MXenes for Bioinspired Soft Actuators:Advancements in Angle-Independent Structural Colors and Beyond

Soft actuators have garnered substantial attention in current years in view of their potential appliances in diverse domains like robotics,biomedical devices,and biomimetic systems.These actuators mimic the natural movements of living organisms,aiming to attain enhanced flexibility,adaptability,and versatility.On the other hand,angle-independent structural color has been achieved through innovative design strategies and engineering approaches.By carefully controlling the size,shape,and arrangement of nanostructures,researchers have been able to create materials exhibiting consistent colors regardless of the viewing angle.One promising class of materials that holds great potential for bioinspired soft actuators is MXenes in view of their exceptional mechanical,electrical,and optical properties.The integration of MXenes for bioinspired soft actuators with angle-independent structural color offers exciting possibilities.Overcoming material compatibility issues,improving color reproducibility,scalability,durability,power supply efficiency,and cost-effectiveness will play vital roles in advancing these technologies.This perspective appraises the development of bioinspired MXene-centered soft actuators with angleindependent structural color in soft robotics.

How to fill the biodiversity data gap:Is it better to invest in fieldwork or curation?

Data gaps and biases are two important issues that affect the quality of biodiversity information and downstream results.Understanding how best to fill existing gaps and account for biases is necessary to improve our current information most effectively.Two current main approaches for obtaining and improving data include(1)curation of biological collections,and(2)fieldwork.However,the comparative effectiveness of these approaches in improving biodiversity data remains little explored.We used the Flora de Bogota project to study the magnitude of change in species richness,spatial coverage,and sample coverage of plant records based on curation versus fieldwork.The process of curation resulted in a decrease in species richness(synonym and error removal),but it significantly increased the number of records per species.Fieldwork contributed to a slight increase in species richness,via accumulation of new records.Additionally,curation led to increases in spatial coverage,species observed by locality,the number of plant records by species,and localities by species compared to fieldwork.Overall,curationwas more efficient in producing new information compared to fieldwork,mainly because of the large number of records available in herbaria.We recommend intensive curatorial work as the first step in increasing biodiversity data quality and quantity,to identify bias and gaps at the regional scale that can then be targeted with fieldwork.The stepwise strategy would enable fieldwork to be planned more costeffectively given the limited resources for biodiversity exploration and characterization.

Numerical three-dimensional modeling of earthen dam piping failure

A physically-based numerical three-dimensional earthen dam piping failure model is developed for homogeneous and zoned soil dams.This model is an erosion model,coupled with force/moment equilibrium analyses.Orifice flow and two-dimensional(2D)shallow water equations(SWE)are solved to simulate dam break flows at different breaching stages.Erosion rates of different soils with different construction compaction efforts are calculated using corresponding erosion formulae.The dam's real shape,soil properties,and surrounding area are programmed.Large outer 2D-SWE grids are used to control upstream and downstream hydraulic conditions and control the boundary conditions of orifice flow,and inner 2D-SWE flow is used to scour soil and perform force/moment equilibrium analyses.This model is validated using the European Commission IMPACT(Investigation of Extreme Flood Processes and Uncertainty)Test#5 in Norway,Teton Dam failure in Idaho,USA,and Quail Creek Dike failure in Utah,USA.All calculated peak outflows are within 10%errors of observed values.Simulation results show that,for a V-shaped dam like Teton Dam,a piping breach location at the abutment tends to result in a smaller peak breach outflow than the piping breach location at the dam's center;and if Teton Dam had broken from its center for internal erosion,a peak outflow of 117851 m'/s,which is 81%larger than the peak outflow of 65120 m3/s released from its right abutment,would have been released from Teton Dam.A lower piping inlet elevation tends to cause a faster/earlier piping breach than a higher piping inlet elevation.

Beyond authorship: Analyzing contributions in PLOS ONE and the challenges of appropriate attribution

