Interpersonal Functions of Doctor-Patient Conversations

As an indispensable part of medical practice.doctor-patient conversation is drawing more and more attention in the field of sociology,psychology and linguistics.Little attention,however,has been paid to the interpersonal aspect of the conversation between doctors and patients,which is regarded as one of the most complex interpersonal relationships.Being dominant in the interaction,doctors'words,mainly in the form of questions,deserve more studies,especially for the interpersonal functions delivered.This study mainly focuses on this aspect.

The Application of Conversational Implicature in Doctor-Patient Conversation

The doctor-patient conversation is the major way of communication between doctors and patients.A good conversation helps to construct a harmonious doctor-patient relationship.This paper attempts to analyze the doctor-patient conversation by applying the Theory of Conversational Implicature.The theory is accepted as the cooperative principle consisting of four maxims:quantity,quality,relation,manner.This paper will analyse how the four maxims work and the violating of the maxims in the doctor-patient conversation.Through linguistic study of the conversation,we try to find out the problems in the doctor-patient conversation and to provide some directive linguistic suggestions to doctors and patients.

Emotional differences based on comments on doctor-patient disputes with varying levels of severity

BACKGROUND The risks associated with negative doctor-patient relationships have seriously hindered the healthy development of medical and healthcare and aroused wide-spread concern in society.The number of public comments on doctor-patient relationship risk events reflects the degree to which the public pays attention to such events.Thirty incidents of doctor-patient disputes were collected from Weibo and TikTok,and 3655 related comments were extracted.The number of comment sentiment words was extracted,and the comment sentiment value was calculated.The Kruskal-Wallis H test was used to compare differences between each variable group at different levels of incidence.Spearman’s correlation analysis was used to examine associations between variables.Regression analysis was used to explore factors influencing scores of comments on incidents.RESULTS The study results showed that public comments on media reports of doctor-patient disputes at all levels are mainly dominated by“good”and“disgust”emotional states.There was a significant difference in the comment scores and the number of partial emotion words between comments on varying levels of severity of doctor-patient disputes.The comment score was positively correlated with the number of emotion words related to positive,good,and happy)and negatively correlated with the number of emotion words related to negative,anger,disgust,fear,and sadness.CONCLUSION The number of emotion words related to negative,anger,disgust,fear,and sadness directly influences comment scores,and the severity of the incident level indirectly influences comment scores.

Optimizing Enterprise Conversational AI: Accelerating Response Accuracy with Custom Dataset Fine-Tuning

As the realm of enterprise-level conversational AI continues to evolve, it becomes evident that while generalized Large Language Models (LLMs) like GPT-3.5 bring remarkable capabilities, they also bring forth formidable challenges. These models, honed on vast and diverse datasets, have undoubtedly pushed the boundaries of natural language understanding and generation. However, they often stumble when faced with the intricate demands of nuanced enterprise applications. This research advocates for a strategic paradigm shift, urging enterprises to embrace a fine-tuning approach as a means to optimize conversational AI. While generalized LLMs are linguistic marvels, their inability to cater to the specific needs of businesses across various industries poses a critical challenge. This strategic shift involves empowering enterprises to seamlessly integrate their own datasets into LLMs, a process that extends beyond linguistic enhancement. The core concept of this approach centers on customization, enabling businesses to fine-tune the AI’s functionality to fit precisely within their unique business landscapes. By immersing the LLM in industry-specific documents, customer interaction records, internal reports, and regulatory guidelines, the AI transcends its generic capabilities to become a sophisticated conversational partner aligned with the intricacies of the enterprise’s domain. The transformative potential of this fine-tuning approach cannot be overstated. It enables a transition from a universal AI solution to a highly customizable tool. The AI evolves from being a linguistic powerhouse to a contextually aware, industry-savvy assistant. As a result, it not only responds with linguistic accuracy but also with depth, relevance, and resonance, significantly elevating user experiences and operational efficiency. In the subsequent sections, this paper delves into the intricacies of fine-tuning, exploring the multifaceted challenges and abundant opportunities it presents. It addresses the technical intricacies of data integration, ethical considerations surrounding data usage, and the broader implications for the future of enterprise AI. The journey embarked upon in this research holds the potential to redefine the role of conversational AI in enterprises, ushering in an era where AI becomes a dynamic, deeply relevant, and highly effective tool, empowering businesses to excel in an ever-evolving digital landscape.

