A Novel Method for Forecasting Freak Wave Occurrence in A Short Crested Coastal Sea

In order to forecast the distribution of crest amplitudes and the occurrence of freak waves in a short crested coastal sea,a novel transformed linear simulation method is initially proposed in this paper.A Hermite transformation model expressed as a monotonic cubic polynomial serves as the foundation for the novel simulation technique.The wave crest amplitude exceedance probabilities of two sea states-one with a directional wave spectrum based on the measured wave elevation data at the Yura coast and the other with a typical directional JONSWAP wave spectrum-have been predicted using the novel simulation method that has been proposed.The likelihood that a particular critical wave crest amplitude will be exceeded is directly correlated with the probability that freak waves will occur.It is shown that the novel simulation approach suggested can provide predictions that are more precise than those obtained from the Rayleigh crest amplitude distribution model,the Jahns and Wheeler crest amplitude distribution model,or the conventional linear simulation method.This study also demonstrated that the nonlinear simulation method is less effective than the novel simulation method in terms of efficiency.

The Effects of Accumulated Short Bouts of Mobile-Based Physical Activity Programs on Depression,Perceived Stress,and Negative Affectivity among College Students in South Korea:Quasi-Experimental Study

Regular physical activity(PA)is known to enhance multifaceted health benefits,including both physical and mental health.However,traditional in-person physical activity programs have drawbacks,including time constraints for busy people.Although evidence suggests positive impacts on mental health through mobile-based physical activity,effects of accumulated short bouts of physical activity using mobile devices are unexplored.Thus,this study aims to investigate these effects,focusing on depression,perceived stress,and negative affectivity among South Korean college students.Forty-six healthy college students were divided into the accumulated group(n=23,female=47.8%)and control group(n=23,female=47.6%).The accumulated group engaged in mobile-based physical activity,following guidelines to accumulate a minimum of two times per day and three times a week.Sessions were divided into short bouts,ensuing each bout lasted at least 10 min.The control group did not engage in any specific physical activity.The data analysis involved comparing the scores of the intervention and control groups using several statistical techniques,such as independent sample t-test,paired sample t-tests,and 2(time)×2(group)repeated measures analysis of variance.The demographic characteristics at the pre-test showed no statistically significant differences between the groups.The accumulated group had significant decreases in depression(t_(40)=2.59,p=0.013,Cohen’s D=0.84)and perceived stress(t_(40)=2.06,p=0.046,Cohen’s D=0.56)from the pre-to post-test.The control group exhibited no statistically significant differences in any variables.Furthermore,there were significant effects of time on depression scores(F1,36=4.77,p=0.036,η_(p)^(2)=0.12)while significant interaction effects were also observed for depression(F_(1,36)=6.59,p=0.015,η_(p)^(2)=0.16).This study offers informative insights into the potential advantages of mobile-based physical activity programs with accumulated periods for enhancing mental health,specifically in relation to depression.This study illuminates the current ongoing discussions on efficient approaches to encourage mobile-based physical activity and improve mental well-being,addressing various lifestyles and busy schedules.

Effectiveness of Short Message Service Support on Adherence to Chemotherapy Treatment among Patients Attending Cancer Treatment Facilities in Kenya

Introduction: Cancer is a chronic debilitating disease that unnerves patients, communities, and nations. At some point in cancer patient’s disease experience, chemotherapy is used, and the patient is expected to adhere to treatment to improve survival and quality of life. Methods: This multisite Cluster Randomized Trial (CRT) evaluated the effectiveness of mobile phone Short Message Service (SMS) support on the adherence to treatment schedules among adult cancer patients in Kenya. Data was collected using questionnaires. Ethical approvals were obtained from relevant Ethical Review Boards (ERBs). Results: The mean adherence was 83%. There was a significant difference between treatment arms in relation to the adherence. The intervention arm had a higher mean adherence difference, M = 3.913, 95% CI 2.632-5.193, t (402) = 6.006, p ≤ 0.001), with Cohen’s d = 0.60. Although not significant, (χ2dd = 0.151, df = 1, p = 2.064), more women were perfect adheres than males. Perfect adherers were satisfied with SMS support (χ2dd = 7.620, df = 1, p = 0.06), were in the intervention arm (χ2dd = 22.942, df = 1, p ≤ 0.001), and had trust in the care provider (χ2dd = 10.591 p ≤ 0.001). SMS support was not significant in the multivariate analysis but had an estimated effect size of 0.958 (z = 1.424, p = 0.154, CI = 0.242-3.781), indicating that mean adherence was slightly better in the presence of the intervention. Conclusions: SMS-support intervention has demonstrated superiority in influencing adherence. Further, health system-related factors have a significant influence on the adherence to chemotherapy treatment. Interventions to re-design health systems that are responsive to unmet care needs of cancer patients must be explored. .

