Unified Description of the Three Stable Particles in Self-Action Allows Determination of Their Relative Masses

The Dirac equation γμ(δμ-eAμ)Ψ=mc2Ψ describes the bound states of the electron under the action of external potentials, Aμ. We assumed that the fundamental form of the Dirac equation γμ(δμ-Sμ)Ψ=0 should describe the stable particles (the electron, the proton and the dark-matter-particle (dmp)) bound to themselves under the action of their own potentials Sμ. The new equation reveals that self energy is consequence of self action, it also reveals that the spin angular momentum is consequence of the dynamic structure of the stable particles. The quantitative results are the determination of their relative masses as well as the determination of the electromagnetic coupling constant.

Safety and efficacy of Kaffes intraductal self-expanding metal stents in the management of post-liver transplant anastomotic strictures

BACKGROUND Endoscopic management is the first-line therapy for post-liver-transplant anas-tomotic strictures.Although the optimal duration of treatment with plastic stents has been reported to be 8-12 months,data on safety and duration for metal stents in this setting is scarce.Due to limited access to endoscopic retrograde cholan-giopancreatography(ERCP)during the coronavirus disease 2019 pandemic in our centre,there was a change in practice towards increased usage and length-of-stay of the Kaffes biliary intraductal self-expanding stent in patients with suitable anatomy.This was mainly due to the theoretical benefit of Kaffes stents allowing for longer indwelling periods compared to the traditional plastic stents.METHODS Adult liver transplant recipients aged 18 years and above who underwent ERCP were retrospectively identified during a 10-year period through a database query.Unplanned admissions post-Kaffes stent insertion were identified manually through electronic and scanned medical records.The main outcome was the incidence of complications when stents were left indwelling for 3 months vs 6 months.Stent efficacy was calculated via rates of stricture recurrence between patients that had stenting courses for≤120 d or>120 d.RESULTS During the study period,a total of 66 ERCPs with Kaffes insertion were performed in 54 patients throughout their stenting course.In 33 ERCPs,the stent was removed or exchanged on a 3-month interval.No pancreatitis,perfor-ations or deaths occurred.Minor post-ERCP complications were similar between the 3-month(abdominal pain and intraductal migration)and 6-month(abdominal pain,septic shower and embedded stent)groups-6.1%vs 9.1%respectively,P=0.40.All strictures resolved at the end of the stenting course,but the stenting course was variable from 3 to 22 months.The recurrence rate for stenting courses lasting for up to 120 d was 71.4%and 21.4%for stenting courses of 121 d or over(P=0.03).There were 28 patients that were treated with a single ERCP with Kaffes,21 with removal after 120 d and 7 within 120 d.There was a significant improvement in stricture recurrence when the Kaffes was removed after 120 d when a single ERCP was used for the entire stenting course(71.0%vs 10.0%,P=0.01).CONCLUSION Utilising a single Kaffes intraductal fully-covered metal stent for at least 4 months is safe and efficacious for the management of post-transplant anastomotic strictures.

Evaluation of Optical Properties of Self-Frequency-Doubling Crystal Yb：GdYAl3（BO3）4 for Laser Applications

Yb：GdYAl3 （B03）4 （Yb：GdYAB） is investigated as a new laser crystal for potential applications in self-frequency doubling. The emission and absorption properties of Yb：GdYAB crystal are studied, and the emission decay times of the upper laser level are measured. The emission cross sections are evaluated using the absorption cross section and principle of reciprocity. The other laser performance parameters, such as the minimum inversion fraction βmin, pump saturation intensity Isat and minimum pump intensity 1rain, are also calculated. The results are discussed in the framework of requirements for an effective diode-pumped Yb^3＋ laser system. Yb：GdYAB is expected to exhibit the most useful laser properties and to be superior to Yb：YAB crystal that has been excellent self-frequency-doubling crystal at present in many key spectroscopic parameter values.

