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In this paper, drained consolidation tests of saturated remolded cohesive soil were carried out at different loading rates, and the samples at different loading stages were measured by nuclear magnetic resonance (NMR) testing. Through qualitative analysis of the relationship between the transverse relaxation time T2, peak area and porosity, the deformation micro-response of the saturated remolded cohesive soil was studied. The results showed that the transverse relaxation time T2 of the saturated remolded cohesive soil samples during the initial stage consisted of two spectral peaks, representing pores with large and small pore diameters, respectively. As loading progressed, the pore diameters in each sample group gradually shifted to smaller sizes, and the final form of the T2 spectrum was unimodal, in which the pores became denser and more uniform. In the initial stage of loading, the T2 spectrum of the soil sample with faster loading showed no obvious change trend due to the influence of drainage lag. After a sufficiently long dead load time, the final shape of the T2 spectrum was very similar regardless of loading rate, indicating that the loading rate only affected the intermediate state of the soil sample, and the final state was determined by the initial state of the sample. At the same time, after a certain dead load time, the changes in pore diameter were no longer obvious, indicating that the flowing fluid in the pore was drained and that drainage consolidation was complete. According to the positive correlation between the loading rate and maximum pore pressure, a boundary rate was obtained. We could reasonably infer that if the controlled loading rate was less than this value, drainage consolidation was complete in the main consolidation stage.

In this paper, the moisture content on the wetting front is obtained by using the Van Genuchten (VG) model of unsaturated soil, and then the distribution of moisture content in the upper part of the wetting front is simplified as a trapezoid. The Green-Ampt (G-A) infiltration model of infinite slope with unsaturated characteristics is derived. The analytical expression of safety coefficient (FOS) of infinite slope with rainfall is solved by combining the limit equilibrium method with the unsaturated soil shear strength theory phase. The results show that: 1) compared with the traditional G-A model and the combined rectangular and 1/4 oval model, the upper part of the wetting front is simplified to a trapezoidal model, which has great advantages in infiltration rate and cumulative infiltration, especially when the slope is large or the rain intensity is heavy; 2) since the distribution of soil moisture content above the wetting front is considered, the matrix suction at the wetting front is not neglected, and the safety coefficient calculated by the method proposed in this paper is closer to the actual situation than the traditional G-A model.

Dust pollution is one of the most severe environmental issues in open pit mines, hindering green mining development. Open pit mine dust has characteristics of multiple dust-generating points, is irregular, influenced by climatic conditions, and has a high degree of distribution with a wide dispersion range in three dimensions. Consequently, evaluating the quantity of dust dispersion and controlling environmental pollution are crucial for supporting green mining. In this paper, dust monitoring above the open pit mine was carried out with an unmanned aerial vehicle (UAV) on board. The dust distribution patterns above the open pit mine were studied in different vertical and horizontal directions at different heights. The results show that the temperature changes less in the morning and more at noon in winter. At the same time, the isothermal layer becomes thinner and thinner as the temperature rises, which makes it easy for dust to spread. The horizontal dust is mainly concentrated at 1300 and 1550 elevations. The dust concentration is polarized at 1350–1450 elevation. The most serious exceedance is at 1400 elevation, with TSP (the concentration of total suspended particulate), PM10 (particulates with aerodynamic diameter

Plasmonic metamaterial absorbers are particularly important in different applications such as photodetectors, microbolometers and solar cells. In this paper, we propose a tungsten boride (WB, a refractory ceramic) based broadband metamaterial absorber whose optical properties is numerically analyzed and experimentally characterized. We have also analyzed the damage characteristics of this absorber using a femtosecond laser and compared with an ordinary Au metamaterial absorber. We observe that WB has almost the double absorption bandwidth with absorption more than 90% over the spectral range of 950 to 1400 nm when compared with the Au counterpart. Furthermore, we show that Au metamaterial is damaged at the power of around 36.4 mW whereas WB metamaterial is not damaged at that power (WB has high Tammann temperature than Au)-however the atom of WB material was knocked off by the bombardment of a femtosecond laser.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Single-cell sequencing provides a new level of granularity in studying the heterogeneous nature of cancer cells. For some cancers, this heterogeneity is the result of copy number changes of genes within the cellular genomes. The ability to accurately determine such copy number changes is critical in tracing and understanding tumorigenesis. Current single-cell genome sequencing methodologies infer copy numbers based on statistical approaches followed by rounding decimal numbers to integer values. Such methodologies are sample dependent, have varying calling sensitivities which heavily depend on the sample’s ploidy and are sensitive to noise in sequencing data. In this paper we have demonstrated the concept of integer-counting by using a novel bioinformatic algorithm built on our library construction chemistry in order to detect the discrete nature of the genome. Supplementary material: [https://cherry.chem.bg.ac.rs/handle/123456789/4686]

