomous services by leveraging artificial intelligence (AI) technologies. In particular, federated learning (FL) is advocated to promote the implementations of ubiquitous AI applications in 6G, where massive distributed data is utilized to cooperatively train AI models as well as protect privacy and reduce resource consumption. However, due to the large number of interactions among mobile devices or infrastructures in FL, the AI inevitably suffers from a series of potential privacy and security risks. In this article, we investigate the security and privacy of AI-enabled 6G. Specifically, we first present the AI-enabled 6G architecture, including the space-air-ground-ocean integrated network (SAGOIN) architecture and two different FL-based AI model training frameworks in 6G. Furthermore, we discuss in detail the privacy and security threats, including cheating attack, low-quality local model training attack, and privacy stealing attack. Afterwards, we present a case study to design the security and privacy preservation scheme by integrating the trust evaluation, Q-learning based incentive, and local differential privacy (LDP) mechanism. Finally, we give out several future research directions in promising AI-enabled 6G. [ABSTRACT FROM AUTHOR]

Background: Axenfeld-Rieger syndrome (ARS, OMIM:602482) is a genetic disease characterized by ocular and systemic features. Clinical features of ARS are highly variable among patients and associated with mutations of human PITX2 and FOXC1 genes. Herein, we present an ARS in two cases (proband and his mother) with a novel variant in the PITX2. Methods: A 3-month-old boy was admitted with an abnormal eye development at birth. Physical examination and ophthalmologic examination findings revealed an abnormal development of the anterior segments, ectropion of redundant skin in the umbilicus, single-sided deafness, teeth eruption failure, patent foramen ovale, and a mid-facial flattening. The proband's mother has been blind since the age of 12. We conducted genetic tests for the family via whole exome sequencing (WES) and quantitative PCR (qPCR) to identify the genetic etiology in the family. We also conducted a retrospective review of the ARS type I phenotype caused by the PITX2 mutations. Results: WES and qPCR results of the proband and his parents suggested that both the child and his mother carry a 1.31kbp deletion (chr4: g.111538559_111539864del [GRCh37]) spanned the exon 4 of PITX2, resulting in the typical and rare phenotype of ARS type I. It can conclude that truncating variants in the exon 3-4 of PITX2 are the more common mechanism to cause the malfunction of the gene with a broader phenotypic spectrum. Conclusion: The study has filled in a new clinical manifestation of the PITX2 and enriched the phenotype of ARS. The retrospective analysis of phenotype of PITX2 mutations provided a comprehensive understanding of the disease. [ABSTRACT FROM AUTHOR]

With the proliferation of electric vehicles (EVs), private charging pile (PCP) sharing networks are likely to be an integral part of future smart cities, especially in places with limited public charging infrastructure. However, there are a number of operational challenges associated with the deployment of PCPs in such a shared and untrusted environment. For example, how do we formulate efficient PCP sharing strategies in PCP sharing networks, while also taking into consideration the dynamic charging behaviors of EVs? Therefore, in this paper, we propose an energy blockchain-based secure PCP sharing scheme (BBC) for PCP sharing networks. First, an energy blockchain-based framework is designed for PCP sharing networks to facilitate energy sharing services for EVs and PCPs, using both distributed ledgers and cryptocurrency. Then, we devise a reputation-based secure PCP sharing algorithm to improve consensus efficiency with smaller signature sizes. In addition, a distributed reputation mechanism is constructed to assess the trustworthiness of consensus nodes in blockchain, based on ratings, behaviors, and fading. We also model the interactions among EVs and cooperative PCPs as a joint coalition-matching game, and obtain the optimal strategies of PCPs and EVs by analyzing the Nash-stable coalitional structure and stable many-to-one matching pairs. Extensive simulations and the real-world implementation demonstrate that the proposed approach improves the utility of EV users and renewable energy efficiency in PCP sharing networks. [ABSTRACT FROM AUTHOR]

By leveraging the power of crowd, the prevalence of mobile devices in mobile crowd-sensing (MCS) networks helps and provides a wide range of sensing services through collecting and sharing sensing data. However, due to the diverse behaviours of mobile users, unreliable or malicious users and platforms could provide untrusted data, which affects the quality of sensing service. Besides, mobile users are reluctant to participate in sensing tasks without sufficient incentives. It is desirable to design a trust and incentive scheme to improve the service efficiency of MCS. In this paper, we propose a novel trust-driven contract incentive framework in MCS, which guarantees the service quality and stimulates mobile users to join sensing tasks. We first design a trust evaluation scheme between mobile users and sensing platforms based on the historical interactions to derive the reliability value of sensing platform. Then, the trust threshold is formulated to filter out malicious sensing platforms. By considering the privacy preferences of mobile users, we establish a contract incentive scheme to maximize the utility of both mobile users and sensing platforms. The design objective is to derive a set of optimal contracts under both discrete and continuous contract models. Meanwhile, the designed contracts guarantee the individual rationality (IR) and incentive compatibility (IC) properties. Finally, simulations are conducted to evaluate the effectiveness of the proposed trust-driven contract incentive scheme, and results demonstrate that the proposed scheme can jointly improve the quality of sensing service and maximize the utilities of mobile users and sensing platforms. [ABSTRACT FROM AUTHOR]

