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The baobab trees (genus Adansonia) have attracted tremendous attention because of their striking shape and distinctive relationships with fauna1. These spectacular trees have also influenced human culture, inspiring innumerable arts, folklore and traditions. Here we sequenced genomes of all eight extant baobab species and argue that Madagascar should be considered the centre of origin for the extant lineages, a key issue in their evolutionary history2,3. Integrated genomic and ecological analyses revealed the reticulate evolution of baobabs, which eventually led to the species diversity seen today. Past population dynamics of Malagasy baobabs may have been influenced by both interspecific competition and the geological history of the island, especially changes in local sea levels. We propose that further attention should be paid to the conservation status of Malagasy baobabs, especially of Adansonia suarezensis and Adansonia grandidieri, and that intensive monitoring of populations of Adansonia za is required, given its propensity for negatively impacting the critically endangered Adansonia perrieri.

Moisture-electric generators (MEGs), harvesting ubiquitous moisture from the environment for electricity generation, have attracted great interest as power supply devices. However, there are great challenges associated with material availability, fabrication accessibility and operation environment, which are key factors to achieve high output with low cost for practical applications, and a deeper understanding of the underlying mechanism of interactions between MEGs and water is urgently required. Here, a whey protein available in supermarkets is used to fabricate low-cost MEGs with controllable performance through tuning surface charges and hydrophilicity, which provides new insights into the electricity generation mechanism and large-scale application. The MEGs exhibit the highest voltage output of 1.45 V at a room humidity level of 40% relative humidity. The whey protein films possess the merits of low cost (70 times cheaper than commonly used polymers), being flexible and semi-transparent, and having self-healing ability, presenting excellent comprehensive device performance. Besides, MEGs can operate well at extreme temperatures (-20 °C or 50 °C) and power a location tracker in a desert with 26% relative humidity. The modified functional layers with selective ion absorption and controllable outputs provided a deeper understanding of electricity generation in MEGs and demonstrated great potential in powering a wide range of electronic devices in various dynamic environments with high sustainability and reliability., Peer Reviewed, Postprint (author's final draft)

This work has explored the possible defects in Mn-doped SnO2 and compared the effects of interstitial Mn and oxygen vacancies on the electronic structure of SnO2. Combining the DFT calculations and experimental measurements, we found that when the Mn-doped SnO2 is synthesised under Sn-rich or O-poor conditions, the defect pair of Mn substitution and interstitial rather than oxygen vacancy will be formed, which induces energy band across the Fermi level and significantly affects the electronic structure of SnO2. With the Mn interstitials, stable intrinsic multi-level resistive states and optical SET can be achieved in the Mn-doped SnO2 memristors. This result can provide guidance in the fabrications of defective metal oxides and promote the investigations on cationic interstitial triggered multi-level resistive switching and optoelectronic memristors., Postprint (author's final draft)

High-nickel layered oxides, LiNixCoyMnzO2 (0.6 < x < 1), are promising cathode materials for producing batteries with high energy density and working voltage, while their poor cycling performance severely limits their commercial applications. Herein, an integrated surface coating/doping strategy is developed to significantly improve the structural stability and electrochemical performance of LiNi0.88Co0.06Mn0.06O2. The titanium ions from a thin TiNb2O7 coating layer diffuse inward during the high-temperature sintering process and a uniform protective layer forms on the surface of the secondary particles of the material. This protective layer suppresses side reactions, and the Ti4+ doping increases the thickness of the lithium layer and reduces the lithium/nickel mixing, thereby enhancing the diffusion of lithium ions in bulk electrode. The capacity retention of modified material after 200 cycles at 1 C is greatly improved from 59.8% of the pristine material to 87.2%. First-principles calculations confirm the interaction affinity of the TiNb2O7 coating on the layered LiNi0.88Co0.06Mn0.06O2 with Ti ion migration in the interlayer region. Moreover, the enhanced oxygen release energy and electronic conductivity benefiting from Ti4+ doping promote the cycling stability of the integrated cathode. The surface engineering strategy proposed herein is generally effective for the electrochemical improvement of nickel-rich ternary cathode materials.

Li-excess cation-disordered oxide cathodes have attracted increasing interests owing to their high energy density originated from cumulative cationic & anionic redox activity. In particular, Ni-based cation-disordered oxides exhibit high theoretical capacity for 2 e− reactions of Ni2+/Ni4+, while the severe overlapping between Ni 3d and O 2p orbitals restricts Ni redox capacity and unstable O redox deteriorates the cycling performance. Benefiting from advanced data mining and high-throughput theoretical calculations technology, we demonstrated that the capacity and cycling performance of Ni-based cation-disordered oxide can be synergically enhanced by carbon/Al2O3 double coating and partial Al3+ substitution. The synergistic mechanism is unveiled via X-ray photoelectron spectroscopy (XPS) and soft X-ray absorption spectroscopy (XAS) characterization together with first-principles calculations. It is confirmed that carbon coating increases the capacity by promoting the formation of peroxo-like species, which boosts O redox activity. Partial intercalating Al3+ enhances the Ni redox reaction by shortening the band overlap between Ni and O. Furthermore, Al2O3 coating and Al3+ doping improved the cycling stability of the cathode material owing to the shielding effect on side reaction and more stable O lattice. This synergistic strategy with nano-coating layer provides a promising pathway to accelerate the discovery of high-energy cation-disordered oxides based cathode materials. © 2022 Elsevier Ltd

High-nickel layered oxides, LiNixCoyMnzO2 (0.6 < x < 1), are promising cathode materials for producing batteries with high energy density and working voltage, while their poor cycling performance severely limits their commercial applications. Herein, an integrated surface coating/doping strategy is developed to significantly improve the structural stability and electrochemical performance of LiNi0.88Co0.06Mn0.06O2. The titanium ions from a thin TiNb2O7 coating layer diffuse inward during the high-temperature sintering process and a uniform protective layer forms on the surface of the secondary particles of the material. This protective layer suppresses side reactions, and the Ti4+ doping increases the thickness of the lithium layer and reduces the lithium/nickel mixing, thereby enhancing the diffusion of lithium ions in bulk electrode. The capacity retention of modified material after 200 cycles at 1 C is greatly improved from 59.8% of the pristine material to 87.2%. First-principles calculations confirm the interaction affinity of the TiNb2O7 coating on the layered LiNi0.88Co0.06Mn0.06O2 with Ti ion migration in the interlayer region. Moreover, the enhanced oxygen release energy and electronic conductivity benefiting from Ti4+ doping promote the cycling stability of the integrated cathode. The surface engineering strategy proposed herein is generally effective for the electrochemical improvement of nickel-rich ternary cathode materials.

