Optimal Alignment Research Articles

Is the lateral tibial spine a reliable landmark for planning tibial or femoral valgus osteotomies?

IntroductionA valgus osteotomy around the knee is a conservative procedure performed to unload the medial tibiofemoral compartment. However, the optimal postoperative alignment target remains controversial. Many studies have applied a “Fujisawa point” at 62.5%. The results of recent studies suggest decreasing the range of the mechanical axis target correction to 50–55%. The primary purpose of this study was to define the mean position of the lateral tibial spine in healthy patients from a reproducible 3-dimensional (3D) analysis. The study hypothesis was that the apex of the lateral tibial spine was a reliable and reproducible landmark for planning valgus osteotomies and preventing overcorrections. Materials and methodsThe study included 1140 patients: 560 women and 580 men, with a mean age of 61.7±16.5 years (18–98) and a mean body mass index (BMI) of 24.9±4.9kg/m2 (13.3–54.6). This analysis was done with the Stryker Orthopaedics Modeling and Analytics (SOMA) system which uses a database of computed tomography (CT) scans and 3D bone models. A statistical assessment was performed to determine the mean position of the lateral tibial spine. These measurements were then compared according to ethnicity, sex, age, BMI, knee side (right and left) and the overall mechanical axis of the leg. ResultsThe mean tibial plateau width was 72.9±5.7mm (59.1–91.1). The mean position of the lateral tibial spine was 53.6±1.1% (48.9–57.2). The mean position of the medial tibial spine was 48.4±2.5% (43.6–56.1) while the center of the tibial spines was 51.0±1.5% (46.4–56.1). Africans had a significantly more lateral mean tibial spine position than Asians (54.7% vs. 53.3%, p=0.001), Caucasians (54.7% vs. 53.7%, p=0.002) and Middle Easterners (54.7% vs. 53.6%, p=0.034). ConclusionThe lateral tibial spine is a simple and reproducible bony landmark. This landmark can be used when planning valgus osteotomies aiming for a “Fujisawa point” at 54%. Level of evidenceIV.

Optoelectrical impact of alternative window layer composition in CdTe thin film solar cells performance

This study investigates the integrability of different alternatives of cadmium sulfide (CdS), namely, oxygenated cadmium sulfide (CdS:O) and cadmium zinc sulfide (CdZnS) as the potential window layers in CdTe thin film solar cells using SCAPS-1D and experimental fabrication. The performance parameters such as open circuit voltage (Voc), short circuit current density (Jsc), fill factor (FF), conversion efficiency (η), and quantum efficiency (QE) have been examined for cells with different carrier concentration and series resistance (Rs) of window layer materials. Calculation results shows that the incorporation of oxygen (CdS:O) with series resistance (Rs ≤ 1E−1 Ω.cm2) and minimum carrier concentration of 1016 cm−3 contributes in optimum band alignment that enhances photo-current collection from both short and long wavelength regions compared to baseline CdS/CdTe solar cell. Moreover, the performance of the proposed cells has been improved in terms of QE, Jsc, Voc, η, and FF upon insertion of novel CdZnS layer. However, carrier recombination increases the saturation current density for CdZnS resulting in unstable performance. Consequently, upon insertion of CdS:O window layer, conversion efficiency enhancement is observed with Jsc (29.10 mA.cm−2), Voc (0.889 V) and FF (70.39%). The proposed window materials are deposited using RF-sputtering method and the experimental results are incorporated in simulation to validate the findings.

Non-Parallel Articulatory-to-Acoustic Conversion Using Multiview-Based Time Warping

