Influence of initial check, information exchange, final accuracy check, reaction information nursing on the psychology of elderly with lung cancer

BACKGROUND As one of the fatal diseases with high incidence,lung cancer has seriously endangered public health and safety.Elderly patients usually have poor self-care and are more likely to show a series of psychological problems.AIM To investigate the effectiveness of the initial check,information exchange,final accuracy check,reaction(IIFAR)information care model on the mental health status of elderly patients with lung cancer.METHODS This study is a single-centre study.We randomly recruited 60 elderly patients with lung cancer who attended our hospital from January 2021 to January 2022.These elderly patients with lung cancer were randomly divided into two groups,with the control group taking the conventional propaganda and education and the observation group taking the IIFAR information care model based on the conventional care protocol.The differences in psychological distress,anxiety and depression,life quality,fatigue,and the locus of control in psychology were compared between these two groups,and the causes of psychological distress were analyzed.RESULTS After the intervention,Distress Thermometer,Hospital Anxiety and Depression Scale(HADS)for anxiety and the HADS for depression,Revised Piper’s Fatigue Scale,and Chance Health Locus of Control scores were lower in the observation group compared to the pre-intervention period in the same group and were significantly lower in the observation group compared to those of the control group(P<0.05).After the intervention,Quality of Life Questionnaire Core 30(QLQ-C30),Internal Health Locus of Control,and Powerful Others Health Locus of Control scores were significantly higher in the observation and the control groups compared to the pre-intervention period in their same group,and QLQ-C30 scores were significantly higher in the observation group compared to those of the control group(P<0.05).CONCLUSION The IIFAR information care model can help elderly patients with lung cancer by reducing their anxiety and depression,psychological distress,and fatigue,improving their tendencies on the locus of control in psychology,and enhancing their life qualities.

Silent information regulator sirtuin 1 ameliorates acute liver failure via the p53/glutathione peroxidase 4/gasdermin D axis

BACKGROUND Acute liver failure(ALF)has a high mortality with widespread hepatocyte death involving ferroptosis and pyroptosis.The silent information regulator sirtuin 1(SIRT1)-mediated deacetylation affects multiple biological processes,including cellular senescence,apoptosis,sugar and lipid metabolism,oxidative stress,and inflammation.AIM To investigate the association between ferroptosis and pyroptosis and the upstream regulatory mechanisms.METHODS This study included 30 patients with ALF and 30 healthy individuals who underwent serum alanine aminotransferase(ALT)and aspartate aminotransferase(AST)testing.C57BL/6 mice were also intraperitoneally pretreated with SIRT1,p53,or glutathione peroxidase 4(GPX4)inducers and inhibitors and injected with lipopolysaccharide(LPS)/D-galactosamine(D-GalN)to induce ALF.Gasdermin D(GSDMD)^(-/-)mice were used as an experimental group.Histological changes in liver tissue were monitored by hematoxylin and eosin staining.ALT,AST,glutathione,reactive oxygen species,and iron levels were measured using commercial kits.Ferroptosis-and pyroptosis-related protein and mRNA expression was detected by western blot and quantitative real-time polymerase chain reaction.SIRT1,p53,and GSDMD were assessed by immunofluorescence analysis.RESULTS Serum AST and ALT levels were elevated in patients with ALF.SIRT1,solute carrier family 7a member 11(SLC7A11),and GPX4 protein expression was decreased and acetylated p5,p53,GSDMD,and acyl-CoA synthetase long-chain family member 4(ACSL4)protein levels were elevated in human ALF liver tissue.In the p53 and ferroptosis inhibitor-treated and GSDMD^(-/-)groups,serum interleukin(IL)-1β,tumour necrosis factor alpha,IL-6,IL-2 and C-C motif ligand 2 levels were decreased and hepatic impairment was mitigated.In mice with GSDMD knockout,p53 was reduced,GPX4 was increased,and ferroptotic events(depletion of SLC7A11,elevation of ACSL4,and iron accumulation)were detected.In vitro,knockdown of p53 and overexpression of GPX4 reduced AST and ALT levels,the cytostatic rate,and GSDMD expression,restoring SLC7A11 depletion.Moreover,SIRT1 agonist and overexpression of SIRT1 alleviated acute liver injury and decreased iron deposition compared with results in the model group,accompanied by reduced p53,GSDMD,and ACSL4,and increased SLC7A11 and GPX4.Inactivation of SIRT1 exacerbated ferroptotic and pyroptotic cell death and aggravated liver injury in LPS/D-GalNinduced in vitro and in vivo models.CONCLUSION SIRT1 activation attenuates LPS/D-GalN-induced ferroptosis and pyroptosis by inhibiting the p53/GPX4/GSDMD signaling pathway in ALF.

