Search

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]

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 development of floral organs, crucial for the establishment of floral symmetry and morphology in higher plants, is regulated by MADS-box genes. In sunflower, the capitulum is comprised of ray and disc florets with various floral organs. In the sunflower long petal mutant (lpm), the abnormal disc (ray-like) floret possesses prolongated petals and degenerated stamens, resulting in a transformation from zygomorphic to actinomorphic symmetry. In this study, we investigated the effect of MADS-box genes on floral organs, particularly on petals, using WT and lpm plants as materials. Based on our RNA-seq data, 29 MADS-box candidate genes were identified, and their roles on floral organ development, especially in petals, were explored, by analyzing the expression levels in various tissues in WT and lpm plants through RNA-sequencing and qPCR. The results suggested that HaMADS3, HaMADS7, and HaMADS8 could regulate petal development in sunflower. High levels of HaMADS3 that relieved the inhibition of cell proliferation, together with low levels of HaMADS7 and HaMADS8, promoted petal prolongation and maintained the morphology of ray florets. In contrast, low levels of HaMADS3 and high levels of HaMADS7 and HaMADS8 repressed petal extension and maintained the morphology of disc florets. Their coordination may contribute to the differentiation of disc and ray florets in sunflower and maintain the balance between attracting pollinators and producing offspring. Meanwhile, Pearson correlation analysis between petal length and expression levels of MADS-box genes further indicated their involvement in petal prolongation. Additionally, the analysis of cis-acting elements indicated that these three MADS-box genes may regulate petal development and floral symmetry establishment by regulating the expression activity of HaCYC2c. Our findings can provide some new understanding of the molecular regulatory network of petal development and floral morphology formation, as well as the differentiation of disc and ray florets in sunflower. [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 deployable telescopic boom, whose mass and stiffness play crucial roles, is extensively used in the design of space-deployable structures. However, the most existing optimal design that neglects the influence of the locking mechanisms in boom joints cannot raise the whole stiffness while reducing the boom mass. To tackle this challenge, a novel optimization model, which utilizes the arrangement of the locking mechanisms to achieve synchronous improvement of the stiffness and mass, is proposed. The proposed optimization model incorporates a novel joint stiffness model developed based on an equivalent parallel mechanism that enables the consideration of multiple internal stiffness factors of the locking mechanisms and tubes, resulting in more accurate representations of the joint stiffness behavior. Comparative analysis shows that the proposed stiffness model achieves more than at least 11% improved accuracy compared with existing models. Furthermore, case verification shows that the proposed optimization model can improve stiffness while effectively reducing mass, and it is applied in boom optimization design. [ABSTRACT FROM AUTHOR]

In a local search algorithm, one of its most important features is the definition of its neighborhood which is crucial to the algorithm's performance. In this paper, we present an analysis of neighborhood combination search for solving the single-machine scheduling problem with sequence-dependent setup time with the objective of minimizing total weighted tardiness (SMSWT). First, We propose a new neighborhood structure named Block Swap (B1) which can be considered as an extension of the previously widely used Block Move (B2) neighborhood, and a fast incremental evaluation technique to enhance its evaluation efficiency. Second, based on the Block Swap and Block Move neighborhoods, we present two kinds of neighborhood structures: neighborhood union (denoted by B1⋃B2) and token-ring search (denoted by B1 → B2), both of which are combinations of B1 and B2. Third, we incorporate the neighborhood union and token-ring search into two representative metaheuristic algorithms: the Iterated Local Search Algorithm (ILSnew) and the Hybrid Evolutionary Algorithm (HEAnew) to investigate the performance of the neighborhood union and token-ring search. Extensive experiments show the competitiveness of the token-ring search combination mechanism of the two neighborhoods. Tested on the 120 public benchmark instances, our HEAnew has a highly competitive performance in solution quality and computational time compared with both the exact algorithms and recent metaheuristics. We have also tested the HEAnew algorithm with the selected neighborhood combination search to deal with the 64 public benchmark instances of the single-machine scheduling problem with sequence-dependent setup time. HEAnew is able to match the optimal or the best known results for all the 64 instances. In particular, the computational time for reaching the best well-known results for five challenging instances is reduced by at least 61.25%. [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]

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]

Background: Freezing of gait (FOG) is a common and disabling phenomenon in patients with Parkinson's disease (PD), but effective treatment approach remains inconclusive. Dysfunctional emotional factors play a key role in FOG. Since primary motor cortex (M1) connects with prefrontal areas via the frontal longitudinal system, where are responsible for emotional regulation, we hypothesized M1 may be a potential neuromodulation target for FOG therapy. The purpose of this study is to explore whether high-frequency rTMS over bilateral M1 could relieve FOG and emotional dysregulation in patients with PD. Methods: This study is a single-center, randomized double-blind clinical trial. Forty-eight patients with PD and FOG from the Affiliated Hospital of Xuzhou Medical University were randomly assigned to receive 10 sessions of either active (N = 24) or sham (N = 24) 10 Hz rTMS over the bilateral M1. Patients were evaluated at baseline (T0), after the last session of treatment (T1) and 30 days after the last session (T2). The primary outcomes were Freezing of Gait Questionnaire (FOGQ) scores, with Timed Up and Go Test (TUG) time, Standing-Start 180° Turn (SS-180) time, SS-180 steps, United Parkinson Disease Rating Scales (UPDRS) III, Hamilton Depression scale (HAMD)-24 and Hamilton Anxiety scale (HAMA)-14 as secondary outcomes. Results: Two patients in each group dropped out at T2 and no serious adverse events were reported by any subject. Two-way repeated ANOVAs revealed significant group × time interactions in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14. Post-hoc analyses showed that compared to T0, the active group exhibited remarkable improvements in FOGQ, TUG, SS-180 turn time, SS-180 turning steps, UPDRS III, HAMD-24 and HAMA-14 at T1 and T2. No significant improvement was found in the sham group. The Spearman correlation analysis revealed a significantly positive association between the changes in HAMD-24 and HAMA-14 scores and FOGQ scores at T1. Conclusion: High-frequency rTMS over bilateral M1 can improve FOG and reduce depression and anxiety in patients with PD. [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]

