RepBoTNet-CESA:An Alzheimer’s Disease Computer Aided Diagnosis Method Using Structural Reparameterization BoTNet and Cubic Embedding Self Attention

Various deep learning models have been proposed for the accurate assisted diagnosis of early-stage Alzheimer’s disease(AD).Most studies predominantly employ Convolutional Neural Networks(CNNs),which focus solely on local features,thus encountering difficulties in handling global features.In contrast to natural images,Structural Magnetic Resonance Imaging(sMRI)images exhibit a higher number of channel dimensions.However,during the Position Embedding stage ofMulti Head Self Attention(MHSA),the coded information related to the channel dimension is disregarded.To tackle these issues,we propose theRepBoTNet-CESA network,an advanced AD-aided diagnostic model that is capable of learning local and global features simultaneously.It combines the advantages of CNN networks in capturing local information and Transformer networks in integrating global information,reducing computational costs while achieving excellent classification performance.Moreover,it uses the Cubic Embedding Self Attention(CESA)proposed in this paper to incorporate the channel code information,enhancing the classification performance within the Transformer structure.Finally,the RepBoTNet-CESA performs well in various AD-aided diagnosis tasks,with an accuracy of 96.58%,precision of 97.26%,and recall of 96.23%in the AD/NC task;an accuracy of 92.75%,precision of 92.84%,and recall of 93.18%in the EMCI/NC task;and an accuracy of 80.97%,precision of 83.86%,and recall of 80.91%in the AD/EMCI/LMCI/NC task.This demonstrates that RepBoTNet-CESA delivers outstanding outcomes in various AD-aided diagnostic tasks.Furthermore,our study has shown that MHSA exhibits superior performance compared to conventional attention mechanisms in enhancing ResNet performance.Besides,the Deeper RepBoTNet-CESA network fails to make further progress in AD-aided diagnostic tasks.

Self-Healable and Stretchable PAAc/XG/Bi_(2)Se_(0.3)Te_(2.7) Hybrid Hydrogel Thermoelectric Materials

Thermoelectric power generators have attracted increasing interest in recent years owing to their great potential in wearable electronics power supply.It is noted that thermoelectric power generators are easy to damage in the dynamic service process,resulting in the formation of microcracks and performance degradation.Herein,we prepare a new hybrid hydrogel thermoelectric material PAAc/XG/Bi_(2)Se_(0.3)Te_(2.7)by an in situ polymerization method,which shows a high stretchable and self-healable performance,as well as a good thermoelectric performance.For the sample with Bi_(2)Se_(0.3)Te_(2.7)content of 1.5 wt%(i.e.,PAAc/XG/Bi2Se0.3Te27(1.5 wt%)),which has a room temperature Seebeck coefficient of-0.45 mV K^(-1),and exhibits an open-circuit voltage of-17.91 mV and output power of 38.1 nW at a temperature difference of 40 K.After being completely cut off,the hybrid thermoelectric hydrogel automatically recovers its electrical characteristics within a response time of 2.0 s,and the healed hydrogel remains more than 99%of its initial power output.Such stretchable and self-healable hybrid hydrogel thermoelectric materials show promising potential for application in dynamic service conditions,such as wearable electronics.

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.

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.

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.

Health education intervention and its impact on patients with unilateral vestibular dysfunction:An information-motivation-behavioral model approach

Unilateral vestibular dysfunction is a one-sided impairment of vestibular function in one ear.Incorporating health education in treatment and rehabilitation plans can improve vestibular function,keep negative emotions at bay,and reduce the extent of the condition.This letter investigates the impact of the informationmotivation-behavioral skills model as a medium for health education on patient outcomes.While offering encouraging observations,there are certain limitations,such as the study’s retrospective design,small sample size,use of subjective measures,and lack of longer follow-ups that challenge the cogency of the study.The study is a step toward transforming vestibular dysfunction treatment through health education.

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.

