Self-powered soft robot in the Mariana Trench.

The deep sea remains the largest unknown territory on Earth because it is so difficult to explore1-4. Owing to the extremely high pressure in the deep sea, rigid vessels5-7 and pressure-compensation systems8-10 are typically required to protect mechatronic systems. However, deep-sea creatures that lack bulky or heavy pressure-tolerant systems can thrive at extreme depths11-17. Here, inspired by the structure of a deep-sea snailfish15, we develop an untethered soft robot for deep-sea exploration, with onboard power, control and actuation protected from pressure by integrating electronics in a silicone matrix. This self-powered robot eliminates the requirement for any rigid vessel. To reduce shear stress at the interfaces between electronic components, we decentralize the electronics by increasing the distance between components or separating them from the printed circuit board. Careful design of the dielectric elastomer material used for the robot's flapping fins allowed the robot to be actuated successfully in a field test in the Mariana Trench down to a depth of 10,900 metres and to swim freely in the South China Sea at a depth of 3,224 metres. We validate the pressure resilience of the electronic components and soft actuators through systematic experiments and theoretical analyses. Our work highlights the potential of designing soft, lightweight devices for use in extreme conditions.

Applications of microcapillary films in bioanalytical techniques.

Microcapillary film (MCF) is an extruded plastic film with an array of parallel microcapillaries (30-500 µm) and it has wide potential applications in bioanalytical techniques as a microfluidic platform. With different surface modification strategies, an MCF combines the advantages of its structure and modified chemical properties to realize various bioanalytical functions. In this review, we begin by introducing the manufacturing process of MCFs, common materials used to produce MCFs, surface treatment approaches of inner surfaces, and a signal detection and readout system of the MCF platform. Then, we summarize some typical applications of MCFs, particularly in protein chromatography, Escherichia coli detection for urinary tract infections, prostate-specific antigen detection for prostate cancer and multiplex immunoassays. Finally, future perspectives of MCFs in bioanalytical techniques are discussed.

Slow feature-based feature fusion methodology for machinery similarity-based prognostics.

Similarity-based prediction methods utilize degradation trend analysis based on degradation indicators (DIs). These methods are gaining prominence in industrial predictive maintenance because they effectively address prognostics for machines with unknown failure mechanisms. However, current studies often neglect the discrepancies in degradation trends when constructing DIs from multi-sensor data and lack automatic normalization of operating regimes during feature fusion. In this study, a feature fusion methodology based on a signal-to-noise ratio metric that leverages slow feature analysis (SFA) is proposed. This customized metric utilizes SFA to quantify degradation trend discrepancies of constructed DIs, while automatically filtering out the effects of multiple operating regimes during feature fusion. The effectiveness and superiority of the proposed method are demonstrated using publicly available aero-engine and rolling bearing datasets.

Fully bio-based epoxy resins from lignin and epoxidized soybean oil: Rigid-flexible, tunable properties and high lignin content.

The application of epoxidized soybean oil (ESO) in thermosetting polymers is impeded by its unsatisfactory thermomechanical properties. Here, in order to address the limitation, technical lignin was modified by tung oil anhydride and then used as the hardener to compensate for the inherent flexibility defects of ESO thermosets (TLs). As the lignin content increased, a notable improvement in the activation energy of TLs was observed, attributed to the restraining effect of lignin's rigid structure on segmental relaxation. Concurrently, the tensile strength of TLs increased from 2.8 MPa to 34.0 MPa, concomitant with a decrease in elongation at break from 32.9 % to 8.0 %. Comparative analysis with TL-0 (devoid of lignin) demonstrated substantial enhancements in glass transition temperature, shape fixation ratio, and shape recovery ratio for TL-50 (comprising 50 wt% of lignin), elevating from 16.9 °C, 89.1 %, and 89.5 % to 118.6 °C, 94.0 %, and 99.3 %, respectively. These results unequivocally highlight the favorable dynamic mechanical and shape memory properties conferred upon TLs by lignin addition. While the introduction of lignin adversely affected thermal stability, a notable improvement in char yield (800 °C) was observed. Collectively, these findings underscore the potential of technical lignin as a promising bio-based curing agent for ESO.

Patterning High-Resolution Microstructures on Thermoplastics by Ceramic Nanoparticles Filled Epoxy Coated Molds for Duplicating Nature-Derived Functional Surfaces.

Patterning high-resolution microstructures on thermoplastic substrates is of fundamental importance for the commercialization of microfluidics, advanced functional surfaces, and optical elements. Though many methods are developed to fabricate micropatterned plastic devices with 100 µm resolution, they suffer substantially higher cost or lower productivity when the resolution of the micropatterns is to be further improved. Here, we develop low-cost molds consisting of thin ceramic-filled-epoxy composite coatings on steel substrates. By virtue of the loaded ZrO2 nanoparticle fillers, the enhanced mechanical and thermal properties of the composite molds enable the epoxy microstructures to survive harsh conditions in conventional thermoplastic processing methods including hot embossing, imprinting, and mold injection. With the ceramic-filled-epoxy coated molds, we are able to improve the fabrication resolution of microstructures on plastics to 10 µm with unprecedented low-cost and excellent durability.