Purpose:This study aims to evaluate the accuracy of authorship attributions in scientific publications,focusing on the fairness and precision of individual contributions within academic works.Design/methodology/approach:The study analyzes 81,823 publications from the journal PLOS ONE,covering the period from January 2018 to June 2023.It examines the authorship attributions within these publications to try and determine the prevalence of inappropriate authorship.It also investigates the demographic and professional profiles of affected authors,exploring trends and potential factors contributing to inaccuracies in authorship.Findings:Surprisingly,9.14%of articles feature at least one author with inappropriate authorship,affecting over 14,000 individuals(2.56%of the sample).Inappropriate authorship is more concentrated in Asia,Africa,and specific European countries like Italy.Established researchers with significant publication records and those affiliated with companies or nonprofits show higher instances of potential monetary authorship.Research limitations:Our findings are based on contributions as declared by the authors,which implies a degree of trust in their transparency.However,this reliance on self-reporting may introduce biases or inaccuracies into the dataset.Further research could employ additional verification methods to enhance the reliability of the findings.Practical implications:These findings have significant implications for journal publishers,Beyond authorship:Analyzing contributions in PLOS ONE and Maddi,A.,&the challenges of appropriate attribution highlighting the necessity for robust control mechanisms to ensure the integrity of authorship attributions.Moreover,researchers must exercise discernment in determining when to acknowledge a contributor and when to include them in the author list.Addressing these issues is crucial for maintaining the credibility and fairness of academic publications.Originality/value:This study contributes to an understanding of critical issues within academic authorship,shedding light on the prevalence and impact of inappropriate authorship attributions.By calling for a nuanced approach to ensure accurate credit is given where it is due,the study underscores the importance of upholding ethical standards in scholarly publishing.

A Harmonic Approach to Handwriting Style Synthesis Using Deep Learning

The challenging task of handwriting style synthesis requires capturing the individuality and diversity of human handwriting.The majority of currently available methods use either a generative adversarial network(GAN)or a recurrent neural network(RNN)to generate new handwriting styles.This is why these techniques frequently fall short of producing diverse and realistic text pictures,particularly for terms that are not commonly used.To resolve that,this research proposes a novel deep learning model that consists of a style encoder and a text generator to synthesize different handwriting styles.This network excels in generating conditional text by extracting style vectors from a series of style images.The model performs admirably on a range of handwriting synthesis tasks,including the production of text that is out-of-vocabulary.It works more effectively than previous approaches by displaying lower values on key Generative Adversarial Network evaluation metrics,such Geometric Score(GS)(3.21×10^(-5))and Fréchet Inception Distance(FID)(8.75),as well as text recognition metrics,like Character Error Rate(CER)and Word Error Rate(WER).A thorough component analysis revealed the steady improvement in image production quality,highlighting the importance of specific handwriting styles.Applicable fields include digital forensics,creative writing,and document security.

Period–Luminosity Relationship forδScuti Stars Revisited

The Gaia DR3 parallax approach was used to estimate the absolute parameters of 2375δScuti stars from the ASAS catalog.The selected stars have a variety of observational characteristics,with a higher than 80%probability of beingδScuti stars.We have displayed all the stars in the Hertzsprung-Russell diagram along with theδScuti instability strip,the Zero Age Main Sequence and the Terminal Age Main Sequence.Then,we determined which fundamental and overtone modes each star belongs to using pulsation constant(Q)calculations.In addition,we evaluated the parameters in the Q calculation equation using three machine learning methods,which showed that surface gravity and temperature have the greatest effect on its calculation.The Period-Luminosity(P-L)relationship of theδScuti stars was also revisited.Eventually,using least squares linear regression,we made four linear fits for fundamental and overtone modes and updated their relationships.

Evaluating the Efficacy of Latent Variables in Mitigating Data Poisoning Attacks in the Context of Bayesian Networks:An Empirical Study

Bayesian networks are a powerful class of graphical decision models used to represent causal relationships among variables.However,the reliability and integrity of learned Bayesian network models are highly dependent on the quality of incoming data streams.One of the primary challenges with Bayesian networks is their vulnerability to adversarial data poisoning attacks,wherein malicious data is injected into the training dataset to negatively influence the Bayesian network models and impair their performance.In this research paper,we propose an efficient framework for detecting data poisoning attacks against Bayesian network structure learning algorithms.Our framework utilizes latent variables to quantify the amount of belief between every two nodes in each causal model over time.We use our innovative methodology to tackle an important issue with data poisoning assaults in the context of Bayesian networks.With regard to four different forms of data poisoning attacks,we specifically aim to strengthen the security and dependability of Bayesian network structure learning techniques,such as the PC algorithm.By doing this,we explore the complexity of this area and offer workablemethods for identifying and reducing these sneaky dangers.Additionally,our research investigates one particular use case,the“Visit to Asia Network.”The practical consequences of using uncertainty as a way to spot cases of data poisoning are explored in this inquiry,which is of utmost relevance.Our results demonstrate the promising efficacy of latent variables in detecting and mitigating the threat of data poisoning attacks.Additionally,our proposed latent-based framework proves to be sensitive in detecting malicious data poisoning attacks in the context of stream data.