A Comparative Study on the Quality Components Between Self Pollinated Seeds and Naturally Pollinated Seeds in Brassica napus L. in Sichuan Ecological Region

[ Objective] This study was to reveal the differences in crude fat and glucosinolates between self pollinated seeds and naturally pollinated seeds in Brassica napus in sichuan ecological region.. [ Method] Near-infrared spectroscopy method （NIRS） was employed to measure the quality components in self pollinated seeds and naturally pollinated seeds of 861 shares of Brassica napus from Sichuan ecological region. And correlation analysis and regression analysis were conducted based on the experimental data via SPSS （statistics package for social science）. [ Result] The contents of crude fat in the self pollinated seeds were commonly a higher than that in the naturally pollinated seeds at 0.01 significant level; while the contents of glucosinolates in the self pollinated seeds and the naturally pollinated seeds were insignificantly different. Both the correlation relationship and linear regression for the crude fat between the self pollinated seeds and naturally pollinated seeds reached the significant level. The regression equations for the contents of crude fat（y1 ） and glucosinolates（ y2 ） in the naturally pollinated seeds and of crude fat（ x1 ） and glucosinolates（ x2 ） in self pollinated seeds were respectively determined to be y1 = 16.844 ＋0.614x1 and y2 = -0.620 ＋ 1.017 x2. [ Conclusion] In Brassica napus breeding, crude fat in naturally pollinated seeds should be emphatically taken into account, meanwhile concurrently considering that in self pollinated seeds; while glucosinolates in both the self pollinated seeds and the naturally pollinated seeds must be simultaneously concerned.

Self tempering effect of near eutectic Al-Si casting with different wall thickness solidified and cooled in permanent die

In order to study the self tempering effect on the solidification of Al-Si alloy, a setup was designed to conduct experiments. The characters of β phases in different thicknesses of Al-Si samples were investigated. The results show that the size distributions of β phases obey the logarithmic normal distribution. The Brinell hardness tests were also carried out. The tested hardness results show that the hardness distribution of the casting cooled in water is evener than that cooled in air, and its averaged value is higher than that cooled in air.

APPLICATION OF FUZZY LOGIC AND SELF-ORGANIZING NETWORK TO TOOL-WEAR CLASSIFICATION

A tool-wear monitoring system for metal turning operations is presented based on the combinative application of fuzzy logic and unsupervised neural network. A group of self-organizing map （SOM） neural networks is established based on the typical cutting condition combinations, and each of networks is corresponding to a typical cutting condition. For a specifie cutting condition, the fuzzy logic method is used to select an optimum trained SOM network. The proposed monitoring system, ealled the Fuzzy-SOM-TWC, is used to classify tool states based on the in-time measurement of force, aeoustic emission（AE）, and motor eurrent signals. An approximate 98%--100% correct classification of tool-wear status is obtained by testing the system with a series data samples under freely selected cutting conditions.

Minor Self-conjugate and Skewpositive Semidefinite Solutions to a System of Matrix Equations over Skew Fields

Minor self conjugate (msc) and skewpositive semidefinite (ssd) solutions to the system of matrix equations over skew fields [A mn X nn =A mn ,B sn X nn =O sn ] are considered. Necessary and sufficient conditions for the existence of and the expressions for the msc solutions and the ssd solutions are obtained for the system.

Studies on Self-Luminous Material and Coating with Long Persistent Yellow-Green Afterglow

The preparation, properties, expression and luminescent mechanism of self luminous material (SrAl 2O 4∶Eu 2+ , Dy 3+ ) were discussed. The long afterglow luminescent coating was prepared by adding proper luminescent powders SrAl 2O 4∶Eu 2+ , Dy 3+ and other aids into styrene/acrylic emulsion. The best prescription of the coating was defined. The properties of luminescent coating were determined. The primary factors which affect the coating properties were discussed.

