Transformation Technique Research Articles

Noise level estimation using locality preserving natural image statistics

Natural images are known to have certain regular statistical properties. These properties get modified under any artificial change or distortion in natural images. Most common form of image degradation occurs in the form of noise. The amount of degradation in noisy images is measured by estimating the noise level. Many image processing applications such as denoising, restoration, segmentation, compression etc. use noise level information as a prior; inaccurate estimate of which may impact their performance. In this article, we explore natural image statistics in locality preserving transform domain. This property groups structurally similar images/image patches when projected in the transform domain. Image patches corrupted with similar noise level get projected close by in the locality preserving domain and show consistent coefficient behaviour. In particular, we use Two Dimensional Orthogonal Locality Preserving Projection (2DOLPP) as the domain transformation technique. 2DOLPP basis, representing natural images, are learnt in advance from a set of clean images, thereby reducing the computational time significantly. Features based on natural image statistics are extracted from 2DOLPP domain representation of input image patches. Mapping from feature space to noise level is carried out using support vector regression. The proposed noise estimation approach is at par with or surpasses the state-of-the-art techniques with much less computational time. Performance of this approach is stable across a wide range of noise levels and independent of the image structure.

The Nanotech Potential of Curcumin in Pharmaceuticals: An Overview.

It is safe to use Curcumin as a cosmetic and therapeutic ingredient in pharmaceutical products. For the uses mentioned above and for fundamental research, it is essential to obtain pure Curcumin from plant sources. There is a requirement for effective extraction and purification techniques that adhere to green chemistry standards for efficiency improvement, process safety, and environmental friendliness. Several outstanding studies have looked into the extraction and purification of Curcumin. This review thoroughly covers the currently available curcumin extraction, synthesis, and transformation techniques. Additionally, Curcumin's poor solubility and low absorption in the human body have limited its potential for pharmaceutical use. However, recent developments in novel curcumin formulations utilizing nanotechnology delivery methods have provided new approaches to transport and maximize the human body's curcumin absorption efficiency. In this review, we explore the various curcumin nanoformulations and the potential medicinal uses of nano curcumin. Additionally, we review the necessary future research directions to recommend Curcumin as an excellent therapeutic candidate.

A review of entomopathogenic fungi as a potential tool for mosquito vector control: A cost‐effective and environmentally friendly approach

AbstractMosquitoes around the world spread diseases like malaria, dengue, zika, lymphatic filariasis and arboviruses, which are dangerous to human health and the economy. Eventually, mosquitoes develop resistance to synthetic chemical insecticides and, moreover, these insecticides have adverse environmental impacts, accumulating in soils and in the food chain. So, researchers are searching for better vector control tools from biological sources such as plants, bacteria, fungi, viruses and other predators. Eco‐friendly methods that use entomopathogenic fungi to reduce vector‐borne disease burdens are becoming more popular because they are selective and safe for the environment. Based on existing literature, several microbial agents show potential for the biocontrol of mosquitoes. With advances in genetic recombination and transformation techniques, in the ongoing battle against insecticide‐resistant mosquitoes, genetically engineered fungal biopesticides represent a cutting‐edge solution. These biopesticides are the result of novel genetic changes that improve the ability of fungi to target and kill mosquitoes. These fungi can effectively combat mosquito populations by introducing genes that produce insecticidal proteins or toxins. This method has several advantages, including a lower environmental impact, because the fungi are highly specific to mosquitoes and are harmless to non‐target organisms. It also helps to reduce the problem of insecticide resistance because the fungi have a unique mode of action. These biopesticides hold great promise for reducing mosquito‐borne diseases while minimizing environmental damage and combating resistance. This review article discusses various entomopathogenic fungal pathogens that can act as biocontrol agents and their mode of action against mosquitoes. We discus recent advances in entomopathogenic fungi‐secreted effector molecules for suppressing host immunity and progress in the development of transgenic mosquito‐killing fungi.

