Transforming Healthcare:AI-NLP Fusion Framework for Precision Decision-Making and Personalized Care Optimization in the Era of IoMT

In the rapidly evolving landscape of healthcare,the integration of Artificial Intelligence(AI)and Natural Language Processing(NLP)holds immense promise for revolutionizing data analytics and decision-making processes.Current techniques for personalized medicine,disease diagnosis,treatment recommendations,and resource optimization in the Internet of Medical Things(IoMT)vary widely,including methods such as rule-based systems,machine learning algorithms,and data-driven approaches.However,many of these techniques face limitations in accuracy,scalability,and adaptability to complex clinical scenarios.This study investigates the synergistic potential of AI-driven optimization techniques and NLP applications in the context of the IoMT.Through the integration of advanced data analytics methodologies with NLP capabilities,we propose a comprehensive framework designed to enhance personalized medicine,streamline disease diagnosis,provide treatment recommendations,and optimize resource allocation.Using a systematic methodology data was collected from open data repositories,then preprocessed using data cleaning,missing value imputation,feature engineering,and data normalization and scaling.Optimization algorithms,such as Gradient Descent,Adam Optimization,and Stochastic Gradient Descent,were employed in the framework to enhance model performance.These were integrated with NLP processes,including Text Preprocessing,Tokenization,and Sentiment Analysis to facilitate comprehensive analysis of the data to provide actionable insights from the vast streams of data generated by IoMT devices.Lastly,through a synthesis of existing research and real-world case studies,we demonstrated the impact of AI-NLP fusion on healthcare outcomes and operational efficiency.The simulation produced compelling results,achieving an average diagnostic accuracy of 93.5%for the given scenarios,and excelled even further in instances involving rare diseases,achieving an accuracy rate of 98%.With regard to patient-specific treatment plans it generated them with an average precision of 96.7%.Improvements in early risk stratification and enhanced documentation were also noted.Furthermore,the study addresses ethical considerations and challenges associated with deploying AI and NLP in healthcare decision-making processes,offering insights into risk-mitigating strategies.This research contributes to advancing the understanding of AI-driven optimization algorithms in healthcare data analytics,with implications for healthcare practitioners,researchers,and policymakers.By leveraging AI and NLP technologies in IoMT environments,this study paves the way for innovative strategies to enhance patient care and operational effectiveness.Ultimately,this work underscores the transformative potential of AI-NLP fusion in shaping the future of healthcare.

Microstructure and forming mechanism of metals subjected to ultrasonic vibration plastic forming: A mini review

Compared with traditional plastic forming,ultrasonic vibration plastic forming has the advantages of reducing the forming force and improving the surface quality of the workpiece.This technology has a very broad application prospect in industrial manufactur-ing.Researchers have conducted extensive research on the ultrasonic vibration plastic forming of metals and laid a deep foundation for the development of this field.In this review,metals were classified according to their crystal structures.The effects of ultrasonic vibration on the microstructure of face-centered cubic,body-centered cubic,and hexagonal close-packed metals during plastic forming and the mech-anism underlying ultrasonic vibration forming were reviewed.The main challenges and future research direction of the ultrasonic vibra-tion plastic forming of metals were also discussed.

Framework for Personalized Chronic Pain Management:Harnessing AI and Personality Insights for Effective Care

This paper introduces a cutting-edge framework for personalized chronic pain management,leveraging the power of artificial intelligence(AI)and personality insights.It explores the intricate relationship between personality traits and pain perception,expression,and management,identifying key correlations that influence an individual’s experience of pain.By integrating personality psychology with AI-driven personality assessment,this framework offers a novel approach to tailoring chronic pain management strategies for each patient’s unique personality profile.It highlights the relevance of well-established personality theories such as the Big Five and the Myers-Briggs Type Indicator(MBTI)in shaping personalized pain management plans.Additionally,the paper introduces multimodal AI-driven personality assessment,emphasizing the ethical considerations and data collection processes necessary for its implementation.Through illustrative case studies,the paper exemplifies how this framework can lead to more effective and patient-centered pain relief,ultimately enhancing overall well-being.In conclusion,the paper positions the need of an“AI-Powered Holistic Pain Management Initiative”which has the potential to transform chronic pain management by providing personalized,data-driven solutions and create a multifaceted research impact influencing clinical practice,patient outcomes,healthcare policy,and the broader scientific community’s understanding of personalized medicine and AI-driven interventions.