Fine-Grained Ship Recognition Based on Visible and Near-Infrared Multimodal Remote Sensing Images: Dataset,Methodology and Evaluation

Fine-grained recognition of ships based on remote sensing images is crucial to safeguarding maritime rights and interests and maintaining national security.Currently,with the emergence of massive high-resolution multi-modality images,the use of multi-modality images for fine-grained recognition has become a promising technology.Fine-grained recognition of multi-modality images imposes higher requirements on the dataset samples.The key to the problem is how to extract and fuse the complementary features of multi-modality images to obtain more discriminative fusion features.The attention mechanism helps the model to pinpoint the key information in the image,resulting in a significant improvement in the model’s performance.In this paper,a dataset for fine-grained recognition of ships based on visible and near-infrared multi-modality remote sensing images has been proposed first,named Dataset for Multimodal Fine-grained Recognition of Ships(DMFGRS).It includes 1,635 pairs of visible and near-infrared remote sensing images divided into 20 categories,collated from digital orthophotos model provided by commercial remote sensing satellites.DMFGRS provides two types of annotation format files,as well as segmentation mask images corresponding to the ship targets.Then,a Multimodal Information Cross-Enhancement Network(MICE-Net)fusing features of visible and near-infrared remote sensing images,has been proposed.In the network,a dual-branch feature extraction and fusion module has been designed to obtain more expressive features.The Feature Cross Enhancement Module(FCEM)achieves the fusion enhancement of the two modal features by making the channel attention and spatial attention work cross-functionally on the feature map.A benchmark is established by evaluating state-of-the-art object recognition algorithms on DMFGRS.MICE-Net conducted experiments on DMFGRS,and the precision,recall,mAP0.5 and mAP0.5:0.95 reached 87%,77.1%,83.8%and 63.9%,respectively.Extensive experiments demonstrate that the proposed MICE-Net has more excellent performance on DMFGRS.Built on lightweight network YOLO,the model has excellent generalizability,and thus has good potential for application in real-life scenarios.

A framework of force of information influence and application for C4KISR system

The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.

Tuning the diffusion constant to optimize the readout of positional information of spatial concentration patterns

Positional information encoded in spatial concentration patterns is crucial for the development of multicellular organisms.However,it is still unclear how such information is affected by the physically dissipative diffusion process.Here we study one-dimensional patterning systems with analytical derivation and numerical simulations.We find that the diffusion constant of the patterning molecules exhibits a nonmonotonic effect on the readout of the positional information from the concentration patterns.Specifically,there exists an optimal diffusion constant that maximizes the positional information.Moreover,we find that the energy dissipation due to the physical diffusion imposes a fundamental upper limit on the positional information.

Improving creep strength of the fine-grained heat-affected zone of novel 9Cr martensitic heat-resistant steel via modified thermo-mechanical treatment

The infamous type Ⅳ failure within the fine-grained heat-affected zone (FGHAZ) in G115 steel weldments seriously threatens the safe operation of ultra-supercritical (USC) power plants.In this work,the traditional thermo-mechanical treatment was modified via the replacement of hot-rolling with cold rolling,i.e.,normalizing,cold rolling,and tempering (NCT),which was developed to improve the creep strength of the FGHAZ in G115 steel weldments.The NCT treatment effectively promoted the dissolution of preformed M_(23)C_(6)particles and relieved the boundary segregation of C and Cr during welding thermal cycling,which accelerated the dispersed reprecipitation of M_(23)C_(6) particles within the fresh reaustenitized grains during post-weld heat treatment.In addition,the precipitation of Cu-rich phases and MX particles was promoted evidently due to the deformation-induced dislocations.As a result,the interacting actions between precipitates,dislocations,and boundaries during creep were reinforced considerably.Following this strategy,the creep rupture life of the FGHAZ in G115 steel weldments can be prolonged by 18.6%,which can further push the application of G115 steel in USC power plants.

