Hybrid fully convolutional networks-based skin lesion segmentation and melanoma detection using deep feature

Fully convolutional networks (FCNs) take the input of arbitrary size and produce correspondingly sized output with efficient inference and learning. The automatic diagnosis of melanoma is very essential for reducing the mortality rate by identifying the disease in earlier stages. A two-stage framework is used for implementing the melanoma detection, segmentation of skin lesion, and identification of melanoma lesions. Two FCNs based on VGG-16 and GoogLeNet are incorporated for improving the segmentation accuracy. A hybrid framework is used for incorporating these two FCNs. The classification is done by extracting the feature from segmented lesion by using deep residual network and a hand-crafted feature. Classification is done by support vector machine. The performance analysis of our framework gives a promising accuracy, that is, 0.8892 for classification in ISBI 2016 dataset and 0.853 for ISIC 2017 dataset.     

Bioactive-Tissue-Derived Nanocomposite Hydrogel for Permanent Arterial Embolization and Enhanced Vascular Healing

Transcatheter embolization is a minimally invasive procedure that uses embolic agents to intentionally block diseased or injured blood vessels for therapeutic purposes. Embolic agents in clinical practice are limited by recanalization, risk of non-target embolization, failure in coagulopathic patients, high cost, and toxicity. Here, a decellularized cardiac extracellular matrix (ECM)-based nanocomposite hydrogel is developed to provide superior mechanical stability, catheter injectability, retrievability, antibacterial properties, and biological activity to prevent recanalization. The embolic efficacy of the shear-thinning ECM-based hydrogel is shown in a porcine survival model of embolization in the iliac artery and the renal artery. The ECM-based hydrogel promotes arterial vessel wall remodeling and a fibroinflammatory response while undergoing significant biodegradation such that only 25% of the embolic material remains at 14 days. With its unprecedented proregenerative, antibacterial properties coupled with favorable mechanical properties, and its superior performance in anticoagulated blood, the ECM-based hydrogel has the potential to be a next-generation biofunctional embolic agent that can successfully treat a wide range of vascular diseases.     

一种大型复杂构件加工新模式及新装备探讨

大型复杂构件是航空航天、能源、船舶等领域装备的核心结构件，此类构件通常具有尺寸大、形状复杂、刚性弱等特点。传统“分体离线加工-在线检测”模式存在工艺不稳定、过程复杂、柔性差、周期长等问题，以龙门式多轴数控机床加工为代表的“包容式”加工模式，难以适应大型复杂构件的高效高质量加工制造需求。提出一种基于移动式和吸附式机器人的多机协同原位加工新模式，通过多机器人系统自主寻位、精确定位加工与加工质量原位检测，实现大型复杂构件多安装面并行铣削、制孔与打磨等作业。多机器人系统包括移动式混联机器人、吸附式并联机器人、移动式串联铣削机器人、移动式双臂加工机器人和移动式打磨机器人。构建多机协同原位加工模式，需要揭示多机器人协同原位加工行为与大型弱刚性结构件质量控制的交互机理，面临着本体、测量、工艺和集成四个方面的挑战，需要设计高灵活、高刚度的移动式和吸附式加工机器人，解决移动机器人自主准确寻位和超大结构件原位高精检测难题，攻克加工变形误差在线补偿和振动抑制技术，通过集成实现多机协同高效高精加工，为大型复杂构件的高效高质量制造提供创新技术及装备，并实现此类构件制造核心技术及装备自主可控。     

Modeling and analysis of multiple access channel capacity based on hybrid energy storage and energy harvesting

Energy harvesting (EH) has been considered as a promising technology to solve the constrained energy problem in the devices of IoT with its advantages of flexible deployment and sustainable energy supply.For multiple access channel with energy harvesting,a hybrid energy storage structure model composed by super capacitor and battery was proposed for the devices of IoT.According to the peculiarities of medium access channel and energy harvesting system,an optimized energy allocation strategy with exponential-type decline (ETD) was presented,the upper and lower bounds of the average throughput were deduced,in particular,the gap of two bounds was derived to be a constant.The channel capacity was further obtained by utilizing the relationship between the average throughput and the channel capacity.In the simulations,the effect of harvested energy,storage capacity and the number of nodes on the channel capacity were analyzed respectively.Experiment results show that compared with the conventional wireless node with single battery storage,the proposed hybrid energy storage structure can improve the harvested energy value and increase the multiple access channel capacity by using adaptive modulation scheme when transmitting the signals.     

Supramolecular Architectures of Nucleic Acid/Peptide Hybrids

Supramolecular architectures that are built artificially from biomolecules, such as nucleic acids or peptides, with structural hierarchical orders ranging from the molecular to nano-scales have attracted increased attention in molecular science research fields. The engineering of nanostructures with such biomolecule-based supramolecular architectures could offer an opportunity for the development of biocompatible supramolecular (nano)materials. In this review, we highlighted a variety of supramolecular architectures that were assembled from both nucleic acids and peptides through the non-covalent interactions between them or the covalently conjugated molecular hybrids between them.     

