Dynamic Alignment Research Articles

Mostly Automated Proof Repair for Verified Libraries

The cost of maintaining formally specified and verified software is widely considered prohibitively high due to the need to constantly keep code and the proofs of its correctness in sync—the problem known as proof repair . One of the main challenges in automated proof repair for evolving code is to infer invariants for a new version of a once verified program that are strong enough to establish its full functional correctness. In this work, we present the first proof repair methodology for higher-order imperative functions, whose initial versions were verified in the Coq proof assistant and whose specifications remained unchanged. Our proof repair procedure is based on the combination of dynamic program alignment, enumerative invariant synthesis, and a novel technique for efficiently pruning the space of invariant candidates, dubbed proof-driven testing , enabled by the constructive nature of Coq’s proof certificates. We have implemented our approach in a mostly-automated proof repair tool called Sisyphus. Given an OCaml function verified in Coq and its unverified new version, Sisyphus produces a Coq proof for the new version, discharging most of the new proof goals automatically and suggesting high-confidence obligations for the programmer to prove for the cases when automation fails. We have evaluated Sisyphus on 10 OCaml programs taken from popular libraries, that manipulate arrays and mutable data structures, considering their verified original and unverified evolved versions. Sisyphus has managed to repair proofs for all those functions, suggesting correct invariants and generating a small number of easy-to-prove residual obligations.

Optimising for Interpretability: Convolutional Dynamic Alignment Networks.

We introduce a new family of neural network models called Convolutional Dynamic Alignment Networks (CoDA Nets), which are performant classifiers with a high degree of inherent interpretability. Their core building blocks are Dynamic Alignment Units (DAUs), which are optimised to transform their inputs with dynamically computed weight vectors that align with task-relevant patterns. As a result, CoDA Nets model the classification prediction through a series of input-dependent linear transformations, allowing for linear decomposition of the output into individual input contributions. Given the alignment of the DAUs, the resulting contribution maps align with discriminative input patterns. These model-inherent decompositions are of high visual quality and outperform existing attribution methods under quantitative metrics. Further, CoDA Nets constitute performant classifiers, achieving on par results to ResNet and VGG models on e.g. CIFAR-10 and TinyImagenet. Lastly, CoDA Nets can be combined with conventional neural network models to yield powerful classifiers that more easily scale to complex datasets such as Imagenet whilst exhibiting an increased interpretable depth, i.e., the output can be explained well in terms of contributions from intermediate layers within the network.

Investigating the strategic IT alignment process with a dynamic capabilities view: A multiple case study

In the turbulent business environments brought about by the digital age, strategic IT alignment remains at the forefront of managers’ concerns, raising important issues for researchers. One of these issues is to further understand how firms enact their IT alignment processes and what IT and non-IT capabilities are required to support these processes. To understand this issue, we conducted four case studies in small and medium-sized enterprises (SMEs). Anchored in a dynamic capability-based view, our findings unveil how three 2nd-order, six 1st-order dynamic IT alignment capabilities, and other IT and non-IT capabilities coherently interact to support the firm's business objectives.

An Object Detection Method Based on Feature Uncertainty Domain Adaptation for Autonomous Driving

The environment perception algorithm in autonomous driving is trained in the source domain, leading to domain drift and reduced detection accuracy in the target domain due to shifts in background feature distribution. To address this issue, a domain adaptive object detection algorithm based on feature uncertainty is proposed, which can improve the detection performance of object detection algorithms in unlabeled data. Firstly, a local alignment module based on channel information is proposed, which can obtain the model’s uncertainty about different domain data based on the feature channels obtained through the feature extraction network, achieving adaptive dynamic local alignment. Secondly, an instance-level alignment module guided by local feature uncertainty is proposed, which can obtain the corresponding instance-level uncertainty through ROI mapping. To improve the domain invariance of bounding box regression, a multi-class, multi-regression instance-level uncertainty alignment module is proposed, which can achieve spatial decoupling of classification and regression tasks, further improving the model’s domain adaptive ability. Finally, the effectiveness of the proposed algorithm is validated on Cityscapes, KITTI, and real vehicle data.