Recent progress in minimizing the warpage and shrinkage deformations by the optimization of process parameters in plastic injection molding: a review.

The quality control of plastic products is an essential aspect of the plastic injection molding (PIM) process. However, the warpage and shrinkage deformations continue to exist because the PIM process is easily interfered with by several related or independent process parameters. Thus, great efforts have been devoted to optimizing process parameters to minimize the warpage and shrinkage deformations of products during the last decades. In this review, we begin by introducing the manufacturing process in PIM and the cause of warpage and shrinkage deformations, followed by the mechanism about how process parameters, like mold temperature, melt temperature, injection rate, injection pressure, holding pressure, holding and cooling duration, affect those defects. Then, we summarize the recent progress of the design of experiments and four advanced methods (artificial neural networks, genetic algorithm, response surface methodology, and Kriging model) on optimizing process parameters to minimize the warpage and shrinkage deformations. In the end, future perspectives of quality control in injection molding machines are discussed.

Multivariate time-series classification with hierarchical variational graph pooling.

In recent years, multivariate time-series classification (MTSC) has attracted considerable attention owing to the advancement of sensing technology. Existing deep-learning-based MTSC techniques, which mostly rely on convolutional or recurrent neural networks, focus primarily on the temporal dependency of a single time series. Based on this, complex pairwise dependencies among multivariate variables can be better described using advanced graph methods, where each variable is regarded as a node in the graph, and their dependencies are regarded as edges. Furthermore, current spatial-temporal modeling (e.g., graph classification) methodologies based on graph neural networks (GNNs) are inherently flat and cannot hierarchically aggregate node information. To address these limitations, we propose a novel graph-pooling-based framework, MTPool, to obtain an expressive global representation of MTS. We first convert MTS slices into graphs using the interactions of variables via a graph structure learning module and obtain the spatial-temporal graph node features via a temporal convolutional module. To obtain global graph-level representation, we design an "encoder-decoder"-based variational graph pooling module to create adaptive centroids for cluster assignments. Then, we combine GNNs and our proposed variational graph pooling layers for joint graph representation learning and graph coarsening, after which the graph is progressively coarsened to one node. Finally, a differentiable classifier uses this coarsened representation to obtain the final predicted class. Experiments on ten benchmark datasets showed that MTPool outperforms state-of-the-art strategies in the MTSC task.

Facile synthesis of lignin-based epoxy resins with excellent thermal-mechanical performance.

Up to now, various approaches have been used to fabricate lignin-based epoxy thermosets by utilizing lignin or lignin-derivatives, but there is still lack of a simple, effective and environmental-friendly pathway for producing lignin-based epoxy resins from industrial lignin. In this work, a novel strategy - one-pot to synthesize phenolated lignin incorporated novolac epoxy networks (PLIENs) was proposed. As expected, PLIENs obtained from the novel route exhibited preferable mechanical and thermal properties compared with the epoxy resins which obtained from common route. Moreover, increasing the loading of lignin did not significantly deteriorate the thermal-mechanical performance of cured epoxy resins. However, the Tg of PLIENs was slightly lowered compared with conventional petroleum-based epoxy resins (DGEBA). Nonetheless, the flexural strength and storage modulus of PLIENs were higher than that of DGEBA. Especially, the char yield of PLIENs at 800 °C was up to 28.9%, much higher than that of DGEBA (only 6.9%), which indicated that lignin has a certain promoting effect on the flame retardancy of epoxy resins. This research provides a new insight for producing commercially viable lignin-based epoxy thermosets.

Artificial intelligence-powered microfluidics for nanomedicine and materials synthesis.

Artificial intelligence (AI) is an emerging technology with great potential, and its robust calculation and analysis capabilities are unmatched by traditional calculation tools. With the promotion of deep learning and open-source platforms, the threshold of AI has also become lower. Combining artificial intelligence with traditional fields to create new fields of high research and application value has become a trend. AI has been involved in many disciplines, such as medicine, materials, energy, and economics. The development of AI requires the support of many kinds of data, and microfluidic systems can often mine object data on a large scale to support AI. Due to the excellent synergy between the two technologies, excellent research results have emerged in many fields. In this review, we briefly review AI and microfluidics and introduce some applications of their combination, mainly in nanomedicine and material synthesis. Finally, we discuss the development trend of the combination of the two technologies.

Effects of different nitrogen sources and light paths of flat plate photobioreactors on the growth and lipid accumulation of Chlorella sp. GN1 outdoors.