Correlation of personality with individual reproductive success in shrub-nesting birds depends on their life history style

Two questions in the research of animal personality—whether there is a correlation between a personality trait and individual reproductive success,and what is the genetic basis underlying a personality trait—remain unresolved.We addressed these two questions in three shrub-nesting birds,the Azure-winged Magpie(Cyanopica cyanus,AM),White-collared Blackbird(Turdus albocinctus,WB),and Brown-cheeked Laughingthrush(Trochalopteron henrici,BL).The personality type of an individual was first identified according to its response to a territorial intruder.Then,we compared the fleeing distance,breeding parameters,and differential expressed genes(DEGs) in the brain transcriptome between bold and shy breeders.In the three species,bold breeders exhibited more aggressiveness towards an intruder of their territory than did shy breeders.The reproductive success of bold breeders was significantly higher than that of shy breeders in AM but not in WB and BL.The three species shared one DEG,crabp1,which was up-regulated in bold relative to in shy individuals.By regulating the expression of corticotropin-releasing hormone,higher crabp1 gene expression can decrease cellular response to retinoic acid.Therefore,bold individuals are insensitive to external stresses and able to exhibit more aggressiveness to intruders than their shier counterparts.Aggressiveness is beneficial to bold individuals in AM but not in WB and BL because the former could evoke neighbors to make the same response of defending against intruders but the latter could not.Although a personality trait may have the same genetic basis across species,its correlation with reproductive success depends largely on the life history style of a species.

MPI/OpenMP-Based Parallel Solver for Imprint Forming Simulation

In this research,we present the pure open multi-processing(OpenMP),pure message passing interface(MPI),and hybrid MPI/OpenMP parallel solvers within the dynamic explicit central difference algorithm for the coining process to address the challenge of capturing fine relief features of approximately 50 microns.Achieving such precision demands the utilization of at least 7 million tetrahedron elements,surpassing the capabilities of traditional serial programs previously developed.To mitigate data races when calculating internal forces,intermediate arrays are introduced within the OpenMP directive.This helps ensure proper synchronization and avoid conflicts during parallel execution.Additionally,in the MPI implementation,the coins are partitioned into the desired number of regions.This division allows for efficient distribution of computational tasks across multiple processes.Numerical simulation examples are conducted to compare the three solvers with serial programs,evaluating correctness,acceleration ratio,and parallel efficiency.The results reveal a relative error of approximately 0.3%in forming force among the parallel and serial solvers,while the predicted insufficient material zones align with experimental observations.Additionally,speedup ratio and parallel efficiency are assessed for the coining process simulation.The pureMPI parallel solver achieves a maximum acceleration of 9.5 on a single computer(utilizing 12 cores)and the hybrid solver exhibits a speedup ratio of 136 in a cluster(using 6 compute nodes and 12 cores per compute node),showing the strong scalability of the hybrid MPI/OpenMP programming model.This approach effectively meets the simulation requirements for commemorative coins with intricate relief patterns.