The chloroplast is one of two organelles containing a separate genome that codes for essential and distinct cellular functions such as photosynthesis. Given the importance of chloroplasts in plant metabolism, the genomic architecture and gene content have been strongly conserved through long periods of time and as such are useful molecular tools for evolutionary inferences. At present, complete chloroplast genomes from over 4000 species have been deposited into publicly accessible databases. Despite the large number of complete chloroplast genomes, comprehensive analyses regarding genome architecture and gene content have not been conducted for many lineages with complete species sampling. In this study, we employed the genus Populus to assess how more comprehensively sampled chloroplast genome analyses can be used in understanding chloroplast evolution in a broadly studied lineage of angiosperms. We conducted comparative analyses across Populus in order to elucidate variation in key genome features such as genome size, gene number, gene content, repeat type and number, SSR (Simple Sequence Repeat) abundance, and boundary positioning between the four main units of the genome. We found that some genome annotations were variable across the genus owing in part from errors in assembly or data checking and from this provided corrected annotations. We also employed complete chloroplast genomes for phylogenetic analyses including the dating of divergence times throughout the genus. Lastly, we utilized re-sequencing data to describe the variations of pan-chloroplast genomes at the population level for P. euphratica. The analyses used in this paper provide a blueprint for the types of analyses that can be conducted with publicly available chloroplast genomes as well as methods for building upon existing datasets to improve evolutionary inference.

The quantum secret sharing is an essential and fundamental technique for sharing a secret with the all participants in quantum cryptography. It can be used to design many complex protocols such as secure multiparty summation, multiplication, sorting, voting, etc. Recently, Song et al. have discussed a quantum protocol for secret sharing, which has (t, n) threshold approach and modulo d, where t and n denote the threshold number of participants and total number of participants, respectively. Kao et al. point out that the secret in the Song et al.’s protocol cannot be reconstructed without other participants’ information. In this paper, we discuss a protocol that overcomes this problem.

Understanding the externalities of transportation networks in the process of the agglomeration and diffusion of production factors has theoretical and practical significance for the coordinated development of China's economic growth in urban agglomerations. Therefore, the social network analysis method is introduced in this paper with the case of the Pan Pearl River Delta Urban Agglomeration to analyze the characteristics of the traffic connection network of the production factor flow within this urban agglomeration, and subsequently, an econometric panel model is adopted to quantitatively analyze the effect of the connection network on the economic growth of the urban agglomeration. The results show that (1) the traffic connection of the Pan Pearl River Delta Urban Agglomeration has network characteristics typical of a “small world”. Although the connections between cities are gradually strengthening, the regional differences are obvious, showing a core–edge pattern of eastern agglomeration and western sparseness. (2) Among the network nodes, Guangzhou, Shenzhen and other cities have obvious agglomeration and diffusion effects, stabilizing economic growth while driving the development of surrounding cities. The "polarization effect" in Chongqing and Chengdu has significantly increased, and the accumulation of factors mainly meets their own economic development but has not yet spread. (3) The Pan Pearl River Delta Urban Agglomeration's transportation network influences the region’s economic growth through the structural effect, as it strengthens the economic ties between cities, and through the action of resource factors, as the network represents the aggregation and diffusion path of factor flow. (4) Due to the different traffic connections and industrial structures across the Pan Pearl River Delta Urban Agglomeration, the factor flow of each suburban agglomeration has a differentiated impact on the regional economic growth under the traffic connection network. Therefore, to realize the coordinated economic development of the Pan Pearl River Delta Urban Agglomeration, it is necessary to "adjust measures to local conditions" and formulate accurate and precise policies.

Ebola virus (EBOV) infection causes a high death toll, killing a high proportion of EBOV infected patients within 7 days. Comprehensive data on EBOV infection are very fragmented, hampering efforts in developing therapeutics and vaccines against EBOV. Under this circumstance, mathematical models become valuable resources to explore potential controlling strategies. In this paper, we employed experimental data of EBOV-infected nonhuman primates (NHPs) to construct a mathematical framework for determining windows of opportunity for treatment and vaccination. Considering a prophylactic vaccine based on recombinant vesicular stomatitis virus expressing the EBOV glycoprotein (VSV-EBOV), we found that the time window can be subject-specific, but vaccination could be protective if a subject is vaccinated during a period from one week to four months before infection. For the case of a therapeutic vaccine based on monoclonal antibodies (mAbs), a single dose might resolve the invasive EBOV replication even it was administrated as late as four days after infection. Our mathematical models can be used as building blocks for developing therapeutic and vaccine modalities as well as for evaluating public health intervention strategies in outbreaks. Future laboratory experiments will help to validate and refine the estimates of the windows of opportunity proposed here.

Zinc–air batteries proffer high energy density and cyclic stability at low costs but lack disadvantages like sluggish reactions at the cathode and the formation of by-products at the cathode. To resolve these issues, a new perovskite material, CaCu3Ti4O12 (CCTO), is proposed as an efficacious electrocatalyst for oxygen evolution/reduction reactions to develop zinc–air batteries (ZAB). Synthesis of this material adopted an effective oxalate route, which led to the purity in the electrocatalyst composition. The CCTO material is a proven potential candidate for energy applications because of its high dielectric permittivity (ε) and occupies an improved ORR-OER activity with better onset potential, current density, and stability. The Tafel value for CCTO was obtained out to be 80 mV dec−1. The CCTO perovskite was also evaluated for the zinc–air battery as an air electrode, corresponding to the high specific capacitance of 801 mAh g−1 with the greater cyclic efficiency and minimum variations in both charge/discharge processes. The highest power density (Pmax) measured was 127 mW cm−2. Also, the CCTO based paper battery shows an excellent performance achieving a specific capacity of 614 mAh g−1. The obtained results promise CCTO as a potential and cheap electrocatalyst for energy applications.