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]

To effectively position the tunnel emergency situations and improve emergency response efficiency, a tunnel emergency positioning system based on Beidou technology has been designed. The types of emergency events, positioning requirements, and the characteristics of positioning technology in highway tunnels are analyzed. Based on the Beidou beacon, the Beidou emergency terminal, and various communication methods, data integration is achieved on the Beidou emergency resource monitoring platform, integrating multimedia scheduling platform to release and receive unified platform information, and providing personnel, equipment, and other positioning data to on-site rescue personnel and rear command personnel quickly, accurately, and effectively. After testing, the time used on positioning is 60.33 s, the positioning error is ≤ 0.6 m, and the time used on data transmission is 0.19 s, which can meet the emergency rescue needs of the tunnel. [ABSTRACT FROM AUTHOR]

The largest marine carbonate oilfield and gas condensate field in China have been found in the Ordovician limestones in the central Tarim Basin. They are defined as large "layered" reef-shoal and karstic reservoirs. However, low and/or unstable oil/gas production has been a big challenge for effective exploitation in ultra-deep (>6000 m) reservoirs for more than 20 years. Together with the static and dynamic reservoir data, we have a review of the unconventional characteristics of the oil/gas fields in that: (1) the large area tight matrix reservoir (porosity less than 5%, permeability less than 0.2 mD) superimposed with localized fracture-cave reservoir (porosity > 5%, permeability > 2 mD); (2) complicated fluid distribution and unstable production without uniform oil/gas/water interface in an oil/gas field; (3) about 30% wells in fractured reservoirs support more than 80% production; (4) high production decline rate is over 20% per year with low recovery ratio. These data suggest that the "sweet spot" of the fractured reservoir rather than the matrix reservoir is the major drilling target for ultra-deep reservoir development. In the ultra-deep pre-Mesozoic reservoirs, further advances in horizontal drilling and large multiple fracturing techniques are needed for the economic exploitation of the matrix reservoirs, and seismic quantitative descriptions and horizontal drilling techniques across the fault zones are needed for oil/gas efficient development from the deeply fractured reservoirs. [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]

Advanced persistent threat (APT) is a kind of stealthy, sophisticated, and long-term cyberattack that has brought severe financial losses and critical infrastructure damages. Existing works mainly focus on APT defense under stable network topologies, while the problem under time-varying dynamic networks (e.g., vehicular networks) remains unexplored, which motivates our work. Besides, the spatiotemporal dynamics in defense resources, complex attackers’ lateral movement behaviors, and lack of timely defense make APT defense a challenging issue under time-varying networks. In this paper, we propose a novel game-theoretical APT defense approach to promote real-time and optimal defense strategy-making under both periodic time-varying and general time-varying environments. Specifically, we first model the interactions between attackers and defenders in an APT process as a dynamic APT repair game, and then formulate the APT damage minimization problem as the precise prevention and control (PPAC) problem. To derive the optimal defense strategy under both latency and defense resource constraints, we further devise an online optimal control-based mechanism integrated with two backtracking-forward algorithms to fastly derive the near-optimal solution of the PPAC problem in real time. Extensive experiments are carried out, and the results demonstrate that our proposed scheme can efficiently obtain optimal defense strategy in 54481 ms under seven attack-defense interactions with 9.64% resource occupancy in stimulated periodic time-varying and general time-varying networks. Besides, even under static networks, our proposed scheme still outperforms existing representative APT defense approaches in terms of service stability and defense resource utilization. [ABSTRACT FROM AUTHOR]

Due to the limited battery and computing resource, offloading unmanned aerial vehicles (UAVs)’ computation tasks to ground infrastructure, e.g., vehicles, is a fundamental framework. Under such an open and untrusted environment, vehicles are reluctant to share their computing resource unless provisioning strong incentives, privacy protection, and fairness guarantee. Precisely, without strategy-proofness guarantee, the strategic vehicles can overclaim participation costs so as to conduct market manipulation. Without the fairness provision, vehicles can deliberately abort the assigned tasks without any punishments, and UAVs can refuse to pay by the end, causing an exchange dilemma. Lastly, the strategy-proofness and fairness provision typically require transparent payment/task results exchange under public audit, which may disclose sensitive information of vehicles and make the privacy preservation a foremost issue. To achieve the three design goals, we propose SEAL, an integrated framework to address Strategy-proof, fair, and privacy-prEserving UAV computation offLoading. SEAL deploys a strategy-proof reverse combinatorial auction mechanism to optimize UAVs’ task offloading under practical constraints while ensuring economic-robustness and polynomial-time efficiency. Based on smart contracts and hashchain micropayment, SEAL implements a fair on-chain exchange protocol to realize the atomic completion of batch payments and computing results in multi-round auctions. In addition, a privacy-preserving off-chain auction protocol is devised with the assistance of the trusted processor to efficiently protect vehicles’ bid privacy. Using rigorous theoretical analysis and extensive simulations, we validate that SEAL can effectively prevent vehicles from manipulating, ensure privacy protection and fairness, improve the offloading efficiency, and reduce UAV’s energy costs and expenses with low overheads. [ABSTRACT FROM AUTHOR]