Effect of Diabetes Self-Management Education on Glycaemic Control in Sudanese Adults with Type 2 Diabetes

Research Background: The high prevalence of diabetes in Sudan, estimated at 16%, highlights the importance of effective health education in diabetes management. Diabetes self-management education has been identified as a crucial tool in enhancing the knowledge, attitudes, and abilities necessary for self-management among individuals with diabetes. Aim: To assess the impact of diabetes self-management education on medication adherence and glycemic control in Sudanese adults with type 2 diabetes before and 3 months after the DSME intervention. Method: The study was conducted in Sudan between September 2022 and March 2023, it was an interventional, one-group, pre- and post-test study that aimed to assess the impact of diabetes self-management education (DSME) on medication adherence and diabetes control in Sudanese adults with type 2 diabetes. The research was conducted in primary health care centers in six cities in Sudan and involved 244 participants. The data entry and statistical analysis were conducted using the Statistical Package for Social Sciences version 27.0. A paired t test was used for analysis. Results: The study included 244 participants, 67% of whom were males. The age mean ± SD was 48.6 ± 9.3 years, and 85.3% of participants were married. Age at onset of diabetes mean ± SD was 40.60 ± 7.81 years;44.6% had diabetes for less than 5 years;and 84.1% had a positive family history of diabetes mellitus. The levels of poor, low, and partial adherence to medication decreased by 8.2%, 4%, and 20.6%, respectively, after the intervention. The levels of good and high medication regime adherence increased by 13% and 19.8%, respectively;BMI decreased by 1.1 ± 0.73 kg/m2 (p = 0.005). The fasting blood sugar decreased by 69 ± 32.9 mg/dl (p = 0.049), and the glycated hemoglobin decreased by 1.21 ± 0.28% (p = 0.001). Conclusions: The findings of this study reinforce the importance of patient education in improving glycemic control and enhancing self-management behaviors. Patient education plays a critical role in enhancing glycemic control and self-management behaviors. It is essential for healthcare providers to adopt a patient-centered approach, taking into account the individual's beliefs, attitudes, and knowledge about their illness and treatment. Overcoming these challenges necessitates a comprehensive approach, including enhancing healthcare professionals’ knowledge and communication skills, offering accessible and culturally sensitive diabetes education programs, and addressing barriers to resources and support for self-management.

基于BERT-SELFATT-CNN模型的垃圾邮件分类方法

针对传统垃圾邮件分类方法中使用静态词向量不能解决一词多义、长序列信息特征提取不足等问题,提出了一种基于BERT-SELFATT-CNN模型的垃圾邮件分类方法。使用动态文本表示方法BERT对邮件内容进行预训练,并生成带有上下语义信息的词向量,经过能够并行计算的自注意力机制层计算词与词之间的相似度去挖掘句子长距离信息,将生成的隐藏层向量输入到CNN网络提取向量局部特征。在中文垃圾邮件数据集上与已有模型进行对比实验,结果表明该模型在精确度、召回率和F1值上均有提高,模型训练速度也得到提升。

Research Progress on Self-Efficacy Level of Patients with Type 2 Diabetes Mellitus and Its Influencing Factors

Self-efficacy plays an important role in the management of type 2 diabetes mellitus (T2DM) patients, and it runs through the whole process of diabetes treatment, which is conducive to controlling and delaying the occurrence and development of complications, as well as improving the quality of life of patients. This paper mainly describes the concept of self-efficacy, the current situation of self-efficacy of diabetic patients at home and abroad, the functional aspects and their influencing factors, so as to take relevant measures on how to improve self-efficacy. It aims to provide a theoretical basis for the development of self-efficacy interventions for patients with type 2 diabetes mellitus.