In this paper, we propose a novel algorithm called multiview temporal alignment by dependence maximisation in the latent space (TRANSIENCE) for the alignment of time series consisting of sequences of feature vectors with different length and dimensionality of the feature vectors. The proposed algorithm, which is based on the theory of multiview learning, can be seen as an extension of the well-known dynamic time warping (DTW) algorithm but, as mentioned, it allows the sequences to have different dimensionalities. Our algorithm attempts to find an optimal temporal alignment between pairs of nonaligned sequences by first projecting their feature vectors into a common latent space where both views are maximally similar. To do this, powerful, nonlinear deep neural network (DNN) models are employed. Then, the resulting sequences of embedding vectors are aligned using DTW. Finally, the alignment paths obtained in the previous step are applied to the original sequences to align them. In the paper, we explore several variants of the algorithm that mainly differ in the way the DNNs are trained. We evaluated the proposed algorithm on a articulatory-to-acoustic (A2A) synthesis task involving the generation of audible speech from motion data captured from the lips and tongue of healthy speakers using a technique known as permanent magnet articulography (PMA). In this task, our algorithm is applied during the training stage to align pairs of nonaligned speech and PMA recordings that are later used to train DNNs able to synthesis speech from PMA data. Our results show the quality of speech generated in the nonaligned scenario is comparable to that obtained in the parallel scenario.

ProALIGN: Directly Learning Alignments for Protein Structure Prediction via Exploiting Context-Specific Alignment Motifs.

Template-based modeling (TBM), including homology modeling and protein threading, is one of the most reliable techniques for protein structure prediction. It predicts protein structure by building an alignment between the query sequence under prediction and the templates with solved structures. However, it is still very challenging to build the optimal sequence-template alignment, especially when only distantly related templates are available. Here we report a novel deep learning approach ProALIGN that can predict much more accurate sequence-template alignment. Like protein sequences consisting of sequence motifs, protein alignments are also composed of frequently occurring alignment motifs with characteristic patterns. Alignment motifs are context-specific as their characteristic patterns are tightly related to sequence contexts of the aligned regions. Inspired by this observation, we represent a protein alignment as a binary matrix (in which 1 denotes an aligned residue pair) and then use a deep convolutional neural network to predict the optimal alignment from the query protein and its template. The trained neural network implicitly but effectively encodes an alignment scoring function, which reduces inaccuracies in the handcrafted scoring functions widely used by the current threading approaches. For a query protein and a template, we apply the neural network to directly infer likelihoods of all possible residue pairs in their entirety, which could effectively consider the correlations among multiple residues. We further construct the alignment with maximum likelihood, and finally build a structure model according to the alignment. Tested on three independent data sets with a total of 6688 protein alignment targets and 80 CASP13 TBM targets, our method achieved much better alignments and 3D structure models than the existing methods, including HHpred, CNFpred, CEthreader, and DeepThreader. These results clearly demonstrate the effectiveness of exploiting the context-specific alignment motifs by deep learning for protein threading.

Is use of the general system justification scale across countries justified? Testing its measurement equivalence.

System justification is a widely researched topic in social and political psychology. One major measurement instrument in system justification research is the General System Justification Scale (G-SJS). This scale has been used, among others, for comparisons across social groups in different countries. Such comparisons rely on the assumption that the scale is measurement equivalent. However, this assumption has never been comprehensively tested. Thus, the present two studies assessed the measurement equivalence of the G-SJS following classic measurement equivalence guidelines (i.e., multigroup confirmatory factor analyses) in Study 1 and using a new method for comparing larger numbers of groups in Study 2 (i.e., alignment optimization). In Study 1, we analysed the measurement equivalence in Great Britain (n=444), Germany (n=454), and France (n=463). In Study 2, we used a publicly available dataset consisting of 66samples from 30 countries (N=13,495) to again assess the measurement equivalence of the scale. Results indicated (partial) metric equivalence, but not scalar equivalence in both studies. Overall, the studies indicate that mean comparisons across the examined countries are not warranted with the current form of the G-SJS. The scale needs to be revised for valid cross-country comparisons of means.