The proliferation of smart devices has led to a huge amount of data streaming in the Internet of Things (IoT). However, the resource-limited devices cannot satisfy the demands of computing-in-tensive but delay-sensitive applications. The data delivery among devices may be tampered with by malicious users. These pose new challenges to provide secure and intelligent services in IoT. Blockchain and reinforcement learning (RL) are promising techniques for establishing a secure environment and intelligent resource management. In this article, we introduce a novel software defined networking (SDN)-enabled architecture for edge-cloud orchestrated computing to support secure and intelligent services in IoT. We first introduce the SDN-enabled architecture by integrating cloud computing, edge computing, and IoT networks. Then we provide several applications of SDN-enabled architecture in edge-cloud orchestrated computing. Next, we propose the blockchain and RL envisioned solutions to implement secure and intelligent services in IoT. Moreover, a case study of blockchain- and RL-enabled secure and intelligent computing offloading is presented to validate its effectiveness. We finally provide our conclusion and discuss several promising research directions. [ABSTRACT FROM AUTHOR]

The X-type strike-slip fault system and weathering crust karst fracture-cave and channel reservoirs were developed in the Halahatang area of the northern Tarim Basin. However, the relationship between the reservoir and the strike-slip fault remains controversial. Based on the core data, and taking an NE-striking strike-slip fault as an example, this paper dissects the karst reservoir from wells along the strike-slip fault damage zone and analyzes the control of scales, properties, and segmentation styles of strike-slip faults on karst reservoirs. The results show that (1) the scale of the strike-slip fault controls the distribution of the reservoir—the wider the fault damage zone, the wider the fracture-cave reservoirs; (2) the transtensional segments of the strike-slip fault are more likely to produce karstification, and the buried-hill area and the interbedded area are controlled by different hydrodynamic conditions to form different types of karst reservoirs; (3) six different parts of the strike-slip fault are conducive to the formation scale of fault fracture zones. This research provides new insight into recognizing karst reservoirs within strike-slip fault damage zones, which can be further applied to predict karst reservoirs controlled by strike-slip faults. [ABSTRACT FROM AUTHOR]

The 5G heterogeneous networks (HetNets) are capable of providing real-time computing services for autonomous vehicles (AVs) by deploying edge computing devices (ECDs) at macro cell base stations (MCBSs) and small cell base stations (SCBSs). With the imbalanced distribution and fast moving AVs contending intensely for computing services, how to efficiently exploit cooperations among participants in 5G HetNets to improve the service performance is therefore challenging. In this paper, we develop a game theoretic scheme for collaborative vehicular task offloading to facilitate the computing services in 5G HetNets. Specifically, we propose a two-stage vehicular task offloading mechanism to promote the cooperation among participants with the target of improving the task completion rate and the utilities of the participants, where the mechanism jointly considers the network architecture of the HetNets, the imbalanced distribution of AVs and the reuse of task results. In the first stage, an auction model is designed to help the MCBS select the optimal SCBS to execute the offloaded task based on the requirement of the task and the available computing resources of SCBSs. According to the task execution cost declared by the selected SCBS, the MCBS then bargains with the AV for the agreement of the task offloading service to maximize their utilities in the second stage. Using simulations, we show that the proposed collaborative task offloading scheme can achieve a higher task completion rate for the task offloading service and bring higher utilities to all participants than conventional schemes. [ABSTRACT FROM AUTHOR]

The sixth generation (6G) networks are expected to provide a fully connected world with terrestrial wireless and satellite communications integration. The design concept of 6G networks is to leverage artificial intelligence (Ai) to promote the intelligent and agile development of network services. intelligent services inevitably involve the processing of large amounts of data, such as storage, computing, and analysis, such that the data may be vulnerable to tampering or contamination by attackers. in this article, we propose a blockchain-based data security scheme for Ai applications in 6G networks. Specifically, we first introduce the 6G architecture (i.e., a space-air-ground-underwater integrated network). Then we discuss two Ai-enabled applications, indoor positioning and autonomous vehicle, in the context of 6G. Through a case study of an indoor navigation system, we demonstrate the effectiveness of blockchain in data security. The integration of Ai and blockchain is developed to evaluate and optimize the quality of intelligent service. Finally, we discuss several open issues about data security in the upcoming 6G networks. [ABSTRACT FROM AUTHOR]

The rise of the intelligent Internet of Things (IoT) promotes the development of emerging technologies and industries with the integration of edge computing and cloud computing. This integrated paradigm becomes a promising prospect to continuously expand the service capabilities of IoT. However, edge-driven intelligent IoT systems raises serious security issues as the systems are prone to be compromised by malicious attacks. In this article, an edge-driven security framework is investigated for intelligent IoT systems. First, we introduce the architecture of edge-driven intelligent IoT, and present typical edge-driven intelligent IoT applications. Second, we point out the security threats in edge-driven intelligent IoT in terms of attack behaviors of adversaries. Third, we develop a case study of edge-driven intelligent IoT from the security perspective. Finally, we discuss future research directions in this emerging area. [ABSTRACT FROM AUTHOR]