Is dynamic spino-pelvic alignment during gait associated with lumbar function in patients with degenerative lumbar spinal stenosis?

IntroductionStatic spine and pelvic posture has been reported to be associated with symptoms in patients with lumbar spinal stenosis (LSS), but it is unknown whether dynamic alignment of the spine and pelvis is associated with lumbar function in daily life. This study aims to investigate the relationship between dynamic alignment of the spine and pelvis during gait and lumbar function in daily life in patients with LSS. MethodsWe evaluated lumbar function in daily life using the Oswestry Disability Index (ODI), trunk and hip muscle strength as physical function, static spinal alignment, and dynamic spinal/pelvic alignment during gait. The relationship between the ODI score and physical function or static and dynamic alignment was examined. ResultsA total of 35 preoperative patients with LSS participated in this study. ODI score significantly correlated with trunk extension strength (r = −0.578, p = 0.000), hip extension strength (r = −0.472, p = 0.004), maximum spinal flexion angle during gait (r = −0.473, p = 0.004) and maximum pelvic anterior tilt angle (r = 0.510, p = 0.002). Multiple regression analysis showed that trunk extension strength (standardized β; - 0.309), hip extension strength (standardized β; −0.287), maximum spinal flexion angle (standardized β; - 0.306) and maximum pelvic anterior tilt angle (standardized β; 0.271) significantly affected the ODI score, with adjusted coefficient of determination of 0.529. ConclusionThe results of this study showed that the patients with LSS with weak hip or trunk extensor muscles, a greater angle of pelvic tilt or a less spinal flexion during gait had a lower lumbar function in daily life.

A new profiling approach for DNA sequences based on the nucleotides' physicochemical features for accurate analysis of SARS-CoV-2 genomes

BackgroundThe prevalence of the COVID-19 disease in recent years and its widespread impact on mortality, as well as various aspects of life around the world, has made it important to study this disease and its viral cause. However, very long sequences of this virus increase the processing time, complexity of calculation, and memory consumption required by the available tools to compare and analyze the sequences.ResultsWe present a new encoding method, named PC-mer, based on the k-mer and physic-chemical properties of nucleotides. This method minimizes the size of encoded data by around 2 k times compared to the classical k-mer based profiling method. Moreover, using PC-mer, we designed two tools: 1) a machine-learning-based classification tool for coronavirus family members with the ability to recive input sequences from the NCBI database, and 2) an alignment-free computational comparison tool for calculating dissimilarity scores between coronaviruses at the genus and species levels.ConclusionsPC-mer achieves 100% accuracy despite the use of very simple classification algorithms based on Machine Learning. Assuming dynamic programming-based pairwise alignment as the ground truth approach, we achieved a degree of convergence of more than 98% for coronavirus genus-level sequences and 93% for SARS-CoV-2 sequences using PC-mer in the alignment-free classification method. This outperformance of PC-mer suggests that it can serve as a replacement for alignment-based approaches in certain sequence analysis applications that rely on similarity/dissimilarity scores, such as searching sequences, comparing sequences, and certain types of phylogenetic analysis methods that are based on sequence comparison.