Harmonizing Cross View Image Transformation Through Local and Global Insights- A Review

Hyperspectral and multispectral information processing systems and technologies have demonstrated their value in enhancing agricultural productivity and practices by providing farmers and crop managers with valuable information on factors influencing crop condition and growth. These technologies play a crucial role in various agricultural applications, such as crop management, crop yield forecasting, crop disease detection, and monitoring soil, water, and land usage. To enhance the process of agriculture through effective crop management and assistance to farmer, using an advanced image transformation techniques the study delves into the exploration of techniques for harmonizing cross-view image transformation, with a focus on integrating both local and global insights. Further the study proposes the application of the 2D-DWT (Two-Dimensional Discrete Wavelet Transform) technique for image data preprocessing and the Extreme Learning Machine (ELM) algorithm for image classification in the context of hyperspectral images. Hyperspectral information sensing allows for the coverage of the electromagnetic spectrum in a single acquisition with several hundred spectral bands, resulting in a data cube containing significant spectral and spatial information ELM is particularly effective for classification problems because of its quick training time and capacity to operate with hidden nodes whose parameters are randomly assigned rather than modified iteratively. This comprehensive review aims to provide valuable insights and a critical analysis of the suggested method, shedding light on its potential contributions to the advancement of image transformation techniques for agricultural development.

Establishment of an efficient genetic transformation system for Tanacetum cinerariifolium

The Dalmatian Daisy Tanacetum cinerariifolium is an Asteraceae plant species that produces the natural insecticide “pyrethrum”, which is effective against mosquito disease vectors and household pests. To enhance the content of pyrethrum in flowers, a more detailed understanding of the mechanisms underlying pyrethrum biosynthesis is needed. Even though gene transformation and genome editing techniques are vital for investigating pyrethrin biosynthesis, limited information is available on the transformation of T. cinerariifolium. Furthermore, each seedling possesses a distinct genotype with large variations by self-incompatibility. We herein employed T. cinerariifolium line #14 with weak self-incompatibility to establish a protocol of efficient regeneration from leaf segments and transformation. Leaf segments formed calli on 1/2 Murashige and Skoog’s basal medium (MS) with naphthalene acetic acid 1 mg L−1 and 6-benzylaminopurine (BAP) 2 mg L−1, regenerated shoots from calli on 1/2 MS with BAP 0.5 mg L−1 and GA3 0.2 mg L−1, and elongated shoot stems on 1/2 MS with indole-3-butyric acid 0.5 mg L−1 and BAP 0.5 mg L−1. To establish genetic transformation, Rhizobium radiobacter strain EHA105 with the highest infectivity and the mas1'-2' bidirectional promoter with the highest expression of the nptII resistance gene were used, and the antibiotic G418 was added to medium at a concentration of 10 to 20 mg L−1 to select transformed cells. Using established regeneration techniques, we successfully obtained transformants that highly expressed the transgene gusA. This technique will be useful for creating genetically modified T. cinerariifolium, particularly for elucidating the mechanism of pyrethrin biosynthesis toward the creation of pyrethrin-rich traits.

Development of an Agrobacterium tumefaciens-mediate transformation system for somatic embryos and transcriptome analysis of LcMYB1’s inhibitory effect on somatic embryogenesis in Litchi chinensis.1