Language Assessment Feedback Towards Pedagogical Conversational Agent

Continuous development of technology provides an opportunity to incorporate feedback in online assessments.The mode of online instruction during the pandemic was the most significant survival change.Technology enabled every teacher and student to enter a virtual classroom to make sense of education.Feedback is part of language instruction and is a powerful key to improving students’learning performance.Feedback plays an influential and crucial role in teaching and learning.Feedback is an invaluable,ultimate learning tool for learners that aids them in not committing the same error again and creates impetus.Thus,knowing about formative exam feedback is students’right because quality feedback allures them.Given students’eagerness,providing feedback is considered a good practice to be followed by all the teaching faculty.Apropos of online feedback,the present study attempts to study how pedagogical agents provide online feedback in language assessments.The study also considers the characteristics of pedagogical conversational agents that are suitable for providing feedback in online language assessment.Simply put,the study encapsulates that screen agents play an essential role in students’motivation and acceptability of learning through feedback.

Classification of Conversational Sentences Using an Ensemble Pre-Trained Language Model with the Fine-Tuned Parameter

Sentence classification is the process of categorizing a sentence based on the context of the sentence.Sentence categorization requires more semantic highlights than other tasks,such as dependence parsing,which requires more syntactic elements.Most existing strategies focus on the general semantics of a conversation without involving the context of the sentence,recognizing the progress and comparing impacts.An ensemble pre-trained language model was taken up here to classify the conversation sentences from the conversation corpus.The conversational sentences are classified into four categories:information,question,directive,and commission.These classification label sequences are for analyzing the conversation progress and predicting the pecking order of the conversation.Ensemble of Bidirectional Encoder for Representation of Transformer(BERT),Robustly Optimized BERT pretraining Approach(RoBERTa),Generative Pre-Trained Transformer(GPT),DistilBERT and Generalized Autoregressive Pretraining for Language Understanding(XLNet)models are trained on conversation corpus with hyperparameters.Hyperparameter tuning approach is carried out for better performance on sentence classification.This Ensemble of Pre-trained Language Models with a Hyperparameter Tuning(EPLM-HT)system is trained on an annotated conversation dataset.The proposed approach outperformed compared to the base BERT,GPT,DistilBERT and XLNet transformer models.The proposed ensemble model with the fine-tuned parameters achieved an F1_score of 0.88.

Strategies for Fostering Interaction in Online Classrooms:A Conversation Analysis of Teacher-Student Verbal Interaction in Random Questioning in Pandemic-Initiated Online Teaching

This paper aims to explore how a veteran teacher organizes online teaching initiated by the pandemic and how she deals with the problems in online teacher-student verbal interaction.By analyzing a corpus of 20 audio-recorded online lessons between a math teacher and her students during the COVID-19 pandemic from April 11 to May 10,2022,four interactional segments are selected as the focus of the study.The results of the conversation analysis of the segments showed that students’modesty,lack of confidence,lack of ability,and network delay are the main factors affecting online teacher-student interaction.By encouraging students to answer questions,enlightening students to give answers,enriching students’answers,and entertaining the teaching atmosphere(“4Es”strategies),the teacher solved the problems successfully.The findings from this study can provide pedagogical experience and implications for practical teaching.