Point-and-Shoot All-in-Focus Photo Synthesis From Smartphone Camera Pair

All-in-Focus (AIF) photography is expected to be a commercial selling point for modern smartphones. Standard AIF synthesis requires manual, time-consuming operations such as focal stack compositing, which is unfriendly to ordinary people. To achieve point-and-shoot AIF photography with a smartphone, we expect that an AIF photo can be generated from one shot of the scene, instead of from multiple photos captured by the same camera. Benefiting from the multi-camera module in modern smartphones, we introduce a new task of AIF synthesis from main (wide) and ultra-wide cameras. The goal is to recover sharp details from defocused regions in the main-camera photo with the help of the ultra-wide-camera one. The camera setting poses new challenges such as parallax-induced occlusions and inconsistent color between cameras. To overcome the challenges, we introduce a predict-and-refine network to mitigate occlusions and propose dynamic frequency-domain alignment for color correction. To enable effective training and evaluation, we also build an AIF dataset with 2686 unique scenes. Each scene includes two photos captured by the main camera, one photo captured by the ultra-wide camera, and a synthesized AIF photo. Results show that our solution, termed EasyAIF, can produce high-quality AIF photos and outperforms strong baselines quantitatively and qualitatively. For the first time, we demonstrate point-and-shoot AIF photo synthesis successfully from main and ultra-wide cameras.

A new dawn? The United Kingdom’s new competition law regime for vertical agreements

On 1 June 2022, competition law practitioners in the UK were placed in the unenviable position of having to assimilate two new regimes for the treatment of vertical agreements under, respectively, European Union and UK competition law. Despite the long lead-up, which in the case of the EU reforms had lasted since October 2018, practitioners had less than a month to assimilate the final text of both the new EU Vertical Agreements Block Exemption Regulation and the UK’s Vertical Agreements Block Exemption Order before they entered into force. Indeed, the Competition and Markets Authority’s Guidance on the new UK regime was only available six weeks after the new Order came into effect. Despite the new UK regime being promoted as being based on ‘bespoke rules better suited to the UK’, the reality is that its final form reflects a carefully balanced review by the CMA that prioritized close alignment with the EU over divergence for its own sake. Although there are some notable differences between the two regimes, which are reviewed in this article, the overall outcome is one of dynamic alignment with an EU regime that provided the original model for modern UK competition law and looks likely to have a dominant influence on its development for the foreseeable future, despite Brexit.

Performance in field-tests and dynamic knee valgus in soccer players psychologically ready and not ready to return to sports after ACL reconstruction

BackgroundThe objective was to compare the performance in field tests, dynamic knee valgus, knee function, and kinesiophobia of soccer players who were psychologically ready and not ready to return to unrestricted training or competitions after ACL reconstruction. MethodsThirty-five male soccer players who had undergone primary ACL reconstruction at least 6 months were divided based on the Anterior Cruciate Ligament Return to Sport after Injury (ACL-RSI) questionnaire score into ready (≥60) and not-ready (<60) groups. The modified Illinois change of direction test (MICODT) and reactive agility test (RAT) were used to impose the demand for directional change and reactive decision-making. We assessed the frontal plane knee projection angle (FPKPA) during a single-leg squat and distance in crossover hop test (CHD). In addition, we assessed kinesiophobia through the shortened version of the Tampa Scale of Kinesiophobia (TSK-11) and knee function using the International Knee Documentation Committee Subjective Knee Form (IKDC). Independent t-tests were used to compare the groups. ResultsThe not-ready group had lower performance on the MICODT (effect size (ES) = −1.2; p < 0.001) and RAT (ES = −1.1; p = 0.004) tests and higher FPKPA (ES = 1.5; p < 0.001). In addition, they presented lower IKDC (ES = 3.1; p < 0.001) and higher TSK-11 (ES = −3.3; p < 0.001) scores. ConclusionsPhysical and psychological deficits may persist in some individuals after rehabilitation. On-field tests and dynamic knee alignment evaluation should be included in the athlete evaluation before the decision-making about clearance to sports participation, especially in athletes who perceive themselves as psychologically not ready.

