Engineering Transition Metal Layers for Long Lasting Anionic Redox in Layered Sodium Manganese Oxide

Oxygen-redox-based-layered cathode materials are of great importance in realizing high-energy-density sodium-ion batteries (SIBs) that can satisfy the demands of next-generation energy storage technologies. However, Mn-based-layered materials (P2-type Na-poor Na_y[A_xMn_1−x]O₂, where A = alkali ions) still suffer from poor reversibility during oxygen-redox reactions and low conductivity. In this work, the dual Li and Co replacement is investigated in P2-type-layered Na_xMnO₂. Experimentally and theoretically, it is demonstrated that the efficacy of the dual Li and Co replacement in Na_0.6[Li_0.15Co_0.15Mn_0.7]O₂ is that it improves the structural and cycling stability despite the reversible Li migration from the transition metal layer during de-/sodiation. Operando X-ray diffraction and ex situ neutron diffraction analysis prove that the material maintains a P2-type structure during the entire range of Na⁺ extraction and insertion with a small volume change of ≈4.3%. In Na_0.6[Li_0.15Co_0.15Mn_0.7]O₂, the reversible electrochemical activity of Co³⁺/Co⁴⁺, Mn³⁺/Mn⁴⁺, and O^2-/(O₂)^n- redox is identified as a reliable mechanism for the remarkable stable electrochemical performance. From a broader perspective, this study highlights a possible design roadmap for developing cathode materials with optimized cationic and anionic activities and excellent structural stabilities for SIBs.     

Advanced Characterization and Optimization of NiOx:Cu-SAM Hole-Transporting Bi-Layer for 23.4% Efficient Monolithic Cu(In,Ga)Se2-Perovskite Tandem Solar Cells

The performance of five hole-transporting layers (HTLs) is investigated in both single-junction perovskite and Cu(In, Ga)Se₂ (CIGSe)-perovskite tandem solar cells: nickel oxide (NiO_x,), copper-doped nickel oxide (NiO_x:Cu), NiO_x+SAM, NiO_x:Cu+SAM, and SAM, where SAM is the [2-(3,-6Dimethoxy-9H-carbazol-9yl)ethyl]phosphonic acid (MeO-2PACz) self-assembled monolayer. The performance of the devices is correlated to the charge-carrier dynamics at the HTL/perovskite interface and the limiting factors of these HTLs are analyzed by performing time-resolved and absolute photoluminescence ((Tr)PL), transient surface photovoltage (tr-SPV), and X-ray/UV photoemission spectroscopy (XPS/UPS) measurements on indium tin oxide (ITO)/HTL/perovskite and CIGSe/HTL/perovskite stacks. A high quasi-Fermi level splitting to open-circuit (QFLS-V_oc) deficit is detected for the NiO_x-based devices, attributed to electron trapping and poor hole extraction at the NiO_x-perovskite interface and a low carrier effective lifetime in the bulk of the perovskite. Simultaneously, doping the NiO_x with 2% Cu and passivating its surface with MeO-2PACz suppresses the electron trapping, enhances the holes extraction, reduces the non-radiative interfacial recombination, and improves the band alignment. Due to this superior interfacial charge-carrier dynamics, NiO_x:Cu+SAM is found to be the most suitable HTL for the monolithic CIGSe-perovskite tandem devices, enabling a power-conversion efficiency (PCE) of 23.4%, V_oc of 1.72V, and a fill factor (FF) of 71%, while the remaining four HTLs suffer from prominent V_oc and FF losses.     

Reduction of the self-forces in Monte Carlo simulations of semiconductor devices on unstructured meshes

When using an unstructured mesh for device geometry, the ensemble Monte Carlo simulations of semiconductor devices may be affected by unwanted self-forces resulting from the particle-mesh coupling. We report on the progress in minimisation of the self-forces on arbitrary meshes by showing that they can be greatly reduced on a finite element mesh with proper interpolation functions. The developed methodology is included into a self-consistent finite element 3D Monte Carlo device simulator. Minimising of the self-forces using the proper interpolation functions is tested by simulating the electron transport in a 10 nm gate length, 6.1 nm body thick, double gate metal-oxide-semiconductor field-effect transistor (MOSFET). We demonstrate the reduction in the self-force and illustrate the practical distinction by showing I-V characteristics for the device.     

Spatial generalization and aggregation of massive movement data

Movement data (trajectories of moving agents) are hard to visualize: numerous intersections and overlapping between trajectories make the display heavily cluttered and illegible. It is necessary to use appropriate data abstraction methods. We suggest a method for spatial generalization and aggregation of movement data, which transforms trajectories into aggregate flows between areas. It is assumed that no predefined areas are given. We have devised a special method for partitioning the underlying territory into appropriate areas. The method is based on extracting significant points from the trajectories. The resulting abstraction conveys essential characteristics of the movement. The degree of abstraction can be controlled through the parameters of the method. We introduce local and global numeric measures of the quality of the generalization, and suggest an approach to improve the quality in selected parts of the territory where this is deemed necessary. The suggested method can be used in interactive visual exploration of movement data and for creating legible flow maps for presentation purposes.     

