The Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-eA<sub>μ</sub>)Ψ=mc<sup>2</sup>Ψ describes the bound states of the electron under the action of external potentials...The Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-eA<sub>μ</sub>)Ψ=mc<sup>2</sup>Ψ describes the bound states of the electron under the action of external potentials, A<sub>μ</sub>. We assumed that the fundamental form of the Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-S<sub>μ</sub>)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 S<sub>μ</sub>. 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.展开更多
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 a...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/m<sup>2</sup> (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.展开更多
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 d...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.展开更多
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. Neurobeha...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.展开更多
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 environmen...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. .展开更多
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-effica...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. .展开更多
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’poo...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.展开更多
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 ba...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.展开更多
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 kno...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%.展开更多
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 shap...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.展开更多
With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex...With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline.Abstractive summarization task is framed as seq2seq modeling.Existing seq2seq methods perform better on short sequences;however,for long sequences,the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this paper.The novelty is to parallelize the sequence computation training by incorporating feed-forward,the self-normalized neural network in the Extractive phase using Intra Cosine Attention Similarity(Ext-ICAS)with sentence dependency position.Also,it does not require any normalization technique explicitly.Our proposed abstractive Bidirectional Long Short Term Memory(Bi-LSTM)encoder sequence model performs better than the Bidirectional Gated Recurrent Unit(Bi-GRU)encoder with minimum training loss and with fast convergence.The proposed model was evaluated on the Cable News Network(CNN)/Daily Mail dataset and an average rouge score of 0.435 was achieved also computational training in the extractive phase was reduced by 59%with an average number of similarity computations.展开更多
为了构建准确表征滚动轴承退化过程的趋势性健康度指标,提高滚动轴承剩余使用寿命(Remaining Useful Life,RUL)的预测精度,提出了一种结合长短期记忆(Long‑Short Term Memory,LSTM)和自注意力(Self‑Attention)机制的神经网络模型(LSTM‑...为了构建准确表征滚动轴承退化过程的趋势性健康度指标,提高滚动轴承剩余使用寿命(Remaining Useful Life,RUL)的预测精度,提出了一种结合长短期记忆(Long‑Short Term Memory,LSTM)和自注意力(Self‑Attention)机制的神经网络模型(LSTM‑SA)用于滚动轴承RUL预测。利用包络解调获得原始信号的包络谱,再将包络谱分段并计算对应频段的皮尔逊相关系数,得到具有单调性和趋势性的退化特征;将退化特征归一化处理后作为LSTM‑SA模型的输入,并利用LSTM自适应提取退化特征时间上的内部相关性以及Self‑Attention对关键信息的筛选,消除无用信息的干扰,挖掘深层次特征,构建健康度指标并得到退化曲线;确定失效阈值,利用最小二乘法拟合退化曲线,预测寿命失效点,实现滚动轴承的RUL预测。在PHM2012数据集上的实验结果表明,所提出的方法相比于其他文献,平均绝对误差分别降低了43.18%,62.57%和59.44%,平均得分分别提高了10.87%,45.71%和34.21%;在工程实际数据中的实验结果表明,所提出方法的平均预测误差分别比Standard‑RNN和CNN方法降低了39.58%和74.86%。展开更多
文摘The Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-eA<sub>μ</sub>)Ψ=mc<sup>2</sup>Ψ describes the bound states of the electron under the action of external potentials, A<sub>μ</sub>. We assumed that the fundamental form of the Dirac equation γ<sub>μ</sub>(δ<sub>μ</sub>-S<sub>μ</sub>)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 S<sub>μ</sub>. 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.
文摘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/m<sup>2</sup> (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.
文摘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.
文摘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.
文摘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. .
文摘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. .
文摘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.
基金National Natural Science Foundation of China,Grant/Award Numbers:11974303,12074332Qinglan Project of Jiangsu Province,Grant/Award Number:137050317the Interdisciplinary Research Project of Chemistry Discipline,Grant/Award Number:yzuxk202014 and High‐End Talent Program of Yangzhou University,Grant/Award Number:137080051。
文摘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.
文摘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%.
基金supported by the National Key Research and Development Program of China under Grant No.2018YFE0206900the National Natural Science Foundation of China under Grant No.61871440 and CAAI‐Huawei Mind-Spore Open Fund.
文摘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.
文摘With the continuous growth of online news articles,there arises the necessity for an efficient abstractive summarization technique for the problem of information overloading.Abstractive summarization is highly complex and requires a deeper understanding and proper reasoning to come up with its own summary outline.Abstractive summarization task is framed as seq2seq modeling.Existing seq2seq methods perform better on short sequences;however,for long sequences,the performance degrades due to high computation and hence a two-phase self-normalized deep neural document summarization model consisting of improvised extractive cosine normalization and seq2seq abstractive phases has been proposed in this paper.The novelty is to parallelize the sequence computation training by incorporating feed-forward,the self-normalized neural network in the Extractive phase using Intra Cosine Attention Similarity(Ext-ICAS)with sentence dependency position.Also,it does not require any normalization technique explicitly.Our proposed abstractive Bidirectional Long Short Term Memory(Bi-LSTM)encoder sequence model performs better than the Bidirectional Gated Recurrent Unit(Bi-GRU)encoder with minimum training loss and with fast convergence.The proposed model was evaluated on the Cable News Network(CNN)/Daily Mail dataset and an average rouge score of 0.435 was achieved also computational training in the extractive phase was reduced by 59%with an average number of similarity computations.
文摘为了构建准确表征滚动轴承退化过程的趋势性健康度指标,提高滚动轴承剩余使用寿命(Remaining Useful Life,RUL)的预测精度,提出了一种结合长短期记忆(Long‑Short Term Memory,LSTM)和自注意力(Self‑Attention)机制的神经网络模型(LSTM‑SA)用于滚动轴承RUL预测。利用包络解调获得原始信号的包络谱,再将包络谱分段并计算对应频段的皮尔逊相关系数,得到具有单调性和趋势性的退化特征;将退化特征归一化处理后作为LSTM‑SA模型的输入,并利用LSTM自适应提取退化特征时间上的内部相关性以及Self‑Attention对关键信息的筛选,消除无用信息的干扰,挖掘深层次特征,构建健康度指标并得到退化曲线;确定失效阈值,利用最小二乘法拟合退化曲线,预测寿命失效点,实现滚动轴承的RUL预测。在PHM2012数据集上的实验结果表明,所提出的方法相比于其他文献,平均绝对误差分别降低了43.18%,62.57%和59.44%,平均得分分别提高了10.87%,45.71%和34.21%;在工程实际数据中的实验结果表明,所提出方法的平均预测误差分别比Standard‑RNN和CNN方法降低了39.58%和74.86%。
