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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.

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.

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.

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.

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.

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.

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.

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

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.

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

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.

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.

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.

Ground-state cooling and pure state preparation of a small object that is embedded in a thermal environment is an important challenge and a highly desirable quantum technology. This paper proves, with two different methods, that a fundamental constraint on the cooling dynamic implies that it is impossible to cool, via a unitary system-bath quantum evolution, a system that is embedded in a thermal environment down to its ground state, if the initial state is a factorized product of system and bath states. The latter is a crucial but artificial assumption included in numerous tools that treat system-bath dynamics, such as master equation approaches and Kraus operator based methods. Adopting these approaches to address ground state and even approximate ground state cooling dynamics should therefore be done with caution, considering the fundamental theorem exposed in this work.

Developing minimally invasive methodologies for imaging of internal organs is an emerging field in the biomedical examination research. This paper introduces a new multi-functional microendoscope device capable of imaging of internal organs with a minimal invasive intervention. In addition, the developed microendoscope can also be employed as a monitoring device for measuring local hemoglobin concentration in blood stream when administrated into a blood artery. The microendoscope device has a total external diameter of only 200 μm and can provide high imaging resolution capability of more than 5,000 pixels. The device can detect features with a spatial resolution of less than 1 μm. The microendoscope has been tested both in-vitro as well as in-vivo in rats presenting a promising and powerful tool as a high resolution and minimally invasive imaging facility suitable for previously unreachable clinical modalities.

A new chemical dual-functional reducing agent, thiophene, was used to produce high-quality reduced graphene oxide (rGO) as a result of a chemical reduction of graphene oxide (GO) and the healing of rGO. Thiophene reduced GO by donation of electrons with acceptance of oxygen while it was converted into an intermediate oxidised polymerised thiophene that was eventually transformed into polyhydrocarbon by loss of sulphur atoms. Surprisingly, the polyhydrocarbon template helped to produce good-quality rGOC (chemically reduced) and high-quality rGOCT after thermal treatment. The resulting rGOCT nanosheets did not contain any nitrogen or sulphur impurities, were highly deoxygenated and showed a healing effect. Thus the electrical properties of the as-prepared rGOCT were superior to those of conventional hydrazine-produced rGO that require harsh reaction conditions. Our novel dual reduction and healing method with thiophene could potentially save energy and facilitate the commercial mass production of high-quality graphene.

The application of elaborately designed magnetic catalysts has long been limited to ease their separation from the products only. In this paper, we for the first time employed a magnetic sulphonated poly(styrene-divinylbenzene) resin catalyst on a magnetically stabilized-bed (MSB) reactor to enhance the etherification of fluidized catalytic cracking (FCC) light gasoline, one of the most important reactions in petroleum refining industry. We demonstrated that the catalytic performance of the magnetic acid resin catalyst on the magnetic reactor is substantially enhanced as compared to its performance on a conventional fixed-bed reactor under otherwise identical operation conditions. The magnetic catalyst has the potential to be loaded and unloaded continuously on the magnetic reactor, which will greatly simplify the current complex industrial etherification processes.

Conventional leaching (extraction) methods for gold recovery from electronic waste involve the use of strong acids and pose considerable threat to the environment. The alternative use of bioleaching microbes for gold recovery is non-pollutive and relies on the secretion of a lixiviant or (bio)chemical such as cyanide for extraction of gold from electronic waste. However, widespread industrial use of bioleaching microbes has been constrained by the limited cyanogenic capabilities of lixiviant-producing microorganisms such as Chromobacterium violaceum. Here we show the construction of a metabolically-engineered strain of Chromobacterium violaceum that produces more (70%) cyanide lixiviant and recovers more than twice as much gold from electronic waste compared to wild-type bacteria. Comparative proteome analyses suggested the possibility of further enhancement in cyanogenesis through subsequent metabolic engineering. Our results demonstrated the utility of lixiviant metabolic engineering in the construction of enhanced bioleaching microbes for the bioleaching of precious metals from electronic waste.

Graphene has a unique atom-thick two-dimensional structure and excellent properties, making it attractive for a variety of electrochemical applications, including electrosynthesis, electrochemical sensors or electrocatalysis, and energy conversion and storage. However, the electrochemistry of single-layer graphene has not yet been well understood, possibly due to the technical difficulties in handling individual graphene sheet. Here, we report the electrochemical behavior at single-layer graphene-based electrodes, comparing the basal plane of graphene to its edge. The graphene edge showed 4 orders of magnitude higher specific capacitance, much faster electron transfer rate and stronger electrocatalytic activity than those of graphene basal plane. A convergent diffusion effect was observed at the sub-nanometer thick graphene edge-electrode to accelerate the electrochemical reactions. Coupling with the high conductivity of a high-quality graphene basal plane, graphene edge is an ideal electrode for electrocatalysis and for the storage of capacitive charges.