Image Style Transfer Based on Dynamic Convolutional Manifold Alignment of Halo Attention

The objective of image style transfer is to render an image with artistic features of a style reference while preserving the details of the content image. With the development of deep learning, many arbitrary style transfer methods have emerged. From the recent arbitrary style transfer algorithms, it has been found that the images generated suffer from the problem of poorly stylized quality. To solve this problem, we propose an arbitrary style transfer algorithm based on halo attention dynamic convolutional manifold alignment. First, the features of the content image and style image are extracted by a pre-trained VGG encoder. Then, the features are extracted by halo attention and dynamic convolution, and then the content feature space and style feature space are aligned by attention operations and spatial perception interpolation. The output is achieved through dynamic convolution and halo attention. During this process, multi-level loss functions are used, and total variation loss is introduced to eliminate noise. The manifold alignment process is then repeated three times. Finally, the pre-trained VGG decoder is used to output the stylized image. The experimental results show that our proposed method can generate high-quality stylized images, achieving values of 33.861, 2.516, and 3.602 for ArtFID, style loss, and content loss, respectively. A qualitative comparison with existing algorithms showed that it achieved good results. In future work, we will aim to make the model lightweight.

A Method Based on Temporal Embedding for the Pairwise Alignment of Dynamic Networks

In network analysis, real-world systems may be represented via graph models, where nodes and edges represent the set of biological objects (e.g., genes, proteins, molecules) and their interactions, respectively. This representative knowledge-graph model may also consider the dynamics involved in the evolution of the network (i.e., dynamic networks), in addition to a classic static representation (i.e., static networks). Bioinformatics solutions for network analysis allow knowledge extraction from the features related to a single network of interest or by comparing networks of different species. For instance, we may align a network related to a well known species to a more complex one in order to find a match able to support new hypotheses or studies. Therefore, the network alignment is crucial for transferring the knowledge between species, usually from simplest (e.g., rat) to more complex (e.g., human). Methods: In this paper, we present Dynamic Network Alignment based on Temporal Embedding (DANTE), a novel method for pairwise alignment of dynamic networks that applies the temporal embedding to investigate the topological similarities between the two input dynamic networks. The main idea of DANTE is to consider the evolution of interactions and the changes in network topology. Briefly, the proposed solution builds a similarity matrix by integrating the tensors computed via the embedding process and, subsequently, it aligns the pairs of nodes by performing its own iterative maximization function. Results: The performed experiments have reported promising results in terms of precision and accuracy, as well as good robustness as the number of nodes and time points increases. The proposed solution showed an optimal trade-off between sensitivity and specificity on the alignments produced on several noisy versions of the dynamic yeast network, by improving by ∼18.8% (with a maximum of 20.6%) the Area Under the Receiver Operating Characteristic (ROC) Curve (i.e., AUC or AUROC), compared to two well known methods: DYNAMAGNA++ and DYNAWAVE. From the point of view of quality, DANTE outperformed these by ∼91% as nodes increase and by ∼75% as the number of time points increases. Furthermore, a ∼23.73% improvement in terms of node correctness was reported with our solution on real dynamic networks.

Theoretical calculation method for critical buckling load of locally stiffened U-shaped steel sheet pile using the dynamic coordination coefficient method

In order to solve the problem that U-shaped steel sheet piles (USSSPs) are prone to buckling when inserted, we propose a local stiffened U-shaped steel sheet pile destabilization critical load calculation method, namely ‘dynamic alignment coefficient method’, and analyze the influence of stiffening area, stiffening position and number of stiffening plates on the stiffening effect.The study shows that when the total stiffening area is certain, there is a scheme of stiffening plate arrangement to maximize the critical load value of USSSPs with determined length,and reveals the law of local instability caused by the small width of single stiffening plate when the number of blocks is too large. The critical load value of the member can be increased by 13.55% with the variation of the single stiffener plate arrangement position for 10 m long USSSPs, and the optimized theoretical scheme of stiffener plate arrangement for 10 m and 30 m long USSSPs with different total stiffener area is obtained.