Self Organization Map for Clustering and Classification in the Ecology of Agent Organizations

Development of computational agent organizations or “societies” has become the domiant computing paradigm in the arena of Distributed Artificial Intelligence, and many foreseeable future applications need agent organizations, in which diversified agents cooperate in a distributed manner, forming teams. In such scenarios, the agents would need to know each other in order to facilitate the interactions. Moreover, agents in such an environment are not statically defined in advance but they can adaptively enter and leave an organization. This begs the question of how agents locate each other in order to cooperate in achieving organizational goals. Locating agents is a quite challenging task, especially in organizations that involve a large number of agents and where the resource avaiability is intermittent. The authors explore here an approach based on self organization map (SOM) which will serve as a clustering method in the light of the knowledge gathered about various agents. The approach begins by categorizing agents using a selected set of agent properties. These categories are used to derive various ranks and a distance matrix. The SOM algorithm uses this matrix as input to obtain clusters of agents. These clusters reduce the search space, resulting in a relatively short agent search time.

A multiscale spatio-temporal framework to regionalize annual precipitation using k-means and self-organizing map technique

Determination of homogenous precipitation-based regions is a very important task in effective management of water resources. The present study tried to propose an effective precipitation-based regionalization methodology by conjugating both temporal pre-processing and spatial clustering approaches in a way to take advantage of multiscale properties of precipitation time series. Annual precipitation data of 51 years(1960-2010) for 31 rain gauges(RGs) were collected and used in proposed clustering approaches. Discreet wavelet transform(DWT) was used to capture the time-frequency attributes of the time series and multiscale regionalization was performed by using k-means and Self Organizing Maps(SOM) clustering techniques. Daubechies function(db) was selected as mother wavelet to decompose the precipitation time series. Also, proper boundary extensions and decomposition level were applied. Different combinations of the approximation(A) and detail(D) coefficients were used to determine the input dataset as a basis of spatial clustering. The proposed model's efficiency in spatial clustering stage was verified using three different indexes namely, Silhouette Coefficient(SC), Dunn index and Davis Bouldin index(DB). Results approved superior performance of k-means technique in comparison to SOM. It was also deduced that DWT-based regionalization methodology showed improvements in comparison to historical-based models. Cross mutual information was used to investigate the RGs of cluster 3's homogeneousness in DWT-k-means approach. Results of non-linear correlation approach verified homogeneity of cluster 3. Verifications based on mean annual precipitation values of rain gauges in each cluster also approved the capability of multiscale approach in precipitation regionalization.

Self-metathesis of 1-butene to ethene and hexene over molybdenum-based heterogeneous catalysts

A novel route involving self‐metathesis of1‐butene under mild conditions that gave high yields ofethene and hexene was proposed.The results of thermodynamic analysis revealed that the Gibbsenergy of the target Metathesis I reaction(1‐butene?ethene+3‐hexene)was much higher thanthat of the main side Metathesis II(1‐butene+2‐butene?propene+2‐pentene).Suppression of1‐butene double‐bond isomerization was the key step to increase the selectivity for the target olefinin the reaction network.The relationship between the catalytic performance and support nature was investigated in detail.On basis of H2‐TPR,UV‐Vis spectra and HRTEM results,an alumina(Al2O3)support with large surface area was beneficial for the dispersion of molybdenum(Mo)species.Both suitable acidity and sufficient Mo dispersion were important to selectively promote the self‐metathesis reaction of1‐butene.On the optimal6Mo/Al2O3catalyst,1‐butene conversion reached47%and ethene selectivity was as high as42%on the premise of good catalytic stability(80°C,1.0MPa,3h?1).?2018,Dalian Institute of Chemical Physics,Chinese Academy of Sciences.Published by Elsevier B.V.All rights reserved.