Exploring and exploiting ant colony optimization algorithm for vertical highway alignment development

AbstractThe vertical alignment optimization is about developing a minimum cost curvilinear vertical profile of constrained grade sections and appropriate non‐overlapping vertical curves passing through fixed control points with elevation constraints. Variations in ground profile and discreteness in unit cutting and filling costs make it a non‐convex, noisy, constrained optimization problem with many local minima. Further, the gradient related constraints and vertical curvature are non‐linear. This paper presents an innovative exploring and exploiting ant colony optimization (E&E‐ACO) algorithm with an appropriate point sampling, vertical curve fitting strategies, and an intuitive feasible region identification approach for solving the vertical alignment optimization problem. The E&E‐ACO algorithm extensively explores the feasible search space to generate a set of potential solutions and effectively exploit the space around the potential solutions for developing the optimized vertical alignment. The efficacy of the proposed method is demonstrated using two case studies. In one case study, the optimized solution by the proposed method had a marginally better objective function value and about three times lesser computational time than the solution by the mesh adaptive direct search method. The optimized alignment satisfied the elevation constraints of fixed control points and imitated the manually designed real‐world vertical alignment. The linearly varying exploration and exploitation parameters had better convergence rate than the other tested variations. Further, the proposed method at the end of 1000 iterations yielded about six times better result than the traditional ACO algorithm.

Household consumption and exchange rate extreme dynamics: Multiple asymmetric threshold non‐linear autoregressive distributed lag model perspective

AbstractThis study re ‐evaluates the relative adjustments of household's consumption expenditure to extremely small and extremely large variations in exchange rate in African emerging economies (AEE). For this purpose, we used a modified version of non‐linear autoregressive distributed lag (ARDL) and multiple threshold non‐linear ARDL models that specifically captures the differential effects of extremely small and extremely large positive and negative variations of the explanatory variable(s) on the explained variable. Consequently, the empirical estimates reveal that changes in exchange rate has asymmetric effects on consumption expenditure in all the countries except in Nigeria. Furthermore, consumption expenditure in Algeria, Egypt and Morocco increases significantly at the upper quantile of exchange rate appreciation, whereas, it declines significantly at all quantiles of exchange rate depreciation, implying that consumption expenditure in these three North African countries are more sensitive to large positive shocks in exchange rate. In Kenya, Nigeria and South Africa, consumption expenditure are exchange rate inelastic as households maintain their consumption levels regardless of the direction and degree of exchange rate deviations. Overall, the diagnostics tests prove the superiority of this enhanced technique over the standard non‐linear ARDL technique. Based on the outcomes of this study, policy recommendations that could ensure optimal exchange rate alignment for the African countries, as well as other emerging economies have been proposed.

Multi-factorial nerve guidance conduit engineering improves outcomes in inflammation, angiogenesis and large defect nerve repair

Nerve guidance conduits (NGCs) are sub-optimal for long-distance injuries with inflammation and poor vascularization related to poor axonal repair. This study used a multi-factorial approach to create an optimized biomaterial NGC to address each of these issues. Through stepwise optimization, a collagen-chondroitin-6-sulfate (Coll-CS) biomaterial was functionalized with extracellular matrix (ECM) components; fibronectin, laminin 1 and laminin 2 (FibL1L2) in specific ratios. A snap-cooled freeze-drying process was then developed with optimal pore architecture and alignment to guide axonal bridging. Culture of adult rat dorsal root ganglia on NGCs demonstrated significant improvements in inflammation, neurogenesis and angiogenesis in the specific Fib:L1:L2 ratio of 1:4:1. In clinically relevant, large 15 mm rat sciatic nerve defects, FibL1L2-NGCs demonstrated significant improvements in axonal density and angiogenesis compared to unmodified NGCs with functional equivalence to autografts. Therefore, a multiparameter ECM-driven strategy can significantly improve axonal repair across large defects, without exogenous cells or growth factors.

Optimized splitting of mixed-species RNA sequencing data.

Gene expression studies using xenograft transplants or co-culture systems, usually with mixed human and mouse cells, have proven to be valuable to uncover cellular dynamics during development or in disease models. However, the mRNA sequence similarities among species presents a challenge for accurate transcript quantification. To identify optimal strategies for analyzing mixed-species RNA sequencing data, we evaluate both alignment-dependent and alignment-independent methods. Alignment of reads to a pooled reference index is effective, particularly if optimal alignments are used to classify sequencing reads by species, which are re-aligned with individual genomes, generating [Formula: see text] accuracy across a range of species ratios. Alignment-independent methods, such as convolutional neural networks, which extract the conserved patterns of sequences from two species, classify RNA sequencing reads with over 85% accuracy. Importantly, both methods perform well with different ratios of human and mouse reads. While non-alignment strategies successfully partitioned reads by species, a more traditional approach of mixed-genome alignment followed by optimized separation of reads proved to be the more successful with lower error rates.