Hypoxic-ischemic encephalopathy (HIE) is the leading cause of long-term neurological disability in neonates and adults. Through bibliometric analysis, we analyzed the current research on HIE in various countries, institutions, and authors. At the same time, we extensively summarized the animal HIE models and modeling methods. There are various opinions on the neuroprotective treatment of HIE, and the main therapy in clinical is therapeutic hypothermia, although its efficacy remains to be investigated. Therefore, in this study, we discussed the progress of neural circuits, injured brain tissue, and neural circuits-related technologies, providing new ideas for the treatment and prognosis management of HIE with the combination of neuroendocrine and neuroprotection. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to investigate the feasibility of Transcranial Doppler Ultrasonography (TCD) in evaluating neonatal hypoxic-ischemic encephalopathy (NHIE) modeling through monitoring the alteration of cerebrovascular flow in neonatal hypoxic-ischemic (HI) rats. Methods: Postnatal 7-day-old Sprague Dawley (SD) rats were divided into the control group, HI group, and hypoxia (H) group. TCD was applied to assess the changes of cerebral blood vessels, cerebrovascular flow velocity, and heart rate (HR) in sagittal and coronal sections at 1, 2, 3, and 7 days after the operation. For accuracy, cerebral infarct of rats was examined by 2,3,5-Triphenyl tetrazolium chloride (TTC) staining and Nissl staining to simultaneously verify the establishment of NHIE modeling. Results: Coronal and sagittal TCD scans revealed obvious alteration of cerebrovascular flow in main cerebral vessels. Obvious cerebrovascular backflow was observed in anterior cerebral artery (ACA), basilar artery (BA), middle cerebral artery (MCA) of HI rats, along with accelerated cerebrovascular flows in the left internal carotid artery (ICA-L) and BA, decreased flows in right internal carotid artery (ICA-R) relative to those in the H and control groups. The alterations of cerebral blood flows in neonatal HI rats indicated successful ligation of right common carotid artery. Besides, TTC staining further validated the cerebral infarct was indeed caused due to ligation-induced insufficient blood supply. Damage to nervous tissues was also revealed by Nissl staining. Conclusion: Cerebral blood flow assessment by TCD in neonatal HI rats contributed to cerebrovascular abnormalities observed in a real-time and non-invasive way. The present study elicits the potentials to utilize TCD as an effective means for monitoring the progression of injury as well as NHIE modeling. The abnormal appearance of cerebral blood flow is also beneficial to the early warning and effective detection in clinical practice. [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]

An amendment to this paper has been published and can be accessed via the original article. [ABSTRACT FROM AUTHOR]

Epstein–Barr virus (EBV) is an oncogenic herpesvirus associated with several cancers of lymphocytic and epithelial origin1–3. EBV encodes EBNA1, which binds to a cluster of 20 copies of an 18-base-pair palindromic sequence in the EBV genome4–6. EBNA1 also associates with host chromosomes at non-sequence-specific sites7, thereby enabling viral persistence. Here we show that the sequence-specific DNA-binding domain of EBNA1 binds to a cluster of tandemly repeated copies of an EBV-like, 18-base-pair imperfect palindromic sequence encompassing a region of about 21 kilobases at human chromosome 11q23. In situ visualization of the repetitive EBNA1-binding site reveals aberrant structures on mitotic chromosomes characteristic of inherently fragile DNA. We demonstrate that increasing levels of EBNA1 binding trigger dose-dependent breakage at 11q23, producing a fusogenic centromere-containing fragment and an acentric distal fragment, with both mis-segregated into micronuclei in the next cell cycles. In cells latently infected with EBV, elevating EBNA1 abundance by as little as twofold was sufficient to trigger breakage at 11q23. Examination of whole-genome sequencing of EBV-associated nasopharyngeal carcinomas revealed that structural variants are highly enriched on chromosome 11. Presence of EBV is also shown to be associated with an enrichment of chromosome 11 rearrangements across 2,439 tumours from 38 cancer types. Our results identify a previously unappreciated link between EBV and genomic instability, wherein EBNA1-induced breakage at 11q23 triggers acquisition of structural variations in chromosome 11.Epstein–Barr Virus (EBV) nuclear antigen 1 is shown to induce breakage of a fragile site on chromosome 11 by binding to a cluster of EBV-like imperfect palindromic repeats. [ABSTRACT FROM AUTHOR]

