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IntroductionSleep disorders are prevalent and significant among individuals receiving methadone maintenance treatment (MMT), adversely affecting their quality of life and treatment adherence. While cerebral blood flow (CBF) plays a crucial role in the development of various diseases, its relationship with sleep disorders remains uncertain. This observational study focuses on possible correlations between CBF and poor subjective sleep quality in MMT patients.MethodsA total of 75 participants with a history of MMT were recruited and assessed using pseudo-continuous arterial spin labeling magnetic resonance imaging to determine CBF. A LAASO regression model was employed to identify the region of interest (ROI) most associated with sleep disturbance. The association between the CBF of the ROI and the Pittsburgh Sleep Quality Index (PSQI) was examined using regression analyses. Age, gender, BMI, history of hypertension, diabetes, hyperlipidemia, and methadone withdrawal were included as covariates.ResultsAmong MMT patients with poor subjective sleep quality, significantly higher CBF was observed in the right paracentral lobule (56.1057 ± 11.1624 ml/100 g/min, p = 0.044), right cerebelum_3 (56.6723 ± 15.3139 ml/100 g/min, p = 0.026), right caudate nucleus (48.9168 ± 6.9910 ml/100 g/min, p = 0.009), and left caudate nucleus (47.6207 ± 6.1374 ml/100 g/min, p = 0.006). Furthermore, a positive correlation was found between CBF in the right paracentral lobule and the total PSQI score (β = 0.1135, p = 0.0323), with the association remaining significant even after adjustment for covariates (β = 0.1276, p = 0.0405).ConclusionMMT patients with poor subjective sleep quality exhibited significantly altered CBF in multiple brain regions. The association between increased CBF in the right paracentral lobule and subjective sleep quality in MMT patients could be crucial in understanding sleep disorders in individuals undergoing MMT.Clinical trial registrationhttps://www.chictr.org.cn/, identifier: ChiCTR2100051931.

Abstract Electrical stimulation of the peripheral nervous system (PNS) is becoming increasingly important for the therapeutic treatment of numerous disorders. Thus, as peripheral nerves are increasingly the target of electrical stimulation, it is critical to determine how, and when, electrical stimulation results in anatomical changes in neural tissue. We introduce here a convolutional neural network and support vector machines for cell segmentation and analysis of histological samples of the sciatic nerve of rats stimulated with varying current intensities. We describe the methodologies and present results that highlight the validity of the approach: machine learning enabled highly efficient nerve measurement collection, while multivariate analysis revealed notable changes to nerves’ anatomy, even when subjected to levels of stimulation thought to be safe according to the Shannon current limits.

Abstract Airborne transmission by droplets and aerosols is known to play a critical role in the spread of many viruses amongst which are the common flu and the more recent SARS-CoV-2 viruses. In the case of SARS-CoV-2, the nasal cavity not only constitutes an important viral entry point, but also a primary site of infection (Sungnak W. et al. Nat. Med. 26:681–687. https://doi.org/10.1038/s41591-020-0868-6 , 2020).. Although face masks are a well-established preventive measure, development of novel and easy-to-use prophylactic measures would be highly beneficial in fighting viral spread and the subsequent emergence of variants of concern (Tao K. et al. Nat Rev Genet 22:757–773. https://doi.org/10.1038/s41576-021-00408-x , 2021). Our group has been working on optimizing a nasal spray delivery system that deposits particles inside the susceptible regions of the nasal cavity to act as a mechanical barrier to impede viral entry. Here, we identify computationally the delivery parameters that maximize the protection offered by this barrier. We introduce the computational approach and quantify the protection rate obtained as a function of a broad range of delivery parameters. We also introduce a modified design and demonstrate that it significantly improves deposition, thus constituting a viable approach to protect against nasal infection of airborne viruses. We then discuss our findings and the implications of this novel system on the prevention of respiratory diseases and targeted drug delivery.

Recently, few-shot learning has attracted significant attention in the field of video action recognition, owing to its data-efficient learning paradigm. Despite the encouraging progress, identifying ways to further improve the few-shot learning performance by exploring additional or auxiliary information for video action recognition remains an ongoing challenge. To address this problem, in this paper we make the first attempt to propose a relational action bank with semantic–visual attention for few-shot action recognition. Specifically, we introduce a relational action bank as the auxiliary library to assist the network in understanding the actions in novel classes. Meanwhile, the semantic–visual attention is devised to adaptively capture the connections to the foregone actions via both semantic correlation and visual similarity. We extensively evaluate our approach via two backbone models (ResNet-50 and C3D) on HMDB and Kinetics datasets, and demonstrate that the proposed model can obtain significantly better performance compared against state-of-the-art methods. Notably, our results demonstrate an average improvement of about 6.2% when compared to the second-best method on the Kinetics dataset.

