Covariate-adjusted generalized pairwise comparisons in small samples.

Semiparametric probabilistic index models allow for the comparison of two groups of observations, whilst adjusting for covariates, thereby fitting nicely within the framework of generalized pairwise comparisons (GPC). As with most regression approaches in this setting, the limited amount of data results in invalid inference as the asymptotic normality assumption is not met. In addition, separation issues might arise when considering small samples. In this article, we show that the parameters of the probabilistic index model can be estimated using generalized estimating equations, for which adjustments exist that lead to estimators of the sandwich variance-covariance matrix with improved finite sample properties and that can deal with bias due to separation. In this way, appropriate inference can be performed as is shown through extensive simulation studies. The known relationships between the probabilistic index and other GPC statistics allow to also provide valid inference for example, the net treatment benefit or the success odds.

Control of Magnetic Shape Anisotropy by Nanopillar Dimensionality in Vertically Aligned Nanocomposites.

Perpendicular magnetic anisotropy forms the foundation of the current data storage technology. However, there is an ever-increasing demand for higher density data storage, faster read-write access times, and lower power consuming storage devices, which requires new materials to reduce the switching current, improve bit-to-bit distributions, and improve reliability of writing with scalability below 10 nm. Here, vertically aligned nanocomposites (VANs) composed of self-assembled ferromagnetic La0.7Sr0.3MnO3 (LSMO) nanopillars in a surrounding ZnO matrix are investigated for controllable magnetic anisotropy. Confinement of LSMO into nanopillar dimensions down to 15 nm in such VAN films aligns the magnetic easy axis along the out-of-plane (i.e., perpendicular) direction, in strong contrast to the typical in-plane easy axis for strained, phase pure LSMO thin films. The dominant contribution to the magnetic anisotropy in these (LSMO)0.1(ZnO)0.9 VAN films comes from the shape of the nanopillars, while the epitaxial strain at the vertical LSMO:ZnO interfaces exhibits a negligible effect. These VAN films with their large, out-of-plane remnant magnetization of 2.6 µB/Mn and bit density of 0.77 Tbits/inch2 offer an interesting strategy for enhanced data storage applications.

Interlayer Affected Diamond Electrochemistry.

Diamond electrochemistry is primarily influenced by quantities of sp3-carbon, surface terminations, and crystalline structure. In this work, a new dimension is introduced by investigating the effect of using substrate-interlayers for diamond growth. Boron and nitrogen co-doped nanocrystalline diamond (BNDD) films are grown on Si substrate without and with Ti and Ta as interlayers, named BNDD/Si, BNDD/Ti/Si, and BNDD/Ta/Ti/Si, respectively. After detailed characterization using microscopies, spectroscopies, electrochemical techniques, and density functional theory simulations, the relationship of composition, interfacial structure, charge transport, and electrochemical properties of the interface between diamond and metal is investigated. The BNDD/Ta/Ti/Si electrodes exhibit faster electron transfer processes than the other two diamond electrodes. The interlayer thus determines the intrinsic activity and reaction kinetics. The reduction in their barrier widths can be attributed to the formation of TaC, which facilitates carrier tunneling, and simultaneously increases the concentration of electrically active defects. As a case study, the BNDD/Ta/Ti/Si electrode is further employed to assemble a redox-electrolyte-based supercapacitor device with enhanced performance. In summary, the study not only sheds light on the intricate relationship between interlayer composition, charge transfer, and electrochemical performance but also demonstrates the potential of tailored interlayer design to unlock new capabilities in diamond-based electrochemical devices.

High-Throughput Morphological Chirality Quantification of Twisted and Wrinkled Gold Nanorods.