To assess the potential of Chlorella sp. GN1 for producing biodiesel raw materials in flat plate photobioreactors (FPPs) outdoors, we optimized the nitrogen sources and concentrations for the growth of the algae. The effects of different light paths of FPPs on the growth, lipid accumulation, and fatty acids of Chlorella sp. GN1 were also studied. As the light path of the FPPs was reduced, the alga could accumulate lipids rapidly, achieving high lipid content and lipid productivity outdoors. The highest lipid content obtained was 53.5%, when the light path was 5 cm. In addition, the lipid productivity was 66.7 mg L-1 day-1. The main fatty acids were C16/C18, accounting more than 90% of the total fatty acids. Results showed that Chlorella sp. GN1 had the ability to accumulate large quantities of lipids in FPPs outdoors and was a promising microalgal species for biofuel production.

Electro-coalescence in step emulsification: dynamics and applications.

Step emulsification is a low-shear method to produce monodispersed microdroplets by spontaneous breakup of dispersed fluid at a spatial "step". As a semi-open microfluidic system, controllable coalescence of multiple components in step emulsification has not been achieved. Here, we use a low voltage to control the coalescence position of flow tips in the terrace. By investigating the interaction between the coalescence behavior and the hydrodynamics of the drop formation, we numerically predict the shape evolution of the flow tips and give a semi-empirical model to calculate the sizes of droplets by the flow rates and the voltage. Furthermore, we explore the capabilities of the electro-coalescer based on step emulsification. To trigger the coalescence in the wide reservoir, the clogging problem in precipitate-producing reactions is avoided. Besides, the low-shear nature of step emulsification also facilitates the production of multilayered droplets.

Cultivation of Chlorella vulgaris on unsterilized dairy-derived liquid digestate for simultaneous biofuels feedstock production and pollutant removal.

In order to assess viability of microalgae cultivation using unsterilized dairy-derived liquid digestate (DLD) for simultaneous biofuels feedstock production and contaminant removal, four DLD concentrations (25%, 50%, 75% and 100%) were used to grow Chlorella vulgaris in batch photobioreactors (PBRs). The 25% DLD was an ideal alternative medium in that high growth rate (0.69 d-1), high lipid productivity (112.9 mg L-1 d-1) as well as high nutrient removal were attained. The high DLD concentration caused inhibition of microalgal growth, where COD was more inhibitive than ammonium. The presence of bacteria did not influence microalgae production because of limited growth. Microalgal growth reduced the richness and diversity of bacterial community. Furthermore, the species of Bacteroidetes, Candidatus Saccharibacteria, and Chlamydiae rather than Proteobacteria benefited microalgal-bacterial symbiosis. These findings contribute to better application of microalgal-bacterial system for large-scale microalgae cultivation as well as environmental sustainability.

Numerical simulations of wall contact angle effects on droplet size during step emulsification.

Terrace-based microfluidic devices are currently used to prepare highly monodisperse micro-droplets. Droplets are generated due to the spontaneous pressure drop induced by the Laplace pressure, and so the flow rate of a dispersed phase has little effect on droplet size. As a result, control over the droplet is limited once a step emulsification device has been fabricated. In this work, a terrace model was established to study the effect of the wall contact angle on droplet size based on computational fluid dynamics simulations. The results for contact angles from 140° to 180° show that a lower contact angle induces wall-wetting, increasing the droplet size. The Laplace pressure equations for droplet generation were determined based on combining pressure change curves with theoretical analyses, to provide a theoretical basis for controlling and handling droplets generated through step emulsification.

Growth and lipid accumulation characteristics of Scenedesmus obliquus in semi-continuous cultivation outdoors for biodiesel feedstock production.

In an effort to identify suitable microalgal species for biodiesel production, seven species were isolated from various habitats and their growth characteristics were compared. The results demonstrated that a green alga Scenedesmus obliquus could grow more rapidly and synthesize more lipids than other six microalgal strains. S. obliquus grew well both indoors and outdoors, and reached higher µmax indoors than that outdoors. However, the cells achieved higher dry weight (4.36 g L(-1)), lipid content (49.6%) and productivity (183 mg L(-1) day(-1)) outdoors than in indoor cultures. During the 61 days semi-continuous cultivation outdoors, high biomass productivities (450-550 mg L(-1) day(-1)) and µmax (1.05-1.44 day(-1)) were obtained. The cells could also achieve high lipid productivities (151-193 mg L(-1) day(-1)). These results indicated that S. obliquus was promising for lipids production in semi-continuous cultivation outdoors.

Scale-up potential of cultivating Chlorella zofingiensis in piggery wastewater for biodiesel production.