Surfactants adsorption onto carbonate reservoirs would cause surfactants concentrations decrease in surfactant flooding, which would decrease surfactant efficiency in practical applications of enhanced oil recovery (EOR) processes. Different surfactants could be classified as cationic surfactants, anionic surfactants, non-ionic surfactants according to the main charge, or be classified as chemical surfactant and bio-surfactant according to the surfactant origin. However, the research on different type surfactants adsorption on carbonate reservoirs surface differences was few. Therefore, five representative surfactants (CTAB, SDS, TX-100, sophorolipid, rhamonilipid) adsorption effect onto carbonate reservoirs surface was studied. Owing to the fact that the salinity and temperature in underground carbonate reservoirs were high during the EOR process, it is vital to study the salinity effect and temperature effect on surfactant adsorption. In this study, different surfactants species, temperature and salinity adsorption onto carbonate reservoirs were studied. The adsorption isotherms were fitted by Langmuir, Freundlich, Temkin and Linear models, and the first three models fitting effect were good. The results showed that cationic surfactants adsorption quantity was higher than anionic surfactants, and the non-ionic surfactants adsorption quantity was the lowest. When the temperature increased, the surfactants adsorption would decrease, because the adsorption process was exothermic process, and increasing temperature would inhibit the adsorption. The higher salinity would increase surfactants adsorption because higher salinity could compress electric double layer. In order to decrease surfactants adsorption, SiO2 nanoparticles and TiO2 nanoparticles were added to surfactants solutions, and then surfactants could adsorb onto nanoparticles surface, then the steric hindrance between surfactant molecules would increase, which could decrease surfactants adsorption. Contact angle results indicated that surfactants adsorption made the carbonate reservoir wettability alteration. In the end, surfactants (with or without SiO2 nanoparticles) adsorption onto carbonate reservoirs mechanism were studied by molecular dynamics simulation. The simulation results indicated that the surfactants molecules could adsorb onto SiO2 nanoparticles surface, and then the surfactants adsorption quantity onto carbonate rocks would decrease, which was in accordance with the experiments results.

The Data Distribution Service (DDS) for real-time systems is an industrial Internet communication protocol. Due to its distributed high reliability and the ability to transmit device data communication in real-time, it has been widely used in industry, medical care, transportation, and national defense. With the wide application of various protocols, protocol security has become a top priority. There are many studies on protocol security, but these studies lack a formal security assessment of protocols. Based on the above status, this paper evaluates and improves the security of the DDS protocol using a model detection method combining the Dolev–Yao attack model and the Coloring Petri Net (CPN) theory. Because of the security loopholes in the original protocol, a timestamp was introduced into the original protocol, and the shared key establishment process in the original protocol lacked fairness and consistency. We adopted a new establishment method to establish the shared secret and re-verified its security. The results show that the overall security of the protocol has been improved by 16.7% while effectively preventing current replay attack.

The combination of in-vehicle networks and smart car devices has gradually developed into Intelligent Connected Vehicles (ICVs). Through the vehicle security protocol, ICVs can quickly realize communication transmission. However, with the more frequent connections between smart in-vehicle devices and the network, the relationship between intelligent cars and external systems is becoming more and more complicated, and in-vehicle networks are gradually facing many security issues. Strengthening the security of in-vehicle protocols has become particularly important. This paper uses the model building method based on the Colored Petri Net (CPN) theory to model the Scalable service-Oriented MiddlewarE over IP (SOME/IP) protocol of the vehicle Ethernet. The security protocol is formally verified and analyzed by combining it with the Dolev–Yao adversary model detection method. After verification, the protocol is subject to three attack vulnerabilities: replay, tampering, and deception. We introduce timestamps and random numbers to strengthen the protocol security. After the final analysis and verification, the improved scheme in this paper can effectively improve the security performance of the protocol.

Abstract In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.

In this study, surfactants were used to enhance heavy oil–solid separation, and a detailed mechanism was explored by SARA (saturates, aromatics, resins, asphaltenes) analysis, element analysis, AFM measurement, and molecular dynamic simulation. Surfactants could effectively decrease oil/solid interaction force and then oil–solid separation would be enhanced. The oil–solid interactive force was in relation to surfactants concentration, pH value, asphaltene content, and salinity. The molecular dynamics simulation results show that the dissociation of saturated hydrocarbon, aromatic hydrocarbon, resin, and asphaltene (SARA) on carbonate minerals is gradually weakened for all surfactants. In the process of molecular dynamics simulation of surfactant stripping SARA, firstly, the surfactant molecules adsorb on the surface of SARA molecules. After that, the surfactant peels SARA molecules off the surface of calcite under the influence of molecular thermal motion. In this process, surfactant molecules will not be directly adsorbed on the surface of trace minerals. The results of energy/temperature balance indicated that saturates, aromatics and resins could remain stable when the molecular dynamics simulation time reached 2000 ps with the phenomenon that saturates, aromatics could liberate from minerals totally within 2000 ps. The molecular dynamics simulation of asphaltenes will not liberate from calcite surface within 6000 ps, meanwhile, they could not reach the energy balance/energy balance within 6000 ps. The functional groups of surfactant molecules would have interactions with the SARA functional group, resulting in different dissociation effects of SARA. The results of molecular dynamics simulation are consistent with the experiment results. The separation effect of saturated hydrocarbon, aromatic hydrocarbon, resin, and asphaltene in five kinds of surfactants were different. The molecular dynamic simulation results were in accordance with the SARA analysis.