Covered self expandable metallic stent with flared plastic one inside for pancreatic pseudocyst avoiding stent dislodgement

Endoscopic ultrasound-guided drainage has recently been recommended for increasing the drainage rate of endoscopically managed pancreatic fluid collections and decreasing the morbidity associated with conventional endoscopic trans-mural drainage. The type of stent used for endoscopic drainage is currently a major area of interest. A covered self expandable metallic stent (CSEMS) is an alternative to conventional drainage with plastic stents because it offers the option of providing a larger-diameter access fi stula for drainage, and may increase the fi nal success rate. One problem with CSEMS is dislodgement, so a metallic stent with flared or looped ends at both extremities may be the best option. An 85-year-old woman with severe comorbidity was treated with percutaneous approach for a large (20 cm) pancreatic pseudocyst with corpuscolated material inside. This approach failed. The patient was transferred to our institute for EUS-guided transmural drainage. EUS confi rmed a large, anechoic cyst with hyperechoic material inside. Because the cyst was large and contained mixed and corpusculated fluid, we used a metallic stent for drainage. To avoid migration of the stent and potential mucosal growth above the stent, a plastic prosthesis (7 cm, 10 Fr) with flaps at the tips was inserted inside the CSEMS. Two months later an esophagogastroduodenoscopy was done, and showed patency of the SEMS and plastic stents, which were then removed with a polypectomy snare. The patient experienced no further problems.

OXIDATION RESISTANCE AND SELF-SEALING PROPERTY OF CERAMIC COATINGS FOR C/C COMPOSITES

The oxidation behavior and damage mechanism of modifiers and compounds of many types of ceramic coatings were investigated experimentally. A MoSi 2/SiC coating was produced by infiltration process. The oxidation behavior of the coated C/C composites was studied at various temperatures below 1650℃. The oxidation results showed that the MoSi 2/SiC coating for thermal protection of C/C composites has high oxidation resistance at temperature up to 1650℃. In the present work, a new model of an oxidation protective, self sealing multi layer coating system was proposed for C/C composites. The multi layer coating possessing the self sealing property was obtained by pack cementation and infiltration process. The protection coating system for C/C composites consists of an inner layer of SiC and an outer layer of porous refractory oxides filled by modified SiO 2 glass. Isothermal and cyclic thermal oxidation tests showed the multi layer coating was capable of protecting the C/C composites in an oxidizing atmosphere at temperature up to 1800℃.

Psychometric properties and characteristics of the Diabetes Self Management Scale

Objective:Assessing diabetes self care management is essential for nursing care for diabetes.There is a need to have valid and reliable scales that assess the actual performance of diabetes self management,The purpose of this study was to revise and conduct psychometric testing and analysis of the Diabetes Self Management Scale(DSMS).Methods:A cross-sectional methodological design was used.A convenience sample was used and 78 adults with diabetes and taking insulin from five sites in the Midwest area of the U.S participated in the study.Reliability analysis was done using Ferketich techniques to make decisions about whether any given item should be retained or deleted.Results:A descriptive analysis for the 60 items of the scale was conducted;several items had low variability compared to the other items on the scale.The correlation matrices showed that a total of 20 items had poor item characteristics.These 20 items were deleted resulting in developing 40-item version of the scale.The 40-item scale had high level of internal consistency(Cronbach'sα=0.947).The validity testing of the 40-item scale was guided by the Research Model for Diabetes Self Care Management;results were congruent with the model and showed strong correlation with self efficacy,moderate correlation with self care agency,and weak correlation with diabetes knowledge.Conclusion:The items and the scale(DSMS)have undergone careful psychometric testing.The 40-item DSMS is a reliable and valid instrument to measure diabetes self care management among people with diabetes.

MERGING AND SPLITTING SECOND-ORDER SELF-SIMILAR PROCESSES (TRAFFICS)

Recent traffic measurements in corporate LANs, Variable Bit Rate (VBR) video sources, ISDN control channels, and other communication systems, have indicated traffic behavior of self similar nature, which has implications for design, control and analysis of high speed networks. Merging and splitting are two basic networking operations. This paper gave the necessary and sufficient conditions for that merging of second order self similar traffic streams also results in a second order self similar stream. It shows that splitting traffic streams of the second order self similar stream are still self similar streams by the independent splitting operation.