Nearly ~ 108 types of High entropy alloys (HEAs) can be developed from about 64 elements in the periodic table. A major challenge for materials scientists and metallurgists at this stage is to predict their crystal structure and, therefore, their mechanical properties to reduce experimental efforts, which are energy and time intensive. Through this paper, we show that it is possible to use machine learning (ML) in this arena for phase prediction to develop novel HEAs. We tested five robust algorithms namely, K-nearest neighbours (KNN), support vector machine (SVM), decision tree classifier (DTC), random forest classifier (RFC) and XGBoost (XGB) in their vanilla form (base models) on a large dataset screened specifically from experimental data concerning HEA fabrication using melting and casting manufacturing methods. This was necessary to avoid the discrepancy inherent with comparing HEAs obtained from different synthesis routes as it causes spurious effects while treating an imbalanced data—an erroneous practice we observed in the reported literature. We found that (i) RFC model predictions were more reliable in contrast to other models and (ii) the synthetic data augmentation is not a neat practice in materials science specially to develop HEAs, where it cannot assure phase information reliably. To substantiate our claim, we compared the vanilla RFC (V-RFC) model for original data (1200 datasets) with SMOTE-Tomek links augmented RFC (ST-RFC) model for the new datasets (1200 original + 192 generated = 1392 datasets). We found that although the ST-RFC model showed a higher average test accuracy of 92%, no significant breakthroughs were observed, when testing the number of correct and incorrect predictions using confusion matrix and ROC-AUC scores for individual phases. Based on our RFC model, we report the development of a new HEA (Ni25Cu18.75Fe25Co25Al6.25) exhibiting an FCC phase proving the robustness of our predictions.

During microbial electrosynthesis (MES) driven CO2 reduction, cathode plays a vital role by donating electrons to microbe. Here, we exploited the advantage of reduced graphene oxide (RGO) paper as novel cathode material to enhance electron transfer between the cathode and microbe, which in turn facilitated CO2 reduction. The acetate production rate of Sporomusa ovata-driven MES reactors was 168.5 ± 22.4 mmol m−2 d−1 with RGO paper cathodes poised at −690 mV versus standard hydrogen electrode. This rate was approximately 8 fold faster than for carbon paper electrodes of the same dimension. The current density with RGO paper cathodes of 2580 ± 540 mA m−2 was increased 7 fold compared to carbon paper cathodes. This also corresponded to a better cathodic current response on their cyclic voltammetric curves. The coulombic efficiency for the electrons conversion into acetate was 90.7 ± 9.3% with RGO paper cathodes and 83.8 ± 4.2% with carbon paper cathodes, respectively. Furthermore, more intensive cell attachment was observed on RGO paper electrodes than on carbon paper electrodes with confocal laser scanning microscopy and scanning electron microscopy. These results highlight the potential of RGO paper as a promising cathode for MES from CO2.

Dielectric-graphene-dielectric (DGD) structure has been widely used to construct optical devices at infrared region with features of small footprint and low-energy dissipation. The optical properties of graphene can be manipulated by changing its chemical potential by applying a biased voltage onto graphene. However, the excitation efficiency of surface wave on graphene by end-fire method is very low because of large wavevector mismatch between infrared light and surface wave. In this paper, a dielectric-semiconductor-dielectric (DSD) tapered waveguide with magnetic tunability for efficient excitation of surface waves on DGD at infrared region is proposed and analyzed. Efficient excitation of surface waves on DGD with various chemical potentials in graphene layer and incident frequencies can be attained by merely changing the external magnetic field applied onto the DSD tapered waveguide. The electromagnetic simulations verify the design of the proposed structure. More importantly, the constituent materials used in the proposed structure are available in nature. This work opens the door toward various applications in the field of using surface waves.

Cell cutting is a significant task in biology study, but the highly productive non-embedded cell cutting is still a big challenge for current techniques. This paper proposes a vision-based nano robotic system and then realizes automatic non-embedded cell cutting with this system. First, the nano robotic system is developed and integrated with a nanoknife inside an environmental scanning electron microscopy (ESEM). Then, the positions of the nanoknife and the single cell are recognized, and the distance between them is calculated dynamically based on image processing. To guarantee the positioning accuracy and the working efficiency, we propose a distance-regulated speed adapting strategy, in which the moving speed is adjusted intelligently based on the distance between the nanoknife and the target cell. The results indicate that the automatic non-embedded cutting is able to be achieved within 1–2 mins with low invasion benefiting from the high precise nanorobot system and the sharp edge of nanoknife. This research paves a way for the high-throughput cell cutting at cell’s natural condition, which is expected to make significant impact on the biology studies, especially for the in-situ analysis at cellular and subcellular scale, such as cell interaction investigation, neural signal transduction and low invasive cell surgery.

