Optimal Alignment Research Articles

REFERENCE AREAS SELECTION AFFECTS REGISTRATION OF AI-SEGMENTED MANDIBLES ACQUIRED WITH CBCT

Introduction Precise registration of sequential 3D datasets is crucial for accurate dimensional analysis. Utilizing the Local Best-Fit (LBF) algorithm and stable Registration Reference Areas (RRAs) facilitates the accurate alignment of 3D surface models. Currently, Cone-beam Computed Tomography (CBCT) and Deep Learning (DL) algorithms are at the forefront for segmenting CBCT scans to monitor morphological changes in the residual alveolar ridge. This study compares the effectiveness of different RRAs in registration sequential 3D surface models of partially edentulous mandibles. Methods DL-assisted software segmented two sequential CBCTs (T0 and T1) from 10 patients, producing sequential 3D mandibular models. These models were aligned using three distinct RRAs: (i) WHOLE, encompassing the entire surface model; (ii) MND_BODY, covering the mandibular body while excluding the unstable alveolar ridge; and (iii) SPIN_FOR, incorporating stable RRAs (mental foramina and mental spine). An innovative method assessed registration accuracy by generating centroids from cross-sectional outlines of the mandibular nerve canals at the anterior third (A), medial third (B), and posterior third (C) of the posterior edentulous areas. The distance between centroids at T0 and T1 quantified registration accuracy. Results The MND_BODY group exhibited superior accuracy, whereas the SPIN_FOR group showed the least, with accuracy decreasing from A to C, suggesting rotational misalignments. ConclusionsWhen selecting RRAs, both stability and spatial distribution must be taken into account. For optimal alignment, sequential 3D surface models should use RRAs that are both stable and widely distributed.

REDalign: accurate RNA structural alignment using residual encoder-decoder network

BackgroundRNA secondary structural alignment serves as a foundational procedure in identifying conserved structural motifs among RNA sequences, crucially advancing our understanding of novel RNAs via comparative genomic analysis. While various computational strategies for RNA structural alignment exist, they often come with high computational complexity. Specifically, when addressing a set of RNAs with unknown structures, the task of simultaneously predicting their consensus secondary structure and determining the optimal sequence alignment requires an overwhelming computational effort of O(L6)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O(L^6)$$\\end{document} for each RNA pair. Such an extremely high computational complexity makes these methods impractical for large-scale analysis despite their accurate alignment capabilities.ResultsIn this paper, we introduce REDalign, an innovative approach based on deep learning for RNA secondary structural alignment. By utilizing a residual encoder-decoder network, REDalign can efficiently capture consensus structures and optimize structural alignments. In this learning model, the encoder network leverages a hierarchical pyramid to assimilate high-level structural features. Concurrently, the decoder network, enhanced with residual skip connections, integrates multi-level encoded features to learn detailed feature hierarchies with fewer parameter sets. REDalign significantly reduces computational complexity compared to Sankoff-style algorithms and effectively handles non-nested structures, including pseudoknots, which are challenging for traditional alignment methods. Extensive evaluations demonstrate that REDalign provides superior accuracy and substantial computational efficiency.ConclusionREDalign presents a significant advancement in RNA secondary structural alignment, balancing high alignment accuracy with lower computational demands. Its ability to handle complex RNA structures, including pseudoknots, makes it an effective tool for large-scale RNA analysis, with potential implications for accelerating discoveries in RNA research and comparative genomics.

Efficacy of R-N cusp-overlap view as a complementary approach for optimal neocommissural alignment with Navitor valve.

Efficacy of R-N cusp-overlap view as a complementary approach for optimal neocommissural alignment with Navitor valve.