Enabling heterogeneous catalysis to achieve carbon neutrality: Directional catalytic conversion of CO_(2) into carboxylic acids

The increase in anthropogenic carbon dioxide(CO_(2))emissions has exacerbated the deterioration of the global environment,which should be controlled to achieve carbon neutrality.Central to the core goal of achieving carbon neutrality is the utilization of CO_(2) under economic and sustainable conditions.Recently,the strong need for carbon neutrality has led to a proliferation of studies on the direct conversion of CO_(2) into carboxylic acids,which can effectively alleviate CO_(2) emissions and create high-value chemicals.The purpose of this review is to present the application prospects of carboxylic acids and the basic principles of CO_(2) conversion into carboxylic acids through photo-,electric-,and thermal catalysis.Special attention is focused on the regulation strategy of the activity of abundant catalysts at the molecular level,inspiring the preparation of high-performance catalysts.In addition,theoretical calculations,advanced technologies,and numerous typical examples are introduced to elaborate on the corresponding process and influencing factors of catalytic activity.Finally,challenges and prospects are provided for the future development of this field.It is hoped that this review will contribute to a deeper understanding of the conversion of CO_(2) into carboxylic acids and inspire more innovative breakthroughs.

Two-photon live imaging of direct glia-to-neuron conversion in the mouse cortex

Over the past decade,a growing number of studies have reported transcription factor-based in situ reprogramming that can directly conve rt endogenous glial cells into functional neurons as an alternative approach for n euro regeneration in the adult mammalian central ne rvous system.Howeve r,many questions remain regarding how a terminally differentiated glial cell can transform into a delicate neuron that forms part of the intricate brain circuitry.In addition,concerns have recently been raised around the absence of astrocyte-to-neuron conversion in astrocytic lineage-tra cing mice.In this study,we employed repetitive two-photon imaging to continuously capture the in situ astrocyte-to-neuron conversion process following ecto pic expression of the neural transcription factor NeuroD1 in both prolife rating reactive astrocytes and lineage-tra ced astrocytes in the mouse cortex.Time-lapse imaging over several wee ks revealed the ste p-by-step transition from a typical astrocyte with numero us short,tapered branches to a typical neuro n with a few long neurites and dynamic growth cones that actively explored the local environment.In addition,these lineage-converting cells were able to migrate ra dially or to ngentially to relocate to suitable positions.Furthermore,two-photon Ca2+imaging and patch-clamp recordings confirmed that the newly generated neuro ns exhibited synchronous calcium signals,repetitive action potentials,and spontaneous synaptic responses,suggesting that they had made functional synaptic connections within local neural circuits.In conclusion,we directly visualized the step-by-step lineage conversion process from astrocytes to functional neurons in vivo and unambiguously demonstrated that adult mammalian brains are highly plastic with respect to their potential for neuro regeneration and neural circuit reconstruction.

Dealuminated Hβ zeolite for selective conversion of fructose to furfural and formic acid

The fructose-to-furfural transformation is facing major challenges in the selectivity and high efficiency. Herein, we have developed a simple and effective approach for the selective conversion of fructose to furfural using Hβ zeolite modified by organic acids for dealuminization to regulate its textural and acidic properties. It was found that citric acid-dealuminized Hβ zeolite possessed high specific surface areas, wide channels and high Brønsted acid amount, which facilitated the selective conversion of fructose to furfural with a maximum yield of 76.2% at433 K for 1 h in the γ-butyrolactone(GBL)-H_(2)O system, as well as the concomitant formation of 83.0% formic acid. The^(13)C-isotope labelling experiments and the mechanism revealed that the selective cleavage of C1–C2 or C5–C6 bond on fructose was firstly occurred to form pentose or C5 intermediate by weak Brønsted acid, which was then dehydrated to furfural by strong Brønsted acid. Also this dealuminized Hβ catalyst showed the great recycling performance and was active for the conversion of glucose and mannose.