Personality Trait Detection via Transfer Learning

Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains,including education,e-commerce,or human resources.Tra-ditional machine learning techniques have been broadly employed for personality trait identification;nevertheless,the development of new technologies based on deep learning has led to new opportunities to improve their performance.This study focuses on the capabilities of pre-trained language models such as BERT,RoBERTa,ALBERT,ELECTRA,ERNIE,or XLNet,to deal with the task of personality recognition.These models are able to capture structural features from textual content and comprehend a multitude of language facets and complex features such as hierarchical relationships or long-term dependencies.This makes them suitable to classify multi-label personality traits from reviews while mitigating computational costs.The focus of this approach centers on developing an architecture based on different layers able to capture the semantic context and structural features from texts.Moreover,it is able to fine-tune the previous models using the MyPersonality dataset,which comprises 9,917 status updates contributed by 250 Facebook users.These status updates are categorized according to the well-known Big Five personality model,setting the stage for a comprehensive exploration of personality traits.To test the proposal,a set of experiments have been performed using different metrics such as the exact match ratio,hamming loss,zero-one-loss,precision,recall,F1-score,and weighted averages.The results reveal ERNIE is the top-performing model,achieving an exact match ratio of 72.32%,an accuracy rate of 87.17%,and 84.41%of F1-score.The findings demonstrate that the tested models substantially outperform other state-of-the-art studies,enhancing the accuracy by at least 3%and confirming them as powerful tools for personality recognition.These findings represent substantial advancements in personality recognition,making them appropriate for the development of user-centric applications.

Approach Based on Response-Surface Method to Optimize Lining of Dies Used in 3D Free-Bending Forming Technology

In three-dimensional free-bending forming(3D-FBF),the tube is not overly constrained,and the plastic deformation behavior and forming quality of the bent tube are significantly affected by the critical structure of the forming die lining.However,the effects of die-lining structural parameters on the tube quality,and a method to determine the combination of die-lining structural parameters is yet to be devised.This study aims to propose a new framework that allows one to understand the effects of various die-lining structural parameters on tube quality and to propose the best combination of die-lining structural parameters.First,finite-element modeling is performed to simulate 3D-FBF and examine the effects of individual die-lining structures on the quality of tube formation.The simulation results show that the deformation-zone length and die gap are positively correlated with the tube-section distortion and wall-thickness variation,whereas it shows an opposite trend with respect to the bending radius.Additionally,the lining chamfer radius of the bending die and the guide lining chamfer radius minimally affect the tube forming quality.Subsequently,the optimal die-lining structure is obtained using the response-surface method.The tube cross-sectional distortion rate reduced from 2.73 to 2.53%after the die lining is optimized.Additionally,the average inner-wall thickness reduced to 1.06 mm,whereas the average outer-wall thickness increased to 0.97 mm.This paper proposes a method for optimizing the forming-die-lining mechanism and for improving the tube forming quality in 3D-FBF.

The Impact of Big Five Personality Traits on Older Europeans’ Physical Health

Investigating the role of Big Five personality traits in relation to various health outcomes has been extensively studied. The impact of “Big Five” on physical health is here explored for older Europeans with a focus on examining age groups differences. The study sample included 378,500 respondents derived from the seventh data wave of Survey of Health, Aging and Retirement in Europe (SHARE). The physical health status of older Europeans was estimated by constructing an index considering the combined effect of well-established health indicators such as the number of chronic diseases, mobility limitations, limitations with basic and instrumental activities of daily living, and self-perceived health. This index was used for an overall physical health assessment, for which the higher the score for an individual, the worst health level. Then, through a dichotomization process applied to the retrieved Principal Component Analysis scores, a two-group discrimination (good or bad health status) of SHARE participants was obtained as regards their physical health condition, allowing for further con-structing logistic regression models to assess the predictive significance of “Big Five” and their protective role for physical health. Results showed that neuroti-cism was the most significant predictor of physical health for all age groups un-der consideration, while extraversion, agreeableness and openness were not found to significantly affect the self-reported physical health levels of midlife adults aged 50 up to 64. Older adults aged 65 up to 79 were more prone to open-ness, whereas the oldest old individuals aged 80 up to 105 were mainly affected by openness and conscientiousness. .