Computational screening of 2D ternary penta-materials with auxetic properties and efficient photocatalytic CO2 reduction

Due to unique structural and electronic properties, pentagon-based two-dimensional (2D) materials have captured significant interest in recent years. However, previous studies on these materials have primarily focused on unary and binary systems, with less exploration of ternary pentagonal structures. Herein, we conducted first-principles calculations to evaluate the stability of 122 ternary pentagonal monolayers composed of metals, nitrogen, and chalcogen. We identify six highly stable candidates, including AuNS, CuNTe, GaNS, InNS, SbNS, and SbNSe that meet the criteria for thermodynamic, mechanical, and dynamic stability. Mechanical property analysis reveals that five of these monolayers demonstrate auxetic behavior. Electronic structure calculations show that all candidates are semiconductors with band gaps ranging from 0.12 to 3.42 eV. Specifically, the SbNS and SbNSe monolayers are indirect semiconductors with band gaps of 2.25 and 2.27 eV, respectively. These materials exhibit strong visible light absorption, and potentially serve as exceptional photocatalysts for the reduction of CO2 to CH4 due to the optimal band alignment. The free energy change in the rate-limiting step is even lower than those found in g-C3N4 and MoS2-based systems. Our findings highlight new pentagon-based 2D materials with remarkable electronic, mechanical, and optical properties, making them promising candidates for applications in mechanics and energy conversion.

Telemedicine Compared to Office-Based Care of Patients With Cardiac Symptoms: Treatment and Outcomes

BackgroundAn increasing proportion of visits are now delivered via a virtual platform. Virtual visits are limited by the lack of important components of cardiovascular assessment such as physician examination and electrocardiogram. ObjectivesThe purpose of this study was to evaluate the quality of care delivered by virtual visits compared to office-based visits among adults who sought care for three common cardiac-related symptoms: dyspnea, dizziness, or palpitations. MethodsRetrospective cohort study of 992,526 outpatient visits between January 1, 2017, and December 31, 2021, within an integrated health system, including 356,159 visits for dyspnea, 412,913 for dizziness, and 223,454 for palpitations. We compared the differences in patient characteristics associated with telemedicine visits versus in-office visits, evaluated the referral rates for noninvasive cardiac testing, and examined the association between virtual visits and 30-day clinical outcomes. ResultsAmong 992,526 visits, 71.5% were office visits, 25.8% telephone visits, and 2.7% video visits. Median (IQR) age was 59 (43-72) years, and 63.1% were women. Patient characteristics associated with increased likelihood of virtual visits included younger age, female sex, being non-Hispanic Black, and being from lower-income households. No association was observed between visit types and 30-day cardiovascular hospitalization for patients with dizziness or palpitations. However, for patients with dyspnea, evaluation via virtual visits was associated with a higher risk of 30-day hospitalization for heart failure (aOR: 1.25; 95% CI: 1.16-1.36 for telephone visits; aOR: 1.45; 95% CI: 1.17-1.80 for video visits). Compared to office-based visits, patients with dyspnea were less likely to be referred for echocardiogram with telephone (aOR: 0.73; 95% CI: 0.72-0.75) or video visits (aOR: 0.92; 95% CI: 0.87-0.98). ConclusionsVirtual visits may be appropriate for some clinical concerns but not all. Optimal alignment of clinical conditions with appropriate care modalities is an important component of a successful telemedicine strategy.

Knowledge graph-driven mountain railway alignment optimization integrating karst hazard assessment

Karst hazard is a considerable threat that should be considered in railway alignment design for mountainous regions with dense water systems. Nevertheless, alignment design principles in karst regions have not been systematically studied. Moreover, a quantitative karst hazard assessment model is currently lacking for automated alignment optimization. To solve the above problems, based on the analyses of karst inducing factors and hazard representation, the railway alignment design principles in karst regions are summarized through an event tree. A highly-coupled knowledge graph (called KaRAD-KG) modeling method is proposed. Then, a bi-objective alignment optimization model considering railway construction cost and karst hazard (mainly including hazard components of synclinal karst, anticlinal karst and karst depression) is constructed. To solve the optimization model, a knowledge-driven distance transform algorithm incorporating a karst hazard assessment method and a multicriteria tournament decision method is customized. Finally, the application in a real-world case indicates that the proposed method can generate an alignment which reduces construction cost by 3.39 % and karst hazard by 18.73 % compared to the best manually-designed alternative, which verifies the effectiveness of this method for assisting actual railway alignment design in a karst-dense mountainous region.