Chirality in gold nanostructures offers an exciting opportunity to tune their differential optical response to left- and right-handed circularly polarized light, as well as their interactions with biomolecules and living matter. However, tuning and understanding such interactions demands quantification of the structural features that are responsible for the chiral behavior. Electron tomography (ET) enables structural characterization at the single-particle level and has been used to quantify the helicity of complex chiral nanorods. However, the technique is time-consuming and consequently lacks statistical value. To address this issue, we introduce herein a high-throughput methodology that combines images acquired by secondary electron-based electron beam-induced current (SEEBIC) with quantitative image analysis. As a result, the geometric chirality of hundreds of nanoparticles can be quantified in less than 1 h. When combining the drastic gain in data collection efficiency of SEEBIC with a limited number of ET data sets, a better understanding of how the chiral structure of individual chiral nanoparticles translates into the ensemble chiroptical response can be reached.

Giant Tunability of Rashba Splitting at Cation-Exchanged Polar Oxide Interfaces by Selective Orbital Hybridization.

The 2D electron gas (2DEG) at oxide interfaces exhibits extraordinary properties, such as 2D superconductivity and ferromagnetism, coupled to strongly correlated electrons in narrow d-bands. In particular, 2DEGs in KTaO3 (KTO) with 5d t2g orbitals exhibit larger atomic spin-orbit coupling and crystal-facet-dependent superconductivity absent for 3d 2DEGs in SrTiO3 (STO). Herein, by tracing the interfacial chemistry, weak anti-localization magneto-transport behavior, and electronic structures of (001), (110), and (111) KTO 2DEGs, unambiguously cation exchange across KTO interfaces is discovered. Therefore, the origin of the 2DEGs at KTO-based interfaces is dramatically different from the electronic reconstruction observed at STO interfaces. More importantly, as the interface polarization grows with the higher order planes in the KTO case, the Rashba spin splitting becomes maximal for the superconducting (111) interfaces approximately twice that of the (001) interface. The larger Rashba spin splitting couples strongly to the asymmetric chiral texture of the orbital angular moment, and results mainly from the enhanced inter-orbital hopping of the t2g bands and more localized wave functions. This finding has profound implications for the search for topological superconductors, as well as the realization of efficient spin-charge interconversion for low-power spin-orbitronics based on (110) and (111) KTO interfaces.

Istore: a project on innovative statistical methodologies to improve rare diseases clinical trials in limited populations.

BACKGROUND: The conduct of rare disease clinical trials is still hampered by methodological problems. The number of patients suffering from a rare condition is variable, but may be very small and unfortunately statistical problems for small and finite populations have received less consideration. This paper describes the outline of the iSTORE project, its ambitions, and its methodological approaches. METHODS: In very small populations, methodological challenges exacerbate. iSTORE's ambition is to develop a comprehensive perspective on natural history course modelling through multiple endpoint methodologies, subgroup similarity identification, and improving level of evidence. RESULTS: The methodological approaches cover methods for sound scientific modeling of natural history course data, showing similarity between subgroups, defining, and analyzing multiple endpoints and quantifying the level of evidence in multiple endpoint trials that are often hampered by bias. CONCLUSION: Through its expected results, iSTORE will contribute to the rare diseases research field by providing an approach to better inform about and thus being able to plan a clinical trial. The methodological derivations can be synchronized and transferability will be outlined.

Stabilizing Perovskite Pb(Mg0.33Nb0.67)O3-PbTiO3 Thin Films by Fast Deposition and Tensile Mismatched Growth Template.

Because of its low hysteresis, high dielectric constant, and strong piezoelectric response, Pb(Mg1/3Nb2/3)O3-PbTiO3 (PMN-PT) thin films have attracted considerable attention for the application in PiezoMEMS, field-effect transistors, and energy harvesting and storage devices. However, it remains a great challenge to fabricate phase-pure, pyrochlore-free PMN-PT thin films. In this study, we demonstrate that a high deposition rate, combined with a tensile mismatched template layer can stabilize the perovskite phase of PMN-PT films and prevent the nucleation of passive pyrochlore phases. We observed that an accelerated deposition rate promoted mixing of the B-site cation and facilitated relaxation of the compressively strained PMN-PT on the SrTiO3 (STO) substrate in the initial growth layer, which apparently suppressed the initial formation of pyrochlore phases. By employing La-doped-BaSnO3 (LBSO) as the tensile mismatched buffer layer, 750 nm thick phase-pure perovskite PMN-PT films were synthesized. The resulting PMN-PT films exhibited excellent crystalline quality close to that of the STO substrate.

