SnO2 decorated graphene nanocomposite anode materials prepared via an up-scalable wet-mechanochemical process for sodium ion batteries

A facile and up-scalable wet-mechanochemical process is designed for fabricating ultra-fine SnO2 nanoparticles anchored on graphene networks for use as anode materials for sodium ion batteries. A hierarchical structure of the SnO2@graphene composite is obtained from the process. The resultant rechargeable SIBs achieved high rate capability and good cycling stability.

On robust face recognition via sparse coding: The good, the bad and the ugly

In the field of face recognition, sparse representation (SR) has received considerable attention during the past few years, with a focus on holistic descriptors in closed-set identification applications. The underlying assumption in such SR-based methods is that each class in the gallery has sufficient samples and the query lies on the subspace spanned by the gallery of the same class. Unfortunately, such an assumption is easily violated in the face verification scenario, where the task is to determine if two faces (where one or both have not been seen before) belong to the same person. In this study, the authors propose an alternative approach to SR-based face verification, where SR encoding is performed on local image patches rather than the entire face. The obtained sparse signals are pooled via averaging to form multiple region descriptors, which then form an overall face descriptor. Owing to the deliberate loss of spatial relations within each region (caused by averaging), the resulting descriptor is robust to misalignment and various image deformations. Within the proposed framework, they evaluate several SR encoding techniques: l1-minimisation, Sparse Autoencoder Neural Network (SANN) and an implicit probabilistic technique based on Gaussian mixture models. Thorough experiments on AR, FERET, exYaleB, BANCA and ChokePoint datasets show that the local SR approach obtains considerably better and more robust performance than several previous state-of-the-art holistic SR methods, on both the traditional closed-set identification task and the more applicable face verification task. The experiments also show that l1-minimisation-based encoding has a considerably higher computational cost when compared with SANN-based and probabilistic encoding, but leads to higher recognition rates.

Multipurpose nanoporous alumina-carbon nanowall bi-dimensional nano-hybrid platform via catalyzed and catalyst-free plasma CVD

Simple, rapid, plasma-assisted synthesis of large-area arrays of vertically-aligned carbon nanowalls on highly-porous, transparent bare and gold-coated alumina membranes with the two pore sizes is reported. It is demonstrated that the complex patterns of vertically aligned nanowalls can nucleate and form different morphologies in the low-temperature plasmas. The process is stable, and the twofold change in the gas flow (10 and 20 sccm) does not noticeably influence the morphology of the nanowall pattern. Application of a thin (5 nm) gold layer to nanoporous membrane prior to the nanowall growth allows controlling the network morphology.

Semi-supervised document clustering via loci

Document clustering is one of the prominent methods for mining important information from the vast amount of data available on the web. However, document clustering generally suffers from the curse of dimensionality. Providentially in high dimensional space, data points tend to be more concentrated in some areas of clusters. We take advantage of this phenomenon by introducing a novel concept of dynamic cluster representation named as loci. Clusters’ loci are efficiently calculated using documents’ ranking scores generated from a search engine. We propose a fast loci-based semi-supervised document clustering algorithm that uses clusters’ loci instead of conventional centroids for assigning documents to clusters. Empirical analysis on real-world datasets shows that the proposed method produces cluster solutions with promising quality and is substantially faster than several benchmarked centroid-based semi-supervised document clustering methods.

Site-controlled growth of Ge nanostructures on Si(100) via pulsed laser deposition nanostenciling

The authors combine nanostenciling and pulsed laser deposition to patterngermanium(Ge)nanostructures into desired architectures. They have analyzed the evolution of the Ge morphology with coverage. Following the formation of a wetting layer within each area defined by the stencil’s apertures, Gegrowth becomes three dimensional and the size and number of Ge nanocrystals evolve with coverage. Micro-Raman spectroscopy shows that the deposits are crystalline and epitaxial. This approach is promising for the parallel patterning of semiconductor nanostructures for optoelectronic applications.