It is well-known that cell adhesion is important in many biological processes such as cell migration and proliferation. A better understanding of the cell adhesion process will shed insight into these cellular biological responses as well as cell adhesion-related diseases treatment. However, there is little research which has attempted to investigate the process of cell adhesion and its mechanism. Thus, this paper aims to study the time-dependent adhesion properties of single living chondrocytes using an advanced coupled experimental-numerical approach. Atomic Force Microscopy (AFM) tips will be used to apply lateral forces to detach chondrocytes that are seeded for three different periods. An advanced Finite Element Analysis (FEA) model combining porohyperelastic (PHE) constitutive model and cohesive zone formulation is developed to explore the mechanism of adhesion. The results revealed that the cells can resist normal traction better than tangential traction in the beginning of adhesion. This is when the cell adhesion molecules establish early attachment to the substrates. After that when the cells are spreading, stress fiber bundles generate tangential traction on the substrate to form strong adhesion. Both simulation and experimental results agree well with each other, providing a powerful tool to study the cellular adhesion process.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Recently, public displays such as liquid crystal displays (LCDs) are often used in urban green spaces, however, the display devices can spoil green landscape of urban green spaces because they look like artificial materials. We previously proposed a green landscape-friendly grass animation display method by controlling a pixel-by-pixel grass color dynamically. The grass color can be changed by moving a green grass length in yellow grass, and the grass animation display can play simple animations using grayscale images. In the previous research, the color scale was mapped to the green grass length subjectively, however, this method has not achieved displaying the grass colors corresponding to the color scale based on objective evaluations. Here, we introduce a dynamic grass color scale display technique based on a grass length. In this paper, we developed a grass color scale setting procedure to map the grass length to the color scale with five levels through image processing. Through the outdoor experiment of the grass color scale setting procedure, the color scale can correspond to the green grass length based on a viewpoint. After the experiments, we demonstrated a grass animation display to show the animations with the color scale using the experiment results., 17 pages

Rapid histopathological evaluation of fresh, unfixed human tissue using optical sectioning microscopy would have applications to intraoperative surgical margin assessment. Microscopy with ultraviolet surface excitation (MUSE) is a low-cost optical sectioning technique using ultraviolet illumination which limits fluorescence excitation to the specimen surface. In this paper, we characterize MUSE using high incident angle, water immersion illumination to improve sectioning. Propidium iodide is used as a nuclear stain and eosin yellow as a counterstain. Histologic features of specimens using MUSE, nonlinear microscopy (NLM) and conventional hematoxylin and eosin (H&E) histology were evaluated by pathologists to assess potential application in Mohs surgery for skin cancer and lumpectomy for breast cancer. MUSE images of basal cell carcinoma showed high correspondence with frozen section H&E histology, suggesting that MUSE may be applicable to Mohs surgery. However, correspondence in breast tissue between MUSE and paraffin embedded H&E histology was limited due to the thicker optical sectioning in MUSE, suggesting that further development is needed for breast surgical applications. We further demonstrate that the transverse image resolution of MUSE is limited by the optical sectioning thickness and use co-registered NLM to quantify the improvement in MUSE optical sectioning from high incident angle water immersion illumination.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Depressive disorder (DD) is a mental illness affecting more than 300 million people worldwide, whereas social stigma and subtle, variant symptoms impede diagnosis. Psychomotor retardation is a common component of DD with a negative impact on motor function, usually reflected on patients’ routine activities, including, nowadays, their interaction with mobile devices. Therefore, such interactions constitute an enticing source of information towards unsupervised screening for DD symptoms in daily life. In this vein, this paper proposes a machine learning-based method for discriminating between subjects with depressive tendency and healthy controls, as denoted by self-reported Patient Health Questionnaire-9 (PHQ-9) compound scores, based on typing patterns captured in-the-wild. The latter consisted of keystroke timing sequences and typing metadata, passively collected during natural typing on touchscreen smartphones by 11/14 subjects with/without depressive tendency. Statistical features were extracted and tested in univariate and multivariate classification pipelines to reach a decision on subjects’ status. The best-performing pipeline achieved an AUC = 0.89 (0.72–1.00; 95% Confidence Interval) and 0.82/0.86 sensitivity/specificity, with the outputted probabilities significantly correlating (>0.60) with the respective PHQ-9 scores. This work adds to the findings of previous research associating typing patterns with psycho-motor impairment and contributes to the development of an unobtrusive, high-frequency monitoring of depressive tendency in everyday living.

To understand the formation, evolution, and function of complex systems, it is crucial to understand the internal organization of their interaction networks. Partly due to the impossibility of visualizing large complex networks, resolving network structure remains a challenging problem. Here we overcome this difficulty by combining the visual pattern recognition ability of humans with the high processing speed of computers to develop an exploratory method for discovering groups of nodes characterized by common network properties, including but not limited to communities of densely connected nodes. Without any prior information about the nature of the groups, the method simultaneously identifies the number of groups, the group assignment, and the properties that define these groups. The results of applying our method to real networks suggest the possibility that most group structures lurk undiscovered in the fast-growing inventory of social, biological, and technological networks of scientific interest., Comment: Software implementing the method described in the paper is available at http://purl.oclc.org/net/find_structural_groups and is accompanied by a demo video available at http://www.nature.com/srep/2011/111109/srep00151/extref/srep00151-s2.mov

This paper analyzes the stability of a coexistence equilibrium point of a model for competition between two stage-structured populations. In this model, for each population, competition for resources may affect any one of the following population parameters: reproduction, juvenile survival, maturation rate, or adult survival. The results show that the competitive strength of a population is affected by (1) the ratio of the population parameter influenced by competition under no resource limitation (maximum compensatory capacity) over the same parameter under a resource limitation due to competition (equilibrium rate) and (2) the ratio of interspecific competition over intraspecific competition; this ratio was previously shown to depend on resource-use overlap. The former ratio, which we define as fitness, can be equalized by adjusting organisms' life history strategies, thereby promoting coexistence. We conclude that in addition to niche differentiation among populations, the life history strategies of organisms play an important role in coexistence.

