Optimal Alignment Research Articles

What cultural values determine student self-efficacy? An empirical study for 42 countries and economies.

Self-efficacy is a vital personal characteristic for student success. However, the challenge of cross-cultural comparisons remains as scalar invariance is hard to be satisfied. Also, it is unclear how to contextually understand student self-efficacy in light of cultural values in different countries. This study implements a novel alignment optimization method to rank the latent means of student self-efficacy of 308,849 students in 11,574 schools across 42 countries and economies that participated in the 2018 Program in International Student Assessment. We then used classification and regression trees to classified countries with differential latent means of student self-efficacy into groups according to Hofstede's six cultural dimensions theory. The results of the alignment method recovered that Albania, Colombia, and Peru had students with the highest mean self-efficacy, while Slovak Republic, Moscow Region (RUS), and Lebanon had the lowest. Moreover, the CART analysis indicated a low student self-efficacy for countries presenting three features: (1) extremely high power distance; (2) restraint; and (3) collectivism. These findings theoretically highlighted the significance of cultural values in shaping student self-efficacy across countries and practically provided concrete suggestions to educators on which countries to emulate such that student self-efficacy could be promoted and informed educators in secondary education institutes on the international expansion of academic exchanges.

General and Reliable Azimuthal Alignment Algorithm for Low Loss Multicore Fiber Fusion Splicing

Multicore fiber is a promising spatial division multiplexing technology to increase the transmission bandwidth of optical fiber links in any given available spatial cross section. To connect multicore fibers, similar to single-core fibers, fusion splicing is an indispensable tool. Since multicore fibers cannot be circularly symmetric, precise transverse and azimuthal alignment is crucial to minimize the insertion loss penalty that would originate from even small offsets in the core locations of the two fibers to be spliced together. In this paper, a novel azimuthal alignment algorithm for multicore fiber splicing is presented. Since it is based on side-view images, it can also determine the twist rates of both fibers to be spliced and take these twist rates into account when calculating the optimum azimuthal alignment angle at the very ends of the two fibers. In the case of fibers with markers, i.e., fibers that are not rotationally symmetric, the relative and absolute polarities of the two fiber ends are computed as well. We present the formulation of the azimuthal alignment algorithm and demonstrate its stability and versatility for a wide range of fibers with vastly different geometries, core numbers and twist rates, including an offset single-core fiber. In the case of 4-core fibers with markers, we achieve average splice losses of less than 0.03 dB regardless of the polarity, which is a substantial advantage in terms of real-world applicability in the field. For a twisted 7-core fiber, we demonstrate an accurate twist rate detection with standard deviation < 1.4/m (turns per meter).

Weakly supervised volumetric prostate registration for MRI-TRUS image driven by signed distance map

Image registration is a fundamental step for MRI-TRUS fusion targeted biopsy. Due to the inherent representational differences between these two image modalities, though, intensity-based similarity losses for registration tend to result in poor performance. To mitigate this, comparison of organ segmentations, functioning as a weak proxy measure of image similarity, has been proposed. Segmentations, though, are limited in their information encoding capabilities. Signed distance maps (SDMs), on the other hand, encode these segmentations into a higher dimensional space where shape and boundary information are implicitly captured, and which, in addition, yield high gradients even for slight mismatches, thus preventing vanishing gradients during deep-network training. Based on these advantages, this study proposes a weakly-supervised deep learning volumetric registration approach driven by a mixed loss that operates both on segmentations and their corresponding SDMs, and which is not only robust to outliers, but also encourages optimal global alignment. Our experimental results, performed on a public prostate MRI-TRUS biopsy dataset, demonstrate that our method outperforms other weakly-supervised registration approaches with a dice similarity coefficient (DSC), Hausdorff distance (HD) and mean surface distance (MSD) of 87.3 ± 11.3, 4.56 ± 1.95 mm, and 0.053 ± 0.026 mm, respectively. We also show that the proposed method effectively preserves the prostate gland's internal structure.

Testing the cross-cultural invariance of an extended theory of planned behaviour in predicting biodiversity-conserving behavioural intentions

Besides climate change, the loss of biodiversity due to human activities marks another planetary boundary that we are currently crossing. Cross-culturally invariant measurement instruments are urgently needed to monitor and evaluate the effects of global and national programmes to halt further biodiversity loss. Based on data from Brazil, China, Colombia, India, Indonesia, Kenya, Mexico, Peru, South Africa, Vietnam, and Germany, we tested the cross-cultural invariance of scales operationalizing an extended theory of planned behaviour for the prediction of biodiversity-conserving behavioural intentions. Cross-cultural invariance was tested using the multi-group confirmatory factor analysis and the alignment optimization approaches, whose methodological setup is described and discussed. Results for both methods indicate metric and partial scalar invariance of the used scales, which means that both regression coefficients and latent means can be compared across countries. The resulting scales can be used to both monitor biodiversity-related behavioural intentions and their predictors across different cultures and evaluate interventions to increase these intentions.