Modified Stranski–Krastanov growth in Ge/Si heterostructures via nanostenciled pulsed laser deposition

The combination of nanostenciling with pulsed laser deposition (PLD) provides a flexible, fast approach for patterning the growth of Ge on Si. Within each stencilled site, the morphological evolution of the Ge structures with deposition follows a modified Stranski–Krastanov (SK) growth mode. By systematically varying the PLD parameters (laser repetition rate and number of pulses) on two different substrate orientations (111 and 100), we have observed corresponding changes in growth morphology, strain and elemental composition using scanning electron microscopy, atomic force microscopy and μ-Raman spectroscopy. The growth behaviour is well predicted within a classical SK scheme, although the Si(100) growth exhibits significant relaxation and ripening with increasing coverage. Other novel aspects of the growth include the increased thickness of the wetting layer and the kinetic control of Si/Ge intermixing via the PLD repetition rate.

Substrate, molecular structure, and solvent effects in 2D self-assembly via hydrogen and halogen bonding

Recently, halogen···halogen interactions have been demonstrated to stabilize two-dimensional supramolecular assemblies at the liquid–solid interface. Here we study the effect of changing the halogen, and report on the 2D supramolecular structures obtained by the adsorption of 2,4,6-tris(4-bromophenyl)-1,3,5-triazine (TBPT) and 2,4,6-tris(4-iodophenyl)-1,3,5-triazine (TIPT) on both highly oriented pyrolytic graphite and the (111) facet of a gold single crystal. These molecular systems were investigated by combining room-temperature scanning tunneling microscopy in ambient conditions with density functional theory, and are compared to results reported in the literature for the similar molecules 1,3,5-tri(4-bromophenyl)benzene (TBPB) and 1,3,5-tri(4-iodophenyl)benzene (TIPB). We find that the substrate exerts a much stronger effect than the nature of the halogen atoms in the molecular building blocks. Our results indicate that the triazine core, which renders TBPT and TIPT stiff and planar, leads to stronger adsorption energies and hence structures that are different from those found for TBPB and TIPB. On the reconstructed Au(111) surface we find that the TBPT network is sensitive to the fcc- and hcp-stacked regions, indicating a significant substrate effect. This makes TBPT the first molecule reported to form a continuous monolayer at room temperature in which molecular packing is altered on the differently reconstructed regions of the Au(111) surface. Solvent-dependent polymorphs with solvent coadsorption were observed for TBPT on HOPG. This is the first example of a multicomponent self-assembled molecular networks involving the rare cyclic, hydrogen-bonded hexamer of carboxylic groups, R66(24) synthon.

Criteria for working-correlation-structure selection in GEE: Assessment via simulation

Efficiency of analysis using generalized estimation equations is enhanced when intracluster correlation structure is accurately modeled. We compare two existing criteria (a quasi-likelihood information criterion, and the Rotnitzky-Jewell criterion) to identify the true correlation structure via simulations with Gaussian or binomial response, covariates varying at cluster or observation level, and exchangeable or AR(l) intracluster correlation structure. Rotnitzky and Jewell's approach performs better when the true intracluster correlation structure is exchangeable, while the quasi-likelihood criteria performs better for an AR(l) structure.

Diet-induced hypercholesterolemia promotes androgen-independent prostate cancer metastasis via IQGAP1 and caveolin-1

Obesity and metabolic syndrome are associated with several cancers, however, the molecular mechanisms remain to be fully elucidated. Recent studies suggest that hypercholesterolemia increases intratumoral androgen signaling in prostate cancer, but it is unclear whether androgenindependent mechanisms also exist. Since hypercholesterolemia is associated with advanced, castrate-resistant prostate cancer, in this study, we aimed to determine whether and how hypercholesterolemia affects prostate cancer progression in the absence of androgen signaling. We demonstrate that diet-induced hypercholesterolemia promotes orthotopic xenograft PC-3 cell metastasis, concomitant with elevated expression of caveolin-1 and IQGAP1 in xenograft tumor tissues. In vitro cholesterol treatment of PC-3 cells stimulated migration and increased IQGAP1 and caveolin-1 protein level and localization to a detergent-resistant fraction. Down-regulation of caveolin-1 or IQGAP1 in PC-3 cells reduced migration and invasion in vitro, and hypercholesterolemia-induced metastasis in vivo. Double knock-down of caveolin-1 and IQGAP1 showed no additive effect, suggesting that caveolin-1 and IQGAP1 act via the same pathway. Taken together, our data show that hypercholesterolemia promotes prostate cancer metastasis independent of the androgen pathway, in part by increasing IQGAP1 and caveolin-1. These results have broader implications for managing metastasis of cancers in general as IQGAP1 and hypercholesterolemia are implicated in the progression of several cancers.