Justification of and Response to the Specificity of Workers’Personality Rights

The pervasive existence of subordination in the work-place endows workers’personality rights with a distinct specificity that differs from other civil subjects.The specificity of workers’per-sonality rights is primarily manifested in three aspects:the exercise of rights is restricted by the employer;personality rights infringements often accompany violations of workers’economic property rights;and the scope of rights is not limited to the duration of employment.To respond to the specificity arising in the labor domain,certain disputes concerning workers’personality rights should be handled through la-bor dispute resolution procedures.In individual cases,judicial author-ities should differentiate among protection levels based on the specific type of personality rights involved,with a focus on examining the rea-sons,methods,and extent of the employer’s restrictive actions,thereby establishing a practical and reasonable review system.。

Analysis and Optimization of the Electrohydraulic Forming Process of Sinusoidal Corrugation Tubes

Aluminum alloy thin-walled structures are widely used in the automotive industry due to their advantages related to light weight and crashworthiness.They can be produced at room temperature by the electrohydraulic forming process.In the present study,the influence of the related parameters on the forming quality of a 6063 aluminum alloy sinusoidal corrugation tube has been assessed.In particular,the orthogonal experimental design(OED)and central composite design(CCD)methods have been used.Through the range analysis and variance analysis of the experimental data,the influence degree of wire diameter(WD)and discharge energy(DE)on the forming quality was determined.Multiple regression analysis was performed using the response surface methodology.A prediction model for the attaching-die state coefficient was established accordingly.The following optimal arrangement of parameters was obtained(WD=0.759 mm,DE=2.926 kJ).The attaching-die state coefficient reached the peak value of 0.001.Better optimized wire diameter and discharge energy for a better attaching-die state could be screened by CCD compared with OED.The response surface method in CCD was more suitable for the design and optimization of the considered process parameters.

Forming and Springback Prediction of Strips Under Multi-square Punch Concave Forming Process Considering Partial-unloading Effects

To further investigate the forming mechanism and springback characteristics of strips under multi-square punch forming (MSPF) considering partial-unloading effects, a series of concave form ing tests of strips are conducted on the MSPF machine. This paper aims to reveal the physical mecha nism of the elastic-plastic deformation in the MSPF process considering the effect of the forming ap proaches, and derive appropriate mathematical interpretations. The theoretical model is firstly estab lished to analyse the concave forming mechanism and springback characteristics of the strip, and its accuracy is then validated by experimental data. The forming history and load evolutions are depicted to explore the required forming capacity through the proposed analytical method. Besides, the paramet ric studies are carried out to discuss their effects on the springback of the strip. The results suggest that the deformation paths of the strip are influenced by the forming approach, and the springback of the strip in convex forming is larger than that in concave forming.

Experimental study on the forming characteristics of 1.5 GPa ultrahigh-strength dual-phase steel

The DP1500 steel series successfully produced by Baosteel is a marked improvement over the cold-rolled hot-dip galvanized dual-phase steel series.Sufficient parameter data related to forming characteristics are needed for the successful application of dual-phase steel series in engineering structures.Therefore,differences in the mech-anical properties,forming limit,hole expansion ratio,and stretch bend limit of the 1.5 GPa ultrahigh-strength steel,including DP1500,QP1500,and MS1500,have been systematically studied.Results show that the DP1500 exhibits good plastic deformation performance and approximately 5% uniform elongation,and its true major strain minimum on the forming limit curve(FLC_(0)) value is approximately 0.083,which is higher and lower than the FLC_(0) values of MS1500 and QP1500 of the same strength grade,respectively.DP1500 also exhibits good flanging and pore expansion capabilities and superior performance to QP1500 and MS1500.The minimum radius-to-thickness(R/T) ratio(1.4) of DP1500 in the 90° bend tests transverse to the rolling direction is between the R/T ratios of MS1500 and the QP1500.Overall,the formability performance of DP1500 is between that of MS1500 and QP1500.Its excellent crash energy absorption and formability performance render it a suitable structural component,and it has been successfully tested and verified on a typical complex ultrahigh-strength steel skeleton structure.