ROSHAMBO: Open-Source Molecular Alignment and 3D Similarity Scoring.

Efficient virtual screening techniques are critical in drug discovery for identifying potential drug candidates. We present an open-source package for molecular alignment and 3D similarity calculations optimized for large-scale virtual screening of small molecules. This work parallels widely used proprietary tools and offers an approach complementary to structure-based virtual screening. Our package employs the PAPER software for optimizing molecular alignments based on Gaussian volume overlaps. GPU acceleration is utilized to significantly reduce computational time and resource requirements. After obtaining the optimal alignments between the target and the query molecules, both shape and color (based on pharmacophore features) scores are computed to assess molecular similarity, with aligned molecules optionally being output in sdf format. The package was benchmarked using the DUDE-Z public data sets. Results demonstrated the package's near-state-of-the-art performance and robustness across multiple target classes, with speed that enables many routine ligand-based drug discovery workflows. As an open-source and freely available resource (github.com/molecularinformatics/roshambo) with both a convenient Python API and command line interface, our package also addresses the need for accessible and efficient virtual screening tools in drug discovery.

Pyrene‐Based Self‐Assembled Monolayer with Improved Surface Coverage and Energy Level Alignment for Perovskite Solar Cells

AbstractRecently, the efficiency of p‐i‐n perovskite solar cells drastically increased, a pivotal factor being the incorporation of self‐assembled monolayers (SAMs) as a hole‐transporting layer (HTL). SAMs offer many advantages over conventional HTLs, including minimal material requirements, low cost, and facile processing. Current research is mainly focused on the development of carbazole‐derived SAMs. However, the versatility of organic chemistry allows for the design of SAMs with alternative organic cores that may possess specific benefits. In this study, three novel SAMs are incorporated in p‐i‐n perovskite solar cells, each based on an aromatic core commonly used in organic semiconductors. The novel SAMs vary in their energy level alignment with the perovskite active layer. Optimal alignment is achieved with a pyrene‐based SAM (4PAPyr), resulting in solar cells that outperform the commercially available 2PACz. Moreover, due to improved surface coverage, the use of 4PAPyr leads to a significantly higher number of working solar cell devices when compared to 2PACz, which is of particular interest with regard to upscaling. After device optimization, a power conversion efficiency of 22.2% is achieved with 4PAPyr. This research underlines the importance of diversifying SAMs to unlock further advancements in perovskite solar cell efficiency and scalability.

Posterior Correction and Fusion Using a 4D Anatomical Spinal Reconstruction Technique Improves Postural Stability Under the Eye-Closed Condition in Patients with Adolescent Idiopathic Scoliosis.

Background: Patients with adolescent idiopathic scoliosis (AIS) has been reported to exhibit impaired postural stability. Posterior correction and fusion using four-dimensional (4D) anatomical spinal reconstruction techniques may improve postural stability to correct the spine for optimal anatomical alignment. This prospective study aimed to determine the effect of posterior correction and fusion using a 4D anatomical spinal reconstruction technique on postural stability in the eye-open and eye-closed standing position in patients with thoracic AIS. Methods: Thirty-three patients with AIS, excluding those with Lenke type 5C AIS, participated in the study. The mean and standard deviation of the minimum values of the time-to-boundary (TTB) were determined. All patients were asked to perform the quiet standing position under the eye-open and eye-closed condition on a force plate preoperatively and at 1 week and 2 years postoperatively. The TTB value was calculated from the velocity and distance to the foot boundary of the acquired center-of-pressure data. Results: Under the eye-closed condition, the mean and standard deviation of the minimum TTB were significantly higher at 2 years postoperatively than preoperatively and at 1 week postoperatively. The mean and standard deviation of the minimum TTB values were significantly lower at 1 week postoperatively than preoperatively. Conclusions: The results of this study suggest that surgery using the 4D anatomical spinal reconstruction technique reduces postural stability immediately after surgery; however, it improves postural stability at 2 years compared to the preoperative values.