Oxygen functionalization-assisted anionic exchange toward unique construction of flower-like transition metal chalcogenide embedded carbon fabric for ultra-long life flexible energy storage and conversion

The metal-organic framework(MOF)derived Ni–Co–C–N composite alloys(NiCCZ)were“embedded”inside the carbon cloth(CC)strands as opposed to the popular idea of growing them upward to realize ultrastable energy storage and conversion application.The NiCCZ was then oxygen functionalized,facilitating the next step of stoichiometric sulfur anion diffusion during hydrothermal sulfurization,generating a flower-like metal hydroxysulfide structure(NiCCZOS)with strong partial implantation inside CC.Thus obtained NiCCZOS shows an excellent capacity when tested as a supercapacitor electrode in a three-electrode configuration.Moreover,when paired with the biomass-derived nitrogen-rich activated carbon,the asymmetric supercapacitor device shows almost 100%capacity retention even after 45,000 charge–discharge cycles with remarkable energy density(59.4 Wh kg^(-1)/263.8μWh cm^(–2))owing to a uniquely designed cathode.Furthermore,the same electrode performed as an excellent bifunctional water-splitting electrocatalyst with an overpotential of 271 mV for oxygen evolution reaction(OER)and 168.4 mV for hydrogen evolution reaction(HER)at 10 mA cm−2 current density along with 30 h of unhinged chronopotentiometric stability performance for both HER and OER.Hence,a unique metal chalcogenide composite electrode/substrate configuration has been proposed as a highly stable electrode material for flexible energy storage and conversion applications.

Reversible solid-liquid conversion enabled by self-capture effect for stable non-flow zinc-bromine batteries

Non-flow aqueous zinc-bromine batteries without auxiliary components(e.g.,pumps,pipes,storage tanks)and ion-selective membranes represent a cost-effective and promising technology for large-scale energy storage.Unfortunately,they generally suffer from serious diffusion and shuttle of polybromide(Br^(-),Br^(3-))due to the weak physical adsorption between soluble polybromide and host carbon materials,which results in low energy efficiency and poor cycling stability.Here,we develop a novel self-capture organic bromine material(1,10-bis[3-(trimethylammonio)propyl]-4,4'-bipyridinium bromine,NVBr4)to successfully realize reversible solid complexation of bromide components for stable non-flow zinc-bromine battery applications.The quaternary ammonium groups(NV^(4+)ions)can effectively capture the soluble polybromide species based on strong chemical interaction and realize reversible solid complexation confined within the porous electrodes,which transforms the conventional“liquid-liquid”conversion of soluble bromide components into“liquid-solid”model and effectively suppresses the shuttle effect.Thereby,the developed non-flow zinc-bromide battery provides an outstanding voltage platform at 1.7 V with a notable specific capacity of 325 mAh g^(-1)NVBr4(1 A g^(-1)),excellent rate capability(200 mAh g^(-1)NVBr4 at 20 A g^(-1)),outstanding energy density of 469.6 Wh kg^(-1)and super-stable cycle life(20,000 cycles with 100%Coulombic efficiency),which outperforms most of reported zinc-halogen batteries.Further mechanism analysis and DFT calculations demonstrate that the chemical interaction of quaternary ammonium groups and bromide species is the main reason for suppressing the shuttle effect.The developed strategy can be extended to other halogen batteries to obtain stable charge storage.

Conversion therapy of a giant hepatocellular carcinoma with portal vein thrombus and inferior vena cava thrombus:A case report and review of literature

BACKGROUND The prognosis of hepatocellular carcinoma(HCC)combined with portal and hepatic vein cancerous thrombosis is poor,for unresectable patients the combination of targeted therapy and immune therapy was the first-line recommended treatment for advanced HCC,with a median survival time of only about 2.7-6 months.In this case report,we present the case of a patient with portal and hepatic vein cancerous thrombosis who achieved pathologic complete response after conversion therapy.CASE SUMMARY In our center,a patient with giant HCC combined with portal vein tumor thrombus and hepatic vein tumor thrombus was treated with transcatheter arterial chemoembolization(TACE),radiotherapy,targeted therapy and immunotherapy,and was continuously given icaritin soft capsules for oral regulation.After 7 months of conversion therapy,the patient's tumor shrank and the tumor thrombus subsided significantly.The pathology of surgical resection was in complete remission,and there was no progression in the postoperative follow-up for 7 months,which provided a basis for the future strategy of combined conversion therapy.CONCLUSION In this case,atezolizumab,bevacizumab,icaritin soft capsules combined with radiotherapy and TACE had a good effect.For patients with hepatocellular carcinoma combined with hepatic vein/inferior vena cava tumor thrombus,adopting a high-intensity,multimodal proactive strategy under the guidance of multidisciplinary team(MDT)is an important attempt to break through the current treatment dilemma.