The autonomous driving era is coming with tremendous potential to revolutionize transportation systems with improved safety, comfort, and intelligence on the road. Integrating connected autonomous vehicles (CAVs) and rising social networking, autonomous vehicular social networks (AVSNs) can facilitate the data dissemination in safety-critical and entertainment-related applications for autonomous driving. However, with time-varying, delay-constrained, and location-dependent characteristics in autonomous driving, it faces great challenges to incentivize CAVs to disseminate massive content in AVSNs. Meanwhile, attackers may not only disseminate fake information to confuse the network, but also pose security vulnerabilities and privacy issues for CAVs. In this article, we investigate secure and incentive content delivery in AVSNs based on the advanced blockchain. Specifically, we first present a blockchain-enabled AVSN framework to safeguard content delivery. Then, we investigate the task-based and credit-based reputation models to evaluate the trustworthiness of CAVs and RSUs, respectively. The reputation increase and task reward are explored as incentives for CAVs delivering reliable content. In addition, a novel proof of reputation consensus protocol is devised to efficiently reach consensus in blockchain-enabled AVSNs while motivating RSUs to behave honestly. Experimental results indicate that the proposed framework outperforms the existing approaches, delivering vehicular content more reliably and securely. Finally, future research directions in this emerging area are discussed. [ABSTRACT FROM AUTHOR]

With ever-increasing penetration of autonomous driving vehicles (ADVs), security becomes of significant essence to autonomous vehicular networks (AVNs). On one hand, although cryptographic systems help deal with various attacks, they cannot resolve inside attacks from compromised or malfunctioning ADVs. On the other hand, ADVs with higher automated levels are easier to attack because the automated components onboard are vulnerable to inside attacks. These issues can be mitigated well by trust-based intrusion detection. Therefore,this article presents an efficient trust-based intrusion detection framework for AVNs. First, we propose a novel trust evaluation model for ADVs, in which all the trust evaluation information of a given ADV is utilized to compute its trust value. Then, based on the trust evaluation model, a two-level intrusion detection framework is presented. In the framework, the trustworthiness of an accident or attack warning is established not only based on trust evaluation with the coverage of a roadside unit (RSU), but also the information exchanged between RSUs through the cloud server. Afterward, we propose a reinforcement-learning-based incentive mechanism to stimulate ADVs to report warnings. Through the case study, the proposed framework outperforms the conventional mechanism and can reach a higher warnin [ABSTRACT FROM AUTHOR]

In a smart community (SC) with renewable energy sources (RES), flexible charging service can be provisioned to electric vehicles (EVs), where EVs can choose clean energy, traditional energy, or the mixture of them on demand in the vehicular networks. Considering the existence of various entities in the SC and the limited generation capacity of RES, it becomes of significance yet very challenging to optimally schedule the charging service for EVs with different consumption preferences. In this paper, we propose a charging scheme for EVs in a SC integrated with RES using a game theoretical approach. First, a three-party energy network is proposed to model the interactions among the main grid, EVs, and aggregators in the smart grid. Second, the trust model is presented to improve the safety of energy trading by evaluating the reliability of aggregators based on direct trust and indirect trust. Third, based on the four-stage Stackelberg game, the optimal strategies of three energy entities are analyzed. The Stackelberg equilibrium can be obtained by the proposed accelerated gradient descent based iteration algorithm. Furthermore, a weighted max–min fairness based energy allocation algorithm is proposed to allocate the limited renewable energy for EVs in a fair and efficient manner. Finally, extensive simulations are carried out to evaluate and demonstrate the effectiveness of the proposed scheme through comparison with conventional schemes. [ABSTRACT FROM AUTHOR]

• A methodology for condition-based maintenance planning and crew scheduling for railway track. • A distributed optimization scheme to apply the proposed approach to large-scale railway networks. • A chance-constrained formulation to achieve a robust but conservative maintenance plan. We develop a multi-level decision making approach for optimal condition-based maintenance planning of a railway network divided into a large number of sections with independent stochastic deterioration dynamics. At higher level, a chance-constrained Model Predictive Control (MPC) controller determines the long-term section-wise maintenance plan, minimizing condition deterioration and maintenance costs for a finite planning horizon, while ensuring that the deterioration level of each section stays below the maintenance threshold with a given probabilistic guarantee in the presence of parameter uncertainty. The resulting large MPC optimization problem containing both continuous and discrete decision variables is solved using Dantzig-Wolfe decomposition to improve the scalability of the proposed approach. At a lower level, the optimal short-term scheduling of the maintenance interventions suggested by the high-level controller and the optimal routing of the corresponding maintenance crew is formulated as a capacitated arc routing problem, which is solved exactly by transforming it into a node routing problem. The proposed approach is illustrated by a numerical case study on the optimal treatment of squats of a regional Dutch railway network. Simulation results show that the proposed approach is robust, non-conservative, and scalable. [ABSTRACT FROM AUTHOR]

Recently, mobile charging stations (MCSs) have attracted more attentions compared with fixed charging stations (FCSs). Electric vehicles (EVs) can be easily provided with charging service through MCSs. However, most of existing approaches cannot be properly used to design the optimal pricing strategy for MCSs, leading to the inefficiency of power in MCSs. Thus, it is necessary to study new incentive mechanisms to improve MCSs' profits. In this paper, we propose a contract-based scheme to maximize MCSs' profits in the heterogeneous networks. Considering the power trading between EV users and MCSs, we develop the utility function with EV users' types. Aiming to maximize MCSs' profits, we formulate this problem as an optimization problem under the complete and incomplete information of EV users, respectively. Through the theoretical analysis, we prove the existence of optimal contract items, which also ensure the feasibility of EV users. Then optimal solutions can be achieved based on our proposed algorithm. Numerical and simulation results validate the effectiveness of our proposal. [ABSTRACT FROM AUTHOR]