The structural and electronic properties of MnO2 based electrocatalysts are key factors determining their electrochemical performance. To date, it is still challenging to synergistically tune the crystal structure, morphology, and electronic band (i.e., band gap and band alignments) of MnO2 through facile synthesis approaches. This study has reported a one-step hydrothermal method to synthesize a prototypical MnO2 electrocatalyst with optimized structural and electrochemical properties. By simply adjusting the hydrothermal time, the phase transition from polymorphic d to a can be induced in MnO2. The obtained nanowires on nanosheets structure grown in-situ on nickel foam provides a large surface area, great accessible active sites, and good mass/charge transfer efficiency. Further investigation through first-principles calculations reveals that compared to d-MnO2, the a-MnO2 polymorph with rich oxygen vacancies has better band-alignment tunability, which is also beneficial for improving the electrochemical performance. The a phase MnO2 exhibits superior catalytic performance for both OER and HER (OER overpotential of 0.45 V at 50 mA cm-2 and HER overpotential of 0.14 V at 50 mA cm-2). The developed synthesis method can be extended to catalyst designs that require precise control of phase and morphology evolution in a wide range of applications., Postprint (published version)

This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Applied Materials and Interfaces, copyright © 2022 American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsami.2c02675., Metallic 1T-phase MoS2 exhibits superior hydrogen evolution reaction (HER) performance than natural 2H-phase MoS2 owing to its higher electrical conductivity and abundance of active sites. However, the reported 1T-MoS2 catalysts usually suffer from extreme instability, which results in quick phase transformation at ambient conditions. Herein, we present a facile approach to engineer the phase of MoS2 by introducing intercalated hydrazine. Interestingly, the as-synthesized 1T-dominant MoS2 sample demonstrates excellent ambient stability without noticeable degradation for 3 months. Additionally, the 1T-dominant MoS2 exhibits superior electrical conductivity (~700 times higher than that of 2H-MoS2) and improved electrochemical catalytic performance (current density ~12 times larger than that of 2H-MoS2 at an overpotential of 300 mV vs the reversible hydrogen electrode, RHE). Through experimental characterizations and density functional theory (DFT) calculation, we conclude that the stabilization of the metallic phase could be attributed to the electron donation from hydrazine molecules to the adjacent Mo atoms. The phase control strategy in this work provides a guideline to develop other highly efficient and stable two-dimensional (2D) electrocatalysts., Peer Reviewed, Postprint (author's final draft)

This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Energy Letters, copyright © 2022 American Chemical Society, after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsenergylett.2c02040., Electronic doping is a promising approach to modulating the optoelectronic properties of semiconductors, but its effect on optoelectronic behaviors of halide perovskites remains controversial. Here, we comprehensively investigate the impact of Pb substitution in n-type CsPbIBr2 perovskite by utilizing monovalent Ag, divalent Zn, and trivalent Sb. Our findings reveal that the trap densities in doped CsPbIBr2 films are in the order of Ag < Zn < Sb. Compared with the pristine CsPbIBr2, the Ag-doped perovskite features a significantly reduced phase separation; however, the Sb doping accelerates halide segregation, and Zn exerts a negligible influence. The p-doping effect from monovalent Ag can shift the Fermi level of CsPbIBr2 toward the intrinsic midgap, which helps prevent the formation of ionic defects and reduce the migration of halide ions in the perovskite lattice. Through combing the density functional theory simulation, this study discloses the correlation between valence-controlled metal doping and phase segregation, providing a guideline for judiciously doping mixed-halide perovskites for optoelectronic applications., Peer Reviewed, Postprint (author's final draft)

Ni-rich layered oxides, such as LiNi0.8Co0.1Mn0.1O2 (NCM811), are promising cathode materials for high-energy lithium-ion batteries. However, the relatively high reactivity of Ni in NCM811 cathodes results in severe capacity fading originating from the undesired side reactions that occur at the cathode-electrolyte interface during prolonged cycling. Therefore, the trade-off between high capacity and long cycle life can obstruct the commercialization process of Ni-rich cathodes in modern lithium-ion batteries (LIBs). In addition, high sensitivity toward air upon storage greatly limits the commercial application. Herein, a facile surface modification strategy is introduced to enhance the cycling and in-air storage stability of NCM811. The NCM811 with a uniform SrTiO3 (STO) nano-coating layer exhibited outstanding electrochemical performances that could deliver a high discharge capacity of 173.5 mAh·g-1 after 200 cycles under 1C with a capacity retention of 90%. In contrast, the uncoated NCM811 only provided 65% capacity retention of 130.8 mAh·g-1 under the same conditions. Structural evolution analysis suggested that the STO coating acted as a buffer layer to suppress the dissolution of transition metal ions caused by the HF attack from the electrolyte and promote the lithium diffusion during the charge–discharge process. In addition, the constructed STO layer prevented the exposure of NCM811 to H2O and CO2 and thus effectively improved the in-air storage stability. This work offers an effective way to enhance the performance stability of Ni-rich oxides for high-performance cathodes of lithium-ion batteries., Peer Reviewed, Postprint (author's final draft)

Visual Dialog requires an agent to engage in a conversation with humans grounded in an image. Many studies on Visual Dialog focus on the understanding of the dialog history or the content of an image, while a considerable amount of commonsense-required questions are ignored. Handling these scenarios depends on logical reasoning that requires commonsense priors. How to capture relevant commonsense knowledge complementary to the history and the image remains a key challenge. In this paper, we propose a novel model by Reasoning with Multi-structure Commonsense Knowledge (RMK). In our model, the external knowledge is represented with sentence-level facts and graph-level facts, to properly suit the scenario of the composite of dialog history and image. On top of these multi-structure representations, our model can capture relevant knowledge and incorporate them into the vision and semantic features, via graph-based interaction and transformer-based fusion. Experimental results and analysis on VisDial v1.0 and VisDialCK datasets show that our proposed model effectively outperforms comparative methods., Comment: MULA Workshop, CVPR 2022

Structural defects are ubiquitous for polycrystalline perovskite films, compromising device performance and stability. Herein, a universal method is developed to overcome this issue by incorporating halide perovskite quantum dots (QDs) into perovskite polycrystalline films. CsPbBr3 QDs are deposited on four types of halide perovskite films (CsPbBr3, CsPbIBr2, CsPbBrI2, and MAPbI3) and the interactions are triggered by annealing. The ions in the CsPbBr3 QDs are released into the thin films to passivate defects, and concurrently the hydrophobic ligands of QDs self-assemble on the film surfaces and grain boundaries to reduce the defect density and enhance the film stability. For all QD-treated films, PL emission intensity and carrier lifetime are significantly improved, and surface morphology and composition uniformity are also optimized. Furthermore, after the QD treatment, light-induced phase segregation and degradation in mixed-halide perovskite films are suppressed, and the efficiency of mixed-halide CsPbIBr2 solar cells is remarkably improved to over 11% from 8.7%. Overall, this work provides a general approach to achieving high-quality halide perovskite films with suppressed phase segregation, reduced defects, and enhanced stability for optoelectronic applications., Peer Reviewed, Postprint (author's final draft)

Harvesting energy from ubiquitous moisture is attracting growing interest for directly powering electronic devices. However, it is still challenging to fabricate high-performing moisture-electric generators (MEGs) with high and stable electric output. Herein, we report a simple strategy to modify the oxygen-based groups of graphene oxide using hydrochloric acid treatment, which boosts the electric output based on the device structure of graphene oxide/polyvinyl alcohol (GO/PVA) MEGs. The resulting MEG enables a stable voltage of 0.85 V and a current of 9.28 µA (92.8 µA·cm-2), which are among the highest values reported so far. More excitingly, electric output gets further improved by simply assembling four MEG units in series or parallel. Moreover, the MEG shows great commercial potential for flexible and wearable applications. Driven by these advancements, the assembled MEGs can successfully power sensors and calculators. This work opens a new era of advance for a new energy conversion technology able to directly powering electronic devices., C.C. acknowledges support from the Spanish Ministry of Science, Innovation and Universities under the "Ramon y Cajal" fellowship RYC2018-024947-I, Peer Reviewed, Postprint (published version)

