采用MUF的倒装芯片封装技术

业界对信号完整性和电学性能提出了越来越高的要求,因而开始向更薄基板的方向发展,Amkor Technology Inc.开发出一种使用模塑底部填充（MUF）而非毛细底部填充（CUF）的倒装芯片模塑球栅阵列（FCMBGA）封装技术,使得无源器件与倒装芯片的间距更小,同时还提供了更优的薄芯基板变形控制,并可以获得更好的焊料连接可靠性。     

你了解锡须了吗？

在工业界转向无引脚封装一年多的时间里,在元件的引脚电镀、焊球、焊膏生长“锡须”的可能性飞速膨胀。然而让人惊讶的是,锡须问题并没有想象中那么肆虐。     

The Role of Gut Microbiota in Overcoming Resistance to Checkpoint Inhibitors in Cancer Patients: Mechanisms and Challenges

The introduction of immune checkpoint inhibitors has constituted a major revolution in the treatment of patients with cancer. In contrast with the traditional cytotoxic therapies that directly kill tumor cells, this treatment modality enhances the ability of the host’s immune system to recognize and target cancerous cells. While immune checkpoint inhibitors have been effective across multiple cancer types, overcoming resistance remains a key area of ongoing research. The gut microbiota and its role in cancer immunosurveillance have recently become a major field of study. Gut microbiota has been shown to have direct and systemic effects on cancer pathogenesis and hosts anti-tumor immune response. Many studies have also shown that the host microbiota profile plays an essential role in the response to immunotherapy, especially immune checkpoint inhibitors. As such, modulating this microbial environment has offered a potential path to overcome the resistance to immune checkpoint inhibitors. In this review, we will talk about the role of microbiota in cancer pathogenesis and immune-system activity. We will also discuss preclinical and clinical studies that have increased our understanding about the roles and the mechanisms through which microbiota influences the response to treatment with immune checkpoint inhibitors.     

Dual contextual module for neural machine translation

Machine Translation - Self-attention-based encoder-decoder frameworks have drawn increasing attention in recent years. The self-attention mechanism generates contextual representations by attending...     

Mediated Electrochemistry to Mimic Biology's Oxidative Assembly of Functional Matrices

Biology uses diffusible oxidants to perform functions that range from signaling to matrix assembly, and these oxidation chemistries offer surprising selectivities. Here, it is reported that mediated electrochemistry can access the richness of such oxidation chemistries. Specifically, electrode‐imposed voltage inputs are used to locally generate oxidized mediators that can diffuse into polymer solutions and induce the formation of covalent bonds for the deposition and functionalization of hydrogels at the electrode surface. Depending on the mediator's redox potential (E⁰), it is possible to “gate” the voltage inputs to target specific residues (e.g., thiols or amines) and oxidation chemistries. Further, mediators of varying E⁰ offer different reactivities and thus allow control of reaction‐diffusion rates to modulate the hydrogel's crosslink density and mechanical properties. Importantly, this mediated oxidation can be performed under physiologically relevant conditions to preserve labile biological functionalities (e.g., cell viability and protein function). Finally, it is demonstrated that protein fusion tags can be engineered to have “targetable” amino acid residues that enable protein function to be oxidatively conjugated to electrodeposited hydrogels. In summary, mediated electrochemistry can engage orthogonal oxidation chemistries to create functionalized matrices and thus mediated electrochemistry should add important capabilities to the electrofabrication toolbox.     

Business Analytics-Based Enterprise Information Systems

Big data analytics and business analytics are a disruptive technology and innovative solution for enterprise development. However, what is the relationship between business analytics, big data analytics, and enterprise information systems (EIS)? How can business analytics enhance the development of EIS? How can analytics be incorporated into EIS? These are still big issues. This article addresses these three issues by proposing ontology of business analytics, presenting an analytics service-oriented architecture (ASOA) and applying ASOA to EIS, where our surveyed data analysis showed that the proposed ASOA is viable for developing EIS. This article then examines incorporation of business analytics into EIS through proposing a model for business analytics service-based EIS, or ASEIS for short. The proposed approach in this article might facilitate the research and development of EIS, business analytics, big data analytics, and business intelligence.     

Fusion of Data and Knowledge for Safe UAV Landing

Autonomous Unmanned Aerial Vehicles (UAVs) have the potential to significantly improve current working practices for a variety of applications including aerial surveillance and search-and-rescue. However before UAVs can be widely integrated into civilian airspace there are a number of technical challenges which must be overcome including provision of an autonomous method of landing which would be executed in the event of an emergency. A fundamental component of autonomous landing is safe landing zone detection of which terrain classification is a major constituent. Presented in this paper is an extension of the Multi-Modal Expectation Maximization algorithm which combines data in the form of multiple images of the same scene, with knowledge in the form of historic training data and Ordnance Survey map information to compute updated class parameters. These updated parameters are subsequently used to classify the terrain of an area based on the pixel data contained within the images. An image''s contribution to the classification of an area is then apportioned according to its coverage of that area. Preliminary results are presented based on aerial imagery of the Antrim Plateau region in Northern Ireland which indicates potential in the approach used.     

Tripalmitin–Sodium Dodecyl Sulfate Emulsion Droplet Liquid vs. Solid State Impacts in vitro Digestive Lipolysis

Questions remain as to the impact of lipid structure, including crystallinity, on digestibility and metabolic response. This study was undertaken to determine the impact of triacylglycerol crystallinity on digestibility using undercooled (liquid emulsion, LE) and crystalline (solid emulsion, SE) particles exposed to an in vitro model simulating upper gastrointestinal tract (GIT) digestive conditions. By hot microfluidization, 10 wt% tripalmitin oil‐in‐water emulsions (D_3,2 ~ 0.115 nm) with 0.9 wt% sodium dodecyl sulfate (SDS) were prepared. SE demonstrated complex melting behavior, was predominantly in the beta polymorph, and consisted of a heterogeneous mixture of anisometric particles. In vitro duodenal lipolysis was more extensive for the spherically shaped LE droplets vs. SE (P < 0.05), despite the fact that exposure to simulated gastric conditions (at pH 2, but not at pH 7) induced partial crystallization. Therefore, lipid droplet physical state impacted and was impacted by exposure to gastrointestinal conditions, with differences observed in fatty acid digestive release and implications for lipid absorption.     

Biochemical markers of the mechanical quality of engineered hyaline cartilage

The aim of this study was to determine whether or not biochemical markers can be used as surrogate measures for the mechanical quality of tissue engineered cartilage. The biochemical composition of tissue engineered cartilage constructs were altered by varying either (i) the initial cell seeding density of the scaffold (seeding density protocol) or (ii) the length of time the engineered tissue was cultured (culture period protocol). The aggregate or Young’s moduli of the constructs were measured (by confined or unconfined compression respectively), and compared with the composition of the extracellular matrix by quantitative measurement of the glycosaminoglycan (GAG), hydroxyproline, collagen I and collagen II and collagen cross-links. The aggregate modulus correlated positively with both GAG and collagen II content, but not with collagen I content. Young’s modulus correlated positively with GAG, collagen II and collagen I content, and the ratio of mature to immature cross-links. There was no significant correlation of Young’s Modulus with total collagen measured as hydroxyproline content. These results suggested that hydroxyproline determination may be an unreliable indicator of mechanical quality of tissue engineered cartilage, and that a measure of collagen II and GAG content is required to predict the biomechanical quality of tissue engineered cartilage.