Premature birth disrupts normal lung development and places infants at risk for bronchopulmonary dysplasia (BPD), a disease disrupting lung health throughout the life of an individual and that is increasing in incidence. The TGF-β superfamily has been implicated in BPD pathogenesis, however, what cell lineage it impacts remains unclear. We show that TGFbr2 is critical for alveolar epithelial (AT1) cell fate maintenance and function. Loss of TGFbr2 in AT1 cells during late lung development leads to AT1-AT2 cell reprogramming and altered pulmonary architecture, which persists into adulthood. Restriction of fetal lung stretch and associated AT1 cell spreading through a model of oligohydramnios enhances AT1-AT2 reprogramming. Transcriptomic and proteomic analyses reveal the necessity of TGFbr2 expression in AT1 cells for extracellular matrix production. Moreover, TGF-β signaling regulates integrin transcription to alter AT1 cell morphology, which further impacts ECM expression through changes in mechanotransduction. These data reveal the cell intrinsic necessity of TGF-β signaling in maintaining AT1 cell fate and reveal this cell lineage as a major orchestrator of the alveolar matrisome. [ABSTRACT FROM AUTHOR]

Vehicular content networks (VCNs), which distribute medium-volume contents to vehicles in a fully distributed manner, represent the key enabling technology of vehicular infotainment applications. In VCNs, the road-side units (RSUs) cache replicas of contents on the edge of networks to facilitate the timely content delivery to driving-through vehicles when requested. However, due to the limited storage at RSUs and soaring content size for distribution, RSUs can only selectively cache content replicas. The edge caching scheme in RSUs, therefore, becomes a fundamental issue in VCNs. This paper addresses the issue by developing an edge caching scheme in RSUs. Specifically, we first analyze the features of vehicular content requests based on the content access pattern, vehicle's velocity, and road traffic density. A model is then proposed to determine whether and where to obtain the replica of content when the moving vehicle requests it. After this, a cross-entropy-based dynamic content caching scheme is proposed accordingly to cache the contents at the edge of VCNs based on the requests of vehicles and the cooperation among RSUs. Finally, the performance of the proposed scheme is evaluated by extensive simulation experiments. [ABSTRACT FROM AUTHOR]

This paper develops a multi-level decision making approach for the optimal planning of maintenance operations of railway infrastructures, which are composed of multiple components divided into basic units for maintenance. Scenario-based chance-constrained Model Predictive Control (MPC) is used at the high level to determine an optimal long-term component-wise intervention plan for a railway infrastructure, and the Time Instant Optimization (TIO) approach is applied to transform the MPC optimization problem with both continuous and integer decision variables into a nonlinear continuous optimization problem. The middle-level problem determines the allocation of time slots for the maintenance interventions suggested at the high level to optimize the trade-off between traffic disruption and the setup cost of maintenance slots. Based on the high-level intervention plan, the low-level problem determines the optimal clustering of the basic units to be treated by a maintenance agent, subject to the time limit imposed by the maintenance slots. The proposed approach is applied to the optimal treatment of squats, with real data from the Eindhoven-Weert line in the Dutch railway network. [ABSTRACT FROM AUTHOR]

Recently, parked vehicles have been shown to be useful to deliver content in vehicular ad hoc networks, where the parked vehicles can form social communities to share and exchange content with other moving vehicles and road side units (RSUs). However, as it takes resource such as bandwidth and power for parked vehicles and RSUs to deliver content, the incentive scheme with the optimal pricing strategy needs to be studied. Furthermore, because multiple places including RSUs and parked vehicles can deliver content to moving vehicles, the optimal algorithm to determine where to obtain the requested content should also be discussed. Therefore, in this paper, we first propose a framework of content delivery with parked vehicles, where moving vehicles can obtain content from both the RSU and parked vehicles according to the competition and cooperation among them. Then, based on a Stackelberg game, we develop a pricing model where each of the three players, including moving vehicles, RSU, and parked vehicles, can obtain their maximum utilities. Next, a gradient based iteration algorithm is presented to obtain the Stackelberg equilibrium. Finally, the simulation results prove that the proposal can outperform other conventional methods and that each player in the game can obtain its optimal strategy during the content delivery. [ABSTRACT FROM PUBLISHER]

Drive-thru Internet has emerged as a fundamental approach for information/content distribution to vehicles on the go. In the drive-thru Internet, one vehicle may connect to multiple roadside units (RSUs) along its trip, and in the meantime, multiple vehicles may compete one RSU at the same time for transmissions. Therefore, both vehicles and RSUs need to optimize their connections to achieve their best utilities. In the perspective of RSUs, it is important to select optimal vehicles to transmit so as to maximize the global RSU system's utilization. For individual vehicles, it needs to wisely select RSUs along its trip to connect so as to minimize its download cost, e.g., energy consumption and bandwidth cost. This paper targets to address the two design goals in one framework using a game theoretic model. Specifically, we model the two-dimensional drive-thru Internet as a second-price sealed-bid auction. In each RSU cell, an adaptive reserve price scheme is designed such that the RSU is allowed to selectively provide connections to vehicles based on the network size, vehicle's transmission rate, urgency of download, and content popularity; the RSU finally obtains the optimal utility on a Bayesian Nash equilibrium of the auction. For individual vehicles, a finite-horizon Markov decision process has been developed to guide vehicles to optimally select RSUs to connect along their road trips. Using extensive simulations, we demonstrate that the proposed framework can achieve the highest utility for the RSUs compared with existing proposals. It can also help vehicles keep a higher utility and transmission ratio when going through a single RSU or multiple RSUs than the conventional schemes. [ABSTRACT FROM AUTHOR]

