Effects Of Dimensions Research Articles

Retraction Note: Effective dimensionality reduction by using soft computing method in data mining techniques

Retraction Note: Effective dimensionality reduction by using soft computing method in data mining techniques

What can be learnt with wide convolutional neural networks?*

Abstract Understanding how convolutional neural networks (CNNs) can efficiently learn high-dimensional functions remains a fundamental challenge. A popular belief is that these models harness the local and hierarchical structure of natural data such as images. Yet, we lack a quantitative understanding of how such structure affects performance, for example the rate of decay of the generalisation error with the number of training samples. In this paper, we study infinitely wide deep CNNs in the kernel regime. First, we show that the spectrum of the corresponding kernel inherits the hierarchical structure of the network, and we characterise its asymptotics. Then, we use this result together with generalisation bounds to prove that deep CNNs adapt to the spatial scale of the target function. In particular, we find that if the target function depends on low-dimensional subsets of adjacent input variables then the decay of the error is controlled by the effective dimensionality of these subsets. Conversely, if the target function depends on the full set of input variables then the error decay is controlled by the input dimension. We conclude by computing the generalisation error of a deep CNN trained on the output of another deep CNN with randomly initialised parameters. Interestingly, we find that, despite their hierarchical structure, the functions generated by infinitely wide deep CNNs are too rich to be efficiently learnable in high dimensions.

Electronic 1/f noise as a probe of dimensional effects on spin-glass dynamics

Over the past decade, spin-glass simulations have improved to the point that they now access time- and length-scales comparable to experiments at the mesoscale. A recent series of thin-film field-cooled/zero-field-cooled magnetization (FC/ZFC) experiments demonstrated activated spin dynamics, with a temperature-independent activation energy proportional to the logarithm of the film thickness and with coefficients in remarkable agreement with the simulation. These measurements require the application of small magnetic fields, which has been shown to affect the spin-glass energy landscape. Measurements of the 1/f noise in metallic spin-glasses have been previously shown to be a sensitive probe of the spin dynamics, and the measurements can be made without applying a magnetic field. In this mini-review, we review these techniques and discuss how transport measurements can fit into the current landscape of spin-glass measurements. We compare previous measurements to more recent measurements on similar films, made with ostensibly different cooling protocols, and compare both the previous and recent measurements to the magnetometry. The transport measurements—taken over a wider range of temperature than magnetometry—suggest that the maximum spin-glass energy barrier height is temperature-dependent, not fixed, possibly due to two-dimensional dynamics. We discuss this possibility, along with future measurements, which may be able to resolve this mystery.

Orchestrating time and color: a programmable source of high-dimensional entanglement

High-dimensional encodings based on temporal modes (TMs) of photonic quantum states provide the foundations for a highly versatile and efficient quantum information science (QIS) framework. Here, we demonstrate a crucial building block for any QIS applications based on TMs: a programmable source of maximally entangled high-dimensional TM states. Our source is based on a parametric downconversion process driven by a spectrally shaped pump pulse, which facilitates the generation of maximally entangled TM states with a well-defined dimensionality that can be chosen programmatically. We characterize the effective dimensionality of the generated states via measurements of second-order correlation functions and joint spectral intensities, demonstrating the generation of bi-photon TM states with a controlled dimensionality in up to 20 dimensions.

Influence of Dimensional Quantization Effects on the Effective Mass of Major Charge Carriers in LED Heterostructures with InxGa1−xN/GaN Multiple Quantum Wells

By numerically solving the self-consistent system of the Schr¨odinger equations and Poisson electroneutrality, zone diagrams of LED heterostructures with InxGa1−xN/GaN multiple quantum wells have been calculated. The effect of electron–phonon interaction, nonparabolicity of the dispersion relation, and hybridization of the wave function on the values of the effective mass of major charge carriers in the InxGa1−xN/GaN quantum wells has been studied. The long-wave shift of 2D-plasmon resonances is associated with the temperature renormalization of the effective mass of two-dimensional carriers. To describe the temperature dependence of the effective mass, the function for the displacement of the 2D-plasmon resonance frequency is introduced.

Tuning Dielectric Properties with Nanofiller Dimensionality in Polymer Nanocomposites.