Multivariate clustering for maximizing the small cell users’ performance based on the dynamic interference alignment

Multivariate clustering for maximizing the small cell users’ performance based on the dynamic interference alignment

Not so silent partners: Exploring the interconnected roles of entrepreneurs and their spouses

When launching their ventures, the majority of entrepreneurs are married. Yet, our understanding of the spousal influence on the entrepreneurial process remains limited. This is surprising considering the spouse represents one of the most influential figures in an individual's life. Through an inductive qualitative analysis of 18 spouse-entrepreneur pairs, we explore the interactive nature of venture-related roles between the spousal couple and how these spousal roles evolve over the course of the venture. Our study shows that the dynamic alignment between entrepreneurial roles and spousal roles allows the venture to progress through various stages of firm innovation, creation, and growth. Thus, our paper extends the broader literature on roles during the venturing process as we illuminate the “not-so-silent role” of spouses in entrepreneurship.

Influence of long-span bridge deformation on driving quality of high-speed trains

ABSTRACT Bridge time-varying deformation is the time-spatial dynamic deformation of a bridge excited by train motion, which serves as the direct alignment affecting a train’s dynamic response and usually moves ahead of the train. In this study, we investigated the influence of the bridge time-varying deformation on the vertical acceleration of a train with 16 cars on a long-span suspension bridge through the train-track-bridge coupled vibration analysis and chord measurements of dynamic spatial alignment. The analysis and measurements reveal the mechanism of the influence of different bridge positions on the car-body acceleration of different cars. Furthermore, we developed a simple method to identify the most unfavourable intersection position of multi-line driving based on the observed mechanism. In single-line operation, the maximum curvature of the main girder caused by bridge deformation with wavelengths above 200 m appears at the bridge tower and mid-span, while the maximum chord-measurement alignment with wavelengths below 200 m appears at the bridge tower, showing that the deformation at the tower area is more significant and that first car or sixteenth car will experience the maximum acceleration. For the multi-line operation, the curvature and chord measurements can be calculated by the superimposition of alignment with the wavelengths above and below 200 m, consecutively; hence, the most unfavourable intersection can be predicted according to the location and intersection of the maximum value. The intersection of two trains can increase the train’s centrifugal and vibration accelerations, causing the maximum acceleration to occur at the tower, where two trains meet at the most unfavourable one-fourth span of the bridge, which is verified by the train-track-bridge system.

Alignment of human aquaporin 4 and ß-amyloid proteins may indicate involvement of ß-amyloid in brain water homeostasis and prevention of brain edema.

Alignment of human aquaporin 4 and ß-amyloid proteins may indicate involvement of ß-amyloid in brain water homeostasis and prevention of brain edema.

Effect of preoperative dynamic cervical sagittal alignment on the loss of cervical lordosis after laminoplasty

PurposeCervical laminoplasty (CLP) is a developed surgical procedure for the treatment of cervical spondylotic myelopathy (CSM), but only a few of those studies focus on preoperative dynamic cervical sagittal alignment and the study of different degrees of loss of cervical lordosis (LCL) is lacking. This study aimed to analyze patients who underwent CLP to investigate the effect of cervical extension and flexion function on different degrees of LCL.MethodsIn this retrospective case–control study, we analyzed 79 patients who underwent CLP for CSM between January 2019 and December 2020. We measured the cervical sagittal alignment parameters on lateral radiographs (neutral, flexion, and extension positions) and used Japanese Orthopedic Association (JOA) score to assess clinical outcomes. We defined the extension ratio (EXR) as 100 × Ext ROM (cervical range of extension)/ROM (cervical range of motion). We observed the relationships between collected variables (demographic and radiological variables) and LCL. Patients were classified into the following three groups according to the LCL: stability group: (LCL ≤ 5°); mild loss group (5° < LCL ≤ 10°); and severe loss group (LCL > 10°). We compared the differences of collected variables (demographic, surgical and radiological variables) among the three groups.ResultsSeventy-nine patients were enrolled (mean age 62.92 years; 51 men, 28 women) in the study. Among the three groups, cervical Ext ROM was the best in the stability group (p < 0.01). Compared with the stability group, range of flexion (Flex ROM) was significantly higher (p < 0.05) and EXR was significantly lower (p < 0.01) in the severe loss group. Compared with the severe loss group, JOA recovery rates were better (p < 0.01) in the stability group. Receiver-operating characteristic curve (ROC) analysis to predict LCL > 10° (area under the curve = 0.808, p < 0.001). The cutoff value for EXR was 16.80%, with sensitivity and specificity of 72.5% and 82.4%, respectively.ConclusionCLP should be carefully considered for patients with a preoperative low Ext ROM and high Flex ROM, as a significant kyphotic change is likely to develop after surgery. EXR is a useful and simple index to predict significant kyphotic changes.