Information Conductivity:Universal Performance Measure for Semantic Communications

As a novel paradigm,semantic communication provides an effective solution for breaking through the future development dilemma of classical communication systems.However,it remains an unsolved problem of how to measure the information transmission capability for a given semantic communication method and subsequently compare it with the classical communication method.In this paper,we first present a review of the semantic communication system,including its system model and the two typical coding and transmission methods for its implementations.To address the unsolved issue of the information transmission capability measure for semantic communication methods,we propose a new universal performance measure called Information Conductivity.We provide the definition and the physical significance to state its effectiveness in representing the information transmission capabilities of the semantic communication systems and present elaborations including its measure methods,degrees of freedom,and progressive analysis.Experimental results in image transmission scenarios validate its practical applicability.

Dynamic Update Scheme of Spectrum Information Based on Spectrum Opportunity Incentive in the Database-Assisted Dynamic Spectrum Management

To solve the problem of delayed update of spectrum information(SI) in the database assisted dynamic spectrum management(DB-DSM), this paper studies a novel dynamic update scheme of SI in DB-DSM. Firstly, a dynamic update mechanism of SI based on spectrum opportunity incentive is established, in which spectrum users are encouraged to actively assist the database to update SI in real time. Secondly, the information update contribution(IUC) of spectrum opportunity is defined to describe the cost of accessing spectrum opportunity for heterogeneous spectrum users, and the profit of SI update obtained by the database from spectrum allocation. The process that the database determines the IUC of spectrum opportunity and spectrum user selects spectrum opportunity is mapped to a Hotelling model. Thirdly, the process of determining the IUC of spectrum opportunities is further modelled as a Stackelberg game by establishing multiple virtual spectrum resource providers(VSRPs) in the database. It is proved that there is a Nash Equilibrium in the game of determining the IUC of spectrum opportunities by VSRPs. Finally, an algorithm of determining the IUC based on a genetic algorithm is designed to achieve the optimal IUC. The-oretical analysis and simulation results show that the proposed method can quickly find the optimal solution of the IUC, and ensure that the spectrum resource provider can obtain the optimal profit of SI update.

Characterization of Small-Scale Farmers and Assessment of Their Access to Crop Production Information in Selected Counties of Kenya

Small-scale farming accounts for 78% of total agricultural production in Kenya and contributes to 23.5% of the country’s GDP. Their crop production activities are mostly rainfed subsistence with any surplus being sold to bring in some income. Timely decisions on farm practices such as farm preparation and planting are critical determinants of the seasonal outcomes. In Kenya, most small-scale farmers have no reliable source of information that would help them make timely and accurate decisions. County governments have extension officers who are mandated with giving farmers advisory services to farmers but they are not able to reach most farmers due to facilitation constraints. The mode and format of sharing information is also critical since it’s important to ensure that it’s timely, well-understood and usable. This study sought to assess access to geospatial derived and other crop production information by farmers in four selected counties of Kenya. Specific objectives were to determine the profile of small-scale farmers in terms of age, education and farm size;to determine the type of information that is made available to them by County and Sub-County extension officers including the format and mode of provision;and to determine if the information provided was useful in terms of accuracy, timeliness and adequacy. The results indicated that over 80% of the farmers were over 35 years of age and over 56% were male. Majority had attained primary education (34%) or secondary education (29%) and most farmers in all the counties grew maize (71%). Notably, fellow farmers were a source of information (71%) with the frequency of sharing information being mostly seasonal (37%) and when information was available (43%). Over 66% of interviewed farmers indicating that they faced challenges while using provided information. The results from the study are insightful and helpful in determining effective ways of providing farmers with useful information to ensure maximum benefits.