An Algorithm for Short-Circuit Current Interval in Distribution Networks with Inverter Type Distributed Generation Based on Affine Arithmetic

During faults in a distribution network,the output power of a distributed generation(DG)may be uncertain.Moreover,the output currents of distributed power sources are also affected by the output power,resulting in uncertainties in the calculation of the short-circuit current at the time of a fault.Additionally,the impacts of such uncertainties around short-circuit currents will increase with the increase of distributed power sources.Thus,it is very important to develop a method for calculating the short-circuit current while considering the uncertainties in a distribution network.In this study,an affine arithmetic algorithm for calculating short-circuit current intervals in distribution networks with distributed power sources while considering power fluctuations is presented.The proposed algorithm includes two stages.In the first stage,normal operations are considered to establish a conservative interval affine optimization model of injection currents in distributed power sources.Constrained by the fluctuation range of distributed generation power at the moment of fault occurrence,the model can then be used to solve for the fluctuation range of injected current amplitudes in distributed power sources.The second stage is implemented after a malfunction occurs.In this stage,an affine optimization model is first established.This model is developed to characterizes the short-circuit current interval of a transmission line,and is constrained by the fluctuation range of the injected current amplitude of DG during normal operations.Finally,the range of the short-circuit current amplitudes of distribution network lines after a short-circuit fault occurs is predicted.The algorithm proposed in this article obtains an interval range containing accurate results through interval operation.Compared with traditional point value calculation methods,interval calculation methods can provide more reliable analysis and calculation results.The range of short-circuit current amplitude obtained by this algorithm is slightly larger than those obtained using the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Therefore,the proposed algorithm has good suitability and does not require iterative calculations,resulting in a significant improvement in computational speed compared to the Monte Carlo algorithm and the Latin hypercube sampling algorithm.Furthermore,the proposed algorithm can provide more reliable analysis and calculation results,improving the safety and stability of power systems.

Numerical Analysis of Cold-Formed Thin-Walled Steel Short Columns with Pitting Corrosion during Bridge Construction

Pitting corrosion is harmful during bridge construction,which will lead to uneven roughness of steel surfaces and reduce the thickness of steel.Hence,the effect of pitting corrosion on the mechanical properties of cold-formed thin-walled steel stub columns is studied,and the empirical formulas are established through regression fitting to predict the ultimate load of web and flange under pitting corrosion.In detail,the failure modes and load-displacement curves of specimens with different locations,area ratios,and depths are obtained through a large number of non-linear finite element analysis.As for the specimens with pitting corrosion on the web,all the specimens are subject to local buckling failure,and the failure mode will not change with pitting corrosion,but the failure location will change with pitting corrosion location;the size,location,and area ratio of pitting corrosion have little influence on the ultimate load of cold-formed thin-walled steel short columns,but the loss rate of pitting corrosion section area has a greater impact on the ultimate bearing capacity.As for the specimen with flange pitting corrosion,the location and area ratio of pitting corrosion have less influence on the ultimate load of cold-formed thin-walled steel short columns,and the section area loss rate has greater influence on the ultimate bearing capacity;the impact of web pitting corrosion on the ultimate load is greater than that of flange pitting corrosion under the same condition of pitting corrosion section area.The prediction formulas of limit load which are suitable for pitting corrosion of web and flange are established,which can provide a reference for performance evaluation of corroded cold-formed thin-walled steel.

