Surface and Content Validity of the Mentoring Function Scale for Novice Nurses

This study aimed to examine the surface and content validity of the Mentoring Function Scale for Novice Nurses, used to assess the mentoring of entry-level nurses, and to refine the scale items. In Study 1, six nurse education researchers, selected using convenience sampling, with five or more years of nursing experience and experience teaching novice nurses, were invited to an expert meeting in July 2015. A group interview was conducted that lasted approximately 120 minutes. Study 2 examined the content validity index. Between September and November 2015, we distributed a self-administered questionnaire survey to 11 participants selected by convenience sampling. The participants included five nurse education researchers with a minimum of five years of nursing experience and experience teaching novice nurses, as well as six clinical nurses with a master’s degree or higher. Finally, 81 questionnaire items were retained from the initial 125 items. The 81-item Mentoring Function Scale for Novice Nurses had higher content validity than the original scale. To further increase the scale’s applicability, future studies should assess its reliability, construct validity, and criterion-related validity.

Mechanical properties and acoustic emission characteristics of soft rock with different water contents under dynamic disturbance

Uniaxial compression tests and cyclic loading acoustic emission tests were conducted on 20%,40%,60%,80%,dry and saturated muddy sandstone by using a creep impact loading system to investigate the mechanical properties and acoustic emission characteristics of soft rocks with different water contents under dynamic disturbance.The mechanical properties and acoustic emission characteristics of muddy sandstones at different water contents were analysed.Results of experimental studies show that water is a key factor in the mechanical properties of rocks,softening them,increasing their porosity,reducing their brittleness and increasing their plasticity.Under uniaxial compression,the macroscopic damage characteristics of the muddy sandstone change from mono-bevel shear damage and‘X’type conjugate bevel shear damage to a roadway bottom-drum type damage as the water content increases.Dynamic perturbation has a strengthening effect on the mechanical properties of samples with 60%and less water content,and a weakening effect on samples with 80%and more water content,but the weakening effect is not obvious.Macroscopic damage characteristics of dry samples remain unchanged,water samples from shear damage and tensile–shear composite damage gradually transformed into cleavage damage,until saturation transformation monoclinic shear damage.The evolution of acoustic emission energy and event number is mainly divided into four stages:loading stage(Ⅰ),dynamic loading stage(Ⅱ),yield failure stage(Ⅲ),and post-peak stage(Ⅳ),the acoustic emission characteristics of the stages were different for different water contents.The characteristic value of acoustic emission key point frequency gradually decreases,and the damage degree of the specimen increases,corresponding to low water content—high main frequency—low damage and high water content—low main frequency—high damage.

基于新型Contention网络的滚动轴承早期故障诊断方法研究

针对滚动轴承早期故障诊断问题,为了同时建模振动信号中的高频和低频特征,实现高精度诊断,提出了一种新的模型Contention。它以一种互补的方式集成了空洞卷积和自注意力机制的优点,具有同时捕捉高频和低频信息的能力。为了验证其诊断能力,首先,在完整信息原则下将振动信号连续构造成数据集;其次,搭建Contention网络并训练,其最终测试集准确度可达100%,t-SNE显示随网络层次的深入特征被明显聚类;最后,设置对照实验,将该模型与传统RNN、CNN、Transformer模型对比,证明该模型具备突出的诊断能力。

Longitudinal dependence of the forecast accuracy of the ionospheric total electron content in the equatorial zone