The rolling up of a graphene sheet into a tube is a standard visualization tool for illustrating carbon nanotube (CNT) formation. However, the actual processes of rolling up graphene sheets into CNTs in laboratory syntheses have never been demonstrated. Here we report conformal growth of graphene by carbon self-assembly on single-wall and multi-wall CNTs using chemical vapor deposition (CVD) of methane without the presence of metal catalysts. The new graphene layers roll up into seamless coaxial cylinders encapsulating the existing CNTs, but their adhesion to the primary CNTs is weak due to the existence of lattice misorientation. Our study shows that graphene nucleation and growth by self-assembly of carbon on the inactive carbon basal plane of CNTs occurs by a new mechanism that is markedly different from epitaxial growth on metal surfaces, opening up the possibility of graphene growth on many other non-metal substrates by simple methane CVD.

Paper, a man-made material that has been used for hundreds of years, is a network of natural cellulosic fibres. To a large extent, it is the strength of bonding between these individual fibres that controls the strength of paper. Using atomic force microscopy, we explore here the mechanical properties of individual fibre-fibre bonds on the nanometre scale. A single fibre-fibre bond is loaded with a calibrated cantilever statically and dynamically until the bond breaks. Besides the calculation of the total energy input, time dependent processes such as creep and relaxation are studied. Through the nanometre scale investigation of the formerly bonded area, we show that fibrils or fibril bundles play a crucial role in fibre-fibre bonding because they act as bridging elements. With this knowledge, new fabrication routes can be deduced to increase the strength of an ancient product that is in fact an overlooked high-tech material.

The authors previously considered a method solving optimization problems by using a system of interconnected network of two component Bose-Einstein condensates (Byrnes, Yan, Yamamoto New J. Phys. 13, 113025 (2011)). The use of bosonic particles was found to give a reduced time proportional to the number of bosons N for solving Ising model Hamiltonians by taking advantage of enhanced bosonic cooling rates. In this paper we consider the same system in terms of neural networks. We find that up to the accelerated cooling of the bosons the previously proposed system is equivalent to a stochastic continuous Hopfield network. This makes it clear that the BEC network is a physical realization of a simulated annealing algorithm, with an additional speedup due to bosonic enhancement. We discuss the BEC network in terms of typical neural network tasks such as learning and pattern recognition and find that the latter process may be accelerated by a factor of N., 3 figures

For centuries mankind has stored its knowledge on paper, a remarkable biomaterial made of natural cellulose fibers. However, spontaneous cellulose degradation phenomena weaken and discolorate paper over time. The detailed knowledge of products arising from cellulose degradation is essential in understanding deterioration pathways and in improving durability of cultural heritage. In this study, for the first time, products of cellulose degradation were individually detected in solid paper samples by means of an extremely powerful proton HR-MAS NMR set-up, in combination to a wise use of both ancient and, as reference, artificially aged paper samples. Carboxylic acids, in addition to more complex dicarboxylic and hydroxy-carboxylic acids, were found in all samples studied. Since these products can catalyze further degradation, their knowledge is fundamental to improve conservation strategies of historical documents. Furthermore, the identification of compounds used in ancient production techniques, also suggests for artifacts dating, authentication and provenance.

The potential energy profile of a binary switch is a symmetric double well. Switching between the wells without energy dissipation requires time-modulating the potential barrier separating them and tilting the profile towards the desired well at the precise juncture when the barrier disappears. This demands perfect timing synchronization and is therefore fault-intolerant, even in the absence of noise. A fault-tolerant strategy that requires no time modulation of the barrier (and hence no timing synchronization) switches by tilting the profile by an amount at least equal to the barrier height and dissipates at least that amount of energy. Here, we present a third strategy that requires a time modulated barrier but no timing synchronization. It is therefore fault-tolerant in the absence of thermal noise and yet it dissipates arbitrarily small energy since an arbitrarily small tilt is required for slow and adiabatic switching. This case is exemplified with stress induced switching of a shape-anisotropic single-domain nanomagnet dipole coupled to a neighbor. We also show by examining various energy profiles and the corresponding probability distributions that when thermal noise is present, the minimum energy dissipated to switch in this scheme is 2kTln(1/p) [p = switching error probability]., There is supplementary material accompanying this paper