Minimizing overprocessing waste in business processes via predictive activity ordering

Overprocessing waste occurs in a business process when effort is spent in a way that does not add value to the customer nor to the business. Previous studies have identied a recurrent overprocessing pattern in business processes with so-called "knockout checks", meaning activities that classify a case into "accepted" or "rejected", such that if the case is accepted it proceeds forward, while if rejected, it is cancelled and all work performed in the case is considered unnecessary. Thus, when a knockout check rejects a case, the effort spent in other (previous) checks becomes overprocessing waste. Traditional process redesign methods propose to order knockout checks according to their mean effort and rejection rate. This paper presents a more fine-grained approach where knockout checks are ordered at runtime based on predictive machine learning models. Experiments on two real-life processes show that this predictive approach outperforms traditional methods while incurring minimal runtime overhead.

Delineating environmental envelopes to improve mapping of species distributions, via a hurdle model with CART &/or MaxEnT

Species distribution modelling (SDM) typically analyses species’ presence together with some form of absence information. Ideally absences comprise observations or are inferred from comprehensive sampling. When such information is not available, then pseudo-absences are often generated from the background locations within the study region of interest containing the presences, or else absence is implied through the comparison of presences to the whole study region, e.g. as is the case in Maximum Entropy (MaxEnt) or Poisson point process modelling. However, the choice of which absence information to include can be both challenging and highly influential on SDM predictions (e.g. Oksanen and Minchin, 2002). In practice, the use of pseudo- or implied absences often leads to an imbalance where absences far outnumber presences. This leaves analysis highly susceptible to ‘naughty-noughts’: absences that occur beyond the envelope of the species, which can exert strong influence on the model and its predictions (Austin and Meyers, 1996). Also known as ‘excess zeros’, naughty noughts can be estimated via an overall proportion in simple hurdle or mixture models (Martin et al., 2005). However, absences, especially those that occur beyond the species envelope, can often be more diverse than presences. Here we consider an extension to excess zero models. The two-staged approach first exploits the compartmentalisation provided by classification trees (CTs) (as in O’Leary, 2008) to identify multiple sources of naughty noughts and simultaneously delineate several species envelopes. Then SDMs can be fit separately within each envelope, and for this stage, we examine both CTs (as in Falk et al., 2014) and the popular MaxEnt (Elith et al., 2006). We introduce a wider range of model performance measures to improve treatment of naughty noughts in SDM. We retain an overall measure of model performance, the area under the curve (AUC) of the Receiver-Operating Curve (ROC), but focus on its constituent measures of false negative rate (FNR) and false positive rate (FPR), and how these relate to the threshold in the predicted probability of presence that delimits predicted presence from absence. We also propose error rates more relevant to users of predictions: false omission rate (FOR), the chance that a predicted absence corresponds to (and hence wastes) an observed presence, and the false discovery rate (FDR), reflecting those predicted (or potential) presences that correspond to absence. A high FDR may be desirable since it could help target future search efforts, whereas zero or low FOR is desirable since it indicates none of the (often valuable) presences have been ignored in the SDM. For illustration, we chose Bradypus variegatus, a species that has previously been published as an exemplar species for MaxEnt, proposed by Phillips et al. (2006). We used CTs to increasingly refine the species envelope, starting with the whole study region (E0), eliminating more and more potential naughty noughts (E1–E3). When combined with an SDM fit within the species envelope, the best CT SDM had similar AUC and FPR to the best MaxEnt SDM, but otherwise performed better. The FNR and FOR were greatly reduced, suggesting that CTs handle absences better. Interestingly, MaxEnt predictions showed low discriminatory performance, with the most common predicted probability of presence being in the same range (0.00-0.20) for both true absences and presences. In summary, this example shows that SDMs can be improved by introducing an initial hurdle to identify naughty noughts and partition the envelope before applying SDMs. This improvement was barely detectable via AUC and FPR yet visible in FOR, FNR, and the comparison of predicted probability of presence distribution for pres/absence.