The longitudinal dependence of the behavior of ionospheric parameters has been the subject of a number of works where significant variations are discovered.This also applies to the prediction of the ionospheric total electron content(TEC),which neural network methods have recently been widely used.However,the results are mainly presented for a limited set of meridians.This paper examines the longitudinal dependence of the TEC forecast accuracy in the equatorial zone.In this case,the methods are used that provided the best accuracy on three meridians:European(30°E),Southeastern(110°E)and American(75°W).Results for the stations considered are analyzed as a function of longitude using the Jet Propulsion Laboratory Global Ionosphere Map(JPL GIM)for 2015.These results are for 2 h ahead and 24 h ahead forecast.It was found that in this case,based on the metric values,three groups of architectures can be distinguished.The first group included long short-term memory(LSTM),gated recurrent unit(GRU),and temporal convolutional networks(TCN)models as a part of unidirectional deep learning models;the second group is based on the recurrent models from the first group,which were supplemented with a bidirectional algorithm,increasing the TEC forecasting accuracy by 2-3 times.The third group,which includes the bidirectional TCN architecture(BiTCN),provided the highest accuracy.For this architecture,according to data obtained for 9 equatorial stations,practical independence of the TEC prediction accuracy from longitude was observed under the following metrics(Mean Absolute Error MAE,Root Mean Square Error RMSE,Mean Absolute Percentage Error MAPE):MAE(2 h)is 0.2 TECU approximately;MAE(24 h)is 0.4 TECU approximately;RMSE(2 h)is less than 0.5 TECU except Niue station(RMSE(2 h)is 1 TECU approximately);RMSE(24 h)is in the range of 1.0-1.7 TECU;MAPE(2 h)<1%except Darwin station,MAPE(24 h)<2%.This result was confirmed by data from additional 5 stations that formed latitudinal chains in the equatorial part of the three meridians.The complete correspondence of the observational and predicted TEC values is illustrated using several stations for disturbed conditions on December 19-22,2015,which included the strongest magnetic storm in the second half of the year(min Dst=-155 nT).

Digital twin driven and intelligence enabled content delivery in end-edge-cloud collaborative 5G networks

The rapid development of 5G/6G and AI enables an environment of Internet of Everything(IoE)which can support millions of connected mobile devices and applications to operate smoothly at high speed and low delay.However,these massive devices will lead to explosive traffic growth,which in turn cause great burden for the data transmission and content delivery.This challenge can be eased by sinking some critical content from cloud to edge.In this case,how to determine the critical content,where to sink and how to access the content correctly and efficiently become new challenges.This work focuses on establishing a highly efficient content delivery framework in the IoE environment.In particular,the IoE environment is re-constructed as an end-edge-cloud collaborative system,in which the concept of digital twin is applied to promote the collaboration.Based on the digital asset obtained by digital twin from end users,a content popularity prediction scheme is firstly proposed to decide the critical content by using the Temporal Pattern Attention(TPA)enabled Long Short-Term Memory(LSTM)model.Then,the prediction results are input for the proposed caching scheme to decide where to sink the critical content by using the Reinforce Learning(RL)technology.Finally,a collaborative routing scheme is proposed to determine the way to access the content with the objective of minimizing overhead.The experimental results indicate that the proposed schemes outperform the state-of-the-art benchmarks in terms of the caching hit rate,the average throughput,the successful content delivery rate and the average routing overhead.

Quantitative characterizations of anisotropic dynamic properties in organic-rich shale with different kerogen content

Understanding the quantitative responses of anisotropic dynamic properties in organic-rich shale with different kerogen content(KC)is of great significance in hydrocarbon exploration and development.Conducting controlled experiments with a single variable is challenging for natural shales due to their high variations in components,diagenesis conditions,or pore fluid.We employed the hot-pressing technique to construct 11 well-controlled artificial shale with varying KC.These artificial shale samples were successive machined into prismatic shape for ultrasonic measurements along different directions.Observations revealed bedding perpendicular P-wave velocities are more sensitive to the increasing KC than bedding paralleling velocities due to the preferential alignments of kerogen.All elastic stiffnesses except C_(13)are generally decreasing with the increasing KC,the variation of C_(1) and C_(33)on kerogen content are more sensitive than those of C_(44)and C_(66).Apparent dynamic mechanical parameters(v and E)were found to have linear correlation with the true ones from complete anisotropic equations independent of KC,which hold value towards the interpretation of well logs consistently across formations,Anisotropic mechanical parameters(ΔE and brittlenessΔB)tend to decrease with the reducing KC,withΔB showing great sensitivity to KC variations.In the range of low KC(<10%),the V_(P)/V_(S) ratio demonstrated a linearly negative correlation with KC,and the V_(P)/V_(S) ratio magnitude of less than 1.75may serve as a significant characterization for highly organic-rich(>10%)shale,compilation of data from natural organic rich-shales globally verified the similar systematic relationships that can be empirically used to predict the fraction of KC in shales.

