基于数据质量评价的目标估计

针对目标估计过程需要大量人工参与、自动化程度低的问题，提出了基于数据质量评价的目标估计方法。利用目标数据质量评价方法，对不同传感器得到的目标数据质量进行科学、有效的测度和评价，并根据质量得分动态调整各数据源在目标估计过程中所占的权重，从而减少人工干预，提高目标估计效能。仿真试验结果证明了该方法的有效性。     

Structural regulation and polishing performance of dendritic mesoporous silica (D-mSiO2) supported with samarium-doped cerium oxide composites

Ceria (CeO₂) particles are prevalent polishing abrasive materials. Trivalent lanthanide ions are the popular category of dopants for enriched surface defects and thus improved physicochemical properties, since they are highly compatible with CeO₂ lattices. Herein, a series of dendritic-like mesoporous silica (D-mSiO₂)-supported samarium (Sm)-doped CeO₂ nanocrystals were synthesized via a facile chemical precipitation method. The relation of the structural characteristics and chemical mechanical polishing (CMP) performances were investigated to explore the effect of Sm-doping amounts on the D-mSiO₂/Sm_xCe_1?xO_2?δ (x = 0–1) composite abrasives. The involved low-modulus D-mSiO₂ cores aimed to eliminate surface scratch and damage, resulting from the optimized contact behavior between abrasives and surfaces. The trivalent cerium (Ce³⁺) and oxygen vacancy (V_O) at CeO₂ surfaces were expected to be reactive sites for the material removal process over SiO₂ films. The optimal oxide-CMP performances in terms of removal efficiency and surface quality were achieved by the 40% Sm-doped composite abrasives. It might be attributed to the high Ce³⁺ and V_O concentrations and the enhancement of tribochemical reactivity between CeO₂SiO₂ interfaces. Furthermore, the relationship between the surface chemistry, polishing performance as well as the actual role in oxide-CMP of the D-mSiO₂/Sm_xCe_1?xO_2?δ abrasives were also discussed.     

Direct ink writing of vancomycin-loaded polycaprolactone/ polyethylene oxide/ hydroxyapatite 3D scaffolds

Novel inks were formulated by dissolving polycaprolactone (PCL), a hydrophobic polymer, in organic solvent systems; polyethylene oxide (PEO) was incorporated to extend the range of hydrophilicity of the system. Hydroxyapatite (HAp) with a weight ratio of 55–85% was added to the polymer-based solution to mimic the material composition of natural bone tissue. The direct ink writing (DIW) technique was applied to extrude the formulated inks to fabricate the predesigned tissue scaffold structures; the influence of HAp concentration was investigated. The results indicate that in comparison to other inks containing HAp (55%, 75%, and 85%w/w), the ink containing 65% w/w HAp had faster ink recovery behavior; the fabricated scaffold had a rougher surface as well as better mechanical properties and wettability. It is noted that the 65% w/w HAp concentration is similar to the inorganic composition of natural bone tissue. The elastic modulus values of PCL/PEO/HAp scaffolds were in the range of 4–12 MPa; the values were dependent on the HAp concentration. Furthermore, vancomycin as a model drug was successfully encapsulated in the PCL/PEO/HAp composite scaffold for drug release applications. This paper presents novel drug-loaded PCL/PEO/HAp inks for 3D scaffold fabrication using the DIW printing technique for potential bone scaffold applications.     

机器翻译译文质量估计综述

机器翻译译文质量估计(Quality Estimation,QE)是指在不需要人工参考译文的条件下,估计机器翻译系统产生的译文的质量,对机器翻译研究和应用具有很重要的价值。机器翻译译文质量估计经过最近几年的发展,取得了丰富的研究成果。该文首先介绍了机器翻译译文质量估计的背景与意义;然后详细介绍了句子级QE、单词级QE、文档级QE的具体任务目标、评价指标等内容,进一步概括了QE方法发展的三个阶段: 基于特征工程和机器学习的QE方法阶段,基于深度学习的QE方法阶段,融入预训练模型的QE方法阶段,并介绍了每一阶段中的代表性研究工作;最后分析了目前的研究现状及不足,并对未来QE方法的研究及发展方向进行了展望。     

A blockchain-based audit approach for encrypted data in federated learning

The development of data-driven artificial intelligence technology has given birth to a variety of big data applications. Data has become an essential factor to improve these applications. Federated learning, a privacy-preserving machine learning method, is proposed to leverage data from different data owners. It is typically used in conjunction with cryptographic methods, in which data owners train the global model by sharing encrypted model updates. However, data encryption makes it difficult to identify the quality of these model updates. Malicious data owners may launch attacks such as data poisoning and free-riding. To defend against such attacks, it is necessary to find an approach to audit encrypted model updates. In this paper, we propose a blockchain-based audit approach for encrypted gradients. It uses a behavior chain to record the encrypted gradients from data owners, and an audit chain to evaluate the gradients’ quality. Specifically, we propose a privacy-preserving homomorphic noise mechanism in which the noise of each gradient sums to zero after aggregation, ensuring the availability of aggregated gradient. In addition, we design a joint audit algorithm that can locate malicious data owners without decrypting individual gradients. Through security analysis and experimental evaluation, we demonstrate that our approach can defend against malicious gradient attacks in federated learning.     