Background: Left atrial appendage (LAA) closure (LAAC) is a viable alternative to anticoagula-tion for stroke prevention in non-valvular atrial fibrillation. However, device-associated thrombosis (DAT) is known as a complication of LAAC as observed within the first few weeks after implantation. A noninvasive method is needed to predict the progress for endothelialization surveillance. The aim of the study was to develop a noninvasive visual contrast-enhanced transesophageal echocardiography (cTEE) method for monitoring the communication between left atrium (LA) and LAA post-LAAC by cTEE-score evaluating the contrast enhancement in LAA. Methods: A total of 29 healthy dogs were studied by LAAC at < 24 h and 1, 2, 3 and 6-months. The LAAC procedure was assessed by TEE with color Doppler flow imaging (CDFI) and contrast imaging. The cTEE score was calculated based on the differential contrast opacification of LA and LAA cavities, the CDFI on the width of peri-device color flow, and that of histology on the level of occluder surface endothelialization in postmortem histological examination. Spearman’s correlation analysis was used to correlate these scores. Results: The correlation between cTEE and histology scores was superior to that between CDFI and histology scores. The trend of average cTEE score was tracked with that of histology, while that of CDFI was far from that of histology. The correlation coefficient of CDFI and histology scores was not signifi-cant (p > 0.05). Conclusions: The noninvasive visual cTEE is feasible and reliable to monitor communication between the LA and LAA post-LAAC. cTEE is superior to CDFI as a tool in predicting the progress for endothelialization surveillance. © 2022 Via Medica.

Background: Device-associated thrombus are potential causes for thromboembolic events post left atrial appendage closure (LAAC), and correlated with the complete endothelialization of the device surface. Our aim was to evaluate the endothelialization of LAMax LAAC™ occluder surface and analyze the potential influence of the implantation technique on the healing response. Methods: A total of 29 healthy dogs (28.0 ± 3.7 kg) were implanted with the devices successfully after ensuring COVER signs was met (Concavity of the disc, Oversizing by 20–50%, Verifying position, Ensuring stability, Residual flow < 5 mm by transesophageal echocardiographic (TEE) examination), and sacrificed at < 24 h, 1-, 2-, 3-, and 6-months. Gross examinations were conducted to evaluate healing response. Results: The mean diameters of LAA orifice measured by angiography and TEE were 19.0 ± 2.9 mm and 16.6 ± 2.9 mm (P < 0.05), respectively. TEE found that the discs in 18 dogs (62.1%) were completely pulled into the LAA with concavity and in 11 dogs incompletely pulled into the LAA with suboptimally concavity, while 5 of them had residual flow. Gross examinations showed that the complete endothelialization on the device surface with concaved disc was found at 1-month after LAAC. Microscopic examinations confirmed complete healing on the device with optimal closure effect. Conclusions: The good healing response and the optimal closure effect were observed using the LAMax device in a canine model by following the COVER implantation technique. © 2022, The Author(s).

Li-excess cation-disordered oxide cathodes have attracted increasing interests owing to their high energy density originated from cumulative cationic & anionic redox activity. In particular, Ni-based cation-disordered oxides exhibit high theoretical capacity for 2 e− reactions of Ni2+/Ni4+, while the severe overlapping between Ni 3d and O 2p orbitals restricts Ni redox capacity and unstable O redox deteriorates the cycling performance. Benefiting from advanced data mining and high-throughput theoretical calculations technology, we demonstrated that the capacity and cycling performance of Ni-based cation-disordered oxide can be synergically enhanced by carbon/Al2O3 double coating and partial Al3+ substitution. The synergistic mechanism is unveiled via X-ray photoelectron spectroscopy (XPS) and soft X-ray absorption spectroscopy (XAS) characterization together with first-principles calculations. It is confirmed that carbon coating increases the capacity by promoting the formation of peroxo-like species, which boosts O redox activity. Partial intercalating Al3+ enhances the Ni redox reaction by shortening the band overlap between Ni and O. Furthermore, Al2O3 coating and Al3+ doping improved the cycling stability of the cathode material owing to the shielding effect on side reaction and more stable O lattice. This synergistic strategy with nano-coating layer provides a promising pathway to accelerate the discovery of high-energy cation-disordered oxides based cathode materials. © 2022 Elsevier Ltd

High-nickel layered oxides, LiNixCoyMnzO2 (0.6 < x < 1), are promising cathode materials for producing batteries with high energy density and working voltage, while their poor cycling performance severely limits their commercial applications. Herein, an integrated surface coating/doping strategy is developed to significantly improve the structural stability and electrochemical performance of LiNi0.88Co0.06Mn0.06O2. The titanium ions from a thin TiNb2O7 coating layer diffuse inward during the high-temperature sintering process and a uniform protective layer forms on the surface of the secondary particles of the material. This protective layer suppresses side reactions, and the Ti4+ doping increases the thickness of the lithium layer and reduces the lithium/nickel mixing, thereby enhancing the diffusion of lithium ions in bulk electrode. The capacity retention of modified material after 200 cycles at 1 C is greatly improved from 59.8% of the pristine material to 87.2%. First-principles calculations confirm the interaction affinity of the TiNb2O7 coating on the layered LiNi0.88Co0.06Mn0.06O2 with Ti ion migration in the interlayer region. Moreover, the enhanced oxygen release energy and electronic conductivity benefiting from Ti4+ doping promote the cycling stability of the integrated cathode. The surface engineering strategy proposed herein is generally effective for the electrochemical improvement of nickel-rich ternary cathode materials.

This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Materials Letters, copyright © 2021 American Chemical Societ, after peer review and technical editing by the publisher. To access the final edited and published work see https://doi.org/10.1021/acsmaterialslett.1c00592., A cost-effective and environmentally friendly Pb source is a prerequisite for achieving large-scale, low-cost perovskite photovoltaic devices. Currently, the commonly used method to prepare the lead source is based on a fire smelting process, requiring a high temperature of more than 1000 °C, which results in environmental pollution. Spent car lead acid batteries are an environmentally hazardous waste; however, they can alternatively serve as an abundant and inexpensive Pb source. Due to “self-purification”, quantum dots feature a high tolerance of impurities in the precursor since the impurities tend to be expelled from the small crystalline cores during colloidal nucleation. Herein, PbI2 recycled from spent lead acid batteries via a facile low-temperature solution process is used to synthesize CsPbI3 quantum dots, which simultaneously brings multiple benefits including (1) avoiding pollution originating from the fire smelting process; (2) recycling the Pb waste from batteries; and (3) synthesizing high-quality quantum dots. The resulting CsPbI3 quantum dots have photophysical properties such as PLQY and carrier lifetimes on par with those synthesized from the commercial PbI2 due to expelling of the impurity Na atoms. The resulting solar cells deliver comparable power conversion efficiencies: 14.0% for the cells fabricated using recycled PbI2 and 14.7% for the cells constructed using commercial PbI2. This work paves a new and feasible path to applying recycled Pb sources in perovskite photovoltaics., Peer Reviewed, Postprint (author's final draft)