Mid-term survival of the Optimys short stem: A prospective case series of 500 patients

BACKGROUND In recent years,there has been an increase in the number of total hip arthroplasty procedures in the younger patient population.This active group has higher expectations of their prosthesis in comparison to the older population,and there is a greater physical demand for the prosthesis.Short femoral stems were in-troduced to retain proximal bone stock and joint biomechanics and became more common to implant in this specific population.Currently,the long-term survival and functional outcomes of various short stems are still being investigated in different clinics.AIM To determine the 5-year survival of the Optimys hip stem.METHODS This was a prospective multicenter cohort study of 500 patients conducted in two hospitals in the Netherlands.All patients received the Optimys short stem(Mathys Ltd,Bettlach,Switzerland).The primary outcome measure was survival of the hip stem,with revision as the endpoint.The secondary outcome measurements included patient-reported outcome measures(PROMs).Kaplan-Meier analysis was used to calculate the 5-year survival rate.Log-minus-log transformation was performed to calculate the 95%confidence interval(95%CI).Mixed model analyses were performed to assess the course of the PROMs during the 1st 2 years after surgery.Analyses were modeled separately for the 1st and 2nd years to calculate the yearly change in PROMs during both follow-up periods with accompanying 95%CIs.RESULTS The mean age of the total 500 patients was 62.3 years(standard deviation:10.6)and 202 were male(40%).At a median follow-up of 5.5 years(interquartile range:4.5-6.7),7 patients were deceased and 6 revisions were registered,for infection(n=3),subsidence(n=2)and malposition(n=1).This resulted in an overall 5-year survival of 98.8%(95%CI:97.3-99.5).If infection was left out as reason for revision,a stem survival of 99.4%(95%CI:98.1-99.8)was seen.Baseline questionnaires were completed by 471 patients(94%),317 patients(63%)completed the 1-year follow-up questionnaires and 233 patients(47%)completed the 2-year follow-up.Both outcome measures significantly improved across all domains in the 1st year after the operation(P<0.03 for all domains).In the 2nd year after surgery,no significant changes were observed in any domain in comparison to the 1-year follow-up.CONCLUSION The Optimys stem has a 5-year survival of 98.8%.Patient-reported outcome measures increased significantly in the 1st postoperative year with stabilization at the 2-year follow-up.

Sepsis during short bowel syndrome hospitalizations:Identifying trends,disparities,and clinical outcomes in the United States

BACKGROUND Short bowel syndrome(SBS)hospitalizations are often complicated with sepsis.There is a significant paucity of data on adult SBS hospitalizations in the United States and across the globe.AIM To assess trends and outcomes of SBS hospitalizations complicated by sepsis in the United States.METHODS The National Inpatient Sample was utilized to identify all adult SBS hospitalizations between 2005-2014.The study cohort was further divided based on the presence or absence of sepsis.Trends were identified,and hospitalization characteristics and clinical outcomes were compared.Predictors of mortality for SBS hospitalizations complicated with sepsis were assessed.RESULTS Of 247097 SBS hospitalizations,21.7%were complicated by sepsis.Septic SBS hospitalizations had a rising trend of hospitalizations from 20.8%in 2005 to 23.5%in 2014(P trend<0.0001).Compared to non-septic SBS hospitalizations,septic SBS hospitalizations had a higher proportion of males(32.8%vs 29.3%,P<0.0001),patients in the 35-49(45.9%vs 42.5%,P<0.0001)and 50-64(32.1%vs 31.1%,P<0.0001)age groups,and ethnic minorities,i.e.,Blacks(12.4%vs 11.3%,P<0.0001)and Hispanics(6.7%vs 5.5%,P<0.0001).Furthermore,septic SBS hospitalizations had a higher proportion of patients with intestinal transplantation(0.33%vs 0.22%,P<0.0001),inpatient mortality(8.5%vs 1.4%,P<0.0001),and mean length of stay(16.1 d vs 7.7 d,P<0.0001)compared to the non-sepsis cohort.A younger age,female gender,White race,and presence of comorbidities such as anemia and depression were identified to be independent predictors of inpatient mortality for septic SBS hospitalizations.CONCLUSION Septic SBS hospitalizations had a rising trend between 2005-2014 and were associated with higher inpatient mortality compared to non-septic SBS hospitalizations.