Background: Despite rapid developments in immunotherapy and targeted therapy, dacarbazine (DTIC)-based chemotherapy still has been placed at the first-line for advanced melanoma patients who are after failure of immunotherapy or targeted therapy. However, the limited response rate and survival benefit challenge the DTIC-based chemotherapy for advanced melanoma patients. Methods: Two melanoma cell lines, A375 and SK-MEL-28 were cultured with PA and DTIC over a range of concentrations for 72 h and the cell viabilities were detected by CCK8 assay. The Bliss model and ZIP model were used for calculating the synergistic effect of PA and DTIC. DNA double-strand breaks in the two cell lines were examined by the Comet assay, and cell apoptosis was analyzed by flow cytometry. The short hairpin RNA (shRNA)-mediated knockdown, Real-time polymerase chain reaction (RT-PCR) and Western blot were performed for molecular analysis. Results: In the present study, we report that Protocatechuic aldehyde (PA) synergistically enhances the cytotoxicity of DTIC to two melanoma cell lines, A375 and SK-MEL-28. The combination of PA and DTIC augments DNA double-strand breaks and increases cell apoptosis. Further mechanism study reveals that PA destabilizes MGMT protein (O-6-Methylguanine-DNA Methyltransferase) through the ubiquitin-proteasome process and directly repairs DTIC-induced genetic lesions. Knockdown of MGMT compromises the synergistic effect between PA and DTIC. Conclusion: Our study demonstrates that the bioactive compound, Protocatechuic aldehyde, synergistically promotes the cytotoxicity of DTIC to melanoma cells through destabilization of MGMT protein. It could be a potential candidate for melanoma chemotherapy. [ABSTRACT FROM AUTHOR]

Aims: Tirzepatide is a novel dual glucose-dependent insulinotropic peptide (GIP) and glucagon-like peptide-1 receptor agonist (GLP-1 RA). At present, there is no controversy over its effectiveness, but its safety. We conducted a systematic review to assess the safety of tirzepatide. Methods: We searched PubMed, Embase and Cochrane databases for randomized controlled trials (RCTs) of tirzepatide from databases inception to August 28, 2022 and used the Cochrane Systematic Assessment Manual Risk of Bias Assessment Tool (version 5.1) and modified Jadad scale to assess risk of bias. The systematic review was conducted via Revman5.4. Results: Nine RCTs with a total of 9818 patients were included. The overall safety profile of tirzepatide is similar to GLP-1RAs, except for the hypoglycemia (tirzepatide 15mg, pooled RR=3.83, 95% CI [1.19- 12.30], P=0.02) and discontinuation (tirzepatide 10mg, pooled RR=1.75,95%CI[1.16-2.63], P=0.007 and 15mg, pooled RR=2.03, 95%CI [1.37-3.01], P=0.0004). It also showed that the dose escalation could not rise the occurrence rates of total, severe, gastrointestinal adverse events and hypoglycemia (P>0.05); Compared with 5mg, tirzepatide 10mg and 15mg were associated with more frequent nausea (P<0.001), discontinuation (P<0.05) and injection-site reaction (P<0.01); The rates of vomiting and diarrhea were dose-dependence at the range of 5-15mg. Conclusion: The safety profile of tirzepatide is generally acceptable, similar to GLP-1 RAs. It is necessary to pay attention to its specific adverse events (hypoglycemia and discontinuation) at high doses (10mg or higher). Nausea, vomiting, diarrhea, discontinuation and injection-site reaction were dose dependence among specific dose ranges.As the heterogeneity in different studies by interventions, the results may be with biases and the further confirmation is needed. Meanwhile, more well-designed trials are needed to control the confounding factors and ensure adequate sample size. [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]

Proof of work (PoW), as the representative consensus protocol for blockchain, consumes enormous amounts of computation and energy to determine bookkeeping rights among miners but does not achieve any practical purposes. To address the drawback of PoW, we propose a novel energy-recycling consensus mechanism named platform-free proof of federated learning (PF-PoFL), which leverages the computing power originally wasted in solving hard but meaningless PoW puzzles to conduct practical federated learning (FL) tasks. Nevertheless, potential security threats and efficiency concerns may occur due to the untrusted environment and miners’ self-interested features. In this paper, by devising a novel block structure, new transaction types, and credit-based incentives, PF-PoFL allows efficient artificial intelligence (AI) task outsourcing, federated mining, model evaluation, and reward distribution in a fully decentralized manner, while resisting spoofing and Sybil attacks. Besides, PF-PoFL equips with a user-level differential privacy mechanism for miners to prevent implicit privacy leakage in training FL models. Furthermore, by considering dynamic miner characteristics (e.g., training samples, non-IID degree, and network delay) under diverse FL tasks, a federation formation game-based mechanism is presented to distributively form the optimized disjoint miner partition structure with Nash-stable convergence. Extensive simulations validate the efficiency and effectiveness of PF-PoFL. [ABSTRACT FROM AUTHOR]

The smart ocean has been regarded as an integrated sensing, communication, and computing ecosystem developed for connecting marine objects in surface and underwater environments. The development of the smart ocean is expected to support a variety of marine applications and services such as resource exploration, marine disaster rescuing, and environment monitoring. However, the complex and dynamic marine environments and the limited network resources raise new challenges in marine communication and computing, especially for these computing-intensive and delay-sensitive tasks. Recently, the space–air–ground–sea integrated networks have been envisioned as a promising network framework to enhance the communication and computing performance. In this paper, we conduct a comprehensive survey on the integrated sensing, communication, and computing networks (ISCCNs) for smart oceans based on the collaboration of space–air–ground–sea networks from four domains (i.e., space layer, aerial layer, sea surface layer, and underwater layer), and five aspects (i.e., sensing-related, communication-related, computation-related, security-related, and application-related). Specifically, we provide the key technologies for the ISCCNs in smart oceans, and introduce the state-of-the-art marine sensing, communication, and computing paradigms. The emerging challenges with the potential solutions of the ISCCNs for smart oceans are illustrated to enable the intelligent services. Moreover, the new applications for the ISCCNs in smart oceans are discussed, and potential research directions in smart oceans are provided for future works. [ABSTRACT FROM AUTHOR]