Fine-grained grid computing model for Wi-Fi indoor localization in complex environments

The fingerprinting-based approach using the wireless local area network(WLAN)is widely used for indoor localization.However,the construction of the fingerprint database is quite time-consuming.Especially when the position of the access point(AP)or wall changes,updating the fingerprint database in real-time is difficult.An appropriate indoor localization approach,which has a low implementation cost,excellent real-time performance,and high localization accuracy and fully considers complex indoor environment factors,is preferred in location-based services(LBSs)applications.In this paper,we proposed a fine-grained grid computing(FGGC)model to achieve decimeter-level localization accuracy.Reference points(RPs)are generated in the grid by the FGGC model.Then,the received signal strength(RSS)values at each RP are calculated with the attenuation factors,such as the frequency band,three-dimensional propagation distance,and walls in complex environments.As a result,the fingerprint database can be established automatically without manual measurement,and the efficiency and cost that the FGGC model takes for the fingerprint database are superior to previous methods.The proposed indoor localization approach,which estimates the position step by step from the approximate grid location to the fine-grained location,can achieve higher real-time performance and localization accuracy simultaneously.The mean error of the proposed model is 0.36 m,far lower than that of previous approaches.Thus,the proposed model is feasible to improve the efficiency and accuracy of Wi-Fi indoor localization.It also shows high-accuracy performance with a fast running speed even under a large-size grid.The results indicate that the proposed method can also be suitable for precise marketing,indoor navigation,and emergency rescue.

Properties of Self-recoverable Mechanoluminescence Phosphor Ca_(5)Ga_(6)O_(14)∶Eu^(3+) and Its Information Encryption Application

A novel self-recoverable mechanoluminescent phosphor Ca_(5)Ga_(6)O_(14)∶Eu^(3+) was developed by the high-tem-perature solid-state reaction method,and its luminescence properties were investigated.Ca_(5)Ga_(6)O_(14)∶Eu^(3+)can produce red mechanoluminescence,and importantly,it shows good repeatability.The mechanoluminescence of Ca_(5)Ga_(6)O_(14)∶Eu^(3+) results from the piezoelectric field generated inside the material under stress,rather than the charge carriers stored in the traps,which can be confirmed by the multiple cycles of mechanoluminescence tests and heat treatment tests.The mechanoluminescence color can be turned from red to green by co-doping varied concentrations of Tb^(3+),which may be meaningful for encrypted letter writing.The encryption scheme for secure communication was devised by harnessing mechanoluminescence patterns in diverse shapes and ASCII codes,which shows good encryption performance.The results suggest that the mechanoluminescence phosphor Ca_(5)Ga_(6)O_(14)∶Eu^(3+),Tb^(3+)may be applied to the optical information encryption.

Attribute Reduction of Hybrid Decision Information Systems Based on Fuzzy Conditional Information Entropy

The presence of numerous uncertainties in hybrid decision information systems(HDISs)renders attribute reduction a formidable task.Currently available attribute reduction algorithms,including those based on Pawlak attribute importance,Skowron discernibility matrix,and information entropy,struggle to effectively manages multiple uncertainties simultaneously in HDISs like the precise measurement of disparities between nominal attribute values,and attributes with fuzzy boundaries and abnormal values.In order to address the aforementioned issues,this paper delves into the study of attribute reduction withinHDISs.First of all,a novel metric based on the decision attribute is introduced to solve the problem of accurately measuring the differences between nominal attribute values.The newly introduced distance metric has been christened the supervised distance that can effectively quantify the differences between the nominal attribute values.Then,based on the newly developed metric,a novel fuzzy relationship is defined from the perspective of“feedback on parity of attribute values to attribute sets”.This new fuzzy relationship serves as a valuable tool in addressing the challenges posed by abnormal attribute values.Furthermore,leveraging the newly introduced fuzzy relationship,the fuzzy conditional information entropy is defined as a solution to the challenges posed by fuzzy attributes.It effectively quantifies the uncertainty associated with fuzzy attribute values,thereby providing a robust framework for handling fuzzy information in hybrid information systems.Finally,an algorithm for attribute reduction utilizing the fuzzy conditional information entropy is presented.The experimental results on 12 datasets show that the average reduction rate of our algorithm reaches 84.04%,and the classification accuracy is improved by 3.91%compared to the original dataset,and by an average of 11.25%compared to the other 9 state-of-the-art reduction algorithms.The comprehensive analysis of these research results clearly indicates that our algorithm is highly effective in managing the intricate uncertainties inherent in hybrid data.