Research on Strategies for Enhancing the Ability of Chinese German Learners to Tell Chinese Stories Through Short Videos

In the age of new media,short videos play an increasingly important role in international cultural exchange.However,German learners often encounter challenges when producing and sharing short videos due to factors such as technology and language proficiency.Such challenges can affect the professionalism and attractiveness of the videos.This study focuses on German learners at the University of Shanghai for Science and Technology.The aim of this study is to investigate students’experiences in producing short videos,identify issues through surveys and interviews,and concentrate on editing skills,language proficiency,and intercultural communication abilities.It proposes strategies for developing these skills and aims to provide insights for German and other foreign language learners in telling Chinese stories using short videos.

Navigating Long-Term Management Challenges in Short Bowel Syndrome: A Case Report of Chronic Intestinal Failure Complicated by Kidney Dysfunction

The most common cause of intestinal failure is short bowel syndrome (SBS), occurring as a result of a small functional intestine length, usually less than 200 cm, leading to intestinal malabsorption. A 59-year-old female with a past medical history of Crohns disease status post total colectomy with ileostomy over 20 years ago came to the hospital due to progressive weakness. Despite medical management, the patient had high ileostomy output, leading to electrolyte disbalance, metabolic acidosis, dehydration, and progressive kidney decline. Due to the high dependence on continuous fluid supplementation, it was decided to place a port for parenteral hydration to maintain fluid replacements and homeostasis after discharge. Prompt initiation of parenteral fluid replacement and close follow-up on patients with ileostomy and intestinal failure is strongly recommended to avoid complications and prevent intestinal, liver, or kidney transplants.

Analysis of the Application and Effect of Homemade Medical Scrotal Support Shorts

Objective:To design and manufacture medical scrotal support shorts for patients with enlarged scrotum and observe its application and effect.Methods:40 patients with enlarged scrotum admitted to the basic surgery department from February 2021 to March 2023 were selected and divided into a test group and a control group according to their time of admission,with the test group using scrotal support shorts and the control group using ordinary shorts without scrotal support pockets or diapers.Results:The complication rate of skin injury in the scrotum and the surrounding inguinal area of the patients in the test group was significantly lower than that of the control group(P<0.01).The medical cost covered by patients in the test group was significantly lower than that of the control group(P<0.01)and the hospitalization satisfaction of the patients in the test group was significantly higher than that of the control group(P<0.01).The difference in the therapeutic effect of the test groups was statistically significant when compared with the control group(P<0.05).Conclusion:Homemade medical scrotal support shorts reduced the local enlargement of the scrotum and bleeding,but also protected the scrotum and the surrounding skin to prevent secondary injuries.The process of patient care was simple and promoted their recovery.The length of hospitalization was also decreased,the burden of health care costs was reduced,and the overall comfort and satisfaction of the patient was improved.

A Study on Rural Cultural Communication of Short Videos From the Perspective of Mediation-Taking the Popularization of “Village BA” (Village Basketball Association) in Qiandongnan as an Example

With the rise of new media and short videos shaping the new communication environment,rural culture has been mediated and transformed to spread to a wider region.As a cultural achievement of rural revitalization,“Village BA”(Village Basketball Association)demonstrates Chinese modernization.The use of short videos,mass rural movements,and“spectacle”spaces to attract spectators has become a key issue in the dissemination of rural culture.

Application Progress of Teaching in the Form of Traffic Short Videos in Nursing Education

With the rapid development of the information technology era,the teaching quality requirements continue to surge,and the mode of education in colleges and universities has also carried out certain innovations.The integration of modern information technology into the teaching process and the combination of medical content has become a new hotspot for reform and innovation of medical education at home and abroad.In this paper,we will describe the application of traffic short videos as the main teaching form in nursing education in domestic and foreign studies,and the role of the application of this teaching form in the improvement of theoretical knowledge and clinical skills of nursing students,as well as the impact on the cultivation of nursing students’professional cognition,communication skills,critical thinking,etc.,with the aim of providing new perspectives for the subsequent nursing education.

Comparative study on the performance of ConvLSTM and ConvGRU in classification problems-taking early warning of short-duration heavy rainfall as an example

卷积长短期记忆单元ConvLSTM和卷积门控循环单元ConvGRU是两种广泛应用的深度学习单元,通过将循环机制与卷积运算相结合,常常用于时空序列的预测.为了明确上述两种模型的收敛速度和分类能力,需要使用相同的模型架构对相同的分类问题进行预测.本研究将北京短时强降水区级预警问题看作深度学习中的二分类问题,使用京津冀雷达网的组合反射率数据和北京区域内的自动气象站降雨数据进行深度学习模型的训练和评估.结果表明,ConvGRU的收敛速度比ConvLSTM快约25%.ConvLSTM和ConvGRU的预警性能随地区,时间,降雨强度的变化趋势相似,但大部分ConvLSTM的得分较高,少数情况下ConvGRU的得分较高.