Compensatory Damages in Personal Information Public Interest Litigation in China: Challenges and Prospects

In contrast to private interest litigation,public interest litigation provides a more potent solution to personal information infringements marked by extensive scope,unspecified victims,and limited individual loss.However,com⁃pensatory damages remain a contentious issue,both in theory and in practice,within the legal framework of personal in⁃formation public interest litigation.Through an empirical study conducted within China's judicial practice,this paper reveals that the pending issue concerning the nature and function of compensatory damages has caused highly contra⁃dictory verdicts regarding their calculation and allocation,as well as their relationship with other forms of pecuniary li⁃abilities.Only by acknowledging the role of compensatory damages imposed in personal information public interest liti⁃gation as"Skimming off Excess Profits",and affirming their function as deterrence rather than compensation can they truly achieve the broader objective of safeguarding personal information security and promoting public welfare,as well as avoid disrupting the harmony of the existing legal landscape.

Method of fabricating artificial rock specimens based on extrusion free forming(EFF)3D printing

Three-dimensional(3D)printing technology has been widely used to create artificial rock samples in rock mechanics.While 3D printing can create complex fractures,the material still lacks sufficient similarity to natural rock.Extrusion free forming(EFF)is a 3D printing technique that uses clay as the printing material and cures the specimens through high-temperature sintering.In this study,we attempted to use the EFF technology to fabricate artificial rock specimens.The results show the physico-mechanical properties of the specimens are significantly affected by the sintering temperature,while the nozzle diameter and layer thickness also have a certain impact.The specimens are primarily composed of SiO_(2),with mineral compositions similar to that of natural rocks.The density,uniaxial compressive strength(UCS),elastic modulus,and tensile strength of the printed specimens fall in the range of 1.65–2.54 g/cm3,16.46–50.49 MPa,2.17–13.35 GPa,and 0.82–17.18 MPa,respectively.It is capable of simulating different types of rocks,especially mudstone,sandstone,limestone,and gneiss.However,the simulation of hard rocks with UCS exceeding 50 MPa still requires validation.

Effect of Low pH on Forming Process of Desulfurization Gypsum Composite Boards Strengthened by Melamine-formaldehyde Resin

Through exploring the effects of low pH on the composite system of desulfurization gypsum(DG)enhanced by melamine-formaldehyde resin(MF),it is found that the inducing of sulfate-ion,in contrast to chloride and oxalate ions,favors the longitudinal growth of the crystalline form of the hydration product,which was relatively simple and had the highest length to width(L/D)ratio.At the same time,MF can also improve L/D ratio of gypsum hydration products,which favors the formation of hydrated whiskers.Finally,in a composite system composed of hemihydrate gypsum,MF,and glass fibers,when dilute sulfuric acid was used to regulate pH=3-4,the tight binding formed among the components of the composite system compared to pH=5-6.The hydration product of gypsum adheres tightly to glass fiber surface and produces a good cross-linking and binding effect with MF.The flexural strength,compressive strength,elastic modulus,and water absorption of the desulphurized gypsum composite board is 22.7 MPa,39.8 MPa,5608 MPa,and 1.8%,respectively.

A Hybrid Optimization Approach of Single Point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with Principal Component Analysiss

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with Principal Component Analysis(PCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with PCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

On the“News Exception”in Personal Information Protection

Protection of personal information is a significant issue in the construction of legal systems in various countries in the information age.Introducing a balanced approach for protecting personal information is an important goal of basic human rights protection and data legislation.Personal information protection involves comprehensive considerations among various values,and the balanced structure between personal information rights and other rights systems has become the key to legislation on personal information protection.The“news exception”is a prominent example representing the balanced structure of personal information protection.As a societal instrument,news not only pursues commercial value but also advocates freedom of expression and public value.There exists a natural tension between news and personal information protection.The“news exception”of the balanced structure has become a fundamental requirement and important connotation for constructing a system for protecting personal information.The balanced structure of the“news exception”requires a reasonable definition of the concept and purpose of news,and both the self-discipline within the news industry and the judicial intervention are necessary factors.China has preliminarily completed the top-level legislative design of personal information protection through laws such as the Civil Code of the People’s Republic of China(PRC)and the Personal Information Protection Law of the People’s Republic of China.However,the balanced mechanism of the“news exception”has not yet been fully established in China.A“news exception”based on the ideas of balance and the improvement of the institutional system is the fundamental principle for the development of China’s personal information protection system.