A Multi-Constraint Path Optimization Scheme Based on Information Fusion in Software Defined Network

The existingmultipath routing in Software Defined Network (SDN) is relatively blind and inefficient, and there is alack of cooperation between the terminal and network sides, making it difficult to achieve dynamic adaptationof service requirements and network resources. To address these issues, we propose a multi-constraint pathoptimization scheme based on information fusion in SDN. The proposed scheme collects network topology andnetwork state information on the network side and computes disjoint paths between end hosts. It uses the FuzzyAnalytic Hierarchy Process (FAHP) to calculate the weight coefficients of multiple constrained parameters andconstructs a composite quality evaluation function for the paths to determine the priority of the disjoint paths. TheSDN controller extracts the service attributes by analyzing the packet header and selects the optimal path for flowrule forwarding. Furthermore, the service attributes are fed back to the path composite quality evaluation function,and the path priority is dynamically adjusted to achieve dynamic adaptation between service requirements andnetwork status. By continuously monitoring and analyzing the service attributes, the scheme can ensure optimalrouting decisions in response to varying network conditions and evolving service demands. The experimentalresults demonstrated that the proposed scheme can effectively improve average throughput and link utilizationwhile meeting the Quality of Service (QoS) requirements of various applications.

The Impact of Health Information Technology on Hospital Performance: A Systematic Integrative Literature Review

Objective: To review, categorise, and synthesise findings from literature on health information technology (HIT) functionalities, HIT use, and the impact of HIT on hospital performance. Materials and Methods: We conducted a systematic integrative literature review based on a compre-hensive database search. To organise, categorise and synthesise the ex-isting literature, we adopted the affordance actualization theory. To align the literature with our research framework, we used four categories: 1) the functionalities of HIT and how these functionalities are measured;2) use and immediate outcomes of HIT functionalities;3) different perfor-mance indicators and how HIT functionalities affect them;and 4) what hospital characteristics influence the outcome of hospital performance. Results: Fifty-two studies were included. We identified four types of HIT. Only ten studies (19.2%) define the use of HIT by explicitly meas-uring the use rate of HIT. We identified five dimensions of hospital per-formance indicators. Every dimension showed mixed results;however, in general, HIT has a positive impact on mortality and patient readmis-sions. We found several hospital characteristics that may affect the rela-tionship between HIT and hospital-level outcomes. Discussion: Further efforts should focus on embedded research on HIT functionalities, use and effects of HIT implementations with more performance indicators and adjusted for hospital characteristics. Conclusion: The proposed framework could help hospitals and researchers make decisions regard-ing the functionalities, use and effects of HIT implementation in hospi-tals. Given our research outcomes, we suggest future research opportuni-ties to improve understanding of how HIT affects hospital performance. .

The Value of Modern Information Technology in Nursing Emergencies

In first aid, traditional information interchange has numerous shortcomings. For example, delayed information and disorganized departmental communication cause patients to miss out on critical rescue time. Information technology is becoming more and more mature, and as a result, its use across numerous industries is now standard. China is still in the early stages of developing its integration of emergency medical services with modern information technology;despite our progress, there are still numerous obstacles and constraints to overcome. Our goal is to integrate information technology into every aspect of emergency patient care, offering robust assistance for both patient rescue and the efforts of medical personnel. Information may be communicated in a fast, multiple, and effective manner by utilizing modern information technology. This study aims to examine the current state of this field’s development, current issues, and the field’s future course of development.