Using rowers’ perceptions of on-water stroke success to evaluate sculling catch efficiency variables via a boat instrumentation system

Aim An effective catch in sculling is a critical determinant of boat velocity. This study used rowers’ performance-based judgments to compare three measures of catch slip efficiency. Two questions were addressed: (1) would rower-judged Yes strokes be faster than No strokes? and (2) which method of quantifying catch slip best reflected these judgements? Methods Eight single scullers performed two 10-min blocks of sub maximal on-water rowing at 20 strokes per minute. Every 30 s, rowers reported either Yes or No about the quality of their stroke at the catch. Results It was found that Yes strokes identified by rowers had, on average, a moderate effect advantage over No strokes with a standardised effect size of 0.43. In addition, a quicker time to positive acceleration best reflected the change in performance; where the standardised mean difference score of 0.57 for time to positive acceleration was larger than the scores of 0.47 for time to PowerLine force, and 0.35 for time to 30% peak pin force catch slip measures. For all eight rowers, Yes strokes corresponded to time to positive acceleration occurring earlier than No strokes. Conclusion Rower judgements about successful strokes was linked to achieving a quicker time to positive acceleration, and may be of the most value in achieving a higher average boat velocity.

Calculations of helium separation via uniform pores of stanene-based membranes

The development of low energy cost membranes to separate He from noble gas mixtures is highly desired. In this work, we studied He purification using recently experimentally realized, two-dimensional stanene (2D Sn) and decorated 2D Sn (SnH and SnF) honeycomb lattices by density functional theory calculations. To increase the permeability of noble gases through pristine 2D Sn at room temperature (298 K), two practical strategies (i.e., the application of strain and functionalization) are proposed. With their high concentration of large pores, 2D Sn-based membrane materials demonstrate excellent helium purification and can serve as a superior membrane over traditionally used, porous materials. In addition, the separation performance of these 2D Sn-based membrane materials can be significantly tuned by application of strain to optimize the He purification properties by taking both diffusion and selectivity into account. Our results are the first calculations of He separation in a defect-free honeycomb lattice, highlighting new interesting materials for helium separation for future experimental validation.

Optical and chemical properties of polyterpenol thin films deposited via plasma-enhanced chemical vapor deposition

The development of novel organic polymer thin films is essential for the advancement of many emerging fields including organic electronics and biomedical coatings. In this study, the effect of synthesis conditions, namely radio frequency (rf) deposition power, on the material properties of polyterpenol thin films derived from nonsynthetic environmentally friendly monomer was investigated. At lower deposition powers, the polyterpenol films preserved more of the original monomer constituents, such as hydroxy functional groups; however, they were also softer and more hydrophilic compared to polymers fabricated at higher power. Enhanced monomer fragmentation and consequent reduction in the presence of the polar groups in the structure of the high-power samples reduced their optical band gap value from 2.95 eV for 10 W to 2.64 eV for 100 W. Regardless of deposition power, all samples were found to be optically transparent with smooth, defect-free, and homogenous surfaces.

Assessing infant exposure to persistent organic pollutants via dietary intake in Australia

Persistent organic pollutants (POPs) including polybrominated diphenyl ethers (PBDEs); organochlorine pesticides (OCPs); and polychlorinated biphenyls (PCBs) persist in the environment, bioaccumulate, and pose a risk of causing adverse human health effects. Typically, exposure assessments undertaken by modeling existing intake data underestimate the concentrations of these chemicals in infants. This study aimed to determine concentrations of POPs in infant foods, assess exposure via dietary intake and compare this to historical exposure. Fruit purees, meat and vegetables, dairy desserts, cereals and jelly foods (n = 33) purchased in 2013 in Brisbane, Australia were analyzed. For OCPs and PCBs, concentrations ranged up to 95 pg/g fw and for PBDEs up to 32 pg/g fw with most analytes below the limit of detection. Daily intake is dependent on type and quantity of foods consumed. Consumption of a 140 g meal would result in intake ranging from 0 to 4.2 ng/day, 4.4 ng/day and 13.3 ng/day, for OCPs, PBDEs and PCBs, respectively. PBDEs were detected in 3/33 samples, OCPs in 9/33 samples and PCBs in 13/33 samples. Results from this study indicate exposure for infants via dietary (in contrast to dust and breast milk) intake in Australia contribute only a minor component to total exposure.