Deviation Detection in Clinical Pathways Based on Business Alignment

Several unexpected behaviors may occur during actual treatment of clinical pathways, which will have negative impact on the implementation and the future work. To increase the performance of current deviation detection algorithms, a method is presented according to business alignment, which can effectively detect the anomaly in the implementation of the clinical pathways, provide judgment basis for the intervention in the process of the clinical pathway implementation, and play a crucial role in improving the clinical pathways. Firstly, the noise in diagnosis and treatment logs of clinical pathways will be removed. Then, the synchronous composition model is constructed to embody the deviations between the actual process and the theoretical model. Finally, A ∗ algorithm is selected to search for optimal alignment. A clinical pathway for ST-Elevation Myocardial Infarction (STEMI) under COVID-19 is used as a case study, and the superiority and effectiveness of this method in deviation detection are illustrated in the result of experiments.

Controlling the Anionic Ratio and Gradient in Kesterite Technology.

Accurate anionic control during the formation of chalcogenide solid solutions is fundamental for tuning the physicochemical properties of this class of materials. Compositional grading is the key aspect of band gap engineering and is especially valuable at the device interfaces for an optimum band alignment, for controlling interface defects and recombination and for optimizing the formation of carrier-selective contacts. However, a simple and reliable technique that allows standardizing anionic compositional profiles is currently missing for kesterites and the feasibility of achieving a compositional gradient remains a challenging task. This work aims at addressing these issues by a simple and innovative technique. It basically consists of first preparing a pure sulfide absorber with a specific thickness followed by the synthesis of a pure selenide part of complementary thickness on top of it. Specifically, the technique is applied to the synthesis of Cu2ZnSn(S,Se)4 and Cu2ZnGe(S,Se)4 kesterite absorbers, and a series of characterizations are performed to understand the anionic redistribution within the absorbers. For identical processing conditions, different Se incorporation dynamics is identified for Sn- and Ge-based kesterites, leading to a homogeneous or graded composition in depth. It is first demonstrated that for Sn-based kesterite the anionic composition can be perfectly controlled through the thicknesses ratio of the sulfide and selenide absorber parts. Then, it is demonstrated that for Ge-based kesterite an anionic (Se–S) gradient is obtained and that by adjusting the processing conditions the composition at the back side can be finely tuned. This technique represents an innovative approach that will help to improve the compositional reproducibility and determine a band gap grading strategy pathway for kesterites. Furthermore, due to its simplicity and reliability, the proposed methodology could be extended to other chalcogenide materials.

Railway Alignment Optimization Based on Multiobjective Bi-Level Programming Considering Ecological Impact

Railway projects frequently pass through ecologically fragile regions and result in various ecological damages. The railway alignment determining the layout of structures plays an important role in ecological protection. This paper presents a railway alignment optimization model based on multiobjective bi-level programming (MBRAO). The upper level of MBRAO is a horizontal alignment optimization for the minimization of investment and ecological impacts from tunnel drainage and train noise. A multiobjective evolutionary algorithm based on decomposition (MOEA/D) solves the horizontal alignment optimization and naturally maintains population diversity. The lower level of MBRAO is a vertical alignment optimization for investment minimization. A self-adaptive differential evolution (DE) algorithm adjusting essential parameters based on optimization status solves the vertical alignment optimization efficiently. MBRAO is applied in multistage at both levels to find the suitable numbers of horizontal and vertical points of intersection. This paper introduces three kinds of vertical feature data generated corresponding to horizontal feature data to define different site modification costs on the bridge, subgrade, and tunnel structures. A real-world case study at Wolong Reserve is studied to verify the effectiveness of MBRAO based on a customized geographic information system (GIS).