Practice of Glycemic Self-Monitoring in Diabetic Patients Followed at the Endocrinology Department of Donka University Hospital in Guinea

Diabetes is a chronic pathology whose evolution is marked by micro and macroangiopathic complications. Optimal management can prevent the onset of complications and improve patients’ quality of life. Objectives: To determine the frequency of self-monitoring of blood glucose and to describe the errors found during self-monitoring in diabetic patients followed at the Endocrinology Department of Donka University Hospital in Guinea. Materials and methods: Descriptive cross-sectional study carried out between August and September 2020 involving diabetic patients followed up at the Endocrinology and Diabetology Department of the Donka National Hospital, CHU Conakry. Results: A total of 301 patients were enrolled, with an average age of 44.24 ± 21.01 years. 64.12% were female. Type 2 diabetes predominated in 64% of cases. The mean duration of diabetes was 6.14 ± 4.67 years, and 75.08% of patients lived in urban areas. Patients were on insulin in 36.21% of cases, insulin and biguanides (26.25%), hypoglycemic sulfonamide and biguanides (19.27%) and biguanides in 18.27% of cases. The frequency of self-monitoring of blood glucose was 43%, and 38% of patients made errors, notably reusing lancets (60%), not checking the expiration date (55.65%) and not washing their hands (48%). Conclusion: This study shows that self-monitoring of blood glucose is not performed by the majority of patients. Numerous errors were identified during blood glucose testing. Continued therapeutic education on the use of blood glucose meters will help empower patients and improve their quality of life.

Decision-Making and Management of Self-Care in Persons with Traumatic Spinal Cord Injuries: A Preliminary Study

Patients and physicians understand the importance of self-care following spinal cord injury (SCI), yet many individuals with SCI do not adhere to recommended self-care activities despite logistical supports. Neurobehavioral determinants of SCI self-care behavior, such as impulsivity, are not widely studied, yet understanding them could inform efforts to improve SCI self-care. We explored associations between impulsivity and self-care in an observational study of 35 US adults age 18 - 50 who had traumatic SCI with paraplegia at least six months before assessment. The primary outcome measure was self-reported self-care. In LASSO regression models that included all neurobehavioral measures and demographics as predictors of self-care, dispositional measures of greater impulsivity (negative urgency, lack of premeditation, lack of perseverance), and reduced mindfulness were associated with reduced self-care. Outcome (magnitude) sensitivity, a latent decision-making parameter derived from computationally modeling successive choices in a gambling task, was also associated with self-care behavior. These results are preliminary;more research is needed to demonstrate the utility of these findings in clinical settings. Information about associations between impulsivity and poor self-care in people with SCI could guide the development of interventions to improve SCI self-care and help patients with elevated risks related to self-care and secondary health conditions.

Edge-Federated Self-Supervised Communication Optimization Framework Based on Sparsification and Quantization Compression

The federated self-supervised framework is a distributed machine learning method that combines federated learning and self-supervised learning, which can effectively solve the problem of traditional federated learning being difficult to process large-scale unlabeled data. The existing federated self-supervision framework has problems with low communication efficiency and high communication delay between clients and central servers. Therefore, we added edge servers to the federated self-supervision framework to reduce the pressure on the central server caused by frequent communication between both ends. A communication compression scheme using gradient quantization and sparsification was proposed to optimize the communication of the entire framework, and the algorithm of the sparse communication compression module was improved. Experiments have proved that the learning rate changes of the improved sparse communication compression module are smoother and more stable. Our communication compression scheme effectively reduced the overall communication overhead.

基于DCNN网络及Self-Attention-BiGRU机制的轴承剩余寿命预测

深度神经网络在剩余寿命预测(RUL)领域得到了广泛的应用。传统的滚动轴承寿命预测模型存在预测精确度较低、鲁棒性较弱的问题。为了进一步提升预测模型的精确度以及鲁棒性,提出了一种融合深度卷积神经网络(DCNN)、双向门控循环单元(BiGRU)以及自注意力机制(Self-Attention)三种模块的滚动轴承剩余使用寿命预测模型。首先,利用DCNN网络对原始振动信号的时域特征、频域特征进行了提取;然后,使用不确定量化的方法对提取到的特征进行了评价和筛选,利用筛选过后的特征构建了新的替代特征集;最后,利用Self-Attention-BiGRU网络对轴承的剩余使用寿命进行了预测,并在IEEE PHM2012数据集上进行了验证。实验结果表明:相较于BiGRU、GRU和BiLSTM三种模型的预测结果,基于DCNN及Self-Attention-BiGRU方法的预测结果最优,两项误差值:平均绝对误差(MAE)、均方根误差(RMSE)最低,其中工况一的一号轴承RUL预测的MAE值相较于BiGRU、GRU以及BiLSTM网络分别下降了7.0%、7.4%和6.5%,RMSE值相较于其他三种模型分别下降了7.6%、8.4%和6.9%,预测的Score值最高,分值为0.985。通过不同数据集的划分,证明了该方法在轴承RUL预测时的强鲁棒性。实验结果验证了基于DCNN网络及Self-Attention-BiGRU模型在轴承剩余使用寿命预测中的有效性。