Disruption management in the airline industry—Concepts,models and methods

This paper provides a thorough review of the current state-of-the-art within airline disruption management of resources, including aircraft, crew, passenger and integrated recovery. An overview of model formulations of the aircraft and crew scheduling problems is presented in order to emphasize similarities between solution approaches applied to the planning and recovery problems. A brief overview of research within schedule robustness in airline scheduling is included in the review, since this proactive measure is a natural complement to disruption management.     

The train driver recovery problem—A set partitioning based model and solution method

The need to recover a train driver schedule occurs during major disruptions in the daily railway operations. Based on data from the Danish passenger railway operator DSB S-tog A/S, a solution method to the train driver recovery problem (TDRP) is developed. The TDRP is formulated as a set partitioning problem. We define a disruption neighbourhood by identifying a small set of drivers and train tasks directly affected by the disruption. Based on the disruption neighbourhood, the TDRP model is formed and solved. If the TDRP solution provides a feasible recovery for the drivers within the disruption neighbourhood, we consider that the problem is solved. However, if a feasible solution is not found, the disruption neighbourhood is expanded by adding further drivers or increasing the recovery time period. Fractional solutions to the LP relaxation of the TDRP are resolved with a constraint branching strategy using the depth-first search of the Branch & Bound tree. The LP relaxation of the TDRP possesses strong integer properties. We present test scenarios generated from the historical real-life operations data of DSB S-tog A/S. The numerical results show that all but one tested instances produce integer solutions to the LP relaxation of the TDRP and solutions are found within a few seconds.     

Parallel batch scheduling of equal-length jobs with release and due dates

In this paper we study parallel batch scheduling problems with bounded batch capacity and equal-length jobs in a single and parallel machine environment. It is shown that the feasibility problem 1|p-batch,b<n,r _j ,p _j =p,C _j ≤d _j |− can be solved in O(n ²) time and that the problem of minimizing the maximum lateness can be solved in O(n ²log n) time. For the parallel machine problem P|p-batch,b<n,r _j ,p _j =p,C _j ≤d _j |− an O(n ³log n)-time algorithm is provided, which can also be used to solve the problem of minimizing the maximum lateness in O(n ³log ² n) time.     

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.     

Urinary proteomic analysis of chronic allograft nephropathy

The pathogenesis of progressive renal allograft injury, which is termed chronic allograft nephropathy (CAN), remains obscure and is currently defined by histology. Prospective protocol-biopsy trials have demonstrated that clinical and standard laboratory tests are insufficiently sensitive indicators of the development and progression of CAN. The study aim was to determine if CAN could be characterized by urinary proteomic data and identify the proteins associated with disease. The urinary proteome of 75 renal transplant recipients and 20 healthy volunteers was analyzed using surface enhanced laser desorption and ionization MS. Patients could be classified into subgroups with normal histology and Banff CAN grades 2-3 with a sensitivity of 86% and a specificity of 92% by applying the classification algorithm Adaboost to urinary proteomic data. Several urinary proteins associated with advanced CAN were identified including α1-microglobulin, β2-microglobulin, prealbumin, and endorepellin, the antiangiogenic C-terminal fragment of perlecan. Increased urinary endorepellin was confirmed by ELISA and increased tissue expression of the endorepellin/perlecan ratio by immunofluoresence analysis of renal biopsies. In conclusion, analysis of urinary proteomic data has further characterized the more severe CAN grades and identified urinary endorepellin, as a potential biomarker of advanced CAN.     

On techniques for angle compensation in nonideal iris recognition.

The popularity of the iris biometric has grown considerably over the past two to three years. Most research has been focused on the development of new iris processing and recognition algorithms for frontal view iris images. However, a few challenging directions in iris research have been identified, including processing of a nonideal iris and iris at a distance. In this paper, we describe two nonideal iris recognition systems and analyze their performance. The word "nonideal" is used in the sense of compensating for off-angle occluded iris images. The system is designed to process nonideal iris images in two steps: 1) compensation for off-angle gaze direction and 2) processing and encoding of the rotated iris image. Two approaches are presented to account for angular variations in the iris images. In the first approach, we use Daugman's integrodifferential operator as an objective function to estimate the gaze direction. After the angle is estimated, the off-angle iris image undergoes geometric transformations involving the estimated angle and is further processed as if it were a frontal view image. The encoding technique developed for a frontal image is based on the application of the global independent component analysis. The second approach uses an angular deformation calibration model. The angular deformations are modeled, and calibration parameters are calculated. The proposed method consists of a closed-form solution, followed by an iterative optimization procedure. The images are projected on the plane closest to the base calibrated plane. Biorthogonal wavelets are used for encoding to perform iris recognition. We use a special dataset of the off-angle iris images to quantify the performance of the designed systems. A series of receiver operating characteristics demonstrate various effects on the performance of the nonideal-iris-based recognition system.