The control network is an important supporting environment for the control system of the heavy ion accelerator in Lanzhou (HIRFL). It is of great importance to maintain the accelerator system’s network security for the stable operation of the accelerator. With the rapid expansion of the network scale and the increasing complexity of accelerator system equipment, the security situation of the control network is becoming increasingly severe. Port scanning detection can effectively reduce the losses caused by viruses and Trojan horses. This article uses Go Concurrency Patterns, combined with transmission control protocol (TCP) full connection scanning and GIMP Toolkit (GTK) graphic display technology, to develop a tool called HIRFL Scanner. It can scan IP addresses in any range with any ports. This is a very fast, installation-free, cross-platform IP address and port scanning tool. Finally, a series of experiments show that the tool developed in this paper is much faster than the same type of software, and meets the expected development needs.

Pretreatment with a microwave was conducted before enzymolysis and shown to enhance the enzymolysis, which changed the secondary structure of the lotus seed protein. Under high-power microwave irradiation, sub bonds of the protein were broken, causing disaggregation and unfolding of the secondary structure, namely a decrease in the intermolecular aggregate structure and increase in the random coil structure, making the protein bonds susceptible to papain in the enzymolysis. On the other hand, a response surface methodology (RSM) was launched to investigate the influence of the enzymolysis process variables on the DH (degree of hydrolysis). The statistical analysis revealed that the optimized conditions were a protein substrate concentration of 15 g/L, pH of 5.5, enzymolysis temperature of 57 °C, papain amount of 0.5 g/L, and enzymolysis time of 45 min, for which the predicted value of the DH was 35.64%. The results indicated that a microwave also had better potential for applications in the enzymolysis of foods.

In order to enhance bitumen recovery from carbonate asphalt rocks, acid-washed process (hydrochloric acid) with bio-surfactants-assisted enhanced was put forward. The acid-washed process for carbonate asphalt rocks was optimized by single factor experiment, and the optimal conditions were as follows: the hydrochloric acid concentration was 14.8%. the stirring rate was 600 rpm, the temperature was 60C and the reaction time was 4 h. The metal ions concentrations decreased with the increase of pH. As the results, the bitumen recovery was 96.7% and the B/S was 2.52 at the optimal condition. SEM (Scanning Electron Microscope) analysis indicated that most carbonate mineral surfaces are covered with bitumen in carbonate asphalt rocks, so the B/S was low for carbonate asphalt rocks by using acid-washed process only. In order to solve the limitation, the sophorolipid was used to enhance the acid-wash process. The bitumen recovery was increased from 96.7% to 98.7% and B/S was increased from 2.52 to 3.07 with the sophorolipid concentration increased from 0 to 1000 ppm. To study the effect of sophorolipid on enhancing acid-washed process, zeta potential and AFM (atomic force microscope) measurements were used. Zeta potential measurement showed that bitumen and CaC03 have strong attractive force in deionized water, but they have strong repulsive force in sophorolipid solution. The AFM measurements showed that the adhesive force between bitumen and carbonate decreased with the increasing concentration of sophorolipid. The sophorolipid could reduce the interaction of oil-solid, and promote the hydrochloric acid react with minerals, leading to increased B/S significantly. [ABSTRACT FROM AUTHOR]

Pretreatment with a microwave was conducted before enzymolysis and shown to enhance the enzymolysis, which changed the secondary structure of the lotus seed protein. Under high-power microwave irradiation, sub bonds of the protein were broken, causing disaggregation and unfolding of the secondary structure, namely a decrease in the intermolecular aggregate structure and increase in the random coil structure, making the protein bonds susceptible to papain in the enzymolysis. On the other hand, a response surface methodology (RSM) was launched to investigate the influence of the enzymolysis process variables on the DH (degree of hydrolysis). The statistical analysis revealed that the optimized conditions were a protein substrate concentration of 15 g/L, pH of 5.5, enzymolysis temperature of 57 °C, papain amount of 0.5 g/L, and enzymolysis time of 45 min, for which the predicted value of the DH was 35.64%. The results indicated that a microwave also had better potential for applications in the enzymolysis of foods. [ABSTRACT FROM AUTHOR]