Artificial iconic memories, also called photomemories, are new types of nonvolatile memory that can simultaneously detect and store light information in a monolithic device. Several approaches have been proposed to construct artificial iconic memories, such as three-terminal field effect transistors, which can achieve an effective control of the gate voltage and external light terminals. The drawbacks in constructing these memories involve complicated fabrication processes, and the resulting performance of, for example, perovskite transistor-type photomemories is limited by the low carrier mobilities and poor ambient stabilities, whereas architectures based on floating gate modulations entail strict interface engineering and poor device reliability. In this paper, we propose a novel monolithic artificial iconic memory with a multilayer architecture of indium tin oxide/perovskite/gold/perovskite/silver, which combines the memory and photodetector functionalities of perovskites in an integrated device. The bottom perovskite layer plays the role of a photodetector, modulating the voltage bias on the top perovskite layer that serves as a resistive switching memory. This multilayer perovskite device can store photo-sensing data in its resistive states, with a memory retention of 5 × 103 s and ambient stability longer than sixty days. As a prototype demonstration, a 7 × 7 artificial iconic memory array is constructed to detect and store data on light intensity distribution, enabling a nonvolatile imaging functionality. Our work provides a new platform for designing perovskite-based architectures with simultaneous light detection and data storage capabilities.

[ntroduction] Gnetophytes, comprising the genera Ephedra, Gnetum and Welwitschia, are an understudied, enigmatic lineage of gymnosperms with a controversial phylogenetic relationship to other seed plants. Here we examined the organization of ribosomal DNA (rDNA) across representative species. [Methods] We applied high-throughput sequencing approaches to isolate and reconstruct rDNA units and to determine their intragenomic homogeneity. In addition, fluorescent in situ hybridization and Southern blot hybridization techniques were used to reveal the chromosome and genomic organization of rDNA. [Key results] The 5S and 35S rRNA genes were separate (S-type) in Gnetum montanum, Gnetum gnemon and Welwitschia mirabilis and linked (L-type) in Ephedra altissima. There was considerable variability in 5S rDNA abundance, ranging from as few as ~4000 (W. mirabilis) to >100 000 (G. montanum) copies. A similar large variation was also observed in 5S rDNA locus numbers (two to 16 sites per diploid cell). 5S rRNA pseudogenes were interspersed between functional genes forming a single unit in E. altissima and G. montanum. Their copy number was comparable or even higher than that of functional 5S rRNA genes. In E. altissima internal transcribed spacers of 35S rDNA were long and intrinsically repetitive while in G. montanum and W. mirabilis they were short without the subrepeats. [Conclusions] Gnetophytes are distinct from other gymnosperms and angiosperms as they display surprisingly large variability in rDNA organization and rDNA copy and locus numbers between genera, with no relationship between copy numbers and genome sizes apparent. Concerted evolution of 5S rDNA units seems to have led to the amplification of 5S pseudogenes in both G. montanum and E. altissima. Evolutionary patterns of rDNA show both gymnosperm and angiosperm features underlining the diversity of the group.

Recently, resistive switching devices have emerged as promising candidates for next generation non-volatile memory and neuromorphic computing applications. In general, resistive switching device consists of a two-terminal metal-insulator-metal structure, in which metal oxide is widely employed as the insulator. Among a variety of metal oxides, SrTiO3 has attracted extensive attention owing to its superior physical and chemical properties. In this dissertation, novel SrTiO3 resistive switching devices through solution processed approaches have been developed and their electrical properties are tuned through engineering the defects and interfaces. The thesis includes the following parts: (1) Specific cation doping is utilized to modulate the electrical properties of SrTiO3 nanoparticles film. In Cr-doped SrTiO3 device, oxygen vacancies are induced since the Ti4+ is partly replaced by Cr3+, leading to reversible hysteresis loops upon application of voltage, while negligible resistance change is observed in the undoped device. (2) By insertion of a reduced graphene oxide layer between SrTiO3 and the bottom electrode, a transition from digital switching to analog switching is demonstrated. Typical potentiation and depression behaviours are implemented towards neuromorphic computing applications. (3) To explore the potential applications of silver nanowires as electrodes and artificial filaments, controlled fragmentation of silver nanowires has been realized through ultraviolet (UV)/ozone irradiation and a low-temperature annealing process. Based on the fragmented silver nanowire network, the device exhibits a reliable threshold switching effect with a selectivity of 5 × 105. (4) A facile sol-precipitation method is introduced to prepare SrTiO3 nanocubes and thin films. Using silver top electrode deposited by ink-jet printing, the device shows a typical bipolar switching behaviour. After deposition of silver nanowires onto the bottom electrode, unipolar switching with a h

Machine learning as a service has been widely deployed to utilize deep neural network models to provide prediction services. However, this raises privacy concerns since clients need to send sensitive information to servers. In this paper, we focus on the scenario where clients want to classify private images with a convolutional neural network model hosted in the server, while both parties keep their data private. We present FALCON, a fast and secure approach for CNN predictions based on Fourier Transform. Our solution enables linear layers of a CNN model to be evaluated simply and efficiently with fully homomorphic encryption. We also introduce the first efficient and privacy-preserving protocol for softmax function, which is an indispensable component in CNNs and has not yet been evaluated in previous works due to its high complexity. We implemented the FALCON and evaluated the performance on real-world CNN models. The experimental results show that FALCON outperforms the best known works in both computation and communication cost.

Semantic segmentation is one of the basic topics in computer vision, it aims to assign semantic labels to every pixel of an image. Unbalanced semantic label distribution could have a negative influence on segmentation accuracy. In this paper, we investigate using data augmentation approach to balance the semantic label distribution in order to improve segmentation performance. We propose using generative adversarial networks (GANs) to generate realistic images for improving the performance of semantic segmentation networks. Experimental results show that the proposed method can not only improve segmentation performance on those classes with low accuracy, but also obtain 1.3% to 2.1% increase in average segmentation accuracy. It shows that this augmentation method can boost accuracy and be easily applicable to any other segmentation models., Comment: 5 pages

The recent advances of deep learning in both computer vision (CV) and natural language processing (NLP) provide us a new way of understanding semantics, by which we can deal with more challenging tasks such as automatic description generation from natural images. In this challenge, the encoder-decoder framework has achieved promising performance when a convolutional neural network (CNN) is used as image encoder and a recurrent neural network (RNN) as decoder. In this paper, we introduce a sequential guiding network that guides the decoder during word generation. The new model is an extension of the encoder-decoder framework with attention that has an additional guiding long short-term memory (LSTM) and can be trained in an end-to-end manner by using image/descriptions pairs. We validate our approach by conducting extensive experiments on a benchmark dataset, i.e., MS COCO Captions. The proposed model achieves significant improvement comparing to the other state-of-the-art deep learning models., Comment: 5 pages, 2 figures, 1 table, IEEE ICASSP 2019

Mixed Reality (MR) is a powerful interactive technology that yields new types of user experience. We present a semantic based interactive MR framework that exceeds the current geometry level approaches, a step change in generating high-level context-aware interactions. Our key insight is to build semantic understanding in MR that not only can greatly enhance user experience through object-specific behaviours, but also pave the way for solving complex interaction design challenges. The framework generates semantic properties of the real world environment through dense scene reconstruction and deep image understanding. We demonstrate our approach with a material-aware prototype system for generating context-aware physical interactions between the real and the virtual objects. Quantitative and qualitative evaluations are carried out and the results show that the framework delivers accurate and fast semantic information in interactive MR environment, providing effective semantic level interactions.