Polymer nanocomposites hold great potential as dielectrics for energy storage devices and flexible electronics. The structural architecture of the nanofillers is expected to play a crucial role in the fundamental mechanisms governing the electrical breakdown and dielectric properties of the nanocomposites. However, the effect of nanofiller structure and dimensionality on these properties has not been studied thoroughly to date. This study explores the critical relationship between nanofiller dimensionality and dielectric properties in polymer nanocomposites. We fabricated polyvinylidene fluoride (PVDF) nanocomposites by incorporating a range of carbon-based nanofillers separately, including zero-dimensional (0D) carbon black (CB), one-dimensional (1D) multiwalled carbon nanotubes (MWCNT), 1D single-walled carbon nanotubes (SWCNT), two-dimensional (2D) reduced graphene oxide (rGO), and three-dimensional (3D) graphite. The frequency-dependent (1 kHz to 1 MHz) dielectric permittivity (k) of the nanocomposites at the same concentration of nanofillers demonstrated a hierarchical order, with MWCNT showing the highest permittivity (∼400%), succeeded by rGO (∼360%), CB (∼290%), SWCNT (∼230%), and graphite (∼70%), respectively. The temperature-dependent (50-150 °C) dielectric spectroscopy revealed high k with increasing temperature due to the enhanced dipole movement. However, their dielectric breakdown strength and energy densities were not correlated to k and exhibited the following order: SWCNT > MWCNT > CB > rGO > graphite. As the electrical breakdown depends upon the nanocomposites' mechanical strength, we correlated the mechanical properties with the nanofiller dimensionality, and Young's modulus followed the 1D ≈ 2D > 0D > 3D order. These findings will provide fundamental insights into designing tunable, conducive nanofiller-based nanocomposites in next-generation flexible electronics and capacitive energy storage devices.

Environment-independent distribution of mutational effects emerges from microscopic epistasis.

Predicting how new mutations alter phenotypes is difficult because mutational effects vary across genotypes and environments. Recently discovered global epistasis, in which the fitness effects of mutations scale with the fitness of the background genotype, can improve predictions, but how the environment modulates this scaling is unknown. We measured the fitness effects of ~100 insertion mutations in 42 strains of Saccharomyces cerevisiae in six laboratory environments and found that the global epistasis scaling is nearly invariant across environments. Instead, the environment tunes one global parameter, the background fitness at which most mutations switch sign. As a consequence, the distribution of mutational effects is predictable across genotypes and environments. Our results suggest that the effective dimensionality of genotype-to-phenotype maps across environments is surprisingly low.

Human macrophage polarisation and regulation of angiogenesis and osteogenesis is dependent on culture extracellular matrix and dimensionality

The immune system plays a crucial role in tissue repair and regeneration. Macrophages have been identified as master regulators of the early immune response and healing outcome, by orchestrating the temporal nature of the initial inflammation phase and coordinating the fate of stem/progenitor cells involved in regeneration. However, traditional in-vitro models for the study of macrophages often fail to fully replicate the complexity of the in-vivo microenvironment, therefore generating models which do not fully capture the extensive spectrum of macrophage behaviour seen in native tissues. To this end, we used a hematoma-mimetic 3D fibrin matrix characteristic of early injured tissues to generate a 3D in-vitro model mirroring the local macrophage microenvironment. Leveraging this framework, we demonstrated significant effects of extracellular matrix and dimensionality on macrophage basal signalling and polarisation, achieving more pronounced regenerative phenotypes upon stimulation with the M2a polarisation factors compared to traditional 2D tissue culture conditions. Moreover, this enhanced physiological macrophage behaviour corresponded to increased coordination of angiogenesis and osteogenesis, better mirroring the healing processes seen in-vivo. Taken together, this study demonstrates the critical importance of integrating tissue composition and 3D architecture when investigating the macrophage behaviour in-vitro, establishing a powerful tool that overcomes known limitations associated with traditional 2D culture on plastic, and can be used to identify and validate novel immunomodulation strategies to enhance tissue regeneration.

Exploring cortical morphology biomarkers of amnesic mild cognitive impairment using novel fractal dimension-based structural MRI analysis.