We report the impact of anti-urothelial autoantibody (AUAb) on urinary bladder phenotype in BALB/c mice deficient of the FcγRIIb and PD-1. AUAb was present in serum samples from approximately half of the double-knockout (DKO) mice, as detected by immunofluorescence and immunoblots for urothelial proteins including uroplakin IIIa. The AUAb-positive DKO mice showed degeneration of urothelial plaque and umbrella cells, along with infiltration of inflammatory cells in the suburothelial layer. TNFα and IL-1β were upregulated in the bladder and the urine of AUAb-positive DKO mice. Voiding behavior of mice was analyzed by the Voided Stain on Paper method. 10-week-old and older AUAb-positive DKO mice voided significantly less urine per void than did wild type (WT) mice. Furthermore, administration of the AUAb-containing serum to WT mice significantly reduced their urine volume per void. In summary, this report presents a novel comprehensive mouse model of autoimmune cystitis.

In heterogeneous wireless networks, random packet loss and high latency lead to conventional TCP variants performing unsatisfactorily in the case of competing communications. Especially on high-latency wireless links, conventional TCP variants are unable to estimate congestion degrees accurately for fine-grained congestion control because of the effects of random packet loss and delay oscillations. This paper proposes a TCP variant at the sender side to identify congestion degrees, namely TCP-WBQ, which quickly responses to the real congestion and effectively shields against random packet loss and oscillations of latency time. The proposed algorithm of congestion control firstly constructs a backlog-queue model based on the dynamics of the congestion window, and deduces the two bounds of the model which delimit oscillations of the backlog queue for non-congestion and random packet loss respectively. TCP-WBQ detects congestion degrees more accurately and thus implements the corresponding schemes of adjusting the congestion window, maintaining a tradeoff between high throughputs and congestion avoidance. The comprehensive simulations show that TCP-WBQ works efficiently in bandwidth utilization with single and multiple bottleneck scenarios, and achieves high performance and competitive fairness in heterogeneous wireless networks.

With the presence of novel coronavirus disease at the end of 2019, several approaches were proposed to help physicians detect the disease, such as using deep learning to recognize lung involvement based on the pattern of pneumonia. These approaches rely on analyzing the CT images and exploring the COVID-19 pathologies in the lung. Most of the successful methods are based on the deep learning technique, which is state-of-the-art. Nevertheless, the big drawback of the deep approaches is their need for many samples, which is not always possible. This work proposes a combined deep architecture that benefits both employed architectures of DenseNet and CapsNet. To more generalize the deep model, we propose a regularization term with much fewer parameters. The network convergence significantly improved, especially when the number of training data is small. We also propose a novel Cost-sensitive loss function for imbalanced data that makes our model feasible for the condition with a limited number of positive data. Our novelties make our approach more intelligent and potent in real-world situations with imbalanced data, popular in hospitals. We analyzed our approach on two publicly available datasets, HUST and COVID-CT, with different protocols. In the first protocol of HUST, we followed the original paper setup and outperformed it. With the second protocol of HUST, we show our approach superiority concerning imbalanced data. Finally, with three different validations of the COVID-CT, we provide evaluations in the presence of a low number of data along with a comparison with state-of-the-art.

As the human population increases and production expands, energy demand and anthropogenic carbon emission rates have been growing rapidly, and the need to decrease carbon emission levels has drawn increasing attention. The link between energy production and consumption has required the large-scale transport of energy within energy transmission networks. Within this energy flow, there is a virtual circulation of carbon emissions. To understand this circulation and account for the relationship between energy consumption and carbon emissions, this paper introduces the concept of "carbon emission flow in networks" and establishes a method to calculate carbon emission flow in networks. Using an actual analysis of China's energy pattern, the authors discuss the significance of this new concept, not only as a feasible approach but also as an innovative theoretical perspective.

The community structure of complex networks reveals both their organization and hidden relationships among their constituents. Most community detection methods currently available are not deterministic, and their results typically depend on the specific random seeds, initial conditions and tie-break rules adopted for their execution. Consensus clustering is used in data analysis to generate stable results out of a set of partitions delivered by stochastic methods. Here we show that consensus clustering can be combined with any existing method in a self-consistent way, enhancing considerably both the stability and the accuracy of the resulting partitions. This framework is also particularly suitable to monitor the evolution of community structure in temporal networks. An application of consensus clustering to a large citation network of physics papers demonstrates its capability to keep track of the birth, death and diversification of topics., Comment: 11 pages, 12 figures. Published in Scientific Reports

Considering cell migration is essential for understanding physiological processes and diseases. The vertical migration of cells in three dimensions is vital, but most previous studies on cell migration have only focused on two-dimensional horizontal migration. In this paper, cell migration in the vertical direction was studied. Barriers with a height of 1, 5, 10, and 25 µm with grating and arrows in channels as guiding patterns were fabricated. The effects of barrier height and guiding patterns on the vertical migration of MC3T3 cells were explored. The study revealed that taller barriers hinder vertical migration of MC3T3 cells, whereas grating and arrows in channels promote it. The time-lapse and micrograph images showed that as the barrier height increased, the cell climbing angle along the barrier sidewall decreased, and the time taken to climb over the barrier increased. These results indicate that taller barriers increase the difficulty of vertical migration by MC3T3 cells. To promote the vertical migration of MC3T3 cells, 10 µm tall barriers with 18° and 40° sloped sidewalls were fabricated. For barriers with 18° sloped sidewalls, the probability for MC3T3 cells to climb up and down the 10 µm tall barriers was 40.6% and 20.3%, respectively; this is much higher than the migration probability over vertical barriers. This study shows topographic guidance on the vertical migration of MC3T3 cells and broadens the understanding of cell migration in the vertical direction.