Three-Dimensional Multi-Phase Microscopic Simulation of Service Life of Recycled Large Aggregate Self-Compacting Concrete

Recycled large aggregate self-compacting concrete (RLA-SCC) within multiple weak areas. These weak areas have poor resistance to chloride ion erosion, which affects the service life of RLA-SCC in the marine environment. A three-dimensional multi-phase mesoscopic numerical model of RLA-SCC was established to simulate the chloride ions transportation in concrete. Experiments of RLA-SCC immersing in chloride solution were carried out to verify the simulation results. The effects of recycled large aggregate (RLA) content and RLA particle size on the service life of concrete were explored. The results indicate that the mesoscopic numerical simulation results are in good agreement with the experimental results. At the same depth, the closer to the surface of the RLA, the greater the chloride ion concentration. The service life of RLA-SCC in marine environment decreases with the increase of RLA content. Compared with the service life of 20% content, the service life of 25% and 30% content decreased by 20% and 42% respectively. Increasing the particle size of RLA can effectively improve the service life of RLA-SCC in chloride environment. Compared with the service life of 50 mm particle size, the service life of 70 mm and 90 mm increased by 61% and 163%, respectively. .

The Impact of Simulation Education on Self-Efficacy in Pre-Registration Nursing Students

This literature review primarily aims to explore and synthesise the previous studies in simulation education research conducted over the past five years related to the effects of simulation training on the self-efficacy of undergraduate pre-registration nursing students. The second aim of this study is to explore additional outcome variables that were examined in the previous studies. Five electronic databases were searched systematically. These databases were MEDLINE, CINAHL Plus, Scopus, Embase and PsycINFO. The PICO model was employed to identify the search terms, with a thesaurus being used to provide synonyms. Reference lists of relevant articles were examined and hand searches of journals were also undertaken. The quality of each study was assessed using the Simulation Research Rubric (SRR). A total of 11 studies were included. All studies explored the impact of simulation education on undergraduate pre-registration nursing. Six studies explored nursing students’ competence and performance and two papers examined their critical thinking. Problem solving, learning motivation, communication skills and knowledge acquisition were examined once. The majority of studies indicated that simulation training has a positive impact on pre-registration nursing students’ self-efficacy and other outcome variables. Furthermore, the study results indicate that simulation training is more dependable than traditional training, and students were extremely satisfied with the simulation training. However, most of the studies included in this review had several gaps, including study design, sample size and dissimilarities between the scales used. Further research with large samples, reliable and valid instruments, and outcomes measures (such as critical thinking and transferability of skills) is required to provide better insight into the effectiveness of simulation in undergraduate nursing education. .

联合Self-attention与Axial-attention的机场跑道裂缝分割

机场跑道裂缝形态多样、方向各异、长短不一且粗细不均,通常不具有统计规律。现有的各类裂缝分割算法难以在此类复杂场景中落地。针对上述问题,提出了联合self-attention与axial-attention的机场跑道裂缝分割网络(CSA-net),通过引入自注意力模块、轴向注意力模块、可变形卷积模块,提取裂缝的局部特征和全局语义特征。通过transformer decoder还原特征图的原始尺寸,融合了不同尺度间的分割结果,保留尽可能多的细节信息,使得CSA-net有更好的分割精度。在机场跑道实拍的数据集上进行的测试表明,针对裂缝的像素级分割指标F1-score达到了78.91%,高于目前各类裂缝分割算法。