Experimental and numerical analyses of the effect of fibre content on the close-in blast performance of a UHPFRC beam

Limited research has been conducted on the influences of fiber content on close-in blasting characteristics for ultrahigh-performance fiber-reinforced concrete(UHPFRC)beams.This paper aims to address this knowledge gap through experimental and mesoscale numerical methods.Experiments were conducted on ten UHPFRC beams built with varying steel fiber volumetric fractions subjected to close-in explosive conditions.Additionally,this study considered other parameters,such as the longitudinal reinforcement type and ratio.In the case of UHPFRC beams featuring normal-strength longitudinal reinforcement of diametersΦ12,Φ16,andΦ20,a reduction in maximum displacement by magnitudes of19.6%,19.5%,and 17.4%was observed,respectively,as the volumetric fractions of fiber increased from1.0%to 2.5%.In addition,increasing the longitudinal reinforcement ratio and using high-strength steel longitudinal reinforcement both significantly reduced the deformation characteristics and increase the blasting resistances of UHPFRC beams.However,the effects on the local crushing and spalling damage were not significant.A mesoscale finite element model,which considers the impacts of fiber parameters on UHPFRC beam behaviors,was also established and well correlated with the test findings.Nevertheless,parametric analyses were further conducted to examine the impacts of the steel fiber content and length and the hybrid effects of various types of microfibers and steel fibers on the blasting performance of UHPFRC beams.

Selection and application of four QTLs for grain protein content in modern wheat cultivars

The grain protein content(GPC)is the key parameter for wheat grain nutritional quality.This study conducted a resampling GWAS analysis using 406 wheat accessions across eight environments,and identified four previously reported GPC QTLs.An analysis of 87 landraces and 259 modern cultivars revealed the loss of superior GPC haplotypes,especially in Chinese cultivars.These haplotypes were preferentially adopted in different agroecological zones and had broad effects on wheat yield and agronomic traits.Most GPC QTLs did not significantly reduce yield,suggesting that high GPC can be achieved without a yield penalty.The results of this study provide a reference for future GPC breeding in wheat using the four identified QTLs.

Improving the Effectiveness of Image Classification Structural Methods by Compressing the Description According to the Information Content Criterion

The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint descriptors.The main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification efficiency.The class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric transformations.It is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content criterion.The informativeness of an etalon descriptor is estimated by the difference of the closest distances to its own and other descriptions.The developed method determines the relevance of the full description of the recognized object with the reduced description of the etalons.Several practical models of the classifier with different options for establishing the correspondence between object descriptors and etalons are considered.The results of the experimental modeling of the proposed methods for a database including images of museum jewelry are presented.The test sample is formed as a set of images from the etalon database and out of the database with the application of geometric transformations of scale and rotation in the field of view.The practical problems of determining the threshold for the number of votes,based on which a classification decision is made,have been researched.Modeling has revealed the practical possibility of tenfold reducing descriptions with full preservation of classification accuracy.Reducing the descriptions by twenty times in the experiment leads to slightly decreased accuracy.The speed of the analysis increases in proportion to the degree of reduction.The use of reduction by the informativeness criterion confirmed the possibility of obtaining the most significant subset of features for classification,which guarantees a decent level of accuracy.