Lei Zhu,1 Feizhou Huang,1 Tao Wan,1 Hongbo Xu,1 Qian Zhao2,3 1Department of Hepatobiliary and Pancreatic Surgery, the Third Xiangya Hospital of Central South University, Changsha, Hunan 410013, People’s Republic of China; 2Department of Adult Stem Cells, Institute of Reproduction and Stem Cell Engineering, Central South University, Changsha, Hunan 410078, People’s Republic of China; 3Institute of Transformation Medicine Affiliated to Hunan Yearth Biotechnology Co., Ltd., Changsha, Hunan 410200, People’s Republic of China Introduction: Hepatocellular carcinoma (HCC) is the third major cause of malignant tumor-related death worldwide because it is initially diagnosed in the advanced stage and its therapeutic outcomes are usually poor. Based on this, it is urgent to identify effective early diagnosis biomarkers and new therapeutic targets to promote HCC treatment. Long noncoding RNAs (lncRNAs) have been reported as promising biomarkers for tumor diagnosis and treatment.Materials and methods: In this study, we profiled expression patterns and dysregulation of lncRNAs in HCC tissues by analyzing two datasets GSE55191 and GSE64631 from Gene Expression Omnibus database firstly, each of which contains expression profiles of 3 primary HCC tissues and 3 normal liver tissues, respectively.Results: LncRNA 882 (LINC00882) is one of the lncRNAs that was significantly upregulated in HCC tissues compared with normal liver tissues. We verified the upregulation of LINC00882 in HCC by using two separate cohorts that contained 85 HCC tissues and paired adjacent noncancerous tissues and 86 HCC tissues and 89 independent noncancerous liver tissues, respectively.Discussion: We found that upregulation of LINC00882 is correlated with poorer prognosis of HCC patients. In vitro cell experiments demonstrated that knockdown of LINC00882 inhibits proliferation, migration and invasion of HCC cell lines.Conclusion: These results indicated that LINC00882 promotes HCC p

Tao Wan,1,* Jing Shao,1,* Bin Hu,2 Gang Liu,1 Peng Luo,1 Yanming Zhou1 1Department of Hepatobiliary & Pancreatovascular Surgery, 2Department of Clinical Laboratory Medicine, First Affiliated Hospital of Xiamen University, Xiamen, China *These authors contributed equally to this work Background and objective: HSF1 is reported to be overexpressed in various solid tumors and play a pivotal role in cancer progression. A meta-analysis was conducted to assess the potential prognostic role of HSF1 in patients with solid tumors.Methods: An extensive electronic search of three databases was performed for relevant articles. The pooled hazard ratios (HRs) or odds ratios with their corresponding 95% CI were calculated with a random-effects model. Heterogeneity and publication bias analyses were also conducted.Results: A total of 3,159 patients from 10 eligible studies were included into the analysis. The results showed that positive HSF1 expression was significantly correlated with poor overall survival in all tumors (HR=2.09; 95% CI: 1.62–2.70; P<0.001). Subgroup analysis revealed that there was a significant association between HSF1 overexpression and poor prognosis in esophageal squamous cell carcinoma (ESCC) (HR=1.83; 95% CI: 1.21–2.77; P=0.004), breast cancer (BC) (HR=1.52; 95% CI: 1.24–2.86; P<0.001), hepatocellular carcinoma (HR=3.02; 95% CI: 1.77–5.18; P<0.001), non-small-cell lung cancer (HR=2.19; 95% CI: 1.20–3.99; P=0.01), and pancreatic cancer (HR=2.58; 95% CI: 1.11–6.03; P=0.03) but not in osteosarcoma (HR=1.58; 95% CI: 0.47–5.35; P=0.46). In addition, HSF1 overexpression was significantly associated with some phenotypes of tumor aggressiveness including TNM stage, histological grade, lymph node metastasis, and vascular invasion.Conclusion: HSF1 overexpression may prove to be an unfavorable prognostic biomarker for solid tumor patients. Keywords: HSF1, solid tumors, p

Kaiyue Yu, Yixuan Wang, Tao Wan, Yuanhao Zhai, Sisi Cao, Wenyi Ruan, Chuanbin Wu, Yuehong Xu School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, People’s Republic of China Background: Topical application of tacrolimus (FK506) was effective in the treatment of atopic dermatitis (AD); however, adverse effects frequently occurred with the increase of FK506 dose during long–term treatment.Objective: The objective of this project was to develop a hybrid skin targeting system encapsulating FK506 based on nicotinamide (NIC) and chitosan nanoparticles (CS–NPs), ie, FK506–NIC–CS–NPs, which took advantages of both of NIC and CS–NPs to obtain the synergetic effects of percutaneous delivery and treatment efficacy enhancement along with dose reduction.Methods: The formulation of FK506–NIC–CS–NPs was optimized and characterized. In vitro and in vivo skin permeation studies were performed. AD–like skin lesions were constructed with BALB/c mice by 1–chloro–2, 4–dinitrobenzene (DNCB)–induced, and FK506–NIC–CS–NPs containing different dose of FK506 were topically administered to treat AD–like skin lesions in comparison with Protopic.Results: NIC was found to significantly increase the FK506 EE to 92.2% by CS–NPs. In comparison with commercial FK506 ointment (Protopic), in vitro and in vivo skin permeation studies demonstrated that NIC–CS–NPs system significantly enhanced FK506 permeation through and into the skin, and deposited more FK506 into the skin. The treatment efficacy on clinical symptoms, histological analysis, and molecular biology of the AD–mice demonstrated that NIC–CS–NPs with ~1/3 dose of FK506 of Protopic was superior to that of Protopic, and NIC–CS–NPs vehicle exhibited the adjuvant th

Tao Wan,* Wenhui Pan,* Yueming Long, Kaiyue Yu, Sibo Liu, Wenyi Ruan, Jingtong Pan, Mengyao Qin, Chuanbin Wu, Yuehong Xu Department of Pharmaceutics, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, People’s Republic of China *These authors contributed equally to this work Abstract: The hybrid system based on nanoparticles (NPs) self-assembled by the conjugations of hyaluronic acid with cholesterol (HA–Chol NPs) combined with nicotinamide (NIC) for tacrolimus (FK506), ie, FK506 NPs–NIC, has been confirmed to exhibit a significant synergistic effect on FK506 permeation through and into intact skin; thus, it may be a promising approach for FK506 to effectively treat skin diseases. The aim of this study was to evaluate its potential for the treatment of psoriasis. In vitro permeation through the psoriatic skin was carried out, and the results revealed that the combination of NPs with NIC exhibited a significant synergistic effect on FK506 deposition within the psoriatic skin (3.40±0.67 µg/cm2) and penetration through the psoriatic skin (30.86±9.66 µg/cm2). The antipsoriatic activity of FK506 NPs–NIC was evaluated through the treatment for imiquimod (IMQ)-induced psoriasis. The psoriasis area and severity index (PASI) score demonstrated that FK506 HA–Chol NPs–NIC exerted the effect on ameliorating the skin lesions comparable to clobetasol propionate (a positive drug for psoriasis) and superior to commercial FK506 ointment (Protopic®), and the histological study showed that it presented a synergistic effect on antipsoriasis after FK506 incorporation into NPs combined with NIC hydrotropic system, which might ultimately increase the therapeutic effect and minimize the systemic side effects by reducing the overall dose of FK506. RAW 264.7 cell uptake presented the enhancement of drugs delivered into cells by HA–Chol N

