钛酸铝陶瓷的结构特点及热震性能研究现状

笔者对钛酸铝晶体结构、性能特点及其研究现状等方面进行了详细总结,分析和探究了影响钛酸铝基陶瓷材料耐热性能和抗热震性能的因素及其作用机理。通过优化和克服钛酸铝热分解和低机械强度2大缺点,钛酸铝陶瓷凭借其高耐火度,低膨胀和优良的抗热疲劳性能,有望代替部分锂质耐热陶瓷和堇青石质耐热陶瓷。

Public integrity verification for data sharing in cloud with asynchronous revocation

Cloud data sharing service,which allows a group of people to access and modify the shared data,is one of the most popular and efficient working styles in enterprises.Recently,there is an uprising trend that enterprises tend to move their IT service from local to cloud to ease the management and reduce the cost.Under the new cloud environment,the cloud users require the data integrity verification to inspect the data service at the cloud side.Several recent studies have focused on this application scenario.In these studies,each user within a group is required to sign a data block created or modified by him.While a user is revoked,all the data previously signed by him should be resigned.In the existing research,the resigning process is dependent on the revoked user.However,cloud users are autonomous.They may exit the system at any time without notifying the system admin and even are revoked due to misbehaviors.As the developers in the cloud-based software development platform,they are voluntary and not strictly controlled by the system.Due to this feature,cloud users may not always follow the cloud service protocol.They may not participate in generating the resigning key and may even expose their secret keys after being revoked.If the signature is not resigned in time,the subsequent verification will be affected.And if the secret key is exposed,the shared data will be maliciously modified by the attacker who grasps the key.Therefore,forcing a revoked user to participate in the revocation process will lead to efficiency and security problems.As a result,designing a practical and efficient integrity verification scheme that supports this scenario is highly desirable.In this paper,we identify this challenging problem as the asynchronous revocation,in which the revocation operations(i.e.,re-signing key generation and resigning process)and the user's revocation are asynchronous.All the revocation operations must be able to be performed without the participation of the revoked user.Even more ambitiously,the revocation process should not rely on any special entity,such as the data owner or a trusted agency.To address this problem,we propose a novel public data integrity verification mechanism in which the data blocks signed by the revoked user will be resigned by another valid user.From the perspectives of security and practicality,the revoked user does not participate in the resigning process and the re-signing key generation.Our scheme allows anyone in the cloud computing system to act as the verifier to publicly and efficiently verify the integrity of the shared data using Homomorphic Verifiable Tags(HVTs).Moreover,the proposed scheme resists the collusion attack between the cloud server and the malicious revoked users.The numerical analysis and experimental results further validate the high efficiency and scalability of the proposed scheme.The experimental results manifest that re-signing 10,000 data blocks only takes 3.815 s and a user can finish the verification in 300 ms with a 99% error detection probability.

Dose-related effects of norepinephrine on early-stage endotoxemic shock in a swine model

Background The benefits of early use of norepinephrine in endotoxemic shock remain unknown.We aimed to elucidate the effects of different doses of norepinephrine in early-stage endotoxemic shock using a clinically relevant large animal model.Methods Vasodilatory shock was induced by endotoxin bolus in 30 Bama suckling pigs.Treatment included fluid resuscitation and administration of different doses of norepinephrine,to induce return to baseline mean arterial pressure(MAP).Fluid management,hemodynamic,microcirculation,inflammation,and organ function variables were monitored.All animals were supported for 6 h after endotoxemic shock.Results Infused fluid volume decreased with increasing norepinephrine dose.Return to baseline MAP was achieved more frequently with doses of 0.8µg/kg/min and 1.6µg/kg/min(P<0.01).At the end of the shock resuscitation period,cardiac index was higher in pigs treated with 0.8µg/kg/min norepinephrine(P<0.01),while systemic vascular resistance was higher in those receiving 0.4µg/kg/min(P<0.01).Extravascular lung water level and degree of organ edema were higher in animals administered no or 0.2µg/kg/min norepinephrine(P<0.01),while the percentage of perfused small vessel density(PSVD)was higher in those receiving 0.8µg/kg/min(P<0.05)and serum lactate was higher in the groups administered no and 1.6µg/kg/min norepinephrine(P<0.01).Conclusions The impact of norepinephrine on the macro-and micro-circulation in early-stage endotoxemic shock is dose-dependent,with very low and very high doses resulting in detrimental effects.Only an appropriate norepinephrine dose was associated with improved tissue perfusion and organ function.