A neutral comparison of statistical methods for analyzing longitudinally measured ordinal outcomes in rare diseases.

Ordinal data in a repeated measures design of a crossover study for rare diseases usually do not allow for the use of standard parametric methods, and hence, nonparametric methods should be considered instead. However, only limited simulation studies in settings with small sample sizes exist. Therefore, starting from an Epidermolysis Bullosa simplex trial with the above-mentioned design, a rank-based approach using the R package nparLD and different generalized pairwise comparisons (GPC) methods were compared impartially in a simulation study. The results revealed that there was not one single best method for this particular design, because a trade-off exists between achieving high power, accounting for period effects, and for missing data. Specifically, nparLD as well as the unmatched GPC approaches do not address crossover aspects, and the univariate GPC variants partly ignore the longitudinal information. The matched GPC approaches, on the other hand, take the crossover effect into account in the sense of incorporating the within-subject association. Overall, the prioritized unmatched GPC method achieved the highest power in the simulation scenarios, although this may be due to the specified prioritization. The rank-based approach yielded good power even at a sample size of N = 6 $N=6$ , whereas the matched GPC method could not control the type I error.

Statistical recommendations for count, binary, and ordinal data in rare disease cross-over trials.

BACKGROUND: Recommendations for statistical methods in rare disease trials are scarce, especially for cross-over designs. As a result various state-of-the-art methodologies were compared as neutrally as possible using an illustrative data set from epidermolysis bullosa research to build recommendations for count, binary, and ordinal outcome variables. For this purpose, parametric (model averaging), semiparametric (generalized estimating equations type [GEE-like]) and nonparametric (generalized pairwise comparisons [GPC] and a marginal model implemented in the R package nparLD) methods were chosen by an international consortium of statisticians. RESULTS: It was found that there is no uniformly best method for the aforementioned types of outcome variables, but in particular situations, there are methods that perform better than others. Especially if maximizing power is the primary goal, the prioritized unmatched GPC method was able to achieve particularly good results, besides being appropriate for prioritizing clinically relevant time points. Model averaging led to favorable results in some scenarios especially within the binary outcome setting and, like the GEE-like semiparametric method, also allows for considering period and carry-over effects properly. Inference based on the nonparametric marginal model was able to achieve high power, especially in the ordinal outcome scenario, despite small sample sizes due to separate testing of treatment periods, and is suitable when longitudinal and interaction effects have to be considered. CONCLUSION: Overall, a balance has to be found between achieving high power, accounting for cross-over, period, or carry-over effects, and prioritizing clinically relevant time points.

Composite endpoints, including patient reported outcomes, in rare diseases.

BACKGROUND: When assessing the efficacy of a treatment in any clinical trial, it is recommended by the International Conference on Harmonisation to select a single meaningful endpoint. However, a single endpoint is often not sufficient to reflect the full clinical benefit of a treatment in multifaceted diseases, which is often the case in rare diseases. Therefore, the use of a combination of several clinically meaningful outcomes is preferred. Many methodologies that allow for combining outcomes in a so-called composite endpoint are however limited in a number of ways, not in the least in the number and type of outcomes that can be combined and in the poor small-sample properties. Moreover, patient reported outcomes, such as quality of life, often cannot be integrated in a composite analysis, in spite of their intrinsic value. RESULTS: Recently, a class of non-parametric generalized pairwise comparisons tests have been proposed, which members do allow for any number and type of outcomes, including patient reported outcomes. The class enjoys good small-sample properties. Moreover, this very flexible class of methods allows for prioritizing the outcomes by clinical severity, allows for matched designs and for adding a threshold of clinical relevance. Our aim is to introduce the generalized pairwise comparison ideas and concepts for rare disease clinical trial analysis, and demonstrate their benefit in a post-hoc analysis of a small-sample trial in epidermolysis bullosa. More precisely, we will include a patient relevant outcome (Quality of life), in a composite endpoint. This publication is part of the European Joint Programme on Rare Diseases (EJP RD) series on innovative methodologies for rare diseases clinical trials, which is based on the webinars presented within the educational activity of EJP RD. This publication covers the webinar topic on composite endpoints in rare diseases and includes participants' response to a questionnaire on this topic. CONCLUSIONS: Generalized pairwise comparisons is a promising statistical methodology for evaluating any type of composite endpoints in rare disease trials and may allow a better evaluation of therapy efficacy including patients reported outcomes in addition to outcomes related to the diseases signs and symptoms.