A large ensemble illustration of how record-shattering heat records can endure

The record-shattering hot day in the Pacific Northwest in June 2021 is used to motivate a study of record-shattering temperature extremes in a very large hindcast ensemble. The hottest days in the Pacific Northwest in the large ensemble have similar large scale and synoptic patterns to those associated with the observed event. From the perspective of a fixed location, the hottest ensemble days are acutely sensitive to the chance sequencing of a dry period with a precisely positioned weather pattern. These days are thus rare and require very large samples (tens of thousands of years) to capture. The enduring nature of record-shattering heat records can be understood through this lens of weather ‘noise’ and sampling. When a record-shattering event occurs due to chance alignment of weather systems in the optimal configuration, any small sample of years subsequent to the (very unlikely) record event has an extremely low chance of finding yet another chance extreme. While warming of the baseline climate can narrow the gap between more regular extremes and record-shattering extremes, this can take many decades depending on the pace of climate change. Climate models are unlikely to capture record-shattering extremes at fixed locations given by observations unless the model samples are large enough to provide enough weather outcomes to include the optimal weather alignments. This underscores the need to account for sampling in assessing models and changes in weather-sensitive extremes. In particular, climate models are not necessarily deficient in representing extremes if that assessment is based on their absence in undersize samples.

What Can Economics Say about Alzheimer’s Disease?

Alzheimer’s disease (AD) affects one in ten people aged 65 or older and is the most expensive disease in the United States. We describe the central economic questions raised by AD. Although there is overlap with the economics of aging and health, the defining feature of the “economics of Alzheimer’s disease” is an emphasis on choice by cognitively impaired patients that affects health and financial well-being, and situations in which dynamic contracts between patients and caregivers are useful but difficult to enforce. A focus on innovation in AD prevention, treatment, and care is also critical given the enormous social cost of AD and present lack of understanding of its causes, which raises questions of optimal resource allocation and alignment of private and social incentives. The enormous scope for economists to contribute to our understanding of AD-related issues including drug development, efficient care delivery, dynamic contracting, long-term care risk, financial decision-making, and the design of public programs for AD suggests a rich research program for many areas of economics. (JEL G22, G50, I10, I38, J14, L65, O31)

Double-flanged knotless technique for iris prosthesis and IOL implantation associated with keratoplasty.

Anterior segment reconstruction and penetrating keratoplasty combined with iris prosthesis (IP) and intraocular lens (IOL) scleral fixation require prolonged open-sky surgery and complex suturing. Herein we present a novel double-flanged knotless surgical technique that minimizes the open sky duration and facilitates the fixation of the IP and IOL complex to the sclera. After corneal trephination and removal, a temporary keratoprosthesis is fixated. Three 5.0 polypropylene suture segments are introduced in the anterior chamber transconjunctivally and then externalized through keratoprosthesis. Each suture is threaded through the eyelets of the IP and then flanged. The temporary keratoprosthesis is removed, and the IP and IOL complex is positioned in the sulcus. A donor cornea button is sutured in place and the IP is centred on the optical axis by adjusting the polypropylene sutures. Finally, the suture ends are shortened, flanged, and buried under the conjunctiva. Surgery was performed on three eyes of three patients. No intraoperative complications occurred, while cystoid macular edema and ocular hypertension occurred in two patients during the follow-up period. The best corrected visual acuity was 6/20, 8/20, and 13/20. So far the IPs remained stable in the three eyes with a maximum follow-up of 18 months. This novel technique of penetrating keratoplasty combined with an intraocular lens (IOL) and iris prosthesis implantation makes it possible to reduce open sky surgery time, avoid complex suturing, and ensure optimal IOL visual axis alignment by adjusting suture tension.