Litchi holds paramount economic significance as a global fruit crop. However, the advancement of litchi functional genomics encounters substantial obstacles due to its recalcitrance to stable transformation. Here, we present an efficacious A. tumefaciens-mediated transformation system in somatic embryo of ‘Heiye’ litchi. This system was developed through meticulous optimization of variables encompassing explant selection, A. tumefaciens strain delineation, bacterium concentration, infection duration, and infection methodology. The subsequent validation of the transformation technique in litchi was realized through the ectopic expression of LcMYB1, resulting in the generation of transgenic calli. However, it was discerned that the differentiation of transgenic calli into somatic embryos encountered substantial challenges. To delve into the intricate molecular underpinnings of LcMYB1’s inhibitory role in somatic embryo induction, a comprehensive transcriptome analysis was conducted encompassing embryogenic calli (C), globular embryos (G), and transgenic calli (TC). A total of 1166 common differentially expressed genes (DEGs) were identified between C-vs-G and C-vs-TC. Gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that these common DEGs were most related to plant hormone signal transduction pathways. Furthermore, RT-qPCR corroborated pronounced down-regulation of numerous genes intricately associated with somatic embryos induction within the transgenic calli. The development of this transformation system has provided valuable support for functional genomics research in litchi.

Analytical study and heat transfer analysis of on couple stress flow of hybrid nanofluid over a nonlinear stretching surface

This research paper investigates a two-dimensional couple stress flow of hybrid nanofluid (HN) over a nonlinear stretching surface with heat transfer analysis. HNs are well-known for their exceptional heat transfer properties compared to conventional fluids. The mathematical modeling of the problem involves the formulation of basic governing equations, namely, continuity, momentum and energy equations. To simplify the analysis, a similarity transformation technique is employed to convert the dimensional NLPDEs into dimensionless NODEs. Subsequently, the obtained governing equations are analytically solved using the HAM. The investigation explores the impact of several parameters, including magnetic field inclination, slip parameter, couple stress parameter, nanoparticle volume fraction, nonlinear stretching parameter, EN, thermophoresis parameter and PN. This study presents graphical representations of temperature and velocity distribution to visualize the effects of these parameters on the HN flow. Furthermore, different graphs and tables are employed to explain the impact of the factors on SF and NN. Notably, the results indicate that the HN exhibits significantly enhanced heat transfer properties over the base fluid, particularly under the influence of an inclined magnetic field. This research is expected to contribute to the advancement of the field of condensed nanostructure and nanomaterials, opening new avenues for further exploration in heat transfer enhancement applications.

AI-Powered Marketing: Transformative Techniques for Advertising Success

This research paper explores the integration of Artificial Intelligence (AI) in marketing and advertising, examining its transformative impact on the industry. The paper explores the various applications of AI in marketing strategies, its potential benefits, and the evolving landscape of consumer engagement. Through an in-depth analysis of case studies and industry trends, we aim to provide insights into how AI technologies are reshaping the way businesses promote their products and services.

Genome editing in Acinetobacter baumannii through enhanced natural transformation.

Acinetobacter baumannii, a multidrug-resistant bacterium has become a significant cause of life-threatening infections acquired in hospitals worldwide. The existing drugs used to treat A. baumannii infections are rapidly losing efficacy, and the increasing antimicrobial resistance, which is expected to turn into a global health crisis, underscores the urgency to develop novel prevention and treatment strategies. We reasoned that the discovery of novel virulence targets for vaccine and therapy interventions requires a more enhanced method for the introduction of multiple elements of foreign DNA for genome editing than the current methods of natural transformation techniques. Herein, we employed a novel and a much-improved enhanced technique for the natural transformation of elements of the genome editing system CRISPR-Cas9 to suppress specific genomic regions linked to selectively suppress bacterial virulence. We modified the genome of the laboratory-adapted strain of A. baumannii BAA-747 by targeting the AmpC, as a marker gene, for disruption by three different genomic manipulation strategies, and created mutant strains of A. baumannii that are, at least, fourfold susceptible to ampicillin. This work has established an optimized enhanced natural transformation system that enables efficient genome editing of pathogenic bacteria in a laboratory setting, providing a valuable future tool for exploring the function of unidentified virulence genes in bacterial genomes.