Rapid developments in mobile services and wireless technologies have prompted users to form mobile social networks (MSNs), where bundles can be delivered via opportunistic peer-to-peer links in a store–carry–forward mode. This mode needs all nodes to work in a cooperative way. However, mobile nodes may be selfish and might not be willing to forward data to others due to the limited resources (e.g., buffer and energy), resulting in degraded system performance. To tackle the aforementioned problem, this paper proposes a novel incentive scheme to stimulate selfish nodes to participate in bundle delivery in MSNs. At first, a virtual currency is introduced to pay for the relay service. Then, a bundle carrier selects a relay node from its friends or other strangers based on its status. Next, a bargain game is employed to model the transaction pricing for relay service. In addition, the simulation results show that the proposal can improve the performance of the existing schemes significantly. [ABSTRACT FROM AUTHOR]

Due to the rapid development of mobile social networks, mobile big data play an important role in providing mobile social users with various mobile services. However, as mobile big data have inherent properties, current MSNs face a challenge to provide mobile social user with a satisfactory quality of experience. Therefore, in this article, we propose a novel framework to deliver mobile big data over content- centric mobile social networks. At first, the characteristics and challenges of mobile big data are studied. Then the content-centric network architecture to deliver mobile big data in MSNs is presented, where each datum consists of interest packets and data packets, respectively. Next, how to select the agent node to forward interest packets and the relay node to transmit data packets are given by defining priorities of interest packets and data packets. Finally, simulation results show the performance of our framework with varied parameters. [ABSTRACT FROM PUBLISHER]

Existing studies rarely focus on manufacturing complex diamond tools via fused filament fabrication subject to the development of corresponding filaments. This work aims to develop diamond-containing metal composites filament to effectively fabricate ultrathin diamond blade. In this study, properties of filaments with different volumes of diamond and surface modifier were characterized and evaluated. The interface adhesion between the diamond particles and the binder matrix was enhanced with the surface modifier, thereby reducing the internal defects and improving the diamond distribution uniformity. Flexibility and tensile strength of the filaments could be greatly enhanced as the improved interfacial adhesion. Besides, the enhanced viscosity of the feedstock contributed to a closer adhesion between the deposited strands. Finally, ultrathin diamond blade with a sintered density of 95.2 % could be achieved with the optimized filament. The results demonstrate the ability of the optimized filament to fabricate diamond tool via fused filament fabrication. [Display omitted] • Diamond-containing metal matrix composite filaments were successfully fabricated. • Diamond content are highly relevant to the quality of the filaments. • Surface modifier improved the interface adhesion between diamond and binder matrix. • Interface adhesion status influences mechanical properties and viscosity of filaments. • Blade with a sintered density and thickness of 95.2 % and 0.33 mm can be achieved. [ABSTRACT FROM AUTHOR]

With the rapid development of mobile communication technologies, various kinds of content can be delivered among mobile users for content sharing. Due to the complexity of networks and particular features of mobile behaviors, to manage networks efficiently, SDMSNs are advocated where the control plane and data plane can work separately but cooperatively. In this article we outline how to deliver mobile content over SDMSNs. We first design the flow table based on the social features including social tie, mobility, and community. Then a novel social switch is introduced to deliver content among mobile users by using the proposed social degree and social stay time. In addition, the process of content delivery is presented according to different scenarios, and extensive experiments are given to prove the efficiency of this approach. [ABSTRACT FROM PUBLISHER]

Due to the rapid growth of network traffic and new demands from mobile users, the current mobile social networks face challenges in dealing with a huge amount of content requests, high operating costs, and mobility control. How to design mobile social networks efficiently for the upcoming 5G era has become an important issue. In this article we propose and outline a framework of content centric mobile social networks for 5G. First, we present a content centric based network architecture consisting of mobile users, communities, content centric nodes, small cells, and macro cells. Next, we discuss the detailed process to deliver mobile content based on the interests of content and mobile users. In addition, a novel caching scheme is presented to store replicas of mobile content, and the related experiment results are also given. [ABSTRACT FROM PUBLISHER]

Cell segmentation in phase contrast microscopy images lays a crucial foundation for numerous subsequent computer-aided cell image analysis, but it encounters many unsolved challenges due to image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose an interactive cell segmentation scheme over phase retardation features. After partitioning the images into phase homogeneous atoms, human annotations are propagated to unlabeled atoms over an affinity graph that is learned based on discrimination analysis. Then, an active query strategy is proposed for which the most informative unlabeled atom is selected for annotation, which is also propagated to the other unlabeled atoms. Cell segmentation converges to quality results after several rounds of interactions involving both the user's intentions and characteristics of image features. Experimental results demonstrate that cells with different optical properties are well segmented via the proposed approach. [ABSTRACT FROM AUTHOR]