Leveraging hierarchical semantic‐emotional memory in emotional conversation generation

Handling emotions in human‐computer dialogues has emerged as a challenging task which requires artificial intelligence systems to generate emotional responses by jointly perceiving the emotion involved in the input posts and incorporating it into the gener-ation of semantically coherent and emotionally reasonable responses.However,most previous works generate emotional responses solely from input posts,which do not take full advantage of the training corpus and suffer from generating generic responses.In this study,we introduce a hierarchical semantic‐emotional memory module for emotional conversation generation(called HSEMEC),which can learn abstract semantic conver-sation patterns and emotional information from the large training corpus.The learnt semantic and emotional knowledge helps to enrich the post representation and assist the emotional conversation generation.Comprehensive experiments on a large real‐world conversation corpus show that HSEMEC can outperform the strong baselines on both automatic and manual evaluation.For reproducibility,we release the code and data publicly at:https://github.com/siat‐nlp/HSEMEC‐code‐data.

Electronic structure engineering of transition metal dichalcogenides for boosting hydrogen energy conversion electrocatalysts

Electrocatalytic water splitting for hydrogen production is an appealing strategy to reduce carbon emissions and generate renewable fuels.This promising process,however,is limited by its sluggish reaction kinetics and high-cost catalysts.The two-dimensional(2D)transition metal dichalcogenides(TMDCs)have presented great potential as electrocatalytic materials due to their tunable bandgaps,abundant defective active sites,and good chemical stability.Consequently,phase engineering,defect engineering and interface engineering have been adopted to manipulate the electronic structure of TMDCs for boosting their exceptional catalytic performance.Particularly,it is essential to clarify the local structure of catalytically active sites of TMDCs and their structural evolution in catalytic reactions using atomic resolution electron microscopy and the booming in situ technologies,which is beneficial for exploring the underlying reaction mechanism.In this review,the growth regulation,characterization,particularly atomic configurations of active sites in TMDCs are summarized.The significant role of electron microscopy in the understanding of the growth mechanism,the controlled synthesis and functional optimization of 2D TMDCs are discussed.This review will shed light on the design and synthesis of novel electrocatalysts with high performance,as well as prompt the application of advanced electron microscopy in the research of materials science.

Ultra-broadband and wide-angle reflective terahertz polarization conversion metasurface based on topological optimization

Terahertz polarization conversion devices have significant potential applications in various fields such as terahertzimaging and spectroscopy.In this paper,we utilize genetic algorithms to topologically optimize the metasurface unit cellsand design a reflective linear polarization conversion metasurface with ultra-broadband and wide-angle characteristics.By partitioning the metallic pattern layer into quadrants,the encoding length is effectively reduced,resulting in a shorteroptimization time.The research results indicate that the converter possesses a polarization conversion efficiency ratio higherthan 90%and a relative bandwidth ratio of 125%in a range of 0.231-0.995 THz.Meanwhile,it can maintain excellentpolarization conversion properties when the incident angle of terahertz waves is less than 45°and the polarization angle isless than 15°,demonstrating excellent practicality.New insights are provided for the design of terahertz wide-angle ultrawidebandpolarization conversion devices,and the proposed metasurfce has potential applications in terahertz polarizationimaging,spectroscopy and communication fields.