Improving outcomes in adult spinal deformity surgery

Proximal junctional kyphosis and failure are important complications in reconstructive spine surgery. The impact of proximal junctional pathology on health status is variable, and junctional failure may involve compromise of neural and physical function, and may require revision surgery. The risk factors for proximal junctional kyphosis include multilevel fusion to the sacrum, malalignment of the spine, choice of upper instrumented vertebra, magnitude of realignment, bone and muscle quality, tension band integrity and characteristics of the unfused spine. The pathophysiology of proximal junctional pathology involve fracture and bony failure, ligamentous and soft tissue failure, and combined bone and soft tissue failure. Prevention of proximal junctional pathology is an important goal, and has a significant impact on improving the outcomes and durability of spinal reconstructive surgery. Prevention strategies are derived from an understanding of the underlying causes of junctional pathology. Preoperative planning to determine optimal post-operative alignment, and intraoperative strategies to achieve that alignment are important for prevention of junctional pathology. Preoperative preparation of the patient with optimization of bone quality, extensor muscle strength and body mass index may prevent junctional complications. Surgical strategies including anterior column load sharing and posterior augmentation of fixation are useful for prevention of junctional pathology. Cement augmentation at the upper instrumented vertebra, with possible inclusion of the next cephalad vertebra may be protective of bone failure. Ligamentoplasty and preservation of the tension band may be protective of soft tissue failure. Proximal junctional pathology remains an important complication in spinal reconstructive surgery. Understanding the factors associated with proximal junctional pathology including the mechanisms underlying junctional kyphosis, and awareness of the strategies for avoidance of junctional pathology will empower the surgeon to reduce the risk of post-operative junctional kyphosis and lead to improved outcomes in adult spinal deformity surgery.

Data-aware conformance checking with SMT

Conformance checking is a key process mining task to confront the normative behavior imposed by a process model with the actual behavior recorded in a log. While this problem has been extensively studied for pure control-flow processes, data-aware conformance checking has received comparatively little attention. In this paper, we tackle the conformance checking problem for the challenging scenario of processes that combine data and control-flow dimensions. Concretely, we adopt the formalism of data Petri nets (DPNs) and show how solid, well-established automated reasoning techniques from the area of Satisfiability Modulo Theories (SMT) can be effectively harnessed to compute conformance metrics and optimal data-aware alignments. To this end, we introduce the CoCoMoT (Computing Conformance Modulo Theories) framework, with a fourfold contribution. First, we show how SMT allows to leverage SAT-based encodings for the pure control-flow setting to the data-aware case. Second, we introduce a novel preprocessing technique based on a notion of property-preserving clustering, to speed up the computation of conformance checking outputs. Third, we show how our approach extends seamlessly to the more comprehensive conformance checking artifacts of multi- and anti-alignments. Fourth, we describe a proof-of-concept implementation based on state-of-the-art SMT solvers, and report on experiments. Finally, we discuss how CoCoMoT directly lends itself to further process mining tasks like log analysis by clustering and model repair, and the use of SMT facilitates the support of even richer multi-perspective models, where, for example, more expressive DPN guards languages are considered or generic datatypes (other than integers or reals) are employed.

Ferromagnetic single-atom spin catalyst for boosting water splitting.

Heterogeneous single-atom spin catalysts combined with magnetic fields provide a powerful means for accelerating chemical reactions with enhanced metal utilization and reaction efficiency. However, designing these catalysts remains challenging due to the need for a high density of atomically dispersed active sites with a short-range quantum spin exchange interaction and long-range ferromagnetic ordering. Here, we devised a scalable hydrothermal approach involving an operando acidic environment for synthesizing various single-atom spin catalysts with widely tunable substitutional magnetic atoms (M1) in a MoS2 host. Among all the M1/MoS2 species, Ni1/MoS2 adopts a distorted tetragonal structure that prompts both ferromagnetic coupling to nearby S atoms as well as adjacent Ni1 sites, resulting in global room-temperature ferromagnetism. Such coupling benefits spin-selective charge transfer in oxygen evolution reactions to produce triplet O2. Furthermore, a mild magnetic field of ~0.5 T enhances the oxygen evolution reaction magnetocurrent by ~2,880% over Ni1/MoS2, leading to excellent activity and stability in both seawater and pure water splitting cells. As supported by operando characterizations and theoretical calculations, a great magnetic-field-enhanced oxygen evolution reaction performance over Ni1/MoS2 is attributed to a field-induced spin alignment and spin density optimization over S active sites arising from field-regulated S(p)-Ni(d) hybridization, which in turn optimizes the adsorption energies for radical intermediates to reduce overall reaction barriers.