Neural network-based hybrid models developed for free radical polymerization of styrene

In the present work, the free radical polymerization of styrene is modeled by considering the phenomenology of the process (a simplified model, which does not include the diffusional effects, gel, and glass effects) in combination with an empirical model represented by an artificial neural network. Differential evolution (DE) algorithm, belonging to the class of evolutionary algorithms, is applied for developing the neural models in optimal forms. For improving the results—predicted conversion and molecular weights as function of time, temperature, and initiator concentration—different combinations between phenomenological model and neural network are tested; also, individual and stacked neural networks have been developed for the polymerization process. This methodology based on hybrid models, including neural networks aggregated in stacks, provides accurate results.     

The Marine Polysaccharide Ulvan Confers Potent Osteoinductive Capacity to PCL-Based Scaffolds for Bone Tissue Engineering Applications

Hybrid composites of synthetic and natural polymers represent materials of choice for bone tissue engineering. Ulvan, a biologically active marine sulfated polysaccharide, is attracting great interest in the development of novel biomedical scaffolds due to recent reports on its osteoinductive properties. Herein, a series of hybrid polycaprolactone scaffolds containing ulvan either alone or in blends with κ-carrageenan and chondroitin sulfate was prepared and characterized. The impact of the preparation methodology and the polysaccharide composition on their morphology, as well as on their mechanical, thermal, water uptake and porosity properties was determined, while their osteoinductive potential was investigated through the evaluation of cell adhesion, viability, and osteogenic differentiation of seeded human adipose-derived mesenchymal stem cells. The results verified the osteoinductive ability of ulvan, showing that its incorporation into the polycaprolactone matrix efficiently promoted cell attachment and viability, thus confirming its potential in the development of biomedical scaffolds for bone tissue regeneration applications.     

A simulation study of protons heated by left/right-handed Alfvén waves generated by electromagnetic proton-proton instability

Most protons in the solar wind belong to one of two different populations,the less dense beam protons and the denser core protons.The beam protons,with a velocity of(1-2)VA(VA is the local Alfvén speed),always drift relative to the core protons;this kind of distribution is unstable and stimulates several kinds of wave mode.In this study,using a 2D hybrid simulation model,we find that the original right-handed elliptically polarized Alfvén waves become linearly polarized,and eventually become right-handed and circularly polarized.Given that linearly polarized waves are a superposition of left-handed and right-handed waves,cyclotron resonance in the right-handed/left-handed component heats beam/core protons perpendicularly.The resonance between beam protons and right-handed polarized waves is stronger when the beam relative density is lower,resulting in more dramatic perpendicular heating of beam protons,whereas the situation is reversed when the beam relative density is larger.     

Effect of baking in different ovens on the quality and structural characteristics of saltine crackers

The aim of the study was to evaluate the physical and microstructural characteristics of crackers baked in four different industrial baking ovens (indirect radiation-cyclotherm, indirect convection, hybrid and industrial tunnel-ITO). Indirect convection and cyclotherm ovens provide the highest (5685.43 ± 51 W m⁻²) and the lowest (4860 ± 38.87 W m⁻²) amount of heat flux, respectively. Despite the amount of heat flux, indirect convection led to crackers with the highest moisture (7.86% vs. 4.82% in clyclotherm) and specific volume, but the lowest hardness. Cyclotherm resulted in crackers with lower specific volume, surface area, porosity, smooth and regular surface. Conversely, the hybrid and ITO ovens showed closer heat flux, leading to crackers with similar moisture content, texture parameters, specific volume, browning and inner porosity. Overall results show the potential of baking using different ovens for modifying the quality parameters of the crackers.     

来瓦希尔骨架材料MIL-53(Al)填充PEBA膜渗透汽化分离水中苯胺

将来瓦希尔骨架材料MIL-53(Al)引入到聚醚共聚酰胺（PEBA-2533）高分子相中制备了不同填充量的PEBA/MIL-53(Al)杂化膜并用于渗透汽化分离水中微量苯胺。X-射线衍射结果证实MIL-53(Al)被成功合成。扫描电镜和激光粒度分析结果表明所制备MIL-53(Al)颗粒粒径在纳米尺度范围内。采用扫描电镜、红外光谱、X-射线衍射、差示扫描量热和水接触角对杂化膜进行了表征，并考察了杂化膜的溶胀行为和分离性能。结果表明，所得杂化膜的热稳定性较好。当MIL-53(Al)质量分数小于20%时，MIL-53(Al)在高分子相中分散均匀，继续增大填充量出现团聚现象。杂化膜的结晶度随MIL-53(Al)填充量的增加而降低。MIL-53(Al)的引入增强了杂化膜的疏水性和溶胀度。在料液温度为60℃、膜下游压力400Pa、料液苯胺质量分数为3.6%时，MIL-53(Al)质量分数为20%的杂化膜（M-20）综合分离性能最优，渗透通量达到2.15kg/(m²·h)，分离因子为264。12天的稳定性测试结果表明所得杂化膜分离性能无显著变化，能够满足渗透汽化应用要求。