Effect of phosphorus content on interfacial heat transfer and film deposition behavior during the high-temperature simulation of strip casting

The interfacial wettability and heat transfer behavior are crucial in the strip casting of high phosphorus-containing steel.A hightemperature simulation of strip casting was conducted using the droplet solidification technique with the aims to reveal the effects of phosphorus content on interfacial wettability,deposited film,and interfacial heat transfer behavior.Results showed that when the phosphorus content increased from 0.014wt%to 0.406wt%,the mushy zone enlarged,the complete solidification temperature delayed from1518.3 to 1459.4℃,the final contact angle decreased from 118.4°to 102.8°,indicating improved interfacial contact,and the maximum heat flux increased from 6.9 to 9.2 MW/m2.Increasing the phosphorus content from 0.081wt%to 0.406wt%also accelerated the film deposition rate from 1.57 to 1.73μm per test,resulting in a thickened naturally deposited film with increased thermal resistance that advanced the transition point of heat transfer from the fifth experiment to the third experiment.

Main controlling factor and mechanism of gas-in-place content of the Lower Cambrian shale from different sedimentary facies in the western Hubei area, South China

The Lower Cambrian shale gas in the western Hubei area,South China has a great resource prospect,but the gas-in-place(GIP)content in different sedimentary facies varies widely,and the relevant mechanism has been not well understood.In the present study,two sets of the Lower Cambrian shale samples from the Wells YD4 and YD5 in the western Hubei area,representing the deep-water shelf facies and shallowwater platform facies,respectively,were investigated on the differences of pore types,pore structure and methane adsorption capacity between them,and the main controlling factor and mechanism of their methane adsorption capacities and GIP contents were discussed.The results show that the organic matter(OM)pores in the YD4 shale samples are dominant,while the inorganic mineral(IM)pores in the YD5 shale samples are primary,with underdeveloped OM pores.The pore specific surface area(SSA)and pore volume(PV)of the YD4 shale samples are mainly from micropores and mesopores,respectively,while those of the YD5 shale samples are mainly from micropores and macropores,respectively.The methane adsorption capacity of the YD4 shale samples is significantly higher than that of the YD5 shale samples,with a maximum absolute adsorption capacity of 3.13 cm^(3)/g and 1.31 cm^(3)/g in average,respectively.Compared with the shallow-water platform shale,the deep-water shelf shale has a higher TOC content,a better kerogen type and more developed OM pores,which is the main mechanism for its higher adsorption capacity.The GIP content models based on two samples with a similar TOC content selected respectively from the Wells YD4 and YD5 further indicate that the GIP content of the deep-water shelf shale is mainly 34 m^(3)/t within a depth range of 1000—4000 m,with shale gas exploration and development potential,while the shallow-water platform shale has normally a GIP content of<1 m^(3)/t,with little shale gas potential.Considering the geological and geochemical conditions of shale gas formation and preservation,the deep-water shelf facies is the most favorable target for the Lower Cambrian shale gas exploration and development in the western Hubei area,South China.

A Calculation Method of Double Strength Reduction for Layered Slope Based on the Reduction of Water Content Intensity

The calculation of the factor of safety(FOS)is an important means of slope evaluation.This paper proposed an improved double strength reductionmethod(DRM)to analyze the safety of layered slopes.The physical properties of different soil layers of the slopes are different,so the single coefficient strength reduction method(SRM)is not enough to reflect the actual critical state of the slopes.Considering that the water content of the soil in the natural state is the main factor for the strength of the soil,the attenuation law of shear strength of clayey soil changing with water content is fitted.This paper also establishes the functional relationship between different reduction coefficients.Then,a USDFLD subroutine is programmed using the secondary development function of finite element software.Controlling the relationship between field variables and calculation time realizes double strength reduction applicable to the layered slope.Finally,by comparing the calculation results of different examples,it is proved that the stress and displacement distribution of the critical slope state obtained by the improved method is more realistic,and the calculated safety factor is more reliable.The newly proposedmethod considers the difference of intensity attenuation between different soil layers under natural conditions and avoids the disadvantage of the strength reduction method with uniform parameters,which provides a new idea and method for stability analysis of layered and complex slopes.