Perilaku Sintaksis Kata Sifat dalam Bahasa Bali

This article is intended to analyze the syntactical behavior of adjectives in Balinese language at phrases and clauses level. The data were collected using the observation method and note-taking and recording techniques. The data were analyzed using the connecting and comparing techniques, and distributional method with deletion, transformational, and insertion techniques. The results of data analysis were formally and informally presented using both inductive and deductive techniques. The results of the study show that in the endocentric and attributive phrases, the adjectives in Balinese language function as the central and attributive elements, that in the endocentric and coordinative phrases, they function as the central element only, and that in the exocentric phrase, they function as the axis. The meaning of the phrase with an adjective + adjective construction refers to equivalence and opposition. In the clausal level, adjectives in Balinese language function as predicate, complement, and adverb.

Queering the genome: ethical challenges of epigenome editing in same-sex reproduction

In this article, I explore the ethical dimensions of same-sex reproduction achieved through epigenome editing—an innovative and transformative technique. For the first time, I analyse the potential normativity of this...

Significance of radiation on the Brinkman-type nanofluid with variable surface velocity embedding with porous matrix

The current flow phenomena based on the flow of water-based nanofluid corresponding to the variable surface velocity. Further, the electrically conducting fluid embedding with porous matrix with an inclusion of thermal radiation enriches the study as well. Because of the varied industrial applications for the use of nanoparticle concentration with radiating heat that is used in cooling process has significant role for the enhancement of heat transport properties. Besides to it in several other applications like engineering, biomedical, and nuclear science the contribution of nanoparticle shows its extensive properties. The main goal of the proposed investigation is to study the influence of thermal radiation on the Brinkman-type nanofluid in the presence of porous matrix. Further, the behavior of variable surface velocity enriches the study. The proposed designed time dependent model associated with various physical restrictions is taken care of analytically using Laplace Transformation Technique and their behavior is deliberated through graphs. However, the validation as well as convergence criteria of the present methodology correlate with the earlier investigation.

Enhanced heat transfer analysis on Ag-Al2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document}O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{3}$$\\end{document}/water hybrid magneto-convective nanoflow

The primary goal of this investigation is to examine the heat and flow characteristics of a hybrid nanofluid consisting of silver (Ag) and aluminum oxide (Al2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document}O3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{3})$$\\end{document} nanoparticles over an unsteady radially stretching sheet embedded in porous medium. The investigation is conducted under the influence of several key parameters, namely joule heating, viscous dissipation, porous, slip, and suction. The technique of similarity transformations is used to transform the governing system of PDEs into nonlinear ODEs and the bvp4c solver is used to solve them numerically. The present study examines the influence of sphere and platelet shape nanoparticles on the temperature and velocity profiles. The outcomes are discussed through graphs and tables. A rise in the porous, slip, and suction parameters makes the velocity profile decrease gradually. The temperature escalates when Biot number, magnetic parameter, and Eckert number increase. As compared to sphere shapes, platelet-shaped nanoparticles exhibit the greatest heat transfer and flow. Results reveal that by using Ag-Al2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document}O3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{3}$$\\end{document}/H2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$_{2}$$\\end{document}O hybrid nanofluid with a volume fraction of 5%, the heat transfer enhancement of platelet shape nanoparticles increased by 11.88% than sphere-shaped nanoparticles. Overall, the platelet shape of nanoparticles offers distinctive advantages in various engineering applications, primarily due to their large surface area, anisotropic properties, and tunable surface chemistry. These properties make them versatile tools for improving the performance of materials and systems in engineering fields. The findings can contribute to the design and optimization of nanofluid-based systems in various engineering applications, such as heat exchangers, microfluidics, and energy conversion devices.