Electrospinning Aligned SF/Magnetic Nanoparticles-Blend Nanofiber Scaffolds for Inducing Skeletal Myoblast Alignment and Differentiation.

In the realm of skeletal muscle tissue engineering, anisotropic materials that emulate natural tissues show substantial promise. Electrospun scaffolds, mimicking the fibrillar structure of the extracellular matrix, are commonly employed but often fall short in achieving optimal alignment and mechanical strength. Silk fibroin has emerged as a versatile material in tissue engineering, valued for its biocompatibility, mechanical robustness, and biodegradability. However, conventional electrospinning methods of SF result in randomly oriented fibers, limiting their efficacy. In this work, we developed a straightforward method to fabricate directional tissue scaffolds using silk fibroin. By integrating a magnetic field collecting device and incorporating Fe3O4 nanoparticles into the spinning solution, we successfully produced well-aligned silk nanofiber scaffolds. These aligned fibers not only improved scaffold orientation and mechanical properties but also exhibited magnetic responsiveness. The aligned SF scaffolds effectively guided the adhesion, proliferation, and differentiation of mesenchymal stem cells along the fiber direction. Cultured on these scaffolds, myoblast C2C12 cells demonstrated oriented growth, highlighting the potential of aligned SF fibers in advancing skeletal muscle engineering for biomedical applications.

An event tree-based distance transform algorithm for simultaneously determining mountain railway alignments and station locations

The concurrent optimization of railway alignments and station locations (RA&SL) is a complex task, especially for the main railway lines in mountainous regions. The intricate coupling constraints between RA and SL are very challenging for the conventional RA&SL search methods, which consider limited solution types to generate an optimized RA&SL solution. To solve this problem, an event tree-based distance transform (ET-DT) algorithm is proposed. The study area is first divided into grid cells, followed by a preprocessing step to identify infeasible areas for station locations. Next, an event tree (ET) is constructed to represent all the possible solution types during the RA&SL design process. Afterward, in the ET-DT method, a total of eight types of RA&SL search operators are integrated to generate diverse RA&SL alternatives. Ultimately, the proposed method is applied to a realistic case with significantly-undulating terrain. Results show that ET-DT generates 2.8 times more solutions than a contemporary DT-based method (PreDT) and further improves solution quality through an 8.7% reduction in construction cost compared to the best manually-designed alignment, while PreDT only achieves a 5.7% reduction.

Metaheuristics-based multistage iterative optimization framework for decomposed high-speed rail systems planning problem

High-speed rail (HSR) systems planning and decision-making is a large-scale, multistage, intricate problem, where each stage represents a complex sub-problem. The solution approach to the multistage problem needs information exchange across the stages. A non-optimal planning and decision at any stage could yield a sub-optimal HSR system. This study proposes a novel multistage iterative HSR station location and alignment optimization framework (HSLAOF) to solve the main problem by decomposing it into the identification of (a) HSR potential regions and corridor, (b) station location, (c) shortest sequence/corridor of stations, and (d) collision-free alignment (horizontal and vertical) sub-problems. It integrates these sub-problems, which are solved separately using customized artificial intelligence- and motion planning-based metaheuristics such as particle swarm optimization for station location, ant colony optimization for shortest sequence of stations, path planner method for horizontal alignment and exploration, and exploitation-based ant colony optimization for vertical profile. In HSLAOF, the information from the upper and lower stages of the optimization process are exchanged and combined for a holistic optimized HSR system. Application of HSLAOF in the Mumbai-Ahmedabad HSR project yielded a solution that has 14.24 % lower total system cost, no environmental impact, 5.82 % better socio-economic impact, 21.14 % lesser noise and vibration impacted population, and 2.79 % higher station location utility than the one proposed by the experts. For predefined station location, the HSLAOF yielded alignment with 13.90 % lower total system cost and 24.00 % less noise and vibration impacted population than the one developed by experts. It required about 150 min to obtain a solution for each iteration.