Amnestic mild cognitive impairment (aMCI) is considered as an intermediate stage of Alzheimer's disease, but no MRI biomarkers currently distinguish aMCI from healthy individuals effectively. Fractal dimension, a quantitative parameter, provides superior morphological information compared to conventional cortical thickness methods. Few studies have used cortical fractal dimension values to differentiate aMCI from healthy controls. In this study, we aim to build an automated discriminator for accurately distinguishing aMCI using fractal dimension measures of the cerebral cortex. Thirty aMCI patients and 30 health controls underwent structural MRI of the brain. First, the atrophy of participants' cortical sub-regions of Desikan-Killiany cortical atlas was assessed using fractal dimension and cortical thickness. The fractal dimension is more sensitive than cortical thickness in reducing dimensional effects and may accurately reflect morphological changes of the cortex in aMCI. The aMCI group had significantly lower fractal dimension values in the bilateral temporal lobes, right limbic lobe and right parietal lobe, whereas they showed significantly lower cortical thickness values only in the bilateral temporal lobes. Fractal dimension analysis was able to depict most of the significantly different focal regions detected by cortical thickness, but additionally with more regions. Second, applying the measured fractal dimensions (and cortical thickness) of both cerebral hemispheres, an unsupervised discriminator was built for the aMCI and healthy controls. The proposed fractal dimension-based method achieves 80.54% accuracy in discriminating aMCI from healthy controls. The fractal dimension appears to be a promising biomarker for cortical morphology changes that can discriminate patients with aMCI from healthy controls.

Observation of nonlinear fractal higher order topological insulator

Higher-order topological insulators (HOTIs) are unique materials hosting topologically protected states, whose dimensionality is at least by 2 lower than that of the bulk. Topological states in such insulators may be strongly confined in their corners which leads to considerable enhancement of nonlinear processes involving such states. However, all nonlinear HOTIs demonstrated so far were built on periodic bulk lattice materials. Here, we demonstrate the first nonlinear photonic HOTI with the fractal origin. Despite their fractional effective dimensionality, the HOTIs constructed here on two different types of the Sierpiński gasket waveguide arrays, may support topological corner states for unexpectedly wide range of coupling strengths, even in parameter regions where conventional HOTIs become trivial. We demonstrate thresholdless spatial solitons bifurcating from corner states in nonlinear fractal HOTIs and show that their localization can be efficiently controlled by the input beam power. We observe sharp differences in nonlinear light localization on outer and multiple inner corners and edges representative for these fractal materials. Our findings not only represent a new paradigm for nonlinear topological insulators, but also open new avenues for potential applications of fractal materials to control the light flow.

Dimensional effect of oxide-derived Cu electrocatalysts to reduce CO2 into multicarbon compounds

Oxide-derived Cu (OD-Cu) are the most promising catalysts for multicarbon formation via CO2 electroreduction (CO2ERR), yet facing structural/compositional reconstruction trends during CO2ERR. Nanocatalysts with specific mesoscopic morphology are more resistant to reconstruction, which would benefit systematical exploration of dimensional effects on CO2ERR. Herein, nanostructured OD-Cu catalysts of 1D nanowires (NWs), 2D nanosheets (NSs) and 3D nanoflowers (NFs) with good reconstruction resistance during CO2ERR are fabricated. Their well-preserved dimensional structures lead to altered Cu–O coordination, which is intensively investigated via X-ray absorption fine structure spectroscopy, resulting in distinctive CO2ERR performances. OD-Cu NWs catalyst with the highest Cu–O coordination possesses an impressive 77.7 % C2+ faradaic efficiency. Further in situ Fourier-transformed infrared spectroscopy and density functional theory calculations suggest more favorable asymmetric C–C coupling over the highest Cu–O coordination surface of OD-Cu NWs. This work provides new insights on developing reconstruction-resistant OD-Cu catalysts for value-added chemicals from advanced CO2 conversion.

Buying inferior to selling: Explore the impact of transaction direction on the effects of related-party transactions

Throughout, the effects of related-party transactions (RPTs) have been a hot topic in financial markets and corporate governance research. This paper analyzes the theoretical foundation of the effects of RPTs and constructs a new indicator, the quasi-profit margin, to assess the effects of RPTs by studying their impact on the quasi-profit margin. Based on the information asymmetry between transaction parties and the information screening theory, the paper proposes the buying inferior to selling theory, systematically explaining the impact of transaction direction on the effects of RPTs. Subsequently, using panel data from Chinese A-share listed companies from 2016 to 2021, the paper constructs fixed-effects models and conducts empirical studies from both exogenous and endogenous perspectives, employing estimation methods such as high dimensional fixed effects method, two-stage least squares method, and three-stage least squares method. The research indicates that RPTs of Chinese A-share listed companies generally exhibit a tunneling effect, and the transaction direction significantly affects the effects of RPTs. The higher the proportion of RPTs conducted as sellers to the total RPTs, the smaller the overall tunneling effect of the RPTs. This study has implications for reducing the tunneling risk of RPTs and improving corporate governance for listed companies, as well as providing some references for financial regulatory authorities to identify and rectify illegal RPTs.