Evaluation of optimal implant alignment in total hip arthroplasty based on postoperative range of motion simulation

BackgroundDislocation after total hip arthroplasty is a frequent cause of revision surgery. This study was performed to determine the optimal implant alignment in total hip arthroplasty by simulating the postoperative range of motion. MethodsAll operations were performed via posterolateral approach using combined anteversion of the stem and cup technique. Maximum range of motion without implant impingement was simulated in 79 replaced hips using postoperative computed tomography and the achievement of the required range of motion defined by previous studies was assessed. Optimal cup and stem alignment for impingement-free range of motion were statistically determined using the receiver operator coefficient curve. FindingsCup inclination and anteversion, stem anteversion, and combined anteversion were 37.6°, 20.1°, 26.2°, and 46.3°, respectively. Maximum range of motion in flexion, extension, internal rotation at 90° of flexion, and external rotation were 131.8°, 42.3°, 56.4°, and 64.5°, respectively. Flexion >110°, extension >30°, internal rotation >30° at 90° of flexion, and external rotation >30° were fulfilled by 96%, 86%, 92%, and 96% of all replaced hips, respectively. Optimal implant alignment for impingement-free range of motion was 34°–43° of cup inclination, 18°–26° of cup anteversion, 17°–29° of stem anteversion, and 35°–56° of combined anteversion. Both cup and stem anteversion showed significant relationship with postoperative range of motion. InterpretationSurgeons could gain valuable insights into optimal cup and stem alignment to perform postoperative range of motion simulations.

Numerical and Experimental Investigation into the Aerodynamic Benefits of Rotorcraft Formation Flight

The use of formation flight to achieve aerodynamic benefit applied to rotorcraft has, unlike its fixed-wing counterpart, received little attention in the literature. This document presents a proof-of-concept of rotorcraft formation flight from two independent investigations: a numerical study of a fully articulated helicopter influenced by an upstream helicopter wake and a wind-tunnel experiment featuring two small-scale helicopter models with fixed-pitch blades. Both cases feature a representation of two helicopters in a diagonal, staggered formation aligned on the advancing side of the main rotor, but do not simulate directly comparable flight conditions. The vertical and lateral alignment of the two helicopters is varied in order to observe the achievable reductions in main rotor power required during cruise flight. The wind-tunnel experiment data yield an estimated maximum total power reduction for the secondary aircraft of approximately 24%, while the numerical models yield reductions between 20% and 34% dependent on flight velocity. Both experiments predict a higher potential for aerodynamic benefit than generally observed for fixed-wing formations, which is attributed to the asymmetric velocity profile induced by the wake of the upstream rotor. Optimal lateral alignment of both experimental and numerical results is found to feature overlap of the rotor disk areas, rather than tip-to-tip alignment, as a result of the circular rotor disk area. Experimental data show an optimal vertical alignment of the secondary rotorcraft below the primary, due to the self-induced vertical displacement of the rotor wake, which is absent from the numerical results due to the application of a flat wake assumption. The results show a promising potential for rotorcraft formation flight, though due to the limited nature of the models used, conclusions cannot be generalized. The potential aerodynamic benefit indicated by the present study invites further research in the field of rotorcraft formation flight.

Parallel multiple DNA sequence alignment using genetic algorithm and asynchronous advantage actor critic model

Multiple sequence alignment plays a crucial role in bioinformatics field. In this process, sequences are compared by establishing residue-residue correspondence among related sequences. In this paper, we present a novel framework that uses genetic algorithm and asynchronous advantage actor critic model to look for the optimal multiple DNA sequence alignment. In the first step, we generate initial alignments by applying the T-COFFEE method. Then, we recursively use a genetic algorithm to find the optimal fragmentation of the pre-aligned sequences. At this stage, the obtained short sub alignments are introduced to the A3C model for parallel alignments. So, the optimal multiple alignment of the original sequences represents the fusion of sub-alignments. To evaluate the performances of the proposed approach, we used the Balibase 3.0 benchmark and compared to TCOFFEE, MAFFT and RLALIGN methods. The obtained experimental results show that the proposed approach can achieve solutions of competitive quality.