Kaiyue Yu, Yixuan Wang, Tao Wan, Yuanhao Zhai, Sisi Cao, Wenyi Ruan, Chuanbin Wu, Yuehong Xu School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, People’s Republic of China Background: Topical application of tacrolimus (FK506) was effective in the treatment of atopic dermatitis (AD); however, adverse effects frequently occurred with the increase of FK506 dose during long–term treatment.Objective: The objective of this project was to develop a hybrid skin targeting system encapsulating FK506 based on nicotinamide (NIC) and chitosan nanoparticles (CS–NPs), ie, FK506–NIC–CS–NPs, which took advantages of both of NIC and CS–NPs to obtain the synergetic effects of percutaneous delivery and treatment efficacy enhancement along with dose reduction.Methods: The formulation of FK506–NIC–CS–NPs was optimized and characterized. In vitro and in vivo skin permeation studies were performed. AD–like skin lesions were constructed with BALB/c mice by 1–chloro–2, 4–dinitrobenzene (DNCB)–induced, and FK506–NIC–CS–NPs containing different dose of FK506 were topically administered to treat AD–like skin lesions in comparison with Protopic.Results: NIC was found to significantly increase the FK506 EE to 92.2% by CS–NPs. In comparison with commercial FK506 ointment (Protopic), in vitro and in vivo skin permeation studies demonstrated that NIC–CS–NPs system significantly enhanced FK506 permeation through and into the skin, and deposited more FK506 into the skin. The treatment efficacy on clinical symptoms, histological analysis, and molecular biology of the AD–mice demonstrated that NIC–CS–NPs with ~1/3 dose of FK506 of Protopic was superior to that of Protopic, and NIC–CS–NPs vehicle exhibited the adjuvant th

Tao Wan,* Wenhui Pan,* Yueming Long, Kaiyue Yu, Sibo Liu, Wenyi Ruan, Jingtong Pan, Mengyao Qin, Chuanbin Wu, Yuehong Xu Department of Pharmaceutics, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, People’s Republic of China *These authors contributed equally to this work Abstract: The hybrid system based on nanoparticles (NPs) self-assembled by the conjugations of hyaluronic acid with cholesterol (HA–Chol NPs) combined with nicotinamide (NIC) for tacrolimus (FK506), ie, FK506 NPs–NIC, has been confirmed to exhibit a significant synergistic effect on FK506 permeation through and into intact skin; thus, it may be a promising approach for FK506 to effectively treat skin diseases. The aim of this study was to evaluate its potential for the treatment of psoriasis. In vitro permeation through the psoriatic skin was carried out, and the results revealed that the combination of NPs with NIC exhibited a significant synergistic effect on FK506 deposition within the psoriatic skin (3.40±0.67 µg/cm2) and penetration through the psoriatic skin (30.86±9.66 µg/cm2). The antipsoriatic activity of FK506 NPs–NIC was evaluated through the treatment for imiquimod (IMQ)-induced psoriasis. The psoriasis area and severity index (PASI) score demonstrated that FK506 HA–Chol NPs–NIC exerted the effect on ameliorating the skin lesions comparable to clobetasol propionate (a positive drug for psoriasis) and superior to commercial FK506 ointment (Protopic®), and the histological study showed that it presented a synergistic effect on antipsoriasis after FK506 incorporation into NPs combined with NIC hydrotropic system, which might ultimately increase the therapeutic effect and minimize the systemic side effects by reducing the overall dose of FK506. RAW 264.7 cell uptake presented the enhancement of drugs delivered into cells by HA–Chol N

Semantic parsing has emerged as a significant and powerful paradigm for natural language interface and question answering systems. Traditional methods of building a semantic parser rely on high-quality lexicons, hand-crafted grammars and linguistic features which are limited by applied domain or representation. In this paper, we propose a general approach to learn from denotations based on Seq2Seq model augmented with attention mechanism. We encode input sequence into vectors and use dynamic programming to infer candidate logical forms. We utilize the fact that similar utterances should have similar logical forms to help reduce the searching space. Under our learning policy, the Seq2Seq model can learn mappings gradually with noises. Curriculum learning is adopted to make the learning smoother. We test our method on the arithmetic domain which shows our model can successfully infer the correct logical forms and learn the word meanings, compositionality and operation orders simultaneously.

How to build a good model for image generation given an abstract concept is a fundamental problem in computer vision. In this paper, we explore a generative model for the task of generating unseen images with desired features. We propose the Generative Cooperative Net (GCN) for image generation. The idea is similar to generative adversarial networks except that the generators and discriminators are trained to work accordingly. Our experiments on hand-written digit generation and facial expression generation show that GCN's two cooperative counterparts (the generator and the classifier) can work together nicely and achieve promising results. We also discovered a usage of such generative model as an data-augmentation tool. Our experiment of applying this method on a recognition task shows that it is very effective comparing to other existing methods. It is easy to set up and could help generate a very large synthesized dataset., Comment: 12 pages, 8 figures

In this paper, we propose a model to analyze sentiment of online stock forum and use the information to predict the stock volatility in the Chinese market. We have labeled the sentiment of the online financial posts and make the dataset public available for research. By generating a sentimental dictionary based on financial terms, we develop a model to compute the sentimental score of each online post related to a particular stock. Such sentimental information is represented by two sentiment indicators, which are fused to market data for stock volatility prediction by using the Recurrent Neural Networks (RNNs). Empirical study shows that, comparing to using RNN only, the model performs significantly better with sentimental indicators., Comment: 10 pages, 5 figures and it is an extended vision of our conference paper in IEA/AIE 2017

Software defined networking implements the network control plane in an external entity, rather than in each individual device as in conventional networks. This architectural difference implies a different design for control functions necessary for essential network properties, e.g., loop prevention and link redundancy. We explore how such differences redefine the security weaknesses in the SDN control plane and provide a framework for comparative analysis which focuses on essential network properties required by typical production networks. This enables analysis of how these properties are delivered by the control planes of SDN and conventional networks, and to compare security risks and mitigations. Despite the architectural difference, we find similar, but not identical, exposures in control plane security if both network paradigms provide the same network properties and are analyzed under the same threat model. However, defenses vary; SDN cannot depend on edge based filtering to protect its control plane, while this is arguably the primary defense in conventional networks. Our concrete security analysis suggests that a distributed SDN architecture that supports fault tolerance and consistency checks is important for SDN control plane security. Our analysis methodology may be of independent interest for future security analysis of SDN and conventional networks.