A hybrid method for fault diagnosis of rolling bearings

Abstract Traditional diagnostic methods often have insufficient accuracy and noise reduction, which leads to diagnostic errors. To address these issues, this paper proposes an advanced fault diagnosis model that combines the variational mode decomposition (VMD) improved by a Variable-Objective Search Whale Optimization Algorithm (VSWOA) with a Pelican Optimization (PO)-boosted Kernel Extreme Learning Machine (KELM) algorithm. The application of the method is shown here in the fault diagnosis of rolling bearings. The proposed VSWOA enhances the performance of VMD by incorporating a Sobol sequence, nonlinear time-varying factors, a multi-objective initial search strategy, and an elite Cauchy chaos mutation strategy, significantly improving noise reduction in vibration signals. Fault information is precisely extracted using waveform factors, sample entropy, and advanced composite multiscale fuzzy entropy, which enables effective feature screening and dimensionality reduction. The POA fine-tunes the KELM parameters, increasing the classification accuracy. The effectiveness of the model is verified through experimental evaluations using bearing data with injected Gaussian noise (from Case Western Reserve University) and the SpectraQuest datasets, where significant improvements in noise reduction and fault detection accuracy are achieved.

Doxorubicin-Intercalated Li-Al-Based LDHs as Potential Drug Delivery Nanovehicle with pH-Responsive Therapeutic Cargo for Tumor Treatment.

Clinical oncology is currently experiencing a technology bottleneck due to the expeditious evolution of therapy defiance in tumors. Although drugs used in chemotherapy work for a sort of cell death with potential clinical application, the effectiveness of chemotherapy-inducing drugs is subject to several endogenous conditions when used alone, necessitating the urgent need for controlled mechanisms. A tumor-targeted drug delivery therapy using Li-Al (M+/M3+)-based layered double hydroxide (LDHs) family has been proposed with the general chemical formula [M+1-x M3+x (OH)]2x+[(Am-)2x/m. n(H2O)]2x-, which is fully biodegradable and works in connection with the therapeutic interaction between LDH nanocarriers and anticancerous doxorubicin (DOX). Compositional variation of Li and Al in LDHs has been used as a nanoplatform, which provides a functional balance between circulation lifetime, drug loading capacity, encapsulation efficiency, and tumor-specific uptake to act as self-regulatory therapeutic cargo to be released intracellularly. First-principle analyses based on DFT have been employed to investigate the interaction of bonding and electronic structure of LDH with DOX and assess its capability and potential for a superior drug carrier. Following the internalization into cancer cells, nanoformulations are carried to the nucleus via lysosomes, and the mechanistic pathways have been revealed. Additionally, in vitro along with in vivo therapeutic assessments on melanoma-bearing mice show a dimensional effect of nanoformulation for better biocompatibility and excellent synergetic anticancer activity. Further, the severe toxic consequences associated with traditional chemotherapy have been eradicated by using injectable hydrogel placed just beneath the tumor site, and regulated release of the drug has been confirmed through protein expression applying various markers. However, Li-Al-based LDH nanocarriers open up new design options for multifunctional nanomedicine, which has intriguing potential for use in cancer treatment through sustained drug delivery.

Dimensionality Effect on Surface States and Piezoelectric Behavior in ZnO Nanowires Grown by Pulsed-Liquid Injection Metal–Organic Chemical Vapor Deposition

Dimensionality Effect on Surface States and Piezoelectric Behavior in ZnO Nanowires Grown by Pulsed-Liquid Injection Metal–Organic Chemical Vapor Deposition

Topology Control of Covalent Organic Frameworks with Interlaced Unsaturated 2D and Saturated 3D Units for Boosting Electrocatalytic Hydrogen Peroxide Production.