The ultimate guide to posture: A review

Postural alignment is the composite of the position of all joint and limbs of the body at any given movement. Optimal alignment is a prerequisite for optimal movement function. Postural control is the ability to control of the body’s position in space for stability and orientation. Postural orientation is the ability to maintain normal alignment relationships between the various body segments and between the body and environment. Methodology: The author conducted a comprehensive search of open access articles of major scientific databases including PuBMed, Scopus, Web of Science, shodhganga, Google Scholar etc. Ten significant scientific studies were found relating to the ultimate guide to posture. Five studies were selected based on inclusion criteria. Results Helps reduce the risk of neck injuries and back pain. Minimizes fatigue and pain from aching joints. Prevents improper spinal alignment, which can lead to headaches and discomfort. Improves your self-esteem. Conclusions: A faulty idea of correct posture can be cured by including the patient to accept a new and satisfactory pattern and then by teaching him how to assume it and make it habitual by repeated voluntary effort.

Commissural Versus Coronary Optimized Alignment During Transcatheter Aortic Valve Replacement.

The aims of this study were to determine the rate of noncentered coronary ostia and their risk for coronary overlap (CO) and to develop an improved orientation strategy for transcatheter aortic valve replacement (TAVR) devices taking into account anatomical cues to identify patients at risk for CO regardless of commissural alignment and compute an alternative, CO-free TAVR rotation angle for those patients. Commissural alignment during TAVR reduces CO risk. However, eccentricity of coronary ostia from the center of the sinus of Valsalva may result in CO even after perfect alignment of TAVR commissures. Baseline computed tomography from TAVR candidates helped identify distance from commissures to the right coronary artery (RCA) and the left coronary artery (LCA). Then, for each case, a virtual valve was simulated with ideal commissural or coronary alignment, and the degree of CO was determined. On the basis of the potential BASILICA (bioprosthetic or native aortic scallop intentional laceration to prevent iatrogenic coronary artery obstruction) efficacy, 3 groups were defined: no risk for CO (>35° from neocommissure to coronary ostia), moderate risk (20°-35°), and severe risk (≤20°). Computed tomographic studies from 107 patients were included. After excluding 7 patients (poor quality or bicuspid valve), 100 patients were analyzed. The RCA showed greater eccentricity compared with the LCA (18.5° [IQR: 3.3°-12.8°] vs 6.5° [IQR: 3.3°-12.8°]; P< 0.001). The mean intercoronary angle was 140.0° ± 18.7° (95% CI: 136.3°-143.7°). Thirty-two patients had moderate to severe risk for CO (≤35°) despite ideal commissural alignment. Greater coronary eccentricity (cutoff for RCA, 24.5°; cutoff for LCA, 19°) and intercoronary angle >147.5° or<103° were associated with greater risk for moderate to severe CO despite commissural alignment (area under the curve: 0.97; 95% CI: 0.91-0.99). If optimal coronary alignment was simulated, this prevented severe CO in all cases and reduced moderate CO from 27% to 5% (P< 0.001). One third of patients would have CO during TAVR-in-TAVR despite commissural alignment; a 6-fold decrease in this risk was achieved with optimized coronary alignment. Coronary eccentricity and intercoronary angle were the main predictors.

A Sequential Exploration Algorithm for the Design Optimization of Horizontal Road Alignment

A Sequential Exploration Algorithm for the Design Optimization of Horizontal Road Alignment

A Novel Population-based Optimization for Multiple Sequence Alignment in Protein Sequencing

A Novel Population-based Optimization for Multiple Sequence Alignment in Protein Sequencing

On Performance of STAR-RIS-Enabled Multiple Two-Way Full-Duplex D2D Communication Systems

This paper investigates performance of simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-enabled multiple two-way full-duplex device-to-device (D2D) communication systems over Rayleigh fading channels under optimal and uncertain phase shift alignments. We derive closed-form expressions for outage probability (OP), sum throughput, ergodic capacity (EC) and energy efficiency. To gain insights, we quantify and reveal some useful guidelines for the performance behavior of the OP and the EC, such as diversity order and ergodic slope from high transmit power configuration. In addition, some critical points also deduced for the sum throughput and the system energy efficiency. Moreover, the impacts of the transmit power configurations, RIS deployments, allocating target data rate transmission, and the number of user deployments on the system performance are examined. Finally, we present some extensive simulations using Monte-Carlo method to corroborate the accuracy of the theoretical analysis.