Trends in mortality among the geriatric population undergoing Surgical aortic valve replacement (SAVR) and potential racial disparities: a 20-year perspective via the National (Nationwide) Inpatient Sample

ed data from the National(Nationwide)Inpatient Sample over a 20-year period from 2001 to 2020 using specific ICD-9 and ICD-10 codes.We included patients aged≥60 and≤80 years with races recorded as White,African American,or Hispanic at the time of their hospitalization for surgery.We analyzed and reported the baseline characteristics,risk-adjusted in-mortality,and complications stratified by race.hospital Results Of 420,181 patients studied,90.0%identified as White,4.0%as African American and 6.0%as Hispanic.Despite a de-crease in overall in-hospital mortality rates from 3.8%between 2001-2005 to 1.8%between 2016-2020,African Americans had higher odds of all-cause in-hospital deaths compared to Whites(aOR=1.390,P<0.001).Additionally,they were more likely to experi-ence cardiogenic shock(aOR=1.241,P<0.001)and acute kidney injury(aOR=1.314,P<0.001)as well as more likely to require organ support such as IABP use(aOR=1.336,P<0.001)or invasive mechanical ventilation(aOR=1.342,P<0.001).Interestingly,Americans were less likely to report events of acute ischemic stroke compared to Whites(aOR=0.852,P<0.001).African Conclusions Despite a reassuring reduction in overall in-hospital mortality rates of geriatric patients undergoing SAVR for aor-tic stenosis,racial disparities in health outcomes remain pervasive with minorities more likely to report higher in-hospital mor-bidity and mortality.

The Impact and Intervention of Handheld Tai Chi Water-Resistance Fitness Ball on Middle-Aged and Elderly Patients with Parkinson’s Disease

Through the use of a survey and statistical methods, this study explores the effects and interventions of handheld Tai Chi water resistance fitness balls on the elderly with Parkinson’s disease. Firstly, a questionnaire on exercise compliance for patients with Parkinson’s disease was developed, and its reliability and validity were tested. Then, a survey was conducted to investigate the current status of exercise compliance among Parkinson’s disease patients, including general information, scoring status, and single and multiple factor analyses of influencing factors [1]. The results of the study show that through qualitative research, the dimensions and item pools of the questionnaire were initially constructed, and the reliability analysis of the questionnaire was conducted through Delphi expert consultation, with favorable results in terms of its reliability and validity [2]. Regarding the current status of exercise compliance among Parkinson’s disease patients, the study found that the level of exercise compliance needs improvement, and there are significant differences in exercise compliance levels among patients under different circumstances. Finally, the research results were discussed and conclusions were drawn. The innovation of this study lies in the development of a questionnaire on exercise compliance for patients with Parkinson’s disease and the preliminary qualitative research and Delphi expert consultation conducted on it, providing new ideas and methods for the study of exercise compliance. However, the study also has limitations as it did not examine the effects of other interventions on Parkinson’s disease, so further research should be conducted [3].

Prediabetes: An overlooked risk factor for major adverse cardiac and cerebrovascular events in atrial fibrillation patients

BACKGROUND Prediabetes is a well-established risk factor for major adverse cardiac and cerebrovascular events(MACCE).However,the relationship between prediabetes and MACCE in atrial fibrillation(AF)patients has not been extensively studied.Therefore,this study aimed to establish a link between prediabetes and MACCE in AF patients.AIM To investigate a link between prediabetes and MACCE in AF patients.METHODS We used the National Inpatient Sample(2019)and relevant ICD-10 CM codes to identify hospitalizations with AF and categorized them into groups with and without prediabetes,excluding diabetics.The primary outcome was MACCE(all-cause inpatient mortality,cardiac arrest including ventricular fibrillation,and stroke)in AF-related hospitalizations.RESULTS Of the 2965875 AF-related hospitalizations for MACCE,47505(1.6%)were among patients with prediabetes.The prediabetes cohort was relatively younger(median 75 vs 78 years),and often consisted of males(56.3%vs 51.4%),blacks(9.8%vs 7.9%),Hispanics(7.3%vs 4.3%),and Asians(4.7%vs 1.6%)than the non-prediabetic cohort(P<0.001).The prediabetes group had significantly higher rates of hypertension,hyperlipidemia,smoking,obesity,drug abuse,prior myocardial infarction,peripheral vascular disease,and hyperthyroidism(all P<0.05).The prediabetes cohort was often discharged routinely(51.1%vs 41.1%),but more frequently required home health care(23.6%vs 21.0%)and had higher costs.After adjusting for baseline characteristics or comorbidities,the prediabetes cohort with AF admissions showed a higher rate and significantly higher odds of MACCE compared to the non-prediabetic cohort[18.6%vs 14.7%,odds ratio(OR)1.34,95%confidence interval 1.26-1.42,P<0.001].On subgroup analyses,males had a stronger association(aOR 1.43)compared to females(aOR 1.22),whereas on the race-wise comparison,Hispanics(aOR 1.43)and Asians(aOR 1.36)had a stronger association with MACCE with prediabetes vs whites(aOR 1.33)and blacks(aOR 1.21).CONCLUSION This population-based study found a significant association between prediabetes and MACCE in AF patients.Therefore,there is a need for further research to actively screen and manage prediabetes in AF to prevent MACCE.