Assessment of respiratory support decision and the outcome of invasive mechanical ventilation in severe COVID-19 with ARDS

Background:The coronavirus disease 2019(COVID-19)is an ongoing pandemic.Invasive mechanical ventilation(IMV)is essential for the management of COVID-19 with acute respiratory distress syndrome(ARDS).We aimed to assess the impact of compliance with a respiratory decision support system on the outcomes of patients with COVID-19-associated ARDS who required IMV.Methods:In this retrospective,single-center,case series study,patients with COVID-19-associated ARDS who required IMV at Zhongnan Hospital of Wuhan University,China,from January 8th,2020,to March 24th,2020,with the final follow-up date of April 20th,2020,were included.Demographic,clinical,laboratory,imaging,and management information were collected and analyzed.Compliance with the respiratory support decision system was documented,and its relationship with 28-day mortality was evaluated.Results:The study included 46 COVID-19-associated ARDS patients who required IMV.The median age of the 46 patients was 68.5 years,and 31 were men.The partial pressure of arterial oxygen(PaO_(2))/fraction of inspired oxygen(FiO_(2))ratio at intensive care unit(ICU)admission was 104 mmHg.The median total length of IMV was 12.0(interquartile range[IQR]:6.0–27.3)days,and the median respiratory support decision score was 11.0(IQR:7.8–16.0).To 28 days after ICU admission,18(39.1%)patients died.Survivors had a significantly higher respiratory support decision score than non-survivors(15.0[10.3–17.0]vs.8.5(6.0–10.3),P=0.001).Using receiver operating characteristic(ROC)curve to assess the discrimination of respiratory support decision score to 28-day mortality,the area under the curve(AUC)was 0.796(95%confidence interval[CI]:0.657–0.934,P=0.001)and the cut-offwas 11.5(sensitivity=0.679,specificity=0.889).Patients with a higher score(>11.5)were more likely to survive at 28 days after ICU admission(log-rank test,P<0.001).Conclusions:For severe COVID-19-associated ARDS with IMV,following the respiratory support decision and assessing completion would improve the progress of ventilation.With a decision score of>11.5,the mortality at 28 days after ICU admission showed an obvious decrease.

Patent expanded retrieval via word embedding under composite-domain perspectives

Patent prior art search uses dispersed information to retrieve all the relevant documents with strong ambiguity from the massive patent database. This challenging task con-sists in patent reduction and patent expansion. Existing stud-ies on patent reduction ignore the relevance between techni-cal characteristics and technical domains, and result in am-biguous queries. Works on patent expansion expand terms from external resource by selecting words with similar dis-tribution or similar semantics. However, this splits the rele-vance between the distribution and semantics of the terms. Besides, common repository hardly meets the requirement of patent expansion for uncommon semantics and unusual terms. In order to solve these problems, we first present a novel composite-domain perspective model which converts the technical characteristic of a query patent to a specific composite classified domain and generates aspect queries. We then implement patent expansion with double consistency by combining distribution and semantics simultaneously. We also propose to train semantic vector spaces via word em-bedding under the specific classified domains, so as to pro-vide domain-aware expanded resource. Finally, multiple re-trieval results of the same topic are merged based on perspec-tive weight and rank in the results. Our experimental results on CLEP-IP 2010 demonstrate that our method is very effec-tive. It reaches about 5.43% improvement in recall and nearly 12.38% improvement in PRES over the state-of-the-art. Our work also achieves the best performance balance in terms of recall, MAP and PRES.