Multi-omics analysis reveals the pivotal role of phytohormone homeostasis in regulating maize grain water content

Grain water content(GWC)is a key determinant for mechanical harvesting of maize(Zea mays).In our previous research,we identified a quantitative trait locus,qGWC1,associated with GWC in maize.Here,we examined near-isogenic lines(NILs)NILL and NILH that differed at the qGWC1 locus.Lower GWC in NILL was primarily attributed to reduced grain water weight(GWW)and smaller fresh grain size,rather than the accumulation of dry matter.The difference in GWC between the NILs became more pronounced approximately 35 d after pollination(DAP),arising from a faster dehydration rate in NILL.Through an integrated analysis of the transcriptome,proteome,and metabolome,coupled with an examination of hormones and their derivatives,we detected a marked decrease in JA,along with an increase in cytokinin,storage forms of IAA(IAA-Glu,IAA-ASP),and IAA precursor IPA in immature NILL kernels.During kernel development,genes associated with sucrose synthases,starch biosynthesis,and zein production in NILL,exhibited an initial up-regulation followed by a gradual down-regulation,compared to those in NILH.This discovery highlights the crucial role of phytohormone homeostasis and genes related to kernel development in balancing GWC and dry matter accumulation in maize kernels.

Predictability of the upper ocean heat content in a Community Earth System Model ensemble prediction system

Upper ocean heat content(OHC)has been widely recognized as a crucial precursor to high-impact climate variability,especially for that being indispensable to the long-term memory of the ocean.Assessing the predictability of OHC using state-of-the-art climate models is invaluable for improving and advancing climate forecasts.Recently developed retrospective forecast experiments,based on a Community Earth System Model ensemble prediction system,offer a great opportunity to comprehensively explore OHC predictability.Our results indicate that the skill of actual OHC predictions varies across different oceans and diminishes as the lead time of prediction extends.The spatial distribution of the actual prediction skill closely resembles the corresponding persistence skill,indicating that the persistence of OHC serves as the primary predictive signal for its predictability.The decline in actual prediction skill is more pronounced in the Indian and Atlantic oceans than in the Pacific Ocean,particularly within tropical regions.Additionally,notable seasonal variations in the actual prediction skills across different oceans align well with the phase-locking features of OHC variability.The potential predictability of OHC generally surpasses the actual prediction skill at all lead times,highlighting significant room for improvement in current OHC predictions,especially for the North Indian Ocean and the Atlantic Ocean.Achieving such improvements necessitates a collaborative effort to enhance the quality of ocean observations,develop effective data assimilation methods,and reduce model bias.

AHFO-based soil water content sensing technology considering soil-sensor thermal contact resistance

The actively heated fiber-optic(AHFO)technology has become emerged as a research focus due to its advantages of distributed,real-time measurement and good durability.These attributes have led to the gradual application of AHFO technology to the water content measurement of in situ soil.However,all existing in situ applications of AHFO technology fail to consider the effect of soilesensor contact quality on water content measurements,limiting potential for the wider application of AHFO technology.To address this issue,the authors propose a method for determining the soilesensor thermal contact resistance based on the principle of an infinite cylindrical heat source.This is then used to establish an AHFO water content measurement technology that considers the thermal contact resistance.The reliability and validity of the new measurement technology are explored through a laboratory test and a field case study,and the spatial-temporal evolution of the soil water content in the case is revealed.The results demonstrate that method for determining the soilesensor thermal contact resistance is highly effective and applicable to all types of soils.This method requires only the moisture content,dry density,and thermal response of the in situ soil to be obtained.In the field case,the measurement error of soil water content between the AHFO method,which takes into account the thermal contact resistance,and the neutron scattering method is only 0.011.The water content of in situ soil exhibits a seasonal variation,with an increase in spring and autumn and a decrease in summer and winter.Furthermore,the response of shallow soils to precipitation and evaporation is significant.These findings contribute to the enhancement of the accuracy of the AHFO technology in the measurement of the water content of in situ soils,thereby facilitating the dissemination and utilization of this technology.