Wideband Tunable Frequency-Doubling Optoelectronic Oscillator Using a Polarization Modulator and an Optical Bandpass Filter

A wideband tunable frequency-doubling optoelectronic oscillator （FD-OEO） is proposed and experimentally demonstrated based on a polarization modulator and an optical bandpass filter （OBPF）. The central frequency of the correspondingly fundamental OEO could be adjusted by tuning the bandwidth and central frequency of the OBPF, which could also be regarded as a photonic-assisted tunable microwave filter. The frequency tuning range of the FD-OEO covers from 9.5 to 32.8？GHz, and the single sideband phase noise of the fundamental signal is lower than -100dBc/Hz at an offset of 10？kHz. Moreover, the frequency stability of the generated signal is investigated by measuring its Allan deviation. The Allan deviation of the generated fundamental signal at 10？GHz is 2.39×10^-9.

Green Output of 1.5 W from a Diode-Pumped Intracavity Frequency-Doubled Self-Q-Switched and Mode-Locked Cr,Nd：YAG Laser

We report a diode-pumped intracavity frequency-doubled self-Q-switched and mode-locked Cr,Nd：YAG/KTP green laser with a Z-type cavity, which produces 1.5 W of average power at 532nm with incident pump power 14.2 W. The individual mode-locked green pulse duration is about 560ps with 149 MHz repetition rate. Almost 100% modulation depth of the mode-locked green pulses is achieved at an incident pump power of 4.13 W. The maximum energy of Q-switched green pulse is 19.8μJ. The experimental results of pulse duration and pulse energy of Q-switched green pulse agree well with the theoretical calculations.

Diabetes self-management education:Benefits and challenges

Diabetes mellitus has spread throughout many nations of the world and is now a serious threat.A lack of patient self‑management has been linked to this drain on global health.The consequences of diabetic patients’poor self‑management have increased a variety of complications and lengthened hospital stays.Poor information and skill acquisition have been linked to poor self‑management.Participating in a co‑operative approach known as diabetes self‑management education will help diabetes patients who want to successfully self‑manage their condition and any associated conditions.Information is one of the most important components of a diabetes management strategy.In conclusion,numerous studies have shown that patients with diabetes have poor self‑management skills and knowledge in all areas,making training in diabetes self‑management necessary to minimize the complications that may result from diabetes mellitus among the patients.This review discussed the severity of diabetes mellitus,diabetes self‑management,and the benefits and challenges of diabetes self‑management,which may aid individuals in understanding the significance of diabetes self‑management and how it relates to diabetes self‑care.

A Graph Theory Based Self-Learning Honeypot to Detect Persistent Threats

Attacks on the cyber space is getting exponential in recent times.Illegal penetrations and breaches are real threats to the individuals and organizations.Conventional security systems are good enough to detect the known threats but when it comes to Advanced Persistent Threats(APTs)they fails.These APTs are targeted,more sophisticated and very persistent and incorporates lot of evasive techniques to bypass the existing defenses.Hence,there is a need for an effective defense system that can achieve a complete reliance of security.To address the above-mentioned issues,this paper proposes a novel honeypot system that tracks the anonymous behavior of the APT threats.The key idea of honeypot leverages the concepts of graph theory to detect such targeted attacks.The proposed honey-pot is self-realizing,strategic assisted which withholds the APTs actionable tech-niques and observes the behavior for analysis and modelling.The proposed graph theory based self learning honeypot using the resultsγ(C(n,1)),γc(C(n,1)),γsc(C(n,1))outperforms traditional techniques by detecting APTs behavioral with detection rate of 96%.