1.42-fold enhancement of formate selectivity by linker conversion on the Zn-based metal organic framework catalyst

Electro-reduction of carbon dioxide(ERCO_(2)) is considered an effective method to alleviate the greenhouse effect and produce value-added chemicals.Achieving the dominant selectivity of Zn-based catalysts for formate remains a challenge.In this article,the ZnIn-E_(12) catalyst is successfully prepared by solvent assisted ligand exchange(SALE) method to convert organic ligands,achieving a Faradaic efficiency of 72.28% for formate at-1.26 V vs.RHE(V_(RHE)),which is 1.42 times higher than the original catalyst.Evidence shows that the successful conversion of organic ligands can transform the catalyst from the original large size polyhedron to cross-linked network of particles with a diameter of about 30 nm.The increased specific surface area can expose more active sites and facilitate the electrocatalytic conversion of CO_(2) to formate.This work is expected to provide inspiration for the regulation of formate selectivity and catalyst size in Zn-based catalysts.

Intrinsic polarization conversion and avoided-mode crossing in X-cut lithium niobate microrings

Compared with well-developed free space polarization converters, polarization conversion between TE and TM modes in the waveguide is generally considered to be caused by shape birefringence, like curvature, morphology of waveguide cross section and scattering. Here, we study the polarization conversion mechanism in 1-THz-FSR X-cut lithium niobate microrings with multiple-resonance condition, that is the conversion can be implemented by birefringence of waveguides,which will also introduce an avoided-mode crossing. In the experiment, we find that this mode crossing results in severe suppression of one sideband in local nondegenerate four-wave mixing and disrupts the cascaded four-wave mixing on this side. Simultaneously, we propose one two-dimensional method to simulate the eigenmodes(TE and TM) in X-cut microrings, and the mode crossing point. This work will provide one approach to the design of polarization converters and simulation for monolithic photonics integrated circuits, and may be helpful to the studies of missed temporal dissipative soliton formation in X-cut lithium niobate rings.

Hollow Metal-Organic Framework/MXene/Nanocellulose Composite Films for Giga/Terahertz Electromagnetic Shielding and Photothermal Conversion

With the continuous advancement of communication technology,the escalating demand for electromagnetic shielding interference(EMI)materials with multifunctional and wideband EMI performance has become urgent.Controlling the electrical and magnetic components and designing the EMI material structure have attracted extensive interest,but remain a huge challenge.Herein,we reported the alternating electromagnetic structure composite films composed of hollow metal-organic frameworks/layered MXene/nanocellulose(HMN)by alternating vacuum-assisted filtration process.The HMN composite films exhibit excellent EMI shielding effectiveness performance in the GHz frequency(66.8 dB at Kaband)and THz frequency(114.6 dB at 0.1-4.0 THz).Besides,the HMN composite films also exhibit a high reflection loss of 39.7 dB at 0.7 THz with an effective absorption bandwidth up to 2.1 THz.Moreover,HMN composite films show remarkable photothermal conversion performance,which can reach 104.6℃under 2.0 Sun and 235.4℃under 0.8 W cm^(−2),respectively.The unique micro-and macrostructural design structures will absorb more incident electromagnetic waves via interfacial polarization/multiple scattering and produce more heat energy via the local surface plasmon resonance effect.These features make the HMN composite film a promising candidate for advanced EMI devices for future 6G communication and the protection of electronic equipment in cold environments.

Insight into structure evolution of carbon nitrides and its energy conversion as luminescence

A series of carbon nitride(CN)materials represented by graphitic carbon nitride(g-C_(3)N_(4))have been widely used in bioimaging,biosensing,and other fields in recent years due to their nontoxicity,low cost,and high luminescent quantum efficiency.What is more attractive is that the luminescent properties such as wavelength and intensity can be regulated by controlling the structure at the molecular level.Hence,it is time to summarize the related research on CN structural evolution and make a prospect on future developments.In this review,we first summarize the research history and multiple structural evolution of CN.Then,the progress of improving the luminescence performance of CN through structural evolution was discussed.Significantly,the relationship between CN structure evolution and energy conversion in the forms of photoluminescence,chemiluminescence,and electrochemiluminescence was reviewed.Finally,key challenges and opportunities such as nanoscale dispersion strategy,luminous efficiency improving methods,standardization evaluation,and macroscopic preparation of CN are highlighted.