Scale-up potential of cultivating Chlorella zofingiensis in piggery wastewater for simultaneous wastewater treatment and biodiesel production was tested. The cultivation of C. zofingiensis with autoclaved wastewater and NaClO-pretreated wastewater, cultivation of algae indoors and outdoors, and stability of semi-continuous feeding operation were examined. The results showed that C. zofingiensis cultivated in piggery wastewater pretreated by autoclaving and NaClO had no evident difference in the performance of nutrient removal, algal growth and biodiesel production. The outdoor cultivation experiments indicated that C. zofingiensis was able to adapt and grow well outdoors. The semi-continuous feeding operation by replacing 50% of algae culture with fresh wastewater every 1.5 days could provide a stable net biomass productivity of 1.314 g L(-1) day(-1). These findings in this study can prove that it is greatly possible to amplify the cultivation of C. zofingiensis in piggery wastewater for nutrient removal and biodiesel production.

Establishment of a predictive genetic model for estimating chemotherapy sensitivity of colorectal cancer with synchronous liver metastasis.

OBJECTIVE: We examined the whole genome expression profile in advanced colorectal cancer (ACC) patients who had received FOLFOX4 chemotherapy to establish a genetic biomarker model predicting chemotherapy sensitivity. METHODS: Eligible ACC patients were divided into two groups, based on postchemotherapy evaluation results: specifically, the sensitive group (experimental group) and the resistant group (control group). The genome expression profiles of colorectal cancer tissues were examined using DNA microarray analysis, and differential gene expression was identified using a significance analysis of the microarray. The probe signal log ratios were used to produce the area-under-the-curve, sensitivity, and specificity for candidate genes. Genes exhibiting differential expression and significant predictive power were used to simulate a genetic model for estimating chemotherapy sensitivity. RESULTS: Totally, 30 ACC patients were eligible for the study, 13 assigned to the experimental group and 17 to the control group. In total, 30 genes showing significant differential expression were identified. Seven candidate genes (NKX2-3, FXYD6, TGFB1I1, ACTG2, ANPEP, HOXB8, and KLK11), which exhibited positive or negative correlations, were incorporated into a genetic model, with an overall accurate predication rate of 93.3%. CONCLUSIONS: The predictive model involving the seven genes listed had high accuracy in estimating chemotherapy sensitivity to the FOLFOX4 regimen.

Identification of prohibitin as a potential biomarker for colorectal carcinoma based on proteomics technology.

Differential protein expression was analyzed in carcinoma tissue to determine the correlation between protein levels and the clinical and pathological parameters of patients with colorectal carcinomas (CRC). Two-dimensional electrophoresis (2-DE) revealed 40 protein spots that were differentially expressed at two or greater fold difference in CRC that were identified by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF/TOF MS). Among these proteins, prohibitin (PHB) was found to be overexpressed in CRC. It was selected for Western blot and immunohistochemistry assay in subsequent tissue microassays (TMA). Thirty-five distinct proteins were differentially expressed at least 2-fold among normal and CRC tissues. The expression of 17 proteins, including PHB, was increased by >2-fold in CRC tissues (p<0.01). Immunohistochemistry and Western blot assays found that PHB was overexpressed in CRC cases, and the expression was higher than adenoma and normal tissues (p<0.01), whereas there was no significant difference in expression of PHB between adenoma and normal tissues. Immunohistochemistry also suggested a link between PHB expression and poor differentiation (p<0.01). However, there was no difference in UICC stage, or location of CRC. Survival analysis suggested no significant correlation between PHB expression and poor prognosis. In summary, the overexpression of PHB might be associated with the transformation process from adenoma to CRC. Further, it is a potential diagnostic and differentiation biomarker of CRC in the clinic.

[Comparison of the incidence rates of anastomotic leak following lower anterior resection of rectal cancer between laparoscopic and open operation].

OBJECTIVE: To investigate and compare the incidence rates of postoperative anastomotic leak following laparoscopic (LP) versus open (OP) lower anterior resection for rectal cancer. METHODS: Fifty-three cases of LP and 135 cases of OP lower anterior resection with rectal cancer site 5-8 cm away from anal edge were operated by the same surgeon team from Sep. 2000 to Dec. 2005. The differences of postoperative anastomotic leak of protective stomy and non-protective stomy between LP and OP groups were analysed. RESULTS: In LP group, the incidence rates of the postoperative anastomotic leak of protective stomy and non-protective stomy were 4.6% (1/22) and 6.5% (2/31) respectively (P>0.05, chi(2)=0.088). In OP group, the incidence rates were 2.3% (1/43) and 8.7% (8/92) respectively (P>0.05, chi(2)=1.024). No significant difference existed between LP and OP groups with protective stomy (P=0.455), neither did LP and OP groups without protective stomy (P=0.288). CONCLUSION: Laparoscopic low anterior resection of rectal cancer is a safe procedure. It doesn't increase the incidence rate of anastomotic leak as compared to traditional open surgery.