Joint learning of text alignment and abstractive summarization for long documents via unbalanced optimal transport

Abstract Recently, neural abstractive text summarization (NATS) models based on sequence-to-sequence architecture have drawn a lot of attention. Real-world texts that need to be summarized range from short news with dozens of words to long reports with thousands of words. However, most existing NATS models are not good at summarizing long documents, due to the inherent limitations of their underlying neural architectures. In this paper, we focus on the task of long document summarization (LDS). Based on the inherent section structures of source documents, we divide an abstractive LDS problem into several smaller-sized problems. In this circumstance, how to provide a less-biased target summary as the supervision for each section is vital for the model’s performance. As a preliminary, we formally describe the section-to-summary-sentence (S2SS) alignment for LDS. Based on this, we propose a novel NATS framework for the LDS task. Our framework is built based on the theory of unbalanced optimal transport (UOT), and it is named as UOTSumm. It jointly learns three targets in a unified training objective, including the optimal S2SS alignment, a section-level NATS summarizer, and the number of aligned summary sentences for each section. In this way, UOTSumm directly learns the text alignment from summarization data, without resorting to any biased tool such as ROUGE. UOTSumm can be easily adapted to most existing NATS models. And we implement two versions of UOTSumm, with and without the pretrain-finetune technique. We evaluate UOTSumm on three publicly available LDS benchmarks: PubMed, arXiv, and GovReport. UOTSumm obviously outperforms its counterparts that use ROUGE for the text alignment. When combined with UOTSumm, the performance of two vanilla NATS models improves by a large margin. Besides, UOTSumm achieves better or comparable performance when compared with some recent strong baselines.

A Review of Alignment Optimization Research for Roads, Railways and Rail Transit Lines

Roads, railways and rail transit lines play major roles in transporting passengers and freight. In the design process for such transportation infrastructures, the alignment determination greatly affects their life-cycle performances. However, due to the great complexity associated with alignment design, conventional manual work is very time-consuming and laborious, which consequently prompts the flourishing development of intelligent alignment optimization (AO). Hitherto, with considerable invested efforts, numerous remarkable AO studies have been reported. In this work, we present the first-known literature review paper in this field from the past 25 years. First, a bibliometric visualization is conducted to show the overall characteristics of AO research. Then, existing mathematical models that formulate AO problems are reviewed. Particularly, GIS-based applications for AO are also analyzed in that part. Afterward, the intelligent solution methodologies for solving AO models are discussed. Moreover, two specific research topics, i.e., concurrent optimization of railroad alignments and station locations as well as the existing alignment recreation and redesign, are provided. Finally, we propose 12 possible research extensions and directions in this realm.

Evaluating the optimum nanofiber alignment in conductive composites with a stereology-based anisotropic degree

Rationally tuning the anisotropic degree of orientation distribution for conductive fibers in composites can maximize the macro electrical conductivity in a specific direction. However, quantitative evaluation of the optimum anisotropic degree of networks with fibers of different shapes and orientation distributions remains largely unexplored. In this work, the optimum fiber orientation distribution at the maximum electrical conductivity is quantified by a newly proposed stereology-based anisotropic degree. This index applies to both straight and curved fiber networks and has one-to-one corresponding relation with the macro electrical properties. Using Monte Carlo simulations, it is found that with the increase of anisotropic degree, the electrical conductivity increases to its maximum and then decreases gradually, which shows good agreement with experimental results. Further, a universal expression to determine the optimum anisotropic degrees of networks at different fiber concentrations is obtained, which is independent of the curliness and orientation distribution laws of fibers.

Time series cluster analysis reveals individual assignment of microbiota in captive tiger (Panthera tigris) and wildebeest (Connochaetes taurinus).

Fecal microbiota variability and individuality are well studied in humans and also in farm animals (related to diet- or disease-specific influences), but very little is known for exotic zoo-housed animals. This includes a wide range of species that differ greatly in microbiota composition and variation. For example, herbivorous species show a very similar and constant fecal microbiota over time, whereas carnivorous species appear to be highly variable in fecal microbial diversity and composition. Our objective was to determine whether species-specific and individual-specific clustering patterns were observed in the fecal microbiota of wildebeest (Connochaetes taurinus) and tigers (Panthera tigris). We collected 95 fecal samples of 11 animal individuals that were each sampled over eight consecutive days and analyzed those with Illumina MiSeq sequencing of the V3-V4 region of the 16SrRNA gene. In order to identify species or individual clusters, we applied two different agglomerative hierarchical clustering algorithms - a community detection algorithm and Ward's linkage. Our results showed that both, species-specific and individual-specific clustering is possible, but more reliable results were achieved when applying dynamic time warping which finds the optimal alignment between different time series. Furthermore, the bacterial families that distinguish individuals from each other in both species included daily occurring core bacteria (e.g., Acidaminococcaceae in wildebeests or Clostridiaceae in tigers) as well as individual dependent and more fluctuating bacterial families. Our results suggest that while it is necessary to consider multiple consecutive samples per individual, it is then possible to characterize individual abundance patterns in fecal microbiota in both herbivorous and carnivorous species. This would allow establishing individual microbiota profiles of animals housed in zoos, which is a basic prerequisite to quickly detect deviations and use microbiome analysis as a non-invasive and cost-effective tool in animal welfare.