Person–Skill Fit: Why a New Form of Employee Fit Is Required

Significant recent changes in labor affect organizations, managers, and employees; however, we do not yet fully understand the depth and scope of these changes. For example, although previous research on person–job and person–organization fit is helpful, it has struggled to provide clarity when the very nature of work and jobs is changing and new types of work are emerging. To contribute to the literature on person–job and person–organization fit, this paper proposes a conceptual model that explains the ways in which individual, job and organizational factors interact with diverse work environments. Specifically, I show that a new work environment generates a new form of employee fit, which I call person–skill fit. I argue that changes in the constructs that contribute to employee fit (e.g., competencies, trust, commitment and values) may generate a fit gap that manifests in the form of a managerial gap. Firms should address this gap to improve their dynamic alignment with new forms of work. This framework offers potentially valuable new ways of assisting managers and organizations in their efforts to adjust to the changing nature of work and to transition from standard management practices to new management practices to achieve improved outcomes by utilizing the person–skill fit model.

Cesium modulated halide perovskites: A theoretical insight on the dynamic evolution, work function and band alignments

Photocathode is a critical component in applications such as electron source, photomultipliers and image intensifiers. The harsh operation conditions put forward multiple requirements of current photocathode materials (i.e., GaAs, GaN, K2CsSb). Meanwhile, Halide perovskites have been reported with plenty of fantastic properties and are expected as a potential candidate for photocathode. In this study, we use first-principle calculations to investigate the feasibility of application of CsPbBr3 as photocathode. The surface coatings of Cs adatoms with different coverages is explored. The dynamic evolution of the adsorption process suggests a saturated coverage of 6/8 ML for in-plane coating. Based on the theoretical framework of electron density and polarization density, a direct link between reduction of work function and dipole moment is established. The minimum work function of functionalized (001) surface attains at 1.05 eV with Cs coverage of 6/8 ML. Significant band bending on the surface after Cs incorporation is observed according to the analysis of band structure and layer-by-layer density of states. The results of this work aim to guide further experimental development of the Cs activated process for broader families of halide perovskites as photocathode materials.

A novel intelligent bearing fault diagnosis method based on signal process and multi-kernel joint distribution adaptation

The present research on intelligent bearing fault diagnosis assumes that the same feature distribution is used to obtain training and testing data. However, the domain shift (distribution discrepancy) issue generally occurs in both datasets because of different operational conditions. The domain adaptation techniques are preferably applied for fault diagnosis to handle the domain shift issue. Moreover, collecting sufficient testing data or labelled data in real industries is a challenging task. Therefore, the multi-kernel joint distribution adaptation (MKJDA) with dynamic distribution alignment is proposed for bearing fault diagnosis. This method dynamically joins both the marginal and conditional distributions and uses the multi-kernel to solve the non-linear problems to extract the most effective and robust representation for cross-domain issues. Moreover, it runs with the unlabelled task domain to perform the diagnosis by iteratively updating the pseudo code. The experimental results (two public datasets and one experimental dataset) demonstrated that the proposed method (MKJDA) exhibited stable and robust accuracy while conducting bearing fault diagnosis. It can effectively address the most crucial issue: intelligent diagnosis methods must re-train the model when the distribution differs between the source domain (the model is learned) and the target domain (the learned model is applied).