Probability Criterion for a Dynamic Financial Model with Short-Selling Allowed

Probability criterion has its practical significance, and its investment decision-making is determined by the expected discounted wealth. In a complete, standard financial market with short-selling allowed, this paper probes into the investment decision-making with probability criterion. The upper limit of criterion function is obtained. The corresponding discounted wealth process and hedging portfolio process are provided. Finally, an illustrative example of one-dimensional constant-coefficient financial market is given.

Saturnin-Short轻量级认证加密算法的统计无效故障分析

面向随机单字节故障模型和唯密文攻击假设,提出了一种针对Saturnin-Short算法的统计无效故障分析方法。该方法基于统计分布和无效状态分析,通过结合故障注入前后中间状态的变化,设计并采用了概率对称卡方-极大似然估计和调和中项-汉明重量新型区分器,最少仅需1097个无效故障并以不低于99%的成功率恢复Saturnin-Short算法的256 bit原始密钥。实验分析表明,所提区分器不仅降低了故障注入数,而且减少了攻击时间和复杂度。因此,Saturnin-Short算法不能抵抗统计无效故障分析的攻击。研究结果为其他轻量级认证加密算法的安全性分析提供了重要参考。

Data-driven short circuit resistance estimation in battery safety issues

Developing precise and fast methods for short circuit detection is crucial for preventing or mitigating the risk of safety issues of lithium-ion batteries(LIBs).In this paper,we developed a Convolutional Neural Networks(CNN)based model that can quickly and precisely predict the short circuit resistance of LIB cells during various working conditions.Cycling tests of cells with an external short circuit(ESC)are produced to obtain the database and generate the training/testing samples.The samples are sequences of voltage,current,charging capacity,charging energy,total charging capacity,total charging energy with a length of 120 s and frequency of 1 Hz,and their corresponding short circuit resistances.A big database with~6×10^(5)samples are generated,covering various short circuit resistances(47~470Ω),current loading modes(Constant current-constant voltage(CC-CV)and drive cycle),and electrochemical states(cycle numbers from 1 to 300).Results show that the average relative absolute error of five random sample splits is 6.75%±2.8%.Further parametric analysis indicates the accuracy estimation benefits from the appropriate model setups:the optimized input sequence length(~120 s),feature selection(at least one total capacity-related variable),and rational model design,using multiple layers with different kernel sizes.This work highlights the capabilities of machine learning algorithms and data-driven methodologies in real-time safety risk prediction for batteries.

A Fault Feature Extraction Model in Synchronous Generator under Stator Inter-Turn Short Circuit Based on ACMD and DEO3S

This paper proposed a new diagnosis model for the stator inter-turn short circuit fault in synchronous generators.Different from the past methods focused on the current or voltage signals to diagnose the electrical fault,the sta-tor vibration signal analysis based on ACMD(adaptive chirp mode decomposition)and DEO3S(demodulation energy operator of symmetrical differencing)was adopted to extract the fault feature.Firstly,FT(Fourier trans-form)is applied to the vibration signal to obtain the instantaneous frequency,and PE(permutation entropy)is calculated to select the proper weighting coefficients.Then,the signal is decomposed by ACMD,with the instan-taneous frequency and weighting coefficient acquired in the former step to obtain the optimal mode.Finally,DEO3S is operated to get the envelope spectrum which is able to strengthen the characteristic frequencies of the stator inter-turn short circuit fault.The study on the simulating signal and the real experiment data indicates the effectiveness of the proposed method for the stator inter-turn short circuit fault in synchronous generators.In addition,the comparison with other methods shows the superiority of the proposed model.