Generalized Pairwise Comparisons to Assess Treatment Effects: JACC Review Topic of the Week.

A time-to-first-event composite endpoint analysis has well-known shortcomings in evaluating a treatment effect in cardiovascular clinical trials. It does not fully describe the clinical benefit of therapy because the severity of the events, events repeated over time, and clinically relevant nonsurvival outcomes cannot be considered. The generalized pairwise comparisons (GPC) method adds flexibility in defining the primary endpoint by including any number and type of outcomes that best capture the clinical benefit of a therapy as compared with standard of care. Clinically important outcomes, including bleeding severity, number of interventions, and quality of life, can easily be integrated in a single analysis. The treatment effect in GPC can be expressed by the net treatment benefit, the success odds, or the win ratio. This review provides guidance on the use of GPC and the choice of treatment effect measures for the analysis and reporting of cardiovascular trials.

How to analyze continuous and discrete repeated measures in small-sample cross-over trials?

To optimize the use of data from a small number of subjects in rare disease trials, an at first sight advantageous design is the repeated measures cross-over design. However, it is unclear how these within-treatment period and within-subject clustered data are best analyzed in small-sample trials. In a real-data simulation study based upon a recent epidermolysis bullosa simplex trial using this design, we compare non-parametric marginal models, generalized pairwise comparison models, GEE-type models and parametric model averaging for both repeated binary and count data. The recommendation of which methodology to use in rare disease trials with a repeated measures cross-over design depends on the type of outcome and the number of time points the treatment has an effect on. The non-parametric marginal model testing the treatment-time-interaction effect is suitable for detecting between group differences in the shapes of the longitudinal profiles. For binary outcomes with the treatment effect on a single time point, the parametric model averaging method is recommended, while in the other cases the unmatched generalized pairwise comparison methodology is recommended. Both provide an easily interpretable effect size measure, and do not require exclusion of periods or subjects due to incompleteness.

Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy.

Electron energy loss spectroscopy (EELS) is a well established technique in electron microscopy that yields information on the elemental content of a sample in a very direct manner. One of the persisting limitations of EELS is the requirement for manual identification of core-loss edges and their corresponding elements. This can be especially bothersome in spectrum imaging, where a large amount of spectra are recorded when spatially scanning over a sample area. This paper introduces a synthetic dataset with 736,000 labeled EELS spectra, computed from available generalized oscillator strength tables, that represents 107 K, L, M or N core-loss edges and 80 chemical elements. Generic lifetime broadened peaks are used to mimic the fine structure due to band structure effects present in experimental core-loss edges. The proposed dataset is used to train and evaluate a series of neural network architectures, being a multilayer perceptron, a convolutional neural network, a U-Net, a residual neural network, a vision transformer and a compact convolutional transformer. An ensemble of neural networks is used to further increase performance. The ensemble network is used to demonstrate fully automated elemental mapping in a spectrum image, both by directly mapping the predicted elemental content and by using the predicted content as input for a physical model-based mapping.

Characterization of a Timepix detector for use in SEM acceleration voltage range.

Hybrid pixel direct electron detectors are gaining popularity in electron microscopy due to their excellent properties. Some commercial cameras based on this technology are relatively affordable which makes them attractive tools for experimentation especially in combination with an SEM setup. To support this, a detector characterization (Modulation Transfer Function, Detective Quantum Efficiency) of an Advacam Minipix and Advacam Advapix detector in the 15-30 keV range was made. In the current work we present images of Point Spread Function, plots of MTF/DQE curves and values of DQE(0) for these detectors. At low beam currents, the silicon detector layer behaviour should be dominant, which could make these findings transferable to any other available detector based on either Medipix2, Timepix or Timepix3 provided the same detector layer is used.