End-to-end BIM-based optimization for dual-objective road alignment design with driving safety and construction cost efficiency

Road alignment design is crucial to ensure driving safety. The application of BIM technology increases efficiency and reliability in the road design process. However, it is challenging to consider multiple factors in BIM-based road alignment design. This study proposed an optimization design framework considering driving safety and road construction costs using BIM. A fast and reliable parameterization method was developed for road alignment. The BIM technique was used for modeling and earthworks statistics. The automated driving simulation was performed using MATLAB to quantify driving safety, and NSGA-II was used to solve the optimal alignment. The entire data interaction procedure is end-to-end. The framework was applied to the design project of the Phnom Penh-Sihanoukville highway. The proposed optimization method results show a combined improvement of 6.6% compared to the expert design results.

Coronal and Sagittal Component Position in Contemporary Total Knee Arthroplasty: Targeting Native Alignment Optimizes Clinical Outcomes

BackgroundAdvanced technologies, like robotics, provide enhanced precision for implanting total knee arthroplasty components; however, optimal component position and limb alignment remain unknown. This study sought to identify sagittal and coronal alignment targets that correlate with minimal clinically important differences (MCIDs) in patient-reported outcome measures (PROMs). MethodsA total of 1,311 consecutive total knee arthroplasties were retrospectively reviewed. Posterior tibial slope (PTS), femoral flexion (FF), and tibio-femoral alignment (TFA) were measured radiographically. Patients were grouped based on whether they achieved multiple MCIDs for PROM scores. Classification and regression tree machine learning models were utilized to identify optimal alignment zones. The mean follow-up was 2.4 years (range, 1 to 11). ResultsThe change in PTS and postoperative TFA were most predictive for achieving MCIDs in 90% of the models. Approximating native PTS within 4° correlated with MCID achievement and superior PROMs. Preoperative varus and neutral aligned knees were more likely to meet MCIDs and superior PROM scores when not overcorrected into valgus postoperatively (≥7°). Preoperative valgus-aligned knees correlated with MCID achievement when postoperative TFA was not overcorrected into substantial varus (<0°). Albeit less impactful, FF ≤ 7° correlated with MCID achievement and superior PROMs regardless of preoperative alignment. Sagittal and coronal alignment measurements had moderate to strong interactions in 13 of 20 models. ConclusionOptimized PROM MCIDs correlated with approximating native PTS while maintaining similar preoperative TFA and incorporating moderate FF. Study findings demonstrate interactions between sagittal and coronal alignment which may optimize PROMs, highlighting the importance of three-dimensional implant alignment targets. Level of EvidenceIII.

In Silico Study in MPO and Molecular Docking of the Synthetic Drynaran Analogues Against the Chronic Tinnitus: Modulation of the M1 Muscarinic Acetylcholine Receptor.

Tinnitus is a syndrome that affects the human auditory system and is characterized by a perception of sounds in the absence of acoustic stimuli, or in total silence. Research indicates that muscarinic acetylcholine receptors (mAChRs), especially the M1 type, have a fundamental role in the alterations of auditory perceptions of tinnitus. Here, a series of computer-aided tools were used, from molecular surface analysis software to services available on the web for estimating pharmacokinetics and pharmacodynamics. The results infer that the low lipophilicity ligands, that is, the 1a-d alkyl furans, present the best pharmacokinetic profile, as compounds with an optimal alignment between permeability and clearance. However, only ligands 1a and 1b have properties that are safe for the central nervous system, the site of cholinergic modulation. These ligands showed similarity with compounds deposited in the European Molecular Biology Laboratory chemical (ChEMBL) database acting on the mAChRs M1 type, the target selected for the molecular docking test. The simulations suggest that the 1g ligand can form the ligand-receptor complex with the best affinity energy order and that, together with the 1b ligand, they are competitive agonists in relation to the antagonist Tiotropium, in addition to acting in synergism with the drug Bromazepam in the treatment of chronic tinnitus.