Estimation of unfrozen water content of saturated sandstones using nuclear magnetic resonance, mercury intrusion porosimetry, and ultrasonic tests

The unfrozenwater content(UWC)is a crucial parameter that affects the strength and thermal properties of rocks in relation to engineering construction and geological disasters in cold regions.In this study,three different methods were employed to test and estimate the UWC of saturated sandstones,including nuclear magnetic resonance(NMR),mercury intrusion porosimetry(MIP),and ultrasonic methods.The NMR method enabled the direct measurement of the UWC of sandstones using the free induction decay(FID).The MIP method was used to analyze the pore structures of sandstones,with the UWC subsequently calculated based on pore ice crystallization.Therefore,the MIP test constituted an indirect measurement method.Furthermore,a correlation was established between the P-wave velocity and the UWC of these sandstones based on the mixture theory,which could be employed to estimate the UWC as an empirical method.All methods demonstrated that the UWC initially exhibited a rapid decrease from 0C to5C and then generally became constant beyond20C.However,these test methods had different characteristics.The NMR method was used to directly and accurately calculate the UWC in the laboratory.However,the cost and complexity of NMR equipment have precluded its use in the field.The UWC can be effectively estimated by the MIP test,but the estimation accuracy is influenced by the ice crystallization process and the pore size distribution.The P-wave velocity has been demonstrated to be a straightforward and practical empirical parameter and was utilized to estimate the UWC based on the mixture theory.This method may be more suitable in the field.All methods confirmed the existence of a hysteresis phenomenon in the freezing-thawing process.The average hysteresis coefficient was approximately 0.538,thus validating the GibbseThomson equation.This study not only presents alternative methodologies for estimating the UWC of saturated sandstones but also contribute to our understanding of the freezing-thawing process of pore water.

Incorporating empirical knowledge into data-driven variable selection for quantitative analysis of coal ash content by laser-induced breakdown spectroscopy

Laser-induced breakdown spectroscopy(LIBS)has become a widely used atomic spectroscopic technique for rapid coal analysis.However,the vast amount of spectral information in LIBS contains signal uncertainty,which can affect its quantification performance.In this work,we propose a hybrid variable selection method to improve the performance of LIBS quantification.Important variables are first identified using Pearson's correlation coefficient,mutual information,least absolute shrinkage and selection operator(LASSO)and random forest,and then filtered and combined with empirical variables related to fingerprint elements of coal ash content.Subsequently,these variables are fed into a partial least squares regression(PLSR).Additionally,in some models,certain variables unrelated to ash content are removed manually to study the impact of variable deselection on model performance.The proposed hybrid strategy was tested on three LIBS datasets for quantitative analysis of coal ash content and compared with the corresponding data-driven baseline method.It is significantly better than the variable selection only method based on empirical knowledge and in most cases outperforms the baseline method.The results showed that on all three datasets the hybrid strategy for variable selection combining empirical knowledge and data-driven algorithms achieved the lowest root mean square error of prediction(RMSEP)values of 1.605,3.478 and 1.647,respectively,which were significantly lower than those obtained from multiple linear regression using only 12 empirical variables,which are 1.959,3.718 and 2.181,respectively.The LASSO-PLSR model with empirical support and 20 selected variables exhibited a significantly improved performance after variable deselection,with RMSEP values dropping from 1.635,3.962 and 1.647 to 1.483,3.086 and 1.567,respectively.Such results demonstrate that using empirical knowledge as a support for datadriven variable selection can be a viable approach to improve the accuracy and reliability of LIBS quantification.