Handily etching nickel foams into catalyst-substrate fusion self‐stabilized electrodes toward industrial‐level water electrolysis

The key challenge of industrial water electrolysis is to design catalytic electrodes that can stabilize high current density with low power consumption(i.e.,overpotential),while industrial harsh conditions make the balance between electrode activity and stability more difficult.Here,we develop an efficient and durable electrode for water oxidation reaction(WOR),which yields a high current density of 1000 mA cm−2 at an overpotential of only 284 mV in 1M KOH at 25°C and shows robust stability even in 6M KOH strong alkali with an elevated temperature up to 80°C.This electrode is fabricated from a cheap nickel foam(NF)substrate through a simple one-step solution etching method,resulting in the growth of ultrafine phosphorus doped nickel-iron(oxy)hydroxide[P-(Ni,Fe)O_(x)H_(y)]nanoparticles embedded into abundant micropores on the surface,featured as a self-stabilized catalyst–substrate fusion electrode.Such self-stabilizing effect fastens highly active P-(Ni,Fe)O_(x)H_(y)species on conductive NF substrates with significant contribution to catalyst fixation and charge transfer,realizing a win–win tactics for WOR activity and durability at high current densities in harsh environments.This work affords a cost-effective WOR electrode that can well work at large current densities,suggestive of the rational design of catalyst electrodes toward industrial-scale water electrolysis.

Short‐term and long‐term memory self‐attention network for segmentation of tumours in 3D medical images

Tumour segmentation in medical images(especially 3D tumour segmentation)is highly challenging due to the possible similarity between tumours and adjacent tissues,occurrence of multiple tumours and variable tumour shapes and sizes.The popular deep learning‐based segmentation algorithms generally rely on the convolutional neural network(CNN)and Transformer.The former cannot extract the global image features effectively while the latter lacks the inductive bias and involves the complicated computation for 3D volume data.The existing hybrid CNN‐Transformer network can only provide the limited performance improvement or even poorer segmentation performance than the pure CNN.To address these issues,a short‐term and long‐term memory self‐attention network is proposed.Firstly,a distinctive self‐attention block uses the Transformer to explore the correlation among the region features at different levels extracted by the CNN.Then,the memory structure filters and combines the above information to exclude the similar regions and detect the multiple tumours.Finally,the multi‐layer reconstruction blocks will predict the tumour boundaries.Experimental results demonstrate that our method outperforms other methods in terms of subjective visual and quantitative evaluation.Compared with the most competitive method,the proposed method provides Dice(82.4%vs.76.6%)and Hausdorff distance 95%(HD95)(10.66 vs.11.54 mm)on the KiTS19 as well as Dice(80.2%vs.78.4%)and HD95(9.632 vs.12.17 mm)on the LiTS.

CoLM^(2)S:Contrastive self‐supervised learning on attributed multiplex graph network with multi‐scale information

Contrastive self‐supervised representation learning on attributed graph networks with Graph Neural Networks has attracted considerable research interest recently.However,there are still two challenges.First,most of the real‐word system are multiple relations,where entities are linked by different types of relations,and each relation is a view of the graph network.Second,the rich multi‐scale information(structure‐level and feature‐level)of the graph network can be seen as self‐supervised signals,which are not fully exploited.A novel contrastive self‐supervised representation learning framework on attributed multiplex graph networks with multi‐scale(named CoLM^(2)S)information is presented in this study.It mainly contains two components:intra‐relation contrast learning and interrelation contrastive learning.Specifically,the contrastive self‐supervised representation learning framework on attributed single‐layer graph networks with multi‐scale information(CoLMS)framework with the graph convolutional network as encoder to capture the intra‐relation information with multi‐scale structure‐level and feature‐level selfsupervised signals is introduced first.The structure‐level information includes the edge structure and sub‐graph structure,and the feature‐level information represents the output of different graph convolutional layer.Second,according to the consensus assumption among inter‐relations,the CoLM^(2)S framework is proposed to jointly learn various graph relations in attributed multiplex graph network to achieve global consensus node embedding.The proposed method can fully distil the graph information.Extensive experiments on unsupervised node clustering and graph visualisation tasks demonstrate the effectiveness of our methods,and it outperforms existing competitive baselines.