Cognitive impairment in patients with bipolar disorder alone versus those with bipolar disorder comorbid with borderline personality disorder

BACKGROUND Bipolar disorder(BD)is a severe mental illness.BD often coexists with borderline personality disorders,making the condition more complex.AIM To explore the differences in cognitive impairment between patients with BD and those with BD comorbid with borderline personality disorder.METHODS Eighty patients with BD and comorbid borderline personality disorder and 80 patients with BD alone were included in groups A and B,respectively,and 80 healthy volunteers were included as controls.Cognitive function in each group was evaluated using the Chinese version of the repeatable battery for the assess-ment of neuropsychological status(RBANS),the Stroop color-word test,and the Wechsler intelligence scale-revised(WAIS-RC).RESULTS The indices of the RBANS,Stroop color-word test,and WAIS-RC in groups A and B were significantly lower than those of the control group(P<0.05).Group A had significantly longer Stroop color-word test times for single-character,single-color,double-character,and double-color,lower scores of immediate memory,visual breadth,verbal function dimensions and total score of the RBANS,as well as lower scores of verbal IQ,performance IQ,and overall IQ of the WAIS-RC compared with group B(P<0.05).Compared to group B,group A exhibited significantly longer single-character time,single-color time,double-character time,and double-color time in the Stroop color-word test(P<0.05).CONCLUSION The cognitive function of patients with BD complicated with borderline personality disorder is lower than that of patients with BD.

Study of microstructure evolution of magnesium alloy cylindrical part with longitudinal inner ribs during hot flow forming by coupling ANN-modified CA and FEA

Hot flow forming(HFF)is a promising forming technology to manufacture thin-walled cylindrical part with longitudinal inner ribs(CPLIRs)made of magnesium(Mg)alloys,which has wide applications in the aerospace field.However,due to the thermo-mechanical coupling effect and the existence of stiffened structure,complex microstructure evolution and uneven microstructure occur easily at the cylindrical wall(CW)and inner rib(IR)of Mg alloy thin-walled CPLIRs during the HFF.In this paper,a modified cellular automaton(CA)model of Mg alloy considering the effects of deformation conditions on material parameters was developed using the artificial neural network(ANN)method.It is found that the ANN-modified CA model exhibits better predictability for the microstructure of hot deformation than the conventional CA model.Furthermore,the microstructure evolution of ZK61 alloy CPLIRs during the HFF was analyzed by coupling the modified CA model and finite element analysis(FEA).The results show that compared with the microstructure at the same layer of the IR,more refined grains and less sufficient DRX resulted from larger strain and strain rate occur at that of the CW;various differences of strain and strain rate in the wall-thickness exist between the CW and IR,which leads to the inhomogeneity of microstructure rising firstly and declining from the inside layer to outside layer;the obtained Hall-Petch relationship between the measured microhardness and predicted grain sizes at the CW and the IR indicates the reliability of the coupled FEA-CA simulation results.

The Dynamic System Theory of Legal Protection for Personal Information Rights Infringement

The advent of the big data era has presented unprecedented challenges to remedies for personal information infringement in areas such as damage assessment,proof of causation,determination of illegality,fault assessment,and liability.Traditional tort law is unable to provide a robust response for these challenges,which severely hinders human rights protection in the digital society.The dynamic system theory represents a third path between fixed constitutive elements and general clauses.It both overcomes the rigidity of the“allor-nothing”legal effect evaluation mechanism of the“element-effect”model and avoids the uncertainty of the general clause model.It can effectively enhance the flexibility of the legal system in responding to social changes.In light of this,it is necessary to construct a dynamic foundational evaluation framework for personal information infringement under the guidance of the dynamic system theory.By relying on the dynamic interplay effect of various foundational evaluation elements,this framework can achieve a flexible evaluation of the constitutive elements of liability and the legal effects of liability for personal information infringement.Through this approach,the crisis of personal information infringement in the era of big data can be mitigated,and the realization of personal information rights as digital human rights can be promoted.