• V 2 O 5 yolk-shell microsphere with hierarchical structure as aqueous Li+ battery anode. • V 2 O 5 yolk-shell microspheres show high capacity and ultrafast rate capability. • V 2 O 5 yolk-shell microspheres exhibit a fast electrochemical kinetics. • V 2 O 5 //LiMn 2 O 4 aqueous Li+ full cells achieve favorable cycle life. Aqueous rechargeable lithium-ion batteries (ARLBs) are promising candidates in grid-scale energy storage systems due to their high safety and low cost. However, it remains a major challenge to develop advanced anode materials with favorable specific capacity and long cycle life. Herein, we fabricate V 2 O 5 yolk-shell microspheres with hierarchical nanostructure as anode material of ARLBs. Annealing temperature-dependent experiments are carried out to investigate the evolution of crystallinity, morphology and structure of the samples. As the annealing temperature varies from 300 °C to 350 °C to 400 °C, the building blocks of microspheres gradually change from nanoplates to nanoclusters to larger nanoparticles. The electrochemical performances of different samples are compared and analyzed. In half-cell tests, the sample annealed at 350 °C (VO-350) achieves a high capacity of 258.6 mA h g −1 at 0.5 A g −1 and ultrafast rate capabilities such as 149.7 mA h g −1 at 15 A g −1. In full-cell tests, the VO-350//LiMn 2 O 4 coin cells exhibit favorable cycle life with a capacity retention of 71.5% after 500 cycles at 1 A g −1 and ultrafast rate capabilities such as 87.4 mA h g −1 at 15 A g −1. In addition, the electrochemical kinetics and energy storage mechanism of V 2 O 5 in ARLBs are investigated. [Display omitted] [ABSTRACT FROM AUTHOR]

Abstract: Li4Ti5O12/C (LTO/C) is synthesized by solid-state reaction with citric acid added as the conductive carbon source, and the residual carbon is only 0.47wt%. For comparison, bare LTO is prepared under similar conditions. The electrodes for both samples are prepared without commercial carbon black added. It shows that the LTO/C composite electrodes perform much better than that of LTO. Combined with XRD, XPS, SEM and TEM analysis, it is suggested that the particle size effect could be dismissed, and the main factors influencing the performances should be attributed to the Ti (III) existence and/or the in situ generated residual carbon, both of which are introduced by citric acid. The two main factors influencing the character can not be separated here, but they both improve the conductivity. So, it indicates that with proper strategies to enhance the electronic conductivity of the material, the electrode of spinel lithium titanium oxide with no carbon black added will exhibit better electrochemical behavior, though the metallic Li7Ti5O12 exists. [Copyright &y& Elsevier]

Cell segmentation in phase contrast microscopy images lays a crucial foundation for numerous subsequent computer-aided cell image analysis, but it encounters many unsolved challenges due to image qualities and artifacts caused by phase contrast optics. Addressing the unsolved challenges, the authors propose an interactive cell segmentation scheme over phase retardation features. After partitioning the images into phase homogeneous atoms, human annotations are propagated to unlabeled atoms over an affinity graph that is learned based on discrimination analysis. Then, an active query strategy is proposed for which the most informative unlabeled atom is selected for annotation, which is also propagated to the other unlabeled atoms. Cell segmentation converges to quality results after several rounds of interactions involving both the user's intentions and characteristics of image features. Experimental results demonstrate that cells with different optical properties are well segmented via the proposed approach. [ABSTRACT FROM AUTHOR]

The application of Czochralski (Cz) monocrystalline silicon material in solar cells is limited by its high cost and serious lightinduced degradation. The use of cast multicrystalline silicon is also hindered by its high dislocation densities and high surface reflectance after texturing. Mono-like crystalline silicon is a promising material because it has the advantages of both mono- and multicrystalline silicon. However, when mono-like wafers are made into cells, the efficiencies of a batch of wafers often fluctuate within a wide range of >1% (absolute). In this work, mono-like wafers are classified by a simple process and fabricated into laser doping selective emitter cells. The effect and mechanism of subgrains on the performance of mono-like crystalline silicon solar cells are studied. The results show that the efficiency of mono-like crystalline silicon solar cells significantly depends on material defects that appear as subgrains on an alkaline textured surface. These subgrains have an almost negligible effect on the optical performance, shunt resistance, and junction recombination but significantly affect the minority carrier diffusion length and quantum efficiency within a long wavelength range. Finally, an average efficiency of 18.2% is achieved on wafers with hardly any subgrain but with a small-grain band. [ABSTRACT FROM AUTHOR]

The title compound, C20H19N, is a second polymorph of N,Ndibenzylaniline [Bi, Tong & Zhou (2007). Acta Cryst. E63, o1809-o1810]. The present polymorph and that already reported crystallize in the monoclinic space group P21/n with one and two independent molecules, respectively. The molecular conformations in the two polymorphs are slightly different. [ABSTRACT FROM AUTHOR]