Impacts of information about COVID-19 on pig farmers'production willingness and behavior:Evidence from China

This paper examines the impacts of information about COVID-19 on pig farmers'production willingness by using endorsement experiments and follow-up surveys conducted in 2020 and 2021 in China.Our results show that,first,farmers were less willing to scale up production when they received information about COVID-19.The information in 2020 that the second wave of COVID-19 might occur without a vaccine reduced farmers'willingness to scale up by 13.4%,while the information in 2021 that COVID-19 might continue to spread despite the introduction of vaccine reduced farmers'willingness by 4.4%.Second,farmers whose production was affected by COVID-19 were considerably less willing to scale up,given the access to COVID-19 information.Third,farmers'production willingness can predict their actual production behavior.

Mutual Information Maximization via Joint Power Allocation in Integrated Sensing and Communications System

In this paper, we focus on the power allocation of Integrated Sensing and Communication(ISAC) with orthogonal frequency division multiplexing(OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is,to maximize the mutual information(MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals,as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However,the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization(AO), sequence convex programming(SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.

Research on Driver’s Fatigue Detection Based on Information Fusion

Driving fatigue is a physiological phenomenon that often occurs during driving.After the driver enters a fatigued state,the attentionis lax,the response is slow,and the ability todeal with emergencies is significantly reduced,which can easily cause traffic accidents.Therefore,studying driver fatigue detectionmethods is significant in ensuring safe driving.However,the fatigue state of actual drivers is easily interfered with by the external environment(glasses and light),which leads to many problems,such as weak reliability of fatigue driving detection.Moreover,fatigue is a slow process,first manifested in physiological signals and then reflected in human face images.To improve the accuracy and stability of fatigue detection,this paper proposed a driver fatigue detection method based on image information and physiological information,designed a fatigue driving detection device,built a simulation driving experiment platform,and collected facial as well as physiological information of drivers during driving.Finally,the effectiveness of the fatigue detection method was evaluated.Eye movement feature parameters and physiological signal features of drivers’fatigue levels were extracted.The driver fatigue detection model was trained to classify fatigue and non-fatigue states based on the extracted features.Accuracy rates of the image,electroencephalogram(EEG),and blood oxygen signals were 86%,82%,and 71%,separately.Information fusion theory was presented to facilitate the fatigue detection effect;the fatigue features were fused using multiple kernel learning and typical correlation analysis methods to increase the detection accuracy to 94%.It can be seen that the fatigue driving detectionmethod based onmulti-source feature fusion effectively detected driver fatigue state,and the accuracy rate was higher than that of a single information source.In summary,fatigue drivingmonitoring has broad development prospects and can be used in traffic accident prevention and wearable driver fatigue recognition.

Robust Information Hiding Based on Neural Style Transfer with Artificial Intelligence

This paper proposes an artificial intelligence-based robust information hiding algorithm to address the issue of confidential information being susceptible to noise attacks during transmission.The algorithm we designed aims to mitigate the impact of various noise attacks on the integrity of secret information during transmission.The method we propose involves encoding secret images into stylized encrypted images and applies adversarial transfer to both the style and content features of the original and embedded data.This process effectively enhances the concealment and imperceptibility of confidential information,thereby improving the security of such information during transmission and reducing security risks.Furthermore,we have designed a specialized attack layer to simulate real-world attacks and common noise scenarios encountered in practical environments.Through adversarial training,the algorithm is strengthened to enhance its resilience against attacks and overall robustness,ensuring better protection against potential threats.Experimental results demonstrate that our proposed algorithm successfully enhances the concealment and unknowability of secret information while maintaining embedding capacity.Additionally,it ensures the quality and fidelity of the stego image.The method we propose not only improves the security and robustness of information hiding technology but also holds practical application value in protecting sensitive data and ensuring the invisibility of confidential information.

Dynamics of Non-Markovianity, Quantum Correlations and Information Scrambling of Three Qubits Systems Interacting via Rashba Interaction

The behavior of the quantum correlations, information scrambling and the non-Markovianity of three entangling qubits systems via Rashba is discussed. The results showed that, the three physical quantities oscillate between their upper and lower bounds, where the number of oscillations increases as the Rashba interaction strength increases. The exchanging rate of these three quantities depends on the Rashba strength, and whether the entangled state is generated via direct/indirect interaction. Moreover, the coherence parameter can be used as a control parameter to maximize or minimize the three physical quantities.