Research on the Legal Framework of Content Regulations for Network Platforms

In the era of the Internet,various network platforms have evolved into new hubs for information dissemination.Currently,China has established a platform-centered content regulation framework,wherein platforms proactively enforce content regulations in accordance with legal censorship obligations.Additionally,platform policies and user agreements augment their authority in content regulation.The platforms can achieve cost-effective and highly efficient content regulation by leveraging their strategic advantages enabled by their own technical capabilities and extensive coverage.The platform self-regulation model,however,still faces challenges.First,accurately evaluating content remains a formidable task;second,ensuring effective platform publicity through self-regulation poses difficulties;third,users may potentially face disadvantages due to the platform’s right of self-regulation;and fourth,digital copyright owners face challenges when defending digital copyright disputes under the safe harbor rule.Therefore,it is imperative to establish,review,and revise the legal framework for content regulation of network platforms in order to enhance the efficiency of their governance systems.The formulation of the legal framework for content regulation of network platforms may encompass the following aspects:rationalizing obligations pertaining to platform content regulations,enhancing supervision over platform self-regulation,and establishing a dual-track responsibility system for digital copyright content regulation.This will ensure a harmonious balance among public interests,users’personal rights and interests,and commercial benefits through regulating the content on network platforms.

Effect of V content on microstructures and properties of TiC cermet fusion welding interface

The effects of vanadium(V)on the microstructures and mechanical properties of the TiC cermet fusion welding interface were studied by adjusting the content of V in the self-developed flux-cored wires using metal inert gas arc(MIG)welding for surfacing on the TiC cermet.The results show that the increase in V content promotes the element diffusion between TiC cermet and weld metal.There are no de-fects observed in the interface,and the diffusion of elements refers to excellent metallurgical bonding.The shear strength of the fusion zone initially decreases and then increases with the increase in V content.The maximum shear strength of the TiC cermet/weld interface,reaching 552 MPa,occurred when the V content reached 0.65%.Meanwhile,the average hardness in the transition zone reached 488.2 HV0.2.

A Survey of Digital Content Required for STD Prevention Education Taught by School Nurses

Purpose: In recent years, there has been concern in Japan about the increase in STDs among adolescents aged 15 - 19. In order to prevent STDs and guide adolescents toward desirable sexual behavior, this study’s goal was to examine the actual state of STD prevention education taught by school nurses as part of the school curriculum, as well as the kinds of digital content they wish to have for teaching on the subject. Method: An anonymous, self-administered questionnaire was distributed by email and leaflet. Targeting the 100 valid responses received from the surveyed school nurses, descriptive statistics were made for each survey item and comparisons were made between the early- and mid-career groups based on years of experience. Results: 70.0% of respondents reported teaching about STDs in Health & Physical Education classes. School nurses in the early-career group used ready-made materials, while the mid-career group used both ready-made and self-made materials. 95% of respondents reported that they had little or no knowledge of STDs, while 84% reported that they were “good” or “fairly good” at teaching classes on sexuality. Both groups reported difficulty with the topics of “phimosis” and “nocturnal emissions” in the physiological category, “sexual behavior” in the “sex-adjacent” category, and “sexual and reproductive issues” in the psychosocial category. Respondents expressed a need for digital content covering the topics of “sexual violence”, “sexual abuse”, “sexually transmitted diseases”, and “how to turn down sex”. The mid-career group desired digital content for more items than the early-career group, with significant differences in the pathogens involved in sexually transmitted diseases and sex-adjacent items. 32.0% of respondents answered that they had done self-study for sex education classes in the past three years, and both groups desired self-study on “sexually transmitted diseases”, with the mid-career group significantly higher than the early-career group on “cervical cancer & HPV”, “emergency contraceptives”, and “media literacy”. Conclusion: Health & Physical Education is the main subject that covers STDs, and pre-existing materials are commonly used. It is expected that this is due to nurses’ busy schedules and the fact that only one school nurse is assigned to each school. The data collected suggested that nurse teachers want categorized digital content that can be used in the classes they are responsible for, rather than educational content on topics they are not comfortable with. In addition, given the changing environment surrounding sex, it was clear that they wish to understand the realities and needs of the high school students they teach, and desire self-study opportunities to improve their teaching methods.