Purpose — Previous literature for the relations between the market interest rates and the targeted or target rate of the Federal Reserve paid little attention to Eurodollar market rates. The present paper attempts to fill this void. Design/methodology/approach — The study investigates the dynamic relationship between the federal funds rate and three short-term Eurodollar deposits rates. Cointegration analysis is utilized to examine the long-run relationships between the short-run dynamics of the market and targeted rates through a vector error-correction mechanism. Findings — The study shows strong evidence that, while the Eurodollar rates and the federal funds rate move together over time regardless of procedural differences in targeting, how they co-move, especially how they adjust toward long-run equilibrium, appears to be related to the targeting procedural changes. Research limitations/implications — Further research should be conducted for the theoretical analysis of strategic interactions between the monetary authority and market participants in the domestic and external financial markets. Practical implications — The result suggests that the Fed may affect the market interest rates through a policy of changing the federal funds rate target by a "fixed" amount for the foreseeable future. Such a policy has improved the market's ability to predict the size and timing of the changes in the target rate. Originality/value — The results of the paper give some new insights into the interactions between monetary policy operations and market interest rates, which is of interest to researchers, monetary authorities, and financial market participants. [ABSTRACT FROM AUTHOR]

• Co-based diamond composites were separately fabricated via the FDMS and the powder hot-pressed sintering technology. • There is a certain difference in the overall performance of the two kinds of specimens. • The Co-based samples fabricated by FDMS form a special coating state for diamond particles. • The Co-based samples fabricated by FDMS have defects of high porosity inside the matrix. • The reduction of knife-cut features can represent the improvement of density and holding ability of the FDMS sample. Fused deposition molding and sintering (FDMS) technology has the characteristics of low cost and low damage to diamonds. In order to explore more possibilities of additive manufacturing diamond tools, FDMS technology was considered to manufacture Co-based diamond composites at different temperatures in this paper. Also, specimens of Co-based diamond composites were manufactured under the same sintering process by using the powder hot-pressed sintering technology. And the matrix microstructure and properties of the specimens made by those two different technologies were analyzed and compared. The results show that a lot of porosity defects were developed inside the specimens manufactured by FDMS. This is because of the specific process characteristics of FDMS. Also, the matrix forms a special coating state for diamond particles due to the binder system used in this study, which causes some diamond particles to suffer slight thermal damage. These all will reduce the density and holding ability of the FDMS specimens. However, when the sintering temperature increases from 800 °C to 880 °C, the performance loss of FDMS samples caused by the porosity defects gradually decreases, thereby reducing the performance difference when comparing with the powder hot-pressed sintering specimens. In addition, the matrix structural uniformity of the FDMS specimens is significantly improved during this process, and the fracture feature changes from intergranular fracture to transgranular fracture. But there is still a certain difference in the overall performance of the two kinds of specimens at the optimal sintering temperature. Therefore, the further optimization of FDMS process parameters and binder system is of great significance for the application of FDMS in diamond tools. [ABSTRACT FROM AUTHOR]

Long non-coding RNAs (lncRNAs) are involved in the development and progression of a variety of diseases. However, the role of the lncRNA HLA complex group 11 (HCG11) in non-small cell lung cancer (NSCLC) remains unclear. The present study showed that the expression levels of HCG11 were reduced in tumor tissues compared with adjacent normal tissues, and similar results were obtained in experiments using lung cancer cell lines. Additionally, patients with high HCG11 expression had an increased survival rate compared with patients with low HCG11 expression. Further studies have shown that overexpression of HCG11 inhibited NSCLC cell proliferation in vitro and in vivo. Interestingly, it was observed that HCG11 expression was negatively associated with the expression levels of oncogenic microRNA-875 (miR-875) in patient specimens. Specifically, HCG11 served as a sponge of miR-875. Notably, it was determined that special AT-rich sequence-binding protein 2 (SATB2) was a direct target gene of miR-875, and overexpression of miR-875 largely abrogated the effects of HCG11 in NSCLC cells. In conclusion, HCG11 was shown to suppress the malignant properties of NSCLC cells by targeting a miR-875/SATB2 axis, and may therefore be a promising target for the treatment of NSCLC. [ABSTRACT FROM AUTHOR]

With the purpose of improving cutting efficiency, nickel-plated graphite particles with different concentrations were added to the Fe-based diamond saw blades (DSB) to investigate the effect of nickel-plated graphites on the cutting performance of DSB. Graphite particles can effectively improve the utilization rate of diamonds by weakening the matrix, creating cavities, forming a graphite lubricating film, and reducing the hot corrosion of diamond particles, thereby effectively improving the sharpness of the DSB. The results of the cutting tests on five different kinds of rock samples show that the DSB can obtain the optimal cutting performance when containing 2% nickel-plated graphite particles, and its average sharpness can increase by 29.89% while the loss of service life is reduced by 51.77%. In addition, the observation and analysis results of the microstructure confirm that plating nickel could effectively increase the ability of the matrix to hold graphite particles. This can effectively protect the matrix materials and the diamond particles on the working surface of the DSB, thereby reducing the loss of service life caused by the addition of graphite particles. Finally, it can be projected that the nickel-plated graphite Fe-based DSB can maximize its advantages when applied to cut the hard rock with large mineral particles. [Display omitted] • Fe-based diamond saw blade with 2% nickel-plated graphite particles has the optimal cutting performance. • Adding graphite particles can effectively enhance the cutting efficiency of diamond saw blades by improving the utilization of diamonds. • Adding graphite particles cause a significant reduction in the service life of diamond saw blades. • Plating nickel can effectively reduce the service life loss of the diamond saw blades caused by adding graphites. • Diamond saw blades containing nickel-plated graphite suit for cutting ard rock formation with a larger mineral particle size. [ABSTRACT FROM AUTHOR]