Short Term Traffic Flow Prediction Using Hybrid Deep Learning

Traffic flow prediction in urban areas is essential in the IntelligentTransportation System (ITS). Short Term Traffic Flow (STTF) predictionimpacts traffic flow series, where an estimation of the number of vehicleswill appear during the next instance of time per hour. Precise STTF iscritical in Intelligent Transportation System. Various extinct systems aim forshort-term traffic forecasts, ensuring a good precision outcome which was asignificant task over the past few years. The main objective of this paper is topropose a new model to predict STTF for every hour of a day. In this paper,we have proposed a novel hybrid algorithm utilizing Principal ComponentAnalysis (PCA), Stacked Auto-Encoder (SAE), Long Short Term Memory(LSTM), and K-Nearest Neighbors (KNN) named PALKNN. Firstly, PCAremoves unwanted information from the dataset and selects essential features.Secondly, SAE is used to reduce the dimension of input data using onehotencoding so the model can be trained with better speed. Thirdly, LSTMtakes the input from SAE, where the data is sorted in ascending orderbased on the important features and generates the derived value. Finally,KNN Regressor takes information from LSTM to predict traffic flow. Theforecasting performance of the PALKNN model is investigated with OpenRoad Traffic Statistics dataset, Great Britain, UK. This paper enhanced thetraffic flow prediction for every hour of a day with a minimal error value.An extensive experimental analysis was performed on the benchmark dataset.The evaluated results indicate the significant improvement of the proposedPALKNN model over the recent approaches such as KNN, SARIMA, LogisticRegression, RNN, and LSTM in terms of root mean square error (RMSE)of 2.07%, mean square error (MSE) of 4.1%, and mean absolute error (MAE)of 2.04%.

Stress Distributions Created by Short and Regular Implants Placed in the Anterior Maxilla at Different Angles: A Finite Element Analysis

Although short implants are seen as alternative treatments that require additional surgical techniques in posterior region, they can be applied to anterior maxilla and various studies are required on this subject. The purpose of this study was to examine and compare the peak von Mises stress distributions in the crown, implant and abutment by using finite element analysis (FEA). Besides, a comparison of the implant-abutment connection types in the short implant with the FEA method was established. A short implant (4 × 5 mm) with a taper-lock connection and a regular implant (4 × 9 mm) with a screw connection were used in maxillary central incisor tooth area. Three different titanium abutments with 0?, 15? and 25? angles were used for abutments. In addition, in order to determine whether the stress change in short implants is due to the length of the implant-abutment connection, a screw was designed for a short implant and it was also evaluated in the same three angles. A total of three groups and nine models were generated. 114.6N load was applied to the cingulum area of the crown at an angle of 135? to the long axis of the crowns. A torque load of 25 Ncm was applied to the regular and short implant screw. Von Mises stress distributions of implants, abutments and crowns were evaluated by using FEA. Increased angle in implants increased von Mises stress values of implant, abutment and crown. Screw connection was found higher at all angles in short implants. Close values were found at different angles in taper-lock short implant crowns. The length and the angle in the bone of implant with the type of implant-abutment connection results in the accumulated stress values. Clinical Implications Taper implant-abutment connection system was found to be more promising in terms of stress accumulation in crowns. Although the amount of stress on the abutment increased due to the length of the implant in short implants, taper implant-abutment connection system slightly reduced related to this increase.

Short Video Recommendation Algorithm Incorporating Temporal Contextual Information and User Context

With the popularity of 5G and the rapid development of mobile terminals,an endless stream of short video software exists.Browsing short-form mobile video in fragmented time has become the mainstream of user’s life.Hence,designing an efficient short video recommendation method has become important for major network platforms to attract users and satisfy their requirements.Nevertheless,the explosive growth of data leads to the low efficiency of the algorithm,which fails to distill users’points of interest on one hand effectively.On the other hand,integrating user preferences and the content of items urgently intensify the requirements for platform recommendation.In this paper,we propose a collaborative filtering algorithm,integrating time context information and user context,which pours attention into expanding and discovering user interest.In the first place,we introduce the temporal context information into the typical collaborative filtering algorithm,and leverage the popularity penalty function to weight the similarity between recommended short videos and the historical short videos.There remains one more point.We also introduce the user situation into the traditional collaborative filtering recommendation algorithm,considering the context information of users in the generation recommendation stage,and weight the recommended short-formvideos of candidates.At last,a diverse approach is used to generate a Top-K recommendation list for users.And through a case study,we illustrate the accuracy and diversity of the proposed method.