Outpatient insulin use in type 2 diabetes mellitus and acute respiratory distress syndrome outcomes:A retrospective cohort study

BACKGROUND The impact of type 2 diabetes mellitus(T2DM)on acute respiratory distress syndrome(ARDS)is debatable.T2DM was suspected to reduce the risk and complications of ARDS.However,during coronavirus disease 2019(COVID-19),T2DM predisposed patients to ARDS,especially those who were on insulin at home.AIMTo evaluate the impact of outpatient insulin use in T2DM patients on non-COVID-19 ARDS outcomes.METHODS We conducted a retrospective cohort analysis using the Nationwide Inpatient Sample database.Adult patients diagnosed with ARDS were stratified into insulin-dependent diabetes mellitus(DM)(IDDM)and non-insulindependent DM(NIDDM)groups.After applying exclusion criteria and matching over 20 variables,we compared cohorts for mortality,duration of mechanical ventilation,incidence of acute kidney injury(AKI),length of stay(LOS),hospitalization costs,and other clinical outcomes.RESULTS Following 1:1 propensity score matching,the analysis included 274 patients in each group.Notably,no statistically significant differences emerged between the IDDM and NIDDM groups in terms of mortality rates(32.8%vs 31.0%,P=0.520),median hospital LOS(10 d,P=0.537),requirement for mechanical ventilation,incidence rates of sepsis,pneumonia or AKI,median total hospitalization costs,or patient disposition upon discharge.CONCLUSION Compared to alternative anti-diabetic medications,outpatient insulin treatment does not appear to exert an independent influence on in-hospital morbidity or mortality in diabetic patients with non-COVID-19 ARDS.

On the Vacuum Hydrodynamics of Moving Bodies—The Theory of General Singularity

The Theory of General Singularity is presented, unifying quantum field theory, general relativity, and the standard model. This theory posits phonons as fundamental excitations in a quantum vacuum, modeled as a Bose-Einstein condensate. Through key equations, the role of phonons as intermediaries between matter, energy, and spacetime geometry is demonstrated. The theory expands Einsteins field equations to differentiate between visible and dark matter, and revises the standard model by incorporating phonons. It addresses dark matter, dark energy, gravity, and phase transitions, while making testable predictions. The theory proposes that singularities, the essence of particles and black holes, are quantum entities ubiquitous in nature, constituting the very essence of elementary particles, seen as micro black holes or quantum fractal structures of spacetime. As the theory is refined with increasing mathematical rigor, it builds upon the foundation of initial physical intuition, connecting the spacetime continuum of general relativity with the hydrodynamics of the quantum vacuum. Inspired by the insights of Tesla and Majorana, who believed that physical intuition justifies the infringement of mathematical rigor in the early stages of theory development, this work aims to advance the understanding of the fundamental laws of the universe and the perception of reality.

Structural Foundation and Geometry of the Material Singularity (and Its Quantum Entanglement)

In this paper we develop and study, as the second part of one more general development, the energy transmutation equation for the material singularity, previously obtained through the symmetrisation of a wave packet, that is, we develop the correlation between the terms of this equation, which accounts for the formation of matter from a previous vibrational state, and the different possible energy species. These energetic species are ascribed, in a simplified form, to the equation E¯ω=E¯k+E¯f, which allows us, through its associated phase factor, to gain an insight into the wave character of the kinetic energy and thus to attain the basis of the matter-wave, and all sorts of related phenomenologies, including that concerning quantum entanglement. The formation of the matter was previously identified as an energetic process, analogous to the kinetic one, in which finally the inertial mass is consolidated as a mass in a different phase, now, in addition, the mass of the material singularity is identified as a volumetric density of waves of toroidal geometry created in the process of singularisation or energy transfer between species, which makes it possible to establish the real relation or correspondence between the corpuscular and photonic energy equation (E=mc2=hν), i.e. to explain through m the intimate sense of the first equivalence, which explains what νis in the second one.