Production of renewable commodity chemicals from bio-oil derived from fast pyrolysis of biomass has received considerable interests, but hindered by the presence of innumerable components in bio-oil. In present work, we proposed and experimentally demonstrated an innovative approach combining atmospheric distillation of bio-oil with co-pyrolysis for mass production of renewable chemicals from biomass, in which no waste was produced. It was estimated that 51.86 wt.% of distillate just containing dozens of separable organic components could be recovered using this approach. Ten protogenetic and three epigenetic compounds in distillate were qualitatively identified by gas chromatography/mass spectrometry and quantified by gas chromatography. Among them, the recovery efficiencies of acetic acid, propanoic acid, and furfural were all higher than 80 wt.%. Formation pathways of the distillate components in this process were explored. This work opens up a fascinating prospect for mass production of chemical feedstock from waste biomass.

Hierarchical alloy nanosheet dendrites (ANSDs) are highly favorable for superior catalytic performance and efficient utilization of catalyst because of the special characteristics of alloys, nanosheets, and dendritic nanostructures. In this paper, we demonstrate for the first time a facile and efficient electrodeposition approach for the controllable synthesis of Pd-Sn ANSDs with high surface area. These synthesized Pd-Sn ANSDs exhibit high electrocatalytic activity and superior long-term cycle stability toward ethanol oxidation in alkaline media. The enhanced electrocataytic activity of Pd-Sn ANSDs may be attributed to Pd-Sn alloys, nanosheet dendrite induced promotional effect, large number of active sites on dendrite surface, large surface area, and good electrical contact with the base electrode. Because of the simple implement and high flexibility, the proposed approach can be considered as a general and powerful strategy to synthesize the alloy electrocatalysts with high surface areas and open dendritic nanostructures.

EGFR is the best studied receptor tyrosine kinase. Yet, a comprehensive mechanistic understanding of EGFR signaling is lacking, despite very active research in the field. In this paper, we investigate the role of the juxtamembrane (JM) domain in EGFR signaling by replacing it with a (GGS)(10) unstructured sequence. We probe the effect of this replacement on (i) EGFR phosphorylation, (ii) EGFR dimerization and (iii) ligand (EGF) binding. We show that the replacement of EGFR JM domain with a (GGS)(10) unstructured linker completely abolishes the phosphorylation of all tyrosine residues, without measurable effects on receptor dimerization or ligand binding. Our results suggest that the JM domain does not stabilize the inactive EGFR dimer in the absence of ligand, and is likely critical only for the last step of EGFR activation, the ligand-induced transition from the inactive to active dimer.

Frequency dependent dielectric properties are important for understanding the structure and dynamics of biological materials. These properties can be used to study underlying biological processes such as changes in the concentration of biological materials, and the formation of chemical species. Computer simulations can be used to determine dielectric properties and atomic details inaccessible via experimental methods. In this paper, a unified theory utilizing molecular dynamics and density functional theory is presented that is able to determine the frequency dependent dielectric properties of biological materials in an aqueous solution from their molecular structure alone. The proposed method, which uses reaction field approximations, does not require a prior knowledge of the static dielectric constant of the material. The dielectric properties obtained from our method agree well with experimental values presented in the literature.

Quantum coherence is one of the primary non-classical features of quantum systems. While protocols such as the Leggett-Garg inequality (LGI) and quantum tomography can be used to test for the existence of quantum coherence and dynamics in a given system, unambiguously detecting inherent "quantumness" still faces serious obstacles in terms of experimental feasibility and efficiency, particularly in complex systems. Here we introduce two "quantum witnesses" to efficiently verify quantum coherence and dynamics in the time domain, without the expense and burden of non-invasive measurements or full tomographic processes. Using several physical examples, including quantum transport in solid-state nanostructures and in biological organisms, we show that these quantum witnesses are robust and have a much finer resolution in their detection window than the LGI has. These robust quantum indicators may assist in reducing the experimental overhead in unambiguously verifying quantum coherence in complex systems., Comment: 10 pages, 6 figures, journal paper

Modern information and communication technologies, especially the Internet, have diminished the role of spatial distances and territorial boundaries on the access and transmissibility of information. This has enabled scientists for closer collaboration and internationalization. Nevertheless, geography remains an important factor affecting the dynamics of science. Here we present a systematic analysis of citation and collaboration networks between cities and countries, by assigning papers to the geographic locations of their authors' affiliations. The citation flows as well as the collaboration strengths between cities decrease with the distance between them and follow gravity laws. In addition, the total research impact of a country grows linearly with the amount of national funding for research & development. However, the average impact reveals a peculiar threshold effect: the scientific output of a country may reach an impact larger than the world average only if the country invests more than about 100,000 USD per researcher annually., Published version. 9 pages, 5 figures + Appendix, The world citation and collaboration networks at both city and country level are available at http://becs.aalto.fi/~rajkp/datasets.html

Growth of vertically aligned carbon nanotube (CNT) forests is highly sensitive to the nature of the substrate. This constraint narrows the range of available materials to just a few oxide-based dielectrics and presents a major obstacle for applications. Using a suspended monolayer, we show here that graphene is an excellent conductive substrate for CNT forest growth. Furthermore, graphene is shown to intermediate growth on key substrates, such as Cu, Pt, and diamond, which had not previously been compatible with nanotube forest growth. We find that growth depends on the degree of crystallinity of graphene and is best on mono- or few-layer graphene. The synergistic effects of graphene are revealed by its endurance after CNT growth and low contact resistances between the nanotubes and Cu. Our results establish graphene as a unique interface that extends the class of substrate materials for CNT growth and opens up important new prospects for applications.