The effect of hydrogen on the properties of Mg0.1Zn0.9O thin film

Opto-electrical properties of MgxZn1−xO can be tuned by adjusting the value of x, but phase separation occurs when x is greater than 0.4. Hydrogen acts as a shallow donor in MgxZn1−xO and can play an important role in tuning the opto-electrical properties in a way that avoids phase separation. Mg0.1Zn0.9O (MZO) films were prepared at different hydrogen partial pressures and their structures and properties were studied. XRD results show that the MZO film has a wurtzite structure with a preferential orientation along the c-axis, but the crystallinity declines with increasing hydrogen partial pressure. Stress in the MZO film changes from tensile to compressive as the hydrogen partial pressure increases. Increasing the hydrogen partial pressure improves the conductivity and increases the optical bandgap, but the electronic affinity of MZO decreases, according to ultraviolet photoelectron spectroscopy results. These key parameters were used to simulate a device with a TCO/MZO/CdTe/ZnTe:Cu type structure, in which TCO is the transparent conductive oxide. The highest efficiency of 17.37% was achieved when the electron affinity of the MZO film was 3.71 eV, corresponding to a spark-like band offset of 0.29 eV at the MZO/CdTe interface. These results suggest that the electron affinity of MZO can be tuned to achieve an optimal band alignment in the device.

Robust full-waveform inversion based on automatic differentiation and differentiable dynamic time warping

AbstractFull waveform inversion is a methodology that determines high-resolution parameters. The widely used L2-norm misfit function has local minima if the low wavenumber components are not accurate. Suffering from a cycle skipping problem, the solution of waveform inversion will be trapped in the local minima. Dynamic time warping aims to find an optimal alignment between two signals, which is a more robust measure to avoid cycle-skipping challenges. However, the discontinuity makes the conventional dynamic time warping distance unsuitable for waveform inversion. We introduce a soft dynamic time warping distance as the misfit function, which is differentiable in that the inverted solution can converge to the accurate global minimum. We compare the convexity of the L2-norm and soft dynamic time warping distance and show that the soft dynamic time warping distance has a wider convexity range with different time shift and amplitudes. It can alleviate the half-wavelength limitation of the conventional L2-norm. We calculate the gradient using the automatic differentiation technique and the minibatch strategy and then analyse the alignment paths of different smooth parameters. A significant smooth parameter γ makes the Soft-DTW distance tending to the L2-norm, which generates new local minima. We recommend a small smooth parameter to ensure the convexity of the Soft-DTW distance. Numerical examples show that the soft dynamic time warping can effectively reconstruct the deep velocity parameters of the BG Compass and Marmousi models with noise robustness and lower dependence on the initial model.

Tetrabutylammonium Bromide Functionalized Ti3C2Tx MXene as Versatile Cathode Buffer Layer for Efficient and Stable Inverted Perovskite Solar Cells

Abstract2D Ti3C2Tx MXene, possessing facile preparation, high electrical conductivity, flexibility, and solution processability, shows good application potential for enhancing device performance of perovskite solar cells (PVSCs). In this study, tetrabutylammonium bromide functionalized Ti3C2Tx (TBAB‐Ti3C2Tx) is developed as cathode buffer layer (CBL) to regulate the PCBM/Ag cathode interfacial property for the first time. By virtue of the charge transfer from TBAB to Ti3C2Tx demonstrated by electron paramagnetic resonance and density functional theory, the TBAB‐Ti3C2Tx CBL with high electrical conductivity exhibits significantly reduced work function of 3.9 eV, which enables optimization of energy level alignment and enhancement of charge extraction. Moreover, the TBAB‐Ti3C2Tx CBL can effectively inhibit the migration of iodine ions from perovskite layer to Ag cathode, which synergistically suppresses defect states and reduce charge recombination. Consequently, utilizing MAPbI3 perovskite without post‐treatment, the TBAB‐Ti3C2Tx based device exhibits a dramatically improved power conversion efficiency of 21.65% with significantly improved operational stability, which is one of the best efficiencies reported for the devices based on MAPbI3/PCBM with different CBLs. These results indicate that TBAB‐Ti3C2Tx shall be a promising CBL for high‐performance inverted PVSCs and inspire the further applications of quaternary ammonium functionalized MXenes in PVSCs.