GNSS-assisted optimal alignment method for low-cost SINS motion of vehicle

Abstract To improve the alignment accuracy and environmental applicability of the micro-electromechanical system (MEMS)-based strapdown inertial navigation system (SINS), this study proposes a global navigation satellite system (GNSS)-assisted multi-vector determination of the attitude optimal indirect coarse alignment. Using the inertial information output from the inertial measurement unit and the velocity information from the GNSS, a simplified velocity observation vector is constructed and the velocity lever arm stemming from the mounting position inconsistencies of the GNSS and SINS is fed back into the velocity of the carrier system. When constructing the observation vectors, the integration interval is shortened by reconstructing the two-vector integration formula for reducing the cumulative error of the inertial device. The attitude matrix problem is defined as the Wahba problem, which is solved using the singular value decomposition method. Based on the relationship between gyro zero bias and misalignment angle, the corresponding state and measurement equations are designed. Furthermore, owing to the measurement noise uncertainty, the adaptive traceless Kalman filtering algorithm is introduced to realize the effective adaptation processing of the measurement noise. More accurate attitude matrix estimates are obtained by continuously correcting the carrier system transformation matrix. The running car experiment results show that the proposed method exhibits higher alignment accuracy and environmental applicability than the current MEMS strapdown inertial navigation coarse alignment method and the traditional optimization-based alignment method.

Enhanced energy storage performance in NBT-based MLCCs via cooperative optimization of polarization and grain alignment

Dielectric ceramics possess a unique competitive advantage in electronic systems due to their high-power density and excellent reliability. Na1/2Bi1/2TiO3-based ceramics, one type of extensively studied energy storage dielectric, however, often experience A-site element volatilization and Ti4+ reduction during high-temperature sintering. These issues may result in increased energy loss, reduced polarization and low dielectric breakdown electric field, ultimately making it challenging to achieve both high energy storage density and efficiency. To address these issues, we introduce a synergistic optimization strategy that combine polarization engineering and grain alignment engineering. First principles calculations and experimental analyses show that the doping of Mn2+ can suppress the reduction of Ti4+ in Na1/2Bi1/2TiO3-based ceramics and enhance ion off-centering displacements, thereby reducing energy loss and improving polarization. In addition, we prepared multilayer ceramic capacitors with grains oriented along the <111> direction using the template grain growth method. This approach effectively reduces electric-field-induced strain by 37% and markedly enhances breakdown electric field by 42% when compared with nontextured counterpart. As a result of this comprehensive strategy, <111 >-textured Na1/2Bi1/2TiO3-based multilayer ceramic capacitors achieve an ultra-high energy density of 15.7 J·cm−3 and an excellent efficiency beyond 95% at 850 kV·cm−1, exhibiting a superior overall energy storage performance.

Multidisciplinary Design Optimization of Alignment and Whirling Vibration Characteristics of a Submarine Propulsion Shafting Using Kriging Surrogate Model

To improve the performance indexes, such as safety, reliability and acoustic stealth, of a submarine, it is significant to optimize the dynamic characteristics of its propulsion shafting. The alignment state of a shafting has a coupling effect on its whirling vibration characteristics, and the multidisciplinary design optimization (MDO) theory can fully consider the coupling relationships between different disciplines like this, which is a scientific and effective method to achieve the design optimization of shafting dynamics. However, the iterative calculation of high-precision numerical models greatly restricts the optimization efficiency of this method. Aiming at this problem, in this paper, an MDO model was established based on the coupling dynamic analysis of submarine propulsion shafting, and the Kriging surrogate model was used to predict the state variables within each subdiscipline. Along with the reduction of computational expense, the MDO of the alignment and whirling vibration characteristics of the shafting was achieved. The studied results can be applied to the design process of submarine propulsion shafting, which can provide technical and theoretical support for improving the optimization efficiency of its coupling dynamics.