Data from Twenty-Three FRB’s Confirm the Universe Is Static and Not Expanding

Fast Radio Bursts from far away galaxies have travelled through the IGM and provide a tool to study its composition. Presently there are 23 FRB’s whose host galaxies have been identified and the redshift found. This gives us the opportunity to test Dispersion Measure versus redshift predictions made by two models. The Macquart relation for an expanding Universe and the New Tired Light relationship in a static universe. In New Tired Light, redshifts are produced when a photon is absorbed and re-emitted by the electrons in the IGM which recoil on both occasions. Some of the energy of the photon has been transferred to the kinetic energy of the recoiling electron. The photon has less energy, a lower frequency and a longer wavelength. It has been redshifted. Since dispersion is due to an interaction between radio signals and these same electrons one would expect a direct relationship between DM and redshift in the New Tired light model. The relation is DM=(mec/2hre)ln(1+z)and contains no adjustable parameters—just a combination of universal constants related to the electron and photon. Notice that the relation is independent of the electron number density ne since a change in ne affects both the DM and redshift equally. A graph of DM versus ln(1 + z) will be a straight line of gradient (mec/2hre)and, using SI units, substituting for the constants gives 7.318 × 1025 m−2. Using the data from the 23 well localized FRB’s, with the weighting of the DM’s for expansion removed (so that the data corresponds to a static universe), a graph of DM versus ln(1 + z) has a gradient of 6.7 × 1025 m−2—9% below the predicted (mec/2hre). The Macquart relation involves highly processed data and adjustable parameters to allow for “dark energy” and “dark matter” (neither of which has yet been found) and can be reduced to DM = 850z (in units of pc∙cm−3). Using the data from this set of localized FRB’s gives a trendline with gradient 1.10 × 103 pc∙cm−3—almost 30% higher than that predicted in an expanding universe model. The FRB data clearly comes down in favour of a static universe rather than an expanding one. Combining the DM-z relationship for the 23 well localized FRB’s, with the Hubble diagram, drawn using the NED-D compilation of redshift independent extragalactic distances, produces a value of “ne” the mean electron number density of the IGM, of ne=0.48 m−3close to the value ne=0.5 m−3, long since predicted by NTL.

Non-Uniform Pion Tetrahedron Aether and Electron Tetrahedron Model

We propose that the QCD vacuum pion tetrahedron condensate density vary in space and drops to extremely low values in the Kennan, Barger and Cowie (KBC) void in analogy to earth’s atmospheric density drop with elevation from earth. We propose a formula for the gravitation acceleration based on the non-uniform pion tetrahedron condensate. Gravity may be due to the underlying microscopic attraction between quarks and antiquarks, which are part of the vacuum pion tetrahedron condensate. We propose an electron tetrahedron model, where electrons are comprised of tetraquark tetrahedrons, and . The quarks determine the negative electron charge and the or quarks determine the electron two spin states. The electron tetrahedron may perform a high frequency quark exchange reactions with the pion tetrahedron condensate by tunneling through the condensation gap creating a delocalized electron cloud with a fixed spin. The pion tetrahedron may act as a QCD glue bonding electron pairs in atoms and molecules and protons to neutrons in the nuclei. Conservation of valence quarks and antiquarks is proposed.

From Signals to Solutions: Exploring Early Detection of Neuropsychiatric and Neurodevelopment Disorders through Biomarkers

In 2013, the percentage of children ranging from 5 to 17 years who reported being diagnosed with autism surged to 1.2% from 0.1% in 1997 [1]. Alongside this increase in the incidence of autism in children, there were findings of a 21% increase in children who displayed behavioral and conduct problems from 2019 to 2020 [2]. Early detection of neuropsychiatric and neurodevelopmental disorders in children is critical for timely intervention and improved long-term outcomes. With early intervention, there is better aptitude to support healthy development and give proper treatment to attain a better quality of life. This paper explores studies aimed at enhancing the early detection of these disorders through the use of biomarkers with the aim of creating a bridge between the worlds of research and clinical practice. The disorders in this paper specifically discussed are Major Depressive Disorder, Bipolar Disorder, and Autism Spectrum Disorder. With this bridge, we can foster collaborations and encourage further advancement in the field of early detection and intervention.