With the ever-increasing demand for the content delivery services in autonomous vehicular networks (AVNs), caching popular contents in the edge nodes in advance is expected to reduce the transmission delay. Current works on the contents cached in connected and autonomous vehicles (CAVs) or roadside units (RSUs) are facing the problems of limited caching size and high deployment cost. In this paper, by exploiting the advantages of high caching space and flexibility of truck platoons composed of connected and autonomous trucks (CATs), we propose a secure content delivery service for CATs based on coalition formation game. Firstly, in order to protect the security and privacy of content delivery services, a differential privacy model is proposed to protect the sensitive information of CATs. Meanwhile, the differential privacy model is combined with the incentive based trust evaluation model to monitor the behaviors of CATs. In the incentive based models, CATs are encouraged to improve their trust values to obtain higher utilities and find a balance between confidence levels and utilities. Moreover, a coalition formation game is established among CATs with the same driving route, in which all CATs can maximize their utilities with the formation of several minor coalitions. Finally, we conduct extensive simulations to demonstrate the effectiveness and superiority of the proposed scheme. [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]

NASICON‐type material NaTi2(PO4)3 has a suitable working potential (−0.87 V vs saturated calomel electrode) in aqueous sodium‐ion cells. Nevertheless, the inherent electronic conductivity in the internal core and external shell limits its rate and cycling performance. Herein, a carbon‐coated porous nanosphere NaTi2(PO4)3 material is synthesized by the solvothermal method. This structure effectively improves the electrical conductivity, enlarges the contact area with the electrolyte, and facilitates the rapid intercalation/deintercalation of Na+. It delivers an excellent rate behavior of 123.59, 113.55, 102.81, 90.85, and 60.95 mAh g−1 at 0.2, 0.5, 1, 2, and 5 A g−1, respectively. Improved long cyclability under a 5 A g−1 high current density is also demonstrated by a capacity retention of 70.2% over 500 cycles and an average Coulombic efficiency of 98%. As‐prepared core–shell porous nanosphere NaTi2(PO4)3 exhibits potentially practical applications in a new type of aqueous sodium‐ion battery system. [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]

Space-air-ocean integrated networks (SAOINs), composed of low earth orbit (LEO) satellites, unmanned aerial vehicles (UAVs), and unmanned surface vehicles (USVs), have been advocated to provide seamless, high-rate, and reliable wireless transmission services for USVs. However, due to the restrictions of limited resources (e.g., spectrum bandwidth, transmission power, etc.), diverse demands of USVs, and selfishness of both UAVs and LEOs, there comes a significant challenge to provision high-quality wireless data rate for USVs to achieve their satisfied quality of experience (QoE). To this end, in this paper, we propose a hierarchical on-demand wireless data rate provisioning scheme to provide ubiquitous transmission services for USVs. Specifically, we first devise a hierarchical wireless data rate provisioning framework. The LEO satellite with an extensive wireless coverage is utilized to provide LEO satellite-to-UAV (L2U) data rate for UAVs with a certain L2U data rate price. Each UAV is employed to provide UAV-to-USV (U2U) data rate for covered multiple USVs with a certain U2U data rate price. We then propose a modified three-stage Stackelberg game to model the wireless data rate assignments among LEO satellites, UAVs, and USVs, where the time-varying data rate demands of USVs are considered to formulate the utility maximization problem. Afterwards, the backward induction approach is leveraged to attain the Stackelberg equilibrium as the solution of the formulated problem, where the closed-form expressions on the optimal strategies of both USVs and UAVs under different data rate budgets are obtained by the nonlinear programming method. Besides, an accelerated conjugate gradient descent (ACGD) based iteration algorithm is also designed to obtain the optimal strategies of the LEO satellites on the L2U data rate prices. At last, extensive simulations are carried out to demonstrate that the proposed scheme can significantly increase the utilities of USVs, as compared to other benchmark schemes. [ABSTRACT FROM AUTHOR]

As the natural disasters may destroy the ground communication infrastructures for the transportation systems, the communication relief in post-disaster networks is more crucial to reduce risk loss. The growing application of unmanned aerial vehicles (UAVs) holds great potential for disaster communication relief due to its flexibility and functionalities. In this paper, we investigate the channel allocation and data delivery problems for UAV-assisted cooperative transportation communications in post-disaster networks to provide communication and data delivery services for affected users. Specifically, we first introduce the UAV-assisted communication relief system, in which UAVs equipped with the communication and caching functionalities are deployed as the aerial base stations in post-disaster regions. Then, we propose the channel allocation scheme between UAVs and users by taking the interferences into consideration, and obtain the channel allocation strategy to improve the network throughput. Based on the optimal channel allocation strategy, users can deliver their data to UAVs for backup. Next, we propose the data delivery scheme to cope with the pricing problem for UAVs and the data delivery strategy for users to improve the efficiency of data delivery, with the objective of maximizing the utilities of both UAVs and users. The optimal strategy for both UAVs and users are derived according to the analysis of Stackelberg game. Finally, we conduct simulations to evaluate the performance of the proposed channel allocation and data delivery scheme, and the numerical results demonstrate that the proposed scheme can significantly improve the efficiency and effectiveness of channel allocation and data delivery in post-disaster networks, compared with benchmark schemes. [ABSTRACT FROM AUTHOR]