Enhanced SAR Compression through Multi-Look Doppler Compensation and Auto-Focusing Technique.

This paper presents a simple and streamlined compensation technique for improving the quality of synthetic aperture radar (SAR) images based on the Range Doppler Algorithm (RDA). Incorrect Doppler estimation in the space orbit, caused by unexpected radar motion errors, orbit mismatches, and other factors, can significantly degrade SAR image quality. These inaccuracies result in mismatches between the azimuth-matched filter and the received Doppler chirp signal. To address this issue, we propose a Doppler estimation method that leverages the Fractional Fourier Transform (FrFT) and cross-correlation techniques. The received signals are compared with the azimuth-matched filter based on the rotation angle in the FrFT domain, and the Doppler centroid is adjusted to achieve the optimal alignment. This process ensures high correlation values and enhanced resolution in the final SAR image. The efficacy of the proposed technique is validated through experiments using real spaceborne SAR data from the practical satellite. The results demonstrate significant improvements in image quality and resolution compared to conventional algorithms, highlighting the advantages of our approach for various remote sensing applications.

Simultaneous photocatalytic degradation of remdesivir, favipiravir, and diclofenac from aqueous solutions using a quaternary plasmonic Ag/Ag-SG-TiO2-rGO photocatalyst: Synthesis, characterization, optimization, and toxicity assessment

This study presents a novel quaternary plasmonic photocatalyst, Ag/Ag-Sol-Gel(SG)-TiO2-rGO, designed for efficient removal of remdesivir (RDV), favipiravir (FAV), and diclofenac (DCF) as COVID-19 antiviral drugs from water samples. Various characterization techniques were employed to analyze the Ag/Ag-SG-TiO2-rGO nanocomposites, which were synthesized with different Ag to SG-TiO2-molar ratios. The photocatalyst, containing 30 % Ag plasmonic within its framework, exhibited the highest pollutant removal under visible light. This efficiency is attributed to the surface plasmon resonance (SPR) generated by metallic Ag nanoparticles and the optimal energy alignment between the TiO2 conduction band and the rGO work function. Trapping experiments were used to identify the most active species. It was confirmed that O2− and OH were the main active species in the photocatalytic process. The degradation kinetics, following a pseudo-first-order model, was assessed using an optimized LC-MS/MS. An optimization of the photodegradation process was done using a central composite design, as well as a study of the effects of prolonged irradiation. This resulted in the total elimination of the target compounds at a dosage of 0.087 g, irradiation time of 80 min, and pH value of 8. The photodegradation efficiency of sewage treatment plant effluent and tap water was reduced by matrix components, particularly in highly contaminated samples. An additional confirmatory MTT assay revealed a very low viability difference for mouse fibroblast cells, L929, in untreated, treated (97 %) and control samples. This study sheds light on the photodegradation of anti-COVID-19 drugs and offers insights into their remediation in aquatic environments.

Predictive factors for deep medial collateral ligament release in adjusted mechanical alignment total knee arthroplasty

BackgroundTotal knee arthroplasty (TKA) demands precision in achieving optimal alignment and soft tissue balance, especially in cases of medial compartment osteoarthritis where the need for medial soft tissue release is critical yet challenging to ascertain.ObjectiveThis study aims to systematically investigate the relationship between preoperative data, initial knee conditions and the necessity for deep collateral ligament (MCL) release in adjusted mechanical alignment total knee arthroplasty.MethodsWe conducted a retrospective study involving 61 TKA patients who underwent adjusted mechanical alignment robotic-assisted procedures. Soft tissue release was carried out when clinically indicated. We collected and statistically analyzed patient demographics, initial knee conditions, and surgical details.ResultsAmong the patients, 52% required deep MCL release. Notably, patients without soft tissue release exhibited lower initial hip-knee-ankle (HKA) angles, reduced varus-valgus stress test angles, and a greater range of flexion. We identified a predictive threshold HKA angle of 6.250 degrees, demonstrating high sensitivity and specificity for determining the need for deep MCL release.ConclusionThis study underscores the significance of the initial HKA angle and varus-valgus stress tests in predicting deep MCL release during TKA. The established HKA angle threshold simplifies surgical decision-making, reducing the likelihood of unnecessary soft tissue release.