On the use of machine learning and data-transformation methods to predict hydration kinetics and strength of alkali-activated mine tailings-based binders

The escalating production of mine tailings (MT), a byproduct of the mining industry, constitutes significant environmental and health hazards, thereby requiring a cost-effective and sustainable solution for its disposal or reuse. This study proposes the use of MT as the primary ingredient (≥70%mass) in binders for construction applications, thereby ensuring their efficient upcycling as well as drastic reduction of environmental impacts associated with the use of ordinary Portland cement (OPC). The early-age hydration kinetics and compressive strength of MT-based binders are evaluated with an emphasis on elucidating the influence of alkali activation parameters and the amount of slag or cement that are used as minor constituents. This study reveals correlations between cumulative heat release and compressive strengths at different ages; these correlations can be leveraged to estimate the compressive strength based on hydration kinetics. Furthermore, this study presents a random forest (RF) model—in conjunction with fast Fourier and direct cosine transformation techniques to overcome the limitations associated with limited volume and diversity of the database—to enable high-fidelity predictions of time-dependent hydration kinetics and compressive strength of MT-based binders in relation to mixture design. Overall, this study demonstrates a sustainable approach to upcycle mine tailings as the primary component in low-carbon construction binders; and presents both analytical and machine learning-based approaches for accurate a priori predictions of hydration kinetics and compressive strength of these binders.

Simulation of Fractional Order 2D-Mathematical Model Using α-Fractional Differential Transform Method

In this paper, we will introduce a well-known transformation technique, the modified α-fractional differential transform, to the differential equation of fractional order. We derive some new results with proof using new techniques that never existed before. By using this new technique, we are attempting to solve the nonlinear fractional-order mathematical epidemic model. Furthermore, the fractional epidemic model’s solution obtained by using this new technique is correlated with the solution of the same model calculated for a different fractional order by the modified α-fractional differential transform method. Moreover, using the Python software, we can numerically and graphically represent the solution of fractional differential equations.

Optimal voltage set-point of automatic tap changer transformers and generators and reactive power compensation to increase power system predictability

In recent years, renewable energy sources (RESs) such as wind turbines (WTs) have received much attention in both the operating and planning of power systems. These sources have caused many uncertainties in the operation of power systems due to their unpredictable nature. Mentioned uncertainties besides load demands uncertainty, and possible failures in power system components, make the system state unpredictable. The operational decisions are completely challenging in these situations. Any efforts to increase the network operator awareness from the system state will be completely valuable for making accurate decisions.This paper tries to increase the predictability of the power system state through optimal regulating of the voltage setpoint of automatic tap changer transformers and generators besides the reactive power of shunt capacitors. However, conventional objectives such as decreasing losses are considered, simultaneously. This paper uses the K-medoids data clustering method to evaluate the effect of uncertainties. Also, the correlation between input uncertain variables is considered and handled by the Cholesky decomposition technique combined with the Nataf transformation technique. The multi-objective optimization problem is tackled using an improved version of the non-dominated sorting genetic algorithm (NSGA-II). To ensure for validity of the results, studies are repeated using the multi-objective particle swarm optimization (MOPSO) algorithm as another evolutionary-based method.The proposed approach is applied to the IEEE 14 and 30 bus standard system. The results showed that the predictability of the power system can be considerably increased while keeping the losses approximately at its minimum amount.

MHD second-grade nanofluid slip flow over a stretching sheet subject to activation energy, thermophoresis, and Brownian effects

In this work, the magnetohydrodynamic flow of two engine oil-based second-grade nanofluids Copper (Cu) and Titanium oxide (TiO 2) over a penetrable stretching sheet is studied. The flow, heat and mass transfer characteristics in the existence of activation energy, inclined magnetic field, Brownian diffusion, elastic deformation, and thermophoresis are examined. The coupled nonlinear model equations are formulated by implementing the Modified Buongiorno model and then are non-dimensionalized by the similarity transformation technique. The non-dimensional equations are simulated numerically using the bvp4c solver. Graphs are plotted to study the flow behaviour of nanofluid with the rate of entropy generation and Bejan number. The outcomes of skin friction coefficient, Nusselt number and Sherwood number are exhibited via surface plots. From the analysis, a higher inclination of the magnetic field decays the velocity and amplifies the temperature profiles. The heat transport rate diminishes with the Brownian diffusion, thermophoresis and elastic deformation parameters. The mass transport rate is accelerated due to the activation energy parameter. The entropy generation rate is enhanced with the Brinkman, Biot and local Reynolds numbers. Furthermore, it is seen that engine oil-based TiO 2 nanofluid has larger velocity, temperature and rate of entropy generation than engine oil-based Cu nanofluid. The current examination has applications in automobile radiators, microchips, biomedical engineering, and extraction of geothermal power.