Prediction of fish quality level with machine learning

In this study, sea bream, sea bass, anchovy and trout were captured and recorded using a digital camera during refrigerated storage for 7 days. In addition, their total viable counts (TVC) were determined on a daily basis. Based on the TVC, each fish was classified as ‘fresh’ when it was <5 log cfu per g, and as ‘not fresh’ when it was >7 log cfu per g. They were uploaded on a web-based machine learning software called Teachable Machine (TM), which was trained about the pupils and heads of the fish. In addition, images of each species from different angles were uploaded to the software in order to ensure the recognition of fish species by TM. The data of the study indicated that the TM was able to distinguish fish species with high accuracy rates and achieved over 86% success in estimating the freshness of the fish species tested.     

Fresh beef tumbling at different post-mortem times to improve tenderness and proteolytic features of M. longissimus lumborum

The aim of this study was to determine the effects of tumbling at different post-mortem times on the proteolytic features and quality attributes of beef loins (M. longissimus lumborum). Loins (n = 12) were cut into 4 sections and assigned to tumbling at 1, 6 or 11 days post-mortem or non-tumbled control. Upon tumbling, additional ageing was applied to a common post-mortem time of 16 days. In general, tumbling had no considerable impacts on water-holding ability of samples. Tumbling resulted in an immediate decrease in shear force values (WBSF) of beef samples. Tumbling at 1 day post-mortem with no ageing had similar WBSF compared to the non-tumbled controls at 16 days (P > 0.05). With ageing, tumbling increased amounts of protein degradation, myofibrillar fragmentation and calpain-1 autolysis of samples. These results suggest that early post-mortem tumbling coupled with ageing can synergistically impact the tenderness development of beef loins and shorten the necessary ageing period.     

超高分子量聚乙烯纤维增强中空蜂窝模压复合材料性能研究

为研制车船等壳体所用的轻质、高强复合板材,选用超高分子量聚乙烯(UHMWPE)短纤维纱,制备成单层经纬为120根/(10 cm)的平纹组织,采用多组经纱持续更替交织层的方法制成2L(1+0)型、4L(2+1)型、6L(3+2)型3种多层角联锁结构织物,采用扦插芯棒、模压成型方法制成菱形蜂窝状的热固性环氧树脂基中空板,并与2块真空吸液法制成的面板组成“三合一”复合板,同时测定了复合板材的结构特征及其平拉、平压和弯曲性能。结果表明:3种类型复合板的密度均远小于水的密度,其中6L(3+2)型最小,为0.48 g/cm³;复合板层数越多,环氧树脂越难渗透尤其是在中空板菱形交叉点处,复合板平拉、平压、抗弯曲强度则呈现递增,制成的6L(3+2)型复合板试样平压强度可达到1.03 MPa。     

日本の寒地，北海道における2030年代の水稲生育への温暖化の影響予測とその対応(日语原文)

北海道では1980年代から2010年代まで，水稲圃場栽培期間である5–9月の気温は年代とともに上昇した。そこで，直近の2010年代（2010—2019年平均）と比べて， 2つの2030年代の予測気象から，既報の関係式より水稲生育を予測した。その結果，2030年代では2010年代に比べ，限界移植日（移植早限）が水稲栽培17地域の平均で8～9日早い。また，早限出穂期が1～5日早く，晩限出穂期が1～5日遅く，安全出穂期間が2～10日長い。出穂期は1～3日早い。出穂期から晩限出穂まで2～9日長いため，遅延型冷害の発生がやや少ない。生育期別気象は，出穂前24日以降30日間では生育が早いため平均気温が同じかやや低い。出穂前10日以降40日間および出穂期以降40日間では平均気温がやや高く，日射量はやや少ない。そのため，玄米収量は96～98％とやや低く，潜在収量性を示す気候登熟量示数は同じである。障害不稔発生に関係する穂ばらみ期冷害危険期の平均気温はわずかに低いかほぼ同じであるため，冷害発生の危険性は残る。一方，不稔発生をもたらす低温域の出現頻度には，地域間で差異がある。精米蛋白質含有率は同じであるが，アミロース含有率はやや低く，やや良食味である。米粒外観品質では被害粒歩合と着色粒歩合は一定の傾向がなく，未熟粒歩合はやや高い。精米白度は同じであるが，玄米白度はやや高い。以上の予測に対する技術的対応方向を示した。