Are "Global Measures" of Psychological Intimate Partner Violence Against Women Really Comparable? A Measurement Invariance Analysis of Controlling Behaviors in 19 Low- and Middle- Income Countries.

Background One third of adult women report lifetime psychological intimate partner violence (IPV). Controlling behavior is a common dimension of psychological IPV; however, evidence is mixed on its cross-national and cross-time measurement invariance, limiting its use to monitor Sustainable Development Goal (SDG) 5.2.1, to eliminate all forms of violence against women. We explored easier-to-modify survey-design features and harder-to-modify individual-level and national-level characteristics that may account for non-invariance of these controlling-behavior items. Methods We analyzed data on five controlling behaviors administered to 373,167 ever-partnered women 15-49 years in 19 low- or middle-income countries in which at least two national Demographic and Health Surveys were administered during 2005-2019. We performed multiple-group confirmatory factor analysis (MGCFA) to test for exact forms of invariance and alignment optimization (AO) to test for approximate invariance across 7-9 survey-design groups, defined by the number of preceding questionnaire modules (to proxy respondent burden) and weeks of interviewer training (to proxy interviewer skills). Adjustment for covariates in the MGCFA assessed whether individual- and national-level characteristics could account for any observed non-invariance across survey-design groups. Results In MGCFA without covariates, configural invariance of the controlling-behavior items was observed across survey-design groups. Exact invariance, partial invariance (with 20% of parameter estimates freed), and approximate invariance were not observed across groups. In adjusted MGCFA, neither woman-level covariates (schooling, attitudes about IPV against women) nor national-level covariates (women's mean schooling, mean attitudes about IPV against women, gender-related legal environment) alone or combined accounted for the non-invariance of controlling-behavior items across survey-design groups. Conclusions Comparing estimates for controlling behavior across country, time, and survey design variations warrants caution. Standardizing questionnaire length and interviewer training may improve the invariance of these items. Other characteristics, like ethnicity and language, may account for the non-invariance of controlling-behavior items across survey-design groups and should be tested. Current controlling-behavior items should be refined to enhance their comparability, and new controlling-behavior items should be identified and tested to improve the item set's content validity. Given current evidence of the high prevalence and health impacts of psychological IPV against women, advancing this research agenda is needed to monitor SDG 5.2.1.

Multi-Functional Silole Hole Transport Layer for Efficient and Stable Lead-Tin Perovskite and Tandem Solar Cells.

Despite high theoretical efficiencies and rapid improvements in performance, high-efficiency ≈1.2eV mixed Sn-Pb perovskite solar cells (PSCs) generally rely on poly(3,4-ethylenedioxythiophene) polystyrenesulfonate (PEDOT: PSS) as the hole transport layer (HTL); a material that is considered to be a bottleneck for long-term stability due to its acidity and hygroscopic nature. Seeking to replace PEDOT: PSS with an alternative HTL with improved atmospheric and thermal stability, herein, a silole derivative (Silole-COOH) tuned with optimal electronic properties and efficient carrier transport by incorporating a carboxyl functional group is designed, which results in an optimal band alignment for hole extraction from Sn-Pb perovskites and robust air and thermal stability. Thin films composed of the Silole-COOH exhibit superior conductivity and carrier mobility compared to PEDOT: PSS, in addition to reduced nonradiative quasi-Fermi-level splitting losses at the HTL/perovskite interface and improved quality of Sn-Pb perovskite. Replacement of PEDOT: PSS with Silole-COOH leads to 23.2%-efficient single-junction Sn-Pb PSCs, 25.8%-efficient all-perovskite tandems, and long operating stability in ambient air.