Diving into Clarity: Restoring Underwater Images using Deep Learning

In this paper we propose a learning-based restoration approach to learn the optimal parameters for enhancing the quality of different types of underwater images and apply a set of intensity transformation techniques to process raw underwater images. The methodology comprises two steps. Firstly, a Convolutional Neural Network (CNN) Regression model is employed to learn enhancing parameters for each underwater image type. Trained on a diverse dataset, the CNN captures complex relationships, enabling generalization to various underwater conditions. Secondly, we apply intensity transformation techniques to raw underwater images. These transformations collectively compensate for visual information loss due to underwater degradation, enhancing overall image quality. In order to evaluate the performance of our proposed approach, we conducted qualitative and quantitative experiments using well-known underwater image datasets (U45 and UIEB), and using the proposed challenging dataset composed by 276 underwater images from the Amazon region (AUID). The results demonstrate that our approach achieves an impressive accuracy rate in different underwater image datasets. For U45 and UIEB datasets, regarding PSNR and SSIM quality metrics, we achieved 26.967, 0.847, 27.299 and 0.793, respectively. Meanwhile, the best comparison techniques achieved 26.879, 0.831, 27.157 and 0.788, respectively.

Dissipative MHD flow of ternary‐hybrid nanofluid over an inclined stretching sheet with heat source and mass flux due to temperature gradient

AbstractAn analysis has been made to illuminate the unsteady MHD slip flow of ternary‐hybrid nanofluid of water conveying spherical Cu, cylindrical Al2O3, and platelet Ag nanoparticles over an inclined stretching sheet. The above complex scenario explores how the presence of a magnetic field affects the behavior of ternary‐hybrid nanofluid over an inclined stretching surface. Understanding this interaction is crucial in advanced thermal systems like cooling mechanisms and energy generation technologies. The study can provide insights into optimizing heat transfer rates, enhancing thermal conductivity and improving efficiency in practical applications by manipulating the flow characteristics and temperature distribution in the system. The heat transfer has been analyzed incorporating Darcy dissipation and heat source in the presence of 1st order velocity slip. The presence of Soret effect makes the study more congenial. Using similarity transformation technique, the governing partial differential equations are converted into a system of ordinary differential equations. The reduced system is dealt with 4th order Runge–Kutta method with shooting technique. The comparison with earlier results gives a reliability of present results. The important findings are: velocity of the flow decelerates for higher values of 1st order slip parameter, velocity of the flow increases with increase in Soret number, increasing values of chemical reaction parameter lead to lower concentration in both the cases, that is, with or without velocity slip.

Bi‐Directional Growth of Thin Films: Unlocking Anisotropic Ferromagnetism and Superconductivity

AbstractThe pursuit of breakthroughs in thin film technology drives the exploration of novel growth strategies for quantum materials that surpass conventional limitations. Departing from the prevailing unidirectional growth approach, the methodology allows for atomic precision in both the in‐plane and out‐of‐plane directions. To demonstrate the capabilities of this transformative technique, a bi‐directionally grown superlattice comprised of alternating LaMnO3 and SrMnO3 layers is engineered, enabling the emergence of interfacial ferromagnetism. By adopting this superlattice as a model system, the vast potential of the approach is highlighted through comprehensive analysis and characterization. Furthermore, the application of the method is extended to the growth of superconducting La1.84Sr0.16CuO4 thin films on various offcut substrates. Remarkably, these substrates induce an anisotropic critical current originating from two distinct mechanisms.