Pattern Formation by Electric-Field Quench in a Mott Crystal.

The control of the Mott phase is intertwined with the spatial reorganization of the electronic states. Out-of-equilibrium driving forces typically lead to electronic patterns that are absent at equilibrium, whose nature is however often elusive. Here, we unveil a nanoscale pattern formation in the Ca2RuO4 Mott insulator. We demonstrate how an applied electric field spatially reconstructs the insulating phase that, uniquely after switching off the electric field, exhibits nanoscale stripe domains. The stripe pattern has regions with inequivalent octahedral distortions that we directly observe through high-resolution scanning transmission electron microscopy. The nanotexture depends on the orientation of the electric field; it is nonvolatile and rewritable. We theoretically simulate the charge and orbital reconstruction induced by a quench dynamics of the applied electric field providing clear-cut mechanisms for the stripe phase formation. Our results open the path for the design of nonvolatile electronics based on voltage-controlled nanometric phases.

Study of the Mechanism and Increasing Crystallinity in the Self-Templated Growth of Ultrathin PbS Nanosheets.

Colloidal 2D semiconductor nanocrystals, the analogue of solid-state quantum wells, have attracted strong interest in material science and physics. Molar quantities of suspended quantum objects with spectrally pure absorption and emission can be synthesized. For the visible region, CdSe nanoplatelets with atomically precise thickness and tailorable emission have been (almost) perfected. For the near-infrared region, PbS nanosheets (NSs) hold strong promise, but the photoluminescence quantum yield is low and many questions on the crystallinity, atomic structure, intriguing rectangular shape, and formation mechanism remain to be answered. Here, we report on a detailed investigation of the PbS NSs prepared with a lead thiocyanate single source precursor. Atomically resolved HAADF-STEM imaging reveals the presence of defects and small cubic domains in the deformed orthorhombic PbS crystal lattice. Moreover, variations in thickness are observed in the NSs, but only in steps of 2 PbS monolayers. To study the reaction mechanism, a synthesis at a lower temperature allowed for the study of reaction intermediates. Specifically, we studied the evolution of pseudo-crystalline templates toward mature, crystalline PbS NSs. We propose a self-induced templating mechanism based on an oleylamine-lead-thiocyanate (OLAM-Pb-SCN) complex with two Pb-SCN units as a building block; the interactions between the long-chain ligands regulate the crystal structure and possibly the lateral dimensions.

Insights into the Photoelectrocatalytic Behavior of gCN-Based Anode Materials Supported on Ni Foams.

Graphitic carbon nitride (gCN) is a promising n-type semiconductor widely investigated for photo-assisted water splitting, but less studied for the (photo)electrochemical degradation of aqueous organic pollutants. In these fields, attractive perspectives for advancements are offered by a proper engineering of the material properties, e.g., by depositing gCN onto conductive and porous scaffolds, tailoring its nanoscale morphology, and functionalizing it with suitable cocatalysts. The present study reports on a simple and easily controllable synthesis of gCN flakes on Ni foam substrates by electrophoretic deposition (EPD), and on their eventual decoration with Co-based cocatalysts [CoO, CoFe2O4, cobalt phosphate (CoPi)] via radio frequency (RF)-sputtering or electrodeposition. After examining the influence of processing conditions on the material characteristics, the developed systems are comparatively investigated as (photo)anodes for water splitting and photoelectrocatalysts for the degradation of a recalcitrant water pollutant [potassium hydrogen phthalate (KHP)]. The obtained results highlight that while gCN decoration with Co-based cocatalysts boosts water splitting performances, bare gCN as such is more efficient in KHP abatement, due to the occurrence of a different reaction mechanism. The related insights, provided by a multi-technique characterization, may provide valuable guidelines for the implementation of active nanomaterials in environmental remediation and sustainable solar-to-chemical energy conversion.