Acupuncture has been indispensable in Chinese medicine. However, its function still remains elusive. This paper studies the effect of acupuncture in ischemia stroke treatment using the Sprague Dawley rat animal model. We induced focal cerebral ischemia in rats using the middle cerebral artery occlusion (MCAO) procedure. For each rat in the real acupuncture group (n = 63), the sham acupoint treatment group (n = 62), and the blank control group (n = 30), we acquired 3-D fluorodeoxyglucose-microPET images at baseline, after MCAO, and after treatment, respectively. Then, we measured the changes of the injury-volume in the right hemisphere of these rats. The measurements showed that real acupuncture slightly reduced the injury-volume, sham acupoint treatment increased the injury-volume, and blank control had no obvious effect in reducing the injury-volume. Statistical tests also confirmed that acupuncture was more effective than random stimulus in improving the metabolic recovery after stroke.

The green and red lights of a traffic signal can be viewed as the up and down states of an Ising spin. Moreover, traffic signals in a city interact with each other, if they are controlled in a decentralised way. In this paper, a simple model of such interacting signals on a finite-size two-dimensional lattice is shown to have Ising-like dynamics that undergoes a ferromagnetic phase transition. Probabilistic behaviour of the model is realised by chaotic billiard dynamics that arises from coupled non-chaotic elements. This purely deterministic model is expected to serve as a starting point for considering statistical mechanics of traffic signals.

Invisible cloak has long captivated the popular conjecture and attracted intensive research in various communities of wave dynamics, e.g., optics, electromagnetics, acoustics, etc. However, their inhomogeneous and extreme parameters imposed by transformation-optic method will usually require challenging realization with metamaterials, resulting in narrow bandwidth, loss, polarization-dependence, etc. In this paper, we demonstrate that thermodynamic cloak can be achieved with homogeneous and finite conductivity only employing naturally available materials. It is demonstrated that the thermal localization inside the coating layer can be tuned and controlled robustly by anisotropy, which enables an incomplete cloak to function perfectly. Practical realization of such homogeneous thermal cloak has been suggested by using two naturally occurring conductive materials, which provides an unprecedentedly plausible way to flexibly realize thermal cloak and manipulate heat flow with phonons.

This paper applies topological methods to study complex high dimensional data sets by extracting shapes (patterns) and obtaining insights about them. Our method combines the best features of existing standard methodologies such as principal component and cluster analyses to provide a geometric representation of complex data sets. Through this hybrid method, we often find subgroups in data sets that traditional methodologies fail to find. Our method also permits the analysis of individual data sets as well as the analysis of relationships between related data sets. We illustrate the use of our method by applying it to three very different kinds of data, namely gene expression from breast tumors, voting data from the United States House of Representatives and player performance data from the NBA, in each case finding stratifications of the data which are more refined than those produced by standard methods. Publisher PDF

The exploration of novel functional carbon polymorphs is an enduring topic of scientific investigations. In this paper, we present simulations demonstrating metastable carbon phases as the result of pressure induced carbon nanotube polymerization. The configuration, bonding, electronic, and mechanical characteristics of carbon polymers strongly depend on the imposed hydrostatic/non-hydrostatic pressure, as well as on the geometry of the raw carbon nanotubes including diameter, chirality, stacking manner, and wall number. Especially, transition processes under hydrostatic/non-hydrostatic pressure are investigated, revealing unexpectedly low transition barriers and demonstrating sp(2)→sp(3) bonding changes as well as peculiar oscillations of electronic property (e.g., semiconducting→metallic→semiconducting transitions). These polymerized nanotubes show versatile and superior physical properties, such as superhardness, high tensile strength and ductility, and tunable electronic properties (semiconducting or metallic).

Scientific Reports 2, Article number: 849 10.1038/srep00849 (2012); Published: November142012; Updated: March082013 The authors regret that previous work reporting the production of aerogels from nanotubes was not properly acknowledged and cited in our paper. These references appear below1,2,3. Reference 1 was referenced in the published paper (reference 29), but was only cited to compare the aerogel properties instead of acknowledging what has already been studied.

A pulsed laser engineering approach is developed to prepare novel functional graphene paper with graphitic nanospheres homogeneously decorated on the surface and the superior performance of engineered paper is revealed in matrix-free mass spectrometry (MS) detection and imaging. We demonstrate that the stability of graphene paper under intense irradiation can be dramatically increased through a designed laser engineering process by forming densely packed graphitic nanospheres on the paper surface. Moreover, the surface hydrophobicity is enhanced and electric conductivity is improved. The engineered graphene paper can image the invisible micro-patterns of trace amount molecules and increases the detection limit towards diverse molecules by over two orders of magnitude compared to the pristine graphene paper and commercial products in MS analysis.