To address the limited driving range of electric vehicles (EVs) and promote EVs’ penetration, vehicular energy networks (VENs) have emerged and opened possibility to charge EVs in motion via dynamic wireless power transfer (DWPT) technology. However, security and efficiency concerns arise due to the untrusted operating environment and EVs’ selfish charging/discharging behaviors. Existing trust models rely on the personal recommendations from neighboring EVs to identify malicious entities in VENs, which may cause potential privacy breaches and data misuse for recommenders. Besides, it is challenging to optimally schedule EVs’ energy behaviors by considering complex interactions among three energy entities (i.e., energy nodes, charging EVs, and discharging EVs). To this end, by leveraging blockchain technology and game theory, this paper proposes a secure and efficient wireless charging scheme to address these issues in VENs. Firstly, a blockchain-based fine-grained access control mechanism with traceability and auditability is presented to enable EV users to fully control and audit their personal rating data usage during trust management by logging data activities and issuing access tokens into decentralized ledgers. In this manner, the privacy of recommenders can be preserved by fully controlling the access and usage of personal rating data. Furthermore, by introducing cooperative wireless energy transfer mode, a hierarchical game-based energy scheduling algorithm is developed to optimize the strategies of three energy parties tier by tier, while considering their cooperation and competition. Finally, extensive simulations are conducted, which demonstrate that the proposed scheme can effectively improve users’ utility and security of energy transmission for EVs, compared with existing representative approaches. [ABSTRACT FROM AUTHOR]

Phase locking of a laser diode array is demonstrated experimentally by using an off-axis external Talbot cavity with a feedback plane mirror. Due to good spatial mode discrimination, the cavity does not need a spatial filter. By employing the cavity, a clear and stable far-field interference pattern can be observed when the driver current is less than 14 A. In addition, the spectral line width can be reduced to 0.8 nm. The slope efficiency of the phase-locked laser diode array is about 0.62 W/A. [ABSTRACT FROM AUTHOR]

A novel Littman-Metcalf external cavity laser diode array with two feedback mirrors is introduced. The line-width broadening effect caused by smile can be reduced by the novel external cavity. At the drive current of 16 A, the line-width is narrowed to 0.1 nm from free-running width of 1.6 nm with output efficiency of 84%. [ABSTRACT FROM AUTHOR]

Aqueous zinc-ion batteries (AZIBs) have become one of the hotspots in large-scale energy storage due to their advantages of high safety, low cost, and environmental friendliness. However, the metallic Zn anode is prone to dendritic growth and electrochemical corrosion on the surface during cycling, posing a serious challenge to the cycling life of AZIBs. Herein, a simple, low-cost and suitable for mass production method is reported to construct an anti-corrosive nano-copper particle protective coating on the surface of a metallic zinc (Cu–Zn) anode. The prepared nano-copper particles are evenly distributed on the surface of Zn, providing a uniform electric field distribution and successfully suppressing electrochemical corrosion on the surface. Importantly, it is confirmed microscopically that the Cu–Zn anode maintains homogeneous stripping and plating processes, effectively alleviating dendrite formation. Additionally, the resulting Cu–Zn anode exhibits a lower overpotential, which offers a lower interfacial transfer resistance of the battery. The symmetric battery test results show that the unmodified bare Zn anode fails after 58 h at 1 mA cm−2 and 0.5 mA h cm−2, while the Cu–Zn anode can remain stable for more than 3200 h. Furthermore, the assembled Cu–Zn‖‖α-MnO2 battery delivers a capacity of 173.2 mA h g−1 after 2500 cycles at a high current density of 2000 mA g−1, and the capacity retention rate is 90.6%. The results indicate the great potential application of the nano-copper particle-modified zinc anode, which has provided an appealing strategy for improving the stability of AZIBs to promote the industrial development of the energy storage field. [ABSTRACT FROM AUTHOR]

In recent years, materials science and engineering have increasingly focused on advanced composite powders. This study examines the preparation of micro–micro Ti-6Al-4V composite powders by electrostatic adsorption (EA). The necessity of this research lies in the demand for optimizing the Ti-6Al-4V composite powder formation process window for high-performance applications across industries. Achieving optimal EA parameters is crucial for enhancing the quality and efficiency of the powder formation process. In this study, the effect of stirring duration and guest particle loading on the EA process is investigated. The stirring time (1 to 25 min) and guest particle loading (10 to 60%) of the solution are varied to determine the ideal conditions for high adsorption efficiency. It was found that shorter stirring durations (1 min) and a lower guest particle load (10%) have a significant effect on adsorption efficiency. The results were analyzed using the DOE approach to guide future optimization of the process window. The study fills a research gap by utilizing the DOE approach to investigate stirring duration and guest particle loading, providing insights for optimizing the EA process for micro–micro Ti-6Al-4V composite powder. This approach has the potential to enhance cost-effective, durable composite powder production with broad applications in industries like aerospace and automotive. While our research currently focuses on stirring duration and guest particle loading, the application of the DOE approach lays the groundwork for future investigations into additional EA process parameters, such as pH value, particle size, and temperature to expand our understanding of efficient composite powder formation. [ABSTRACT FROM AUTHOR]