Aqueous alkaline batteries (AABs) with the merits of both high energy density and power density have emerged as one of the most promising candidates for the new generation of energy storage devices, while their practical applications are still limited by the lack of high-performance electrode materials, especially for the anode materials. Herein, metallic bismuth–bismuth oxide nanoparticles (Bi–Bi2O3), with numerous heterogeneous interfaces, are successfully anchored and uniformly distributed on reduced graphene oxide (rGO) sheets. When Bi–Bi2O3/rGO-20 electrode is used as the anode material for an AAB, it shows a high specific capacity of 288.0 mA h g−1 (1036.9 F g−1) at 1 A g−1 and good rate capability (74.7% of capacity retention ratio at 20 A g−1). Additionally, in order to match well with a Bi–Bi2O3/rGO-20 anode, CoVSx thin sheets decorated with Ni–Co layered double hydroxide sheets (NiCo-LDH) were successfully constructed via a facile multistep hydrothermal method and a subsequent electrodeposition process. The resulting cathode exhibits a high specific capacity of 306.0 mA h g−1 (2448 F g−1) at 1 A g−1. The assembled CoVSx@NiCo-LDH//Bi–Bi2O3/rGO-20 AAB delivers an outstanding energy density of 106.1 Wh kg−1 at a power density of 789.6 W kg−1. Besides, the as-synthesized Bi-based electrode is also used in aqueous Zn alkaline batteries to further extend its application and the assembled Bi–Bi2O3/rGO-20//Zn batteries possess an ultralong flat discharge plateau and exhibit a specific capacity of 250.6 mA h g−1 at 1 A g−1. The results demonstrate that the as-assembled AAB has huge potential for practical applications and provides an inspiration for the next-generation energy storage devices. [ABSTRACT FROM AUTHOR]

Feature extraction is a key step for fault diagnosis of rolling bearings based on vibration measurements. Lempel-Ziv complexity (LZC) has been widely applied to extracting fault features. However, LZC with single-scale analysis may result in the loss of fault information. Then, the multiscale LZC is proposed to uncover the multiscale features. Nevertheless, multiscale LZC would shorten the length of sequences, leading to inaccurate calculation results. Moreover, the mean operation during the coarse-grained process of the traditional multiscale analysis cannot reveal the dynamic changes of the original sequences, which may also result in the loss of potential information. Thus, this paper develops a feature extraction method called generalized variable-step multiscale LZC (GVSMLZC) for the vibration-based fault diagnosis of rolling bearings. GVSMLZC reveals more information and gains more robust complexity by improving the coarse-grained process. Moreover, GVSMLZC enhances the capability of mining dynamic characteristics by generalizing first-order moments to second-order moments. Based on the proposed GVSMLZC, fault type identification and fault detection of life-cycle data schemes are designed to realize the fault diagnosis of rolling bearings. Simulated and experimental results demonstrate that GVSMLZC outperforms multiscale LZC, variable-step multiscale LZC, and multiscale sample entropy in extracting bearing fault information. [ABSTRACT FROM AUTHOR]

The cusp is a region in which the solar wind plasma can directly penetrate into the ionosphere. Most previous studies mainly focused on the low‐ and high‐latitude boundaries of the cusps, the identification of the dawnside and duskside boundaries of them appears to be questionable. The auroras are the ionospheric manifestations of solar‐terrestrial energy coupling. This paper presents a new approach to diagnose the duskside boundary of the cusp with the observation of a particular polar cap arc (PCA) located near the ∼1500 magnetic local time sector (15MLT‐PCA). Using measurements from Defense Meteorological Satellite Program satellite, we selected several 15MLT‐PCA examples where the satellite flew over different regions and analyze the particle characteristics. We identified the precipitating particles in dawnside and duskside regions next to 15MLT‐PCA are from the low latitude boundary layer/cusp and boundary plasma sheet/central plasma sheet respectively. The statistical result further confirms our findings. Therefore, we proposed that 15MLT‐PCA can be used as an identifiable optical signature of the duskside boundary of the cusp. This paper provides a valuable approach to identify the cusp boundaries, and the results are critical for understanding the generation mechanism of 15MLT‐PCA. Plain Language Summary: The polar cusps are important regions in which the particles originating from the solar wind can directly enter the upper atmosphere. Those precipitating particles can produce auroras in the ionosphere. The polar cusps have been studied in great detail for several decades and their properties have been characterized under different interplanetary magnetic field conditions. Until now, how to determine the cusp boundaries is still a topic of investigation. This study emphasizes one special auroral phenomenon called 1500 magnetic local time‐polar cap arc (15MLT‐PCA), and we check the particle distributions around 15MLT‐PCA using the observations provided by the Defence Meteorological Satellite Program satellite. We found that the 15MLT‐PCA occurs at the duskside boundary of the cusp, thus allowing the possibility that 15MLT‐PCA can be regarded as an optical signature of duskside boundary of the cusp. Key Points: The 1500 magnetic local time‐polar cap arc (15MLT‐PCA) is suggested to be an auroral indicator of the duskside boundary of the cuspAt the dawnside (duskside) auroral oval of 15MLT‐PCA, the precipitating particles appear as low latitude boundary layer (LLBL)/cusp (boundary plasma sheet/central plasma sheet [BPS/CPS]) characteristicsThe 15MLT‐PCA can be viewed as a separator between dayside LLBL/cusp and duskside CPS/BPS auroras [ABSTRACT FROM AUTHOR]