Since crystal phase dominantly affects the properties of nanocrystals, phase control is important for the applications. To demonstrate the size dependence in anatase-rutile phase transition of titania, we used quantum-size titania prepared from the restricted number of titanium ions within dendrimer templates for size precision purposes and optical wave guide spectroscopy for the detection. Contrary to some theoretical calculations, the observed irreversibility in the transition indicates the metastablity of anatase; thermodynamics cannot explain the formation of metastable states. Therefore, we take into account the kinetic control polymerization of TiO6 octahedral units to explain how the crystal phase of the crystal-nucleus-size titania is dependent on which coordination sites, cis- or trans-, react in the TiO6 octahedra, suggesting possibilities for the synthetic phase control of nanocrystals. In short, the dendrimer templates give access to crystal nucleation chemistry. The paper will also contribute to the creation of artificial metastable nanostructures with atomic-level precision.

The relation between the handedness of helical twist and the S-shaped cross section of the lamellar crystals is discussed for linear polyethylene. The lamellar crystals are found to rotate so that the convex surfaces of “S” push aside the melt when they advance in the growth direction. This relation, which has not been examined sufficiently so far, is found to be opposite from what was proposed earlier. A model to explain these observations is presented. This paper also demonstrates that the twist handedness can be clarified based on the stack order of crystalline lamellae without any treatment such as etching or extraction to isolate the lamellar crystals.

The coating of thin films is applied in numerous fields and many methods are employed for the deposition of these films. Some coating techniques may deposit films at high speed; for example, ordinary printing paper is coated with micrometre-thick layers of clay at a speed of tens of meters per second. However, to coat nanometre thin films at high speed, vacuum techniques are typically required, which increases the complexity of the process. Here, we report a simple wet chemical method for the high-speed coating of films with thicknesses at the nanometre level. This soap-film coating technique is based on forcing a substrate through a soap film that contains nanomaterials. Molecules and nanomaterials can be deposited at a thickness ranging from less than a monolayer to several layers at speeds up to meters per second. We believe that the soap-film coating method is potentially important for industrial-scale nanotechnology. We acknowledge support from the Sundsvall Community, Länstyrelsen Västernorrland, KK foundation, and EU Regional funds.

The paper reports a new method for three-dimensional observation of the location of focused particle streams along both the depth and width of the channel cross-section in spiral inertial microfluidic systems. The results confirm that particles are focused near the top and bottom walls of the microchannel cross-section, revealing clear insights on the focusing and separation mechanism. Based on this detailed understanding of the force balance, we introduce a novel spiral microchannel with a trapezoidal cross-section that generates stronger Dean vortices at the outer half of the channel. Experiments show that particles focusing in such device are sensitive to particle size and flow rate, and exhibits a sharp transition from the inner half to the outer half equilibrium positions at a size-dependent critical flow rate. As particle equilibration positions are well segregated based on different focusing mechanisms, a higher separation resolution is achieved over conventional spiral microchannels with rectangular cross-section., United States. Defense Advanced Research Projects Agency. Dialysis-Like Therapeutics (SSC Pacific Grant N66001-11-1-4182)

Vanadium dioxide (VO2) is a Mott phase transition compound that can be applied as a thermochromic smart material for energy saving and comfort, and titanium dioxide (TiO2) is a well-known photocatalyst for self-cleaning coatings. In this paper, we report a VO2@TiO2 core-shell structure, in which the VO2 nanorod core exhibits a remarkable modulation ability for solar infrared light, and the TiO2 anatase shell exhibits significant photocatalytic degradation of organic dye. In addition, the TiO2 overcoating not only increased the luminous transmittance of VO2 based on an antireflection effect, but also modified the intrinsic colour of VO2 films from yellow to light blue. The TiO2 also enhanced the chemical stability of VO2 against oxidation. This is the first report of such a single nanoparticle structure with both thermochromic and photocatalytic properties that offer significant potential for creating a multifunctional smart coating.

The chaotic Boltzmann machine proposed in this paper is a chaotic pseudo-billiard system that works as a Boltzmann machine. Chaotic Boltzmann machines are shown numerically to have computing abilities comparable to conventional (stochastic) Boltzmann machines. Since no randomness is required, efficient hardware implementation is expected. Moreover, the ferromagnetic phase transition of the Ising model is shown to be characterised by the largest Lyapunov exponent of the proposed system. In general, a method to relate probabilistic models to nonlinear dynamics by derandomising Gibbs sampling is presented.

Graphene has been predicted to play a role in post-silicon electronics due to the extraordinary carrier mobility. Chemical vapor deposition of graphene on transition metals has been considered as a major step towards commercial realization of graphene. However, fabrication based on transition metals involves an inevitable transfer step which can be as complicated as the deposition of graphene itself. By ambient-pressure chemical vapor deposition, we demonstrate large-scale and uniform depositon of high-quality graphene directly on a Ge substrate which is wafer scale and has been considered to replace conventional Si for the next generation of high-performance metal-oxide-semiconductor field-effect transistors (MOSFETs). The immiscible Ge-C system under equilibrium conditions dictates graphene depositon on Ge via a self-limiting and surface-mediated process rather than a precipitation process as observed from other metals with high carbon solubility. Our technique is compatible with modern microelectronics technology thus allowing integration with high-volume production of complementary metal-oxide-semiconductors (CMOS).