Chemotherapy and radiotherapy:Could they contribute to the development of new tumors and metastases?

Objective: Both chemotherapy and radiotherapy have demonstrated high effectiveness as the best mechanisms in the fight against cancer;however, various studies seem to confirm that they could also favor the development of other unwanted effects of great importance for the patient. The main objective of this study is to find out the possible existence of this type of links. Method: This is a systematic literature review that seeks to find out which and how long cases of late interactions related to chemotherapy and radiotherapy treatments have been known. The bibliographic review was carried out based on references published in the last five years. Results: Various studies confirm the possible relationship between chemotherapy and radiotherapy treatments with the development of new undesirable side effects, especially as a consequence of the hepatotoxicity generated in the case of chemotherapy and radiation in radiotherapy. However, in this last type of treatment, the problems raised are really few. Conclusions: The existence of a risk of suffering new unwanted side effects after different types of treatment seems to have been demonstrated, especially in the case of chemotherapy. In the case of radiotherapy, adverse effects are practically non-existent, although they are no less important.

Proposal of a Deuterium-Deuterium Fusion Reactor Intended for a Large Power Plant

This article looks for the necessary conditions to use Deuterium-Deuterium (D-D) fusion for a large power plant. At the moment, for nearly all the projects (JET, ITER…) only the Deuterium-Tritium (D-T) fuel is considered for a power plant. However, as shown in this article, even if a D-D reactor would be necessarily much bigger than a D-T reactor due to the much weaker fusion reactivity of the D-D fusion compared to the D-T fusion, a D-D reactor size would remain under an acceptable size. Indeed, a D-D power plant would be necessarily large and powerful, i.e. the net electric power would be equal to a minimum of 1.2 GWe and preferably above 10 GWe. A D-D reactor would be less complex than a D-T reactor as it is not necessary to obtain Tritium from the reactor itself. It is proposed the same type of reactor yet proposed by the author in a previous article, i.e. a Stellarator “racetrack” magnetic loop. The working of this reactor is continuous. It is reminded that the Deuterium is relatively abundant on the sea water, and so it constitutes an almost inexhaustible source of energy. Thanks to secondary fusions (D-T and D-He3) which both occur at an appreciable level above 100 keV, plasma can stabilize around such high equilibrium energy (i.e. between 100 and 150 keV). The mechanical gain (Q) of such reactor increases with the internal pipe radius, up to 4.5 m. A radius of 4.5 m permits a mechanical gain (Q) of about 17 which thanks to a modern thermo-dynamical conversion would lead to convert about 21% of the thermal power issued from the D-D reactor in a net electric power of 20 GWe. The goal of the article is to create a physical model of the D-D reactor so as to estimate this one without the need of a simulator and finally to estimate the dimensions, power and yield of such D-D reactor for different net electrical powers. The difficulties of the modeling of such reactor are listed in this article and would certainly be applicable to a future D-He3 reactor, if any.

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.

A new electric field mill array with each of the mill’s rotor controlled precisely by a GPS module:Equipment and initial results

We have newly designed an electrostatic sensor,called an electric field mill(EFM),to simplify the estimation of the charge position and charge amount transferred by lightning discharges.It is necessary for this remote estimation of the transferred charge to measure electric field changes caused by charge loss at the time of a lightning strike at multiple locations.For multiple-station measurement of electric field changes,not only speed but also phase for exposure and shielding of the sensing plates inside each EFM of the array should be synchronized to maintain the sensitivities of the deployed instruments.Currently,there is no such EFM with specified speed and phase control performance of the rotary part.Thus,we developed a new EFM in which the rotary mechanism was controlled consistently to within 3%error by a GPS module.Five EFMs had been distributed in the Hokuriku area of Japan during the winter season of 2022-2023 for a test observation.Here we describe the design and a simple calibration method for our new EFM array.Data analysis method based on the assumption of a simple monopole charge structure is also summarized.For validation,locations of assumed point charges were compared with three-dimensional lightning mapping data estimated by radio observations in the MF-HF bands.Initial results indicated the validity to estimate transferred charge amounts and positions of winter cloud-to-ground lightning discharges with our new EFM array.