Natural disasters often cause huge and unpredictable losses to human lives and properties. In such an emergency post-disaster rescue situation, unmanned aerial vehicles (UAVs) are effective tools to enter the damaged areas to perform immediate disaster recovery missions, owing to their flexible mobilities and fast deployment. However, UAVs typically have very limited battery and computational capacities, which makes them harder to perform heavy computation tasks during the complicated disaster recovery process. This paper addresses the issue of the battery and computation resource limitation with a fog computing based UAV system. Specifically, we first introduce the vehicular fog computing (VFC) system in which the unmanned ground vehicles (UGVs) perform the computation tasks offloaded from UAVs. To avoid the transmission competitions yet enable cooperations among UAVs and UGVs, a stable matching algorithm is developed to transform the computation task offloading problem into a two-sided matching problem. An iterative algorithm is then developed which matches each UAV with the most suitable UGV for offloading. Finally, extensive simulations are carried out to demonstrate that the proposed scheme can effectively improve utilities of UAVs and reduce average delay through comparison with conventional schemes. [ABSTRACT FROM AUTHOR]

Continuous exploration has triggered a heated debate on hydrocarbon resource potential in the southern slope zone of the Kuqa foreland basin, and sources of the Mesozoic-Cenozoic oil and gas have become a key problem to be solved in this region. Composition and organic geochemical parameters of crude oil and natural gas from the southern slope zone of the Kuqa foreland basin were illustrated in order to reveal their origin by using a combination of gas chromatograph (GC), gas chromatogram-mass spectrum (GC-MS) and carbon isotope analyses. The characteristics of crude oil, such as low density, viscosity, solidification point and sulfur content, and high wax content, indicate that source of the crude oil is continental. The biomarker compositions of crude oil are characterized by low to medium molecular weight compounds (n-C12 to n-C20), high Pr/Ph ratios (>1.0), low phytane/n-C18 ratios (0.06–0.54), and predominant regular sterane C29. All biomarker parameters clearly indicate that the crude oil was derived mainly from algae and aquatic plankton and deposited under weak reduction-oxidation environment, and has the characteristics of mixed kerogens. The Cretaceous crude oil was mainly derived from the Triassic lacustrine source rocks, which also contributed to the Paleogene crude oil together with Jurassic coal source rocks. Natural gas is characterized by moderate methane content, high heavy hydrocarbon and nitrogen content, and no hydrogen sulfide. The methane and ethane in Paleogene natural gas are relatively rich in 13C with δ13C1 and δ13C2 values ranging from −37.3‰ to −31.2‰ (mean = −34.25‰) and from −25‰ to −21.3‰ (mean = −23.09‰), respectively, indicating the coal-derived gas from the Middle and Lower Jurassic strata. Hydrocarbon products in the southern slope zone of the Kuqa foreland basin are primarily generated from source rocks in the mature stage. The low-amplitude structural and lithologic traps with the updip pinch-out sand bodies or plugging secondary fault at relatively high tectonic positions are the most favorable areas for discovery and breakthrough in the study area. Results of this study will provide useful information for controlling factors of reservoirs and oil and gas exploration deployment in the southern slope zone of the Kuqa foreland basin. [ABSTRACT FROM AUTHOR]

The autonomous vehicles (AVs) in smart city, as intelligent mobile robots, are expected to provide diversified services to facilitate the life of citizens. However, the attributes of the services requested by users are different and the statuses of the AVs managed by different central servers are dynamically changed. To execute the services with the minimum cost based on the requirements of users and the statuses of AVs therefore becomes a challenge. In this article, we establish an intelligent multi-attribute service response framework in smart city based on the request of users and the response of AVs. In the first phase of the framework, each central server decides the minimum service execution cost (SEC) to respond to the user’s service by considering the available resources of its AVs, where the minimization problems are formulated for the services with one attribute and the services with multiple attributes, respectively. To address the problems, the optimal AV selection (OAVS) algorithm for the services with one attribute and the OAVS-M algorithm for the services with multiple attributes are designed. In the second phase, based on the SEC of each central server, an auction game is developed to model the competition among the central servers to help the user select the optimal one to execute the service with the lowest service transaction price (STP). By achieving the Nash equilibrium of the game, the optimal strategy of each central server to win the chance for executing the service is obtained. The simulation results show that the designed framework can reduce the STP compared with the conventional schemes. [ABSTRACT FROM AUTHOR]