One of the major challenges in Minimally Invasive Surgery (MIS) such as laparoscopy is the lack of depth perception. In recent years, laparoscopic scene tracking and surface reconstruction has been a focus of investigation to provide rich additional information to aid the surgical process and compensate for the depth perception issue. However, robust 3D surface reconstruction and augmented reality with depth perception on the reconstructed scene are yet to be reported. This paper presents our work in this area. First, we adopt a state-of-the-art visual simultaneous localization and mapping (SLAM) framework - ORB-SLAM - and extend the algorithm for use in MIS scenes for reliable endoscopic camera tracking and salient point mapping. We then develop a robust global 3D surface reconstruction frame- work based on the sparse point clouds extracted from the SLAM framework. Our approach is to combine an outlier removal filter within a Moving Least Squares smoothing algorithm and then employ Poisson surface reconstruction to obtain smooth surfaces from the unstructured sparse point cloud. Our proposed method has been quantitatively evaluated compared with ground-truth camera trajectories and the organ model surface we used to render the synthetic simulation videos. In vivo laparoscopic videos used in the tests have demonstrated the robustness and accuracy of our proposed framework on both camera tracking and surface reconstruction, illustrating the potential of our algorithm for depth augmentation and depth-corrected augmented reality in MIS with monocular endoscopes., Comment: 15 pages

In this paper, we propose a model using generative adversarial net (GAN) to generate realistic text. Instead of using standard GAN, we combine variational autoencoder (VAE) with generative adversarial net. The use of high-level latent random variables is helpful to learn the data distribution and solve the problem that generative adversarial net always emits the similar data. We propose the VGAN model where the generative model is composed of recurrent neural network and VAE. The discriminative model is a convolutional neural network. We train the model via policy gradient. We apply the proposed model to the task of text generation and compare it to other recent neural network based models, such as recurrent neural network language model and SeqGAN. We evaluate the performance of the model by calculating negative log-likelihood and the BLEU score. We conduct experiments on three benchmark datasets, and results show that our model outperforms other previous models.

Social media mining has become one of the most popular research areas in Big Data with the explosion of social networking information from Facebook, Twitter, LinkedIn, Weibo and so on. Understanding and representing the structure of a social network is a key in social media mining. In this paper, we propose the Motif Iteration Model (MIM) to represent the structure of a social network. As the name suggested, the new model is based on iteration of basic network motifs. In order to better show the properties of the model, a heuristic and greedy algorithm called Vertex Reordering and Arranging (VRA) is proposed by studying the adjacency matrix of the three-vertex undirected network motifs. The algorithm is for mapping from the adjacency matrix of a network to a binary image, it shows a new perspective of network structure visualization. In summary, this model provides a useful approach towards building link between images and networks and offers a new way of representing the structure of a social network., Comment: 10 pages, 3 figures and it is an extended vision of our conference paper in ICONIP 2017

The minority game is a simple game theory model for describing the collective behavior of agents in an idealized situation where they compete for some finite resources. In this paper, we assume that collective behavior is generated by the aggregation of independent actions of agents and the action follows the minority game. A probabilistic machine learning model is proposed to model the generative process of how collective behavior emerges from individual actions. By training on collective data, we can infer the most likely parameters use the trained system to make predictions. This model can be regarded as a new learning paradigm of analyzing collective data by decomposing the generative process into independent micro-level games. To demonstrate the effectiveness of the model, we conduct experiments on an artificial data set and the real-world data. A set of selected stock indices are tested to capture their rises and falls in the market.

The minority game is a simple game theory model for describing the collective behavior of agents in an idealized situation where they compete for some finite resources. In this paper, we assume that collective behavior is generated by the aggregation of independent actions of agents and the action follows the minority game. A probabilistic machine learning model is proposed to model the generative process of how collective behavior emerges from individual actions. By training on collective data, we can infer the most likely parameters use the trained system to make predictions. This model can be regarded as a new learning paradigm of analyzing collective data by decomposing the generative process into independent micro-level games. To demonstrate the effectiveness of the model, we conduct experiments on an artificial data set and the real-world data. A set of selected stock indices are tested to capture their rises and falls in the market.

Wenhui Pan, Mengyao Qin, Guoguang Zhang, Yueming Long, Wenyi Ruan, Jingtong Pan, Zushuai Wu, Tao Wan, Chuanbin Wu, Yuehong Xu Department of Pharmaceutics, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, People’s Republic of China Abstract: Tacrolimus (FK506), an effective immunosuppressant for treating inflammatory skin diseases, hardly penetrates into and through the skin owing to its high hydrophobicity and molecular weight. The aim of this study was to develop a hybrid system based on nicotinamide (NIC) and nanoparticles (NPs) encapsulating FK506, such as FK506–NPs–NIC, for facilitating percutaneous delivery, which exploited virtues of both NIC and NPs to obtain the synergetic effect. Solubility and percutaneous permeation studies were carried out. The results showed that NIC could increase the solubility and permeability of FK506 and that 20% (w/v) NIC presented higher FK506 permeability and was thus chosen as the hydrotropic solution to solubilize FK506 and prepare FK506–NPs–NIC. Hyaluronic acid (HA) was chemically conjugated with cholesterol (Chol) to obtain amphiphilic conjugate of HA–Chol, which self-assembled NPs in 20% NIC solution containing FK506. The particle size, zeta potential, and morphology of NPs were characterized. The encapsulation efficiency and in vitro percutaneous permeation of NPs were evaluated in the presence and absence of NIC. The results demonstrated that hydrotropic solubilizing FK506 was readily encapsulated into NPs with a higher encapsulation efficiency of 79.2%±4.2%, and the combination of NPs with NIC exhibited a significantly synergistic effect on FK506 deposition within the skin (2.39±0.53 µg/cm2) and penetration through the skin (13.38±2.26 µg/cm2). The effect of the combination of NPs with NIC on drug permeation was further visualized by confocal laser scanning microscope thr

This work has previously been published [LDS 16] and this extended abstract provides a synopsis for further discussion at the UK CGVC 2016 conference. We introduce the concept of tactile mesh saliency, where tactile salient points on a virtual mesh are those that a human is more likely to grasp, press, or touch if the mesh were a real-world object. We solve the problem of taking as input a 3D mesh and computing the tactile saliency of every mesh vertex. The key to solving this problem is in a new formulation that combines deep learning and learning-to-rank methods to compute a tactile saliency measure. Finally, we discuss possibilities for future work.

Reproductive allocation is a key process in the plant life cycle and aquatic plants exhibit great diversity in their reproductive systems. In the present study, we conduct a field investigation of three aquatic macrophytes: Stuckenia pectinata, Myriophyllum spicatum, and Potamogeton perfoliatus. Our results showed that widespread species, including S. pectinata and M. spicatum had greater plasticity in their allocation patterns in the form of increased sexual and asexual reproduction, and greater potential to set seeds and increase fitness in more eutrophic environments. P. perfoliatus also exhibited a capacity to adopt varied sexual reproductive strategies such as setting more offspring for the future, although only in clear conditions with low nutrient levels. Our results establish strategies and mechanisms of some species for tolerating and surviving in varied eutrophic lake conditions.

This work has previously been published [LDS 16] and this extended abstract provides a synopsis for further discussion at the UK CGVC 2016 conference. We introduce the concept of tactile mesh saliency, where tactile salient points on a virtual mesh are those that a human is more likely to grasp, press, or touch if the mesh were a real-world object. We solve the problem of taking as input a 3D mesh and computing the tactile saliency of every mesh vertex. The key to solving this problem is in a new formulation that combines deep learning and learning-to-rank methods to compute a tactile saliency measure. Finally, we discuss possibilities for future work.