BACKGROUND In monsoonal climates, grape anthocyanin and proanthocyanidin (PA) accumulations are unsatisfactory for producing optimal wine. Agronomical practices are often considered to be effective means for regulating fruit components. However, there is a lack of quantitative information on the effects of deficit irrigation (DI), basal leaf removal (LR) or their combination of deficit irrigation and leaf removal (DILR) on the characteristics of anthocyanin and PA compositions and their implications on the resulting wine quality. In this study, the dynamics of grape anthocyanin and PA accumulation were investigated in DI, LR and DILR during grape ripening, and the resulting wine profile was assessed. RESULTS: The contents of reducing sugar and total anthocyanins in Cabernet Sauvignon berries were significantly increased by DI, LR and DILR, while titratable acidity, total flavan‐3‐ols and tannins levels were generally decreased. Notably, the levels of 3′5′‐substituted anthocyanins, such as malvidin and its derivatives significantly increased, and 3′‐substituted anthocyanins decreased in both grape and wine under DI and DILR strategies. Skin PAs were sensitive to water deficits, whereas they were insensitive to LR. In resulting wine, PAs content and the proportion of 3′‐hydroxylated PAs, such as (+)‐catechin, (−)‐epicatechin and (−)‐epicatechin‐3‐O‐gallate units were significantly decreased under DI and DILR, while molecular mass and the proportion of 3′5′‐hydroxylated units of PAs were increased in response to DILR. CONCLUSION: The DILR was the most favorable for the repartitioning of anthocyanin and PA metabolites, and promoted the accumulation of tri‐substituted forms contributing a higher color intensity, mouthfeel persistence, structure, and astringency of wine. This information provides an important strategy for modulating the anthocyanin and PA compositions by agricultural practices and achieving the desired quality of grapes and wines in monsoonal climates. © 2021 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

With the prevalence of smart appliances, smart meters, and Internet of Things (IoT) devices in smart grids, artificial intelligence (AI) built on the rich IoT big data enables various energy data analysis applications and brings intelligent and personalized energy services for users. In conventional AI of Things (AIoT) paradigms, a wealth of individual energy data distributed across users’ IoT devices needs to be migrated to a central storage (e.g., cloud or edge device) for knowledge extraction, which may impose severe privacy violation and data misuse risks. Federated learning, as an appealing privacy-preserving AI paradigm, enables energy data owners (EDOs) to cooperatively train a shared AI model without revealing the local energy data. Nevertheless, potential security and efficiency concerns still impede the deployment of federated-learning-based AIoT services in smart grids due to the low-quality shared local models, non-independently and identically distributed (non-IID) data distributions, and unpredictable communication delays. In this article, we propose a secure and efficient federated-learning-enabled AIoT scheme for private energy data sharing in smart grids with edge-cloud collaboration. Specifically, we first introduce an edge-cloud-assisted federated learning framework for communication-efficient and privacy-preserving energy data sharing of users in smart grids. Then, by considering non-IID effects, we design a local data evaluation mechanism in federated learning and formulate two optimization problems for EDOs and energy service providers. Furthermore, due to the lack of knowledge of multidimensional user private information in practical scenarios, a two-layer deep reinforcement-learning-based incentive algorithm is developed to promote EDOs’ participation and high-quality model contribution. Extensive simulation results show that the proposed scheme can effectively stimulate EDOs to share high-quality local model updates and improve the communication efficiency. [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]

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]

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 exponential growth of data generated from increasing smart meters and smart appliances brings about huge potentials for more efficient energy production, pricing, and personalized energy services in smart grids. However, it also causes severe concerns due to improper use of individuals’ private data, as well as the lack of transparency and auditability for data usage. To bridge this gap, in this article, we propose a secure and auditable private data sharing (SPDS) scheme under data processing-as-a-service mode in smart grid. Specifically, we first present a novel blockchain-based framework for trust-free private data computation and data usage tracking, where smart contracts are employed to specify fine-grained data usage policies (i.e., who can access what kinds of data, for what purposes, at what price) while the distributed ledgers keep an immutable and transparent record of data usage. A trusted execution environment based off-chain smart contract execution mechanism is exploited as well to process confidential user datasets and relieve the computation overhead in blockchain systems. A two-phase atomic delivery protocol is designed to ensure the atomicity of data transactions in computing result release and payment. Furthermore, based on contract theory, the optimal contracts are designed under information asymmetry to stimulate user's participation and high-quality data sharing while optimizing the payoff of the energy service provider. Extensive simulation results demonstrate that the proposed SPDS can effectively improve the payoffs of participants, compared with conventional schemes. [ABSTRACT FROM AUTHOR]

Reliable and flexible emergency networks are of paramount essence for disaster relief during or after the event of disasters due to the destruction or lack of terrestrial communication infrastructures. Thanks to fast deployment and flexible mobilities, unmanned aerial vehicles (UAVs) emerge as a promising paradigm to efficiently establish emergency networks and perform immediate disaster relief tasks in affected areas. However, in such UAV-assisted disaster relief networks (UDRNs), the limited onboard batteries and computational capacities of UAVs hinder them from performing computation-intensive missions. Moreover, critical security vulnerabilities arise in data transmission among UAVs owing to the untrusted environment, open communication channels, and unreliable misbehavior tracing. To this end, this article investigates UDRNs based on blockchain and machine learning to achieve secure and efficient data transmission. Specifically, we first present a lightweight blockchain-enabled collaborative aerial-ground networking framework to safeguard data delivery under disasters, where a credit-based delegated proof-of-stake consensus protocol is further devised to enhance consensus efficiency while promoting UAVs' honest behaviors. In addition, by harnessing the idle computing power of ground vehicles (referred to as vehicular fog computing), a novel reinforcement learning-based algorithm is developed to intelligently offload UAVs' computation missions to the moving vehicles in the dynamic environment. Experimental results demonstrate that the proposed framework outperforms the existing approaches, in terms of consensus security, user utility, task latency, and energy consumption. Finally, future research directions in this emerging area are discussed. [ABSTRACT FROM AUTHOR]