Wenhui Pan, Mengyao Qin, Guoguang Zhang, Yueming Long, Wenyi Ruan, Jingtong Pan, Zushuai Wu, Tao Wan, Chuanbin Wu, Yuehong Xu Department of Pharmaceutics, School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, People’s Republic of China Abstract: Tacrolimus (FK506), an effective immunosuppressant for treating inflammatory skin diseases, hardly penetrates into and through the skin owing to its high hydrophobicity and molecular weight. The aim of this study was to develop a hybrid system based on nicotinamide (NIC) and nanoparticles (NPs) encapsulating FK506, such as FK506–NPs–NIC, for facilitating percutaneous delivery, which exploited virtues of both NIC and NPs to obtain the synergetic effect. Solubility and percutaneous permeation studies were carried out. The results showed that NIC could increase the solubility and permeability of FK506 and that 20% (w/v) NIC presented higher FK506 permeability and was thus chosen as the hydrotropic solution to solubilize FK506 and prepare FK506–NPs–NIC. Hyaluronic acid (HA) was chemically conjugated with cholesterol (Chol) to obtain amphiphilic conjugate of HA–Chol, which self-assembled NPs in 20% NIC solution containing FK506. The particle size, zeta potential, and morphology of NPs were characterized. The encapsulation efficiency and in vitro percutaneous permeation of NPs were evaluated in the presence and absence of NIC. The results demonstrated that hydrotropic solubilizing FK506 was readily encapsulated into NPs with a higher encapsulation efficiency of 79.2%±4.2%, and the combination of NPs with NIC exhibited a significantly synergistic effect on FK506 deposition within the skin (2.39±0.53 µg/cm2) and penetration through the skin (13.38±2.26 µg/cm2). The effect of the combination of NPs with NIC on drug permeation was further visualized by confocal laser scanning microscope thr

The minority game is a simple game theory model for describing the collective behavior of agents in an idealized situation where they compete for some finite resources. In this paper, we assume that collective behavior is generated by the aggregation of independent actions of agents and the action follows the minority game. A probabilistic machine learning model is proposed to model the generative process of how collective behavior emerges from individual actions. By training on collective data, we can infer the most likely parameters use the trained system to make predictions. This model can be regarded as a new learning paradigm of analyzing collective data by decomposing the generative process into independent micro-level games. To demonstrate the effectiveness of the model, we conduct experiments on an artificial data set and the real-world data. A set of selected stock indices are tested to capture their rises and falls in the market.

[Background]Niviventer is a genus of white-bellied rats that are among the most common rodents in the Indo-Sundaic region. The taxonomy of the genus has undergone extensive revisions and remains controversial. The current phylogeny is unresolved and was developed primarily on the basis of mitochondrial genes. Identification is extremely difficult, and a large number of GenBank sequences seem to be problematic. We extensively sampled specimens of Niviventer in China and neighboring northern Vietnam, including topotypes of the most reported species (n = 6), subspecies (n = 8), and synonyms (n = 4). We estimated phylogenetic relationships on the basis of one mitochondrial and three nuclear genes, using concatenation and coalescent-based approaches. We also employed molecular species delimitation approaches to test the existence of cryptic and putative new species. [Results]Our phylogeny was finely resolved, especially for the N. confucianus-like species. Our data provided the first support for N. brahma and N. eha as sister species, an assignment that is congruent with their morphological similarities. Species delimitation analyses provided new insight into species diversity and systematics. Three geographic populations of N. confucianus and one of N. fulvescens were supported as genetically distinct in our species delimitation analyses, while three recognized species (N. coninga, N. huang, and N. lotipes) were not strongly supported as distinct. [Conclusions]Our results suggested that several genetically distinct species may be contained within the species currently known as N. confucianus and N. fulvescens. In addition, the results of Bayesian Phylogenetics and Phylogeography (BPP) for N. coninga, N. huang, and N. lotipes indicated that either inter-specific gene flow had occurred or imperfect taxonomy was present. Morphological examinations and morphometric analyses are warranted to examine the molecular results.

Reproductive allocation is a key process in the plant life cycle and aquatic plants exhibit great diversity in their reproductive systems. In the present study, we conduct a field investigation of three aquatic macrophytes: Stuckenia pectinata, Myriophyllum spicatum, and Potamogeton perfoliatus. Our results showed that widespread species, including S. pectinata and M. spicatum had greater plasticity in their allocation patterns in the form of increased sexual and asexual reproduction, and greater potential to set seeds and increase fitness in more eutrophic environments. P. perfoliatus also exhibited a capacity to adopt varied sexual reproductive strategies such as setting more offspring for the future, although only in clear conditions with low nutrient levels. Our results establish strategies and mechanisms of some species for tolerating and surviving in varied eutrophic lake conditions.

Lei Zhu, Feizhou Huang, Gang Deng, Wanpin Nie, Wei Huang, Hongbo Xu, Shaopeng Zheng, Zhongjie Yi, Tao Wan Department of Hepatobiliary and Pancreatic Surgery, The Third Xiangya Hospital of Central South University, Changsha, Hunan, People’s Republic of China Abstract: In spite of improvements in surgical technology, the resectability and curability of intrahepatic cholangiocarcinoma (ICC) are still low. Our previous study showed that the strong Sal-like protein 4 (Sall4)-positive cases had shorter overall survival compared to Sall4-negative cases, indicating an oncogenic role of Sall4 in ICC. In this study, we aimed to explore the precise mechanism of Sall4 on ICC cell invasion and metastasis. We evaluated the expression of Sall4, PTEN, and Bmi-1 in 28 cases of adjacent tissues and 175 cases of ICC tissues by using immunohistochemical staining. We found that the expression of Sall4 and Bmi-1 was significantly increased in ICC tissues compared with the adjacent tissues, while PTEN expression was reduced in ICC tissues compared with the adjacent tissues, and there was a reverse relationship between Sall4 and PTEN in ICC, whereas there was a positive correlation in Sall4 and Bmi-1 expression in ICC. In addition, overall survival analysis showed that ICC patients with low PTEN exhibited a worse prognosis than ICC patients with high PTEN, and lower Bmi-1 expression showed a better prognosis than ICC patients with high Bmi-1. By a battery of experiments in vitro, we demonstrated that Sall4 promotes ICC cell proliferation, and progression of ICC might be through PTEN/PI3K/Akt and Bmi-1/Wnt/β-catenin signaling and enhancing epithelial–mesenchymal transition process. Thus, Sall4 may be a potential target for the treatment of ICC metastasis. Keywords: intrahepatic cholangiocarcinoma, Sal-like protein 4, PTEN, Bmi-1, metastasis, EMT

In this paper, we investigate stable matching in structured networks. Consider case of matching in social networks where candidates are not fully connected. A candidate on one side of the market gets acquaintance with which one on the heterogeneous side depends on the structured network. We explore four well-used structures of networks and define the social circle by the distance between each candidate. When matching within social circle, we have equilibrium distinguishes from each other since each social network's topology differs. Equilibrium changes with the change on topology of each network and it always converges to the same stable outcome as complete information algorithm if there is no block to reach anyone in agent's social circle., Comment: 13 pages; 6 figures