Modulating the electronic state of multicomponent covalent organic framework (COF) electrocatalysts is crucial for enhancing catalytic activity. However, the effect of dimensionality on their physicochemical functionalities is still lacking. Herein, we report an interlaced unsaturated 2D and saturated 3D strategy to develop multicomponent-regulated COFs with tunable gradient dimensionality for high selectivity and activity electrocatalysis. Compared with the two-component 2D and 3D model COFs, the 2D/3D framework interlaced COFs with locally irregular dimensions and electronic structures are more practical in optimizing the intrinsic electrode surface reaction and mass transfer. Remarkably, the unsaturated 2D-inserted 3D TAE-COF regulates the adsorption mode of OOH* species to supply a favorable dynamic pathway for the H2O2 process, thereby achieving an excellent production rate of 8.50 mol gcat -1 h-1. Moreover, utilizing theoretical calculation and in situ ATR-FTIR experiment, we found that the central carbon atom of the tetraphenyl-based unit (site-1 and site-6) are potential active sites. This strategy of operating the adsorption ability of reactants with dimensionality-interconnected building blocks provides an idea for designing durable and efficient electrocatalysts.

Topology Control of Covalent Organic Frameworks with Interlaced Unsaturated 2D and Saturated 3D Units for Boosting Electrocatalytic Hydrogen Peroxide Production

AbstractModulating the electronic state of multicomponent covalent organic framework (COF) electrocatalysts is crucial for enhancing catalytic activity. However, the effect of dimensionality on their physicochemical functionalities is still lacking. Herein, we report an interlaced unsaturated 2D and saturated 3D strategy to develop multicomponent‐regulated COFs with tunable gradient dimensionality for high selectivity and activity electrocatalysis. Compared with the two‐component 2D and 3D model COFs, the 2D/3D framework interlaced COFs with locally irregular dimensions and electronic structures are more practical in optimizing the intrinsic electrode surface reaction and mass transfer. Remarkably, the unsaturated 2D‐inserted 3D TAE‐COF regulates the adsorption mode of OOH* species to supply a favorable dynamic pathway for the H2O2 process, thereby achieving an excellent production rate of 8.50 mol gcat−1 h−1. Moreover, utilizing theoretical calculation and in situ ATR‐FTIR experiment, we found that the central carbon atom of the tetraphenyl‐based unit (site‐1 and site‐6) are potential active sites. This strategy of operating the adsorption ability of reactants with dimensionality‐interconnected building blocks provides an idea for designing durable and efficient electrocatalysts.

Scaling Transition of Active Turbulence from Two to Three Dimensions.

Turbulent flows are observed in low-Reynolds active fluids, which display similar phenomenology to the classical inertial turbulence but are of a different nature. Understanding the dependence of this new type of turbulence on dimensionality is a fundamental challenge in non-equilibrium physics. Real-space structures and kinetic energy spectra of bacterial turbulence are experimentally measured from two to three dimensions. The turbulence shows three regimes separated by two critical confinement heights, resulting from the competition of bacterial length, vortex size and confinement height. Meanwhile, the kinetic energy spectra display distinct universal scaling laws in quasi-2D and 3D regimes, independent of bacterial activity, length, and confinement height, whereas scaling exponents transition in two steps around the critical heights. The scaling behaviors are well captured by the hydrodynamic model wedevelop, which employs image systems to represent the effects of confining boundaries. The study suggests a framework for investigating the effect of dimensionality on non-equilibrium self-organizedsystems.

Optimizing Electronic Conductivity to Improve the Thick Battery Electrode Performance for Lithium-Ion Batteries

Thick battery electrode designs have attracted broad interest from the lithium-ion battery industry because they represent a promising approach to significantly increase the battery energy density at the cell level and reduce the materials and manufacturing cost at the same time. However, increasing the electrode thickness also increases the ionic and electronic transport distance, leading to inferior rate performance. Previous studies on improving thick electrode performance have mainly focused on the design and fabrication of three-dimensional electrode architecture (e.g. electrodes with low tortuosity porous channels) to facilitate ionic transport. On the other hand, how the electronic conductivity should be optimized for thick electrodes has received less attention. Several existing studies report the effect of adding carbon nanotubes on the thick electrode performance, but it is not clear how the results could be generalized to other types of conductive additives. In this study, we ask the questions: how does the electrical conductivity affect the rate performance of thick electrodes, and are there general criteria for determining the optimal amount of conductive additives? Using LiFePO4 as a model system, we prepared a series of electrodes with different thickness and systematically varied electrical conductivity, which was achieved by adjusting the amount and ratios of two types of carbon additives, i.e. carbon black (C65) and vapor grown carbon nanofibers (VGCF). To obtain accurate readings of the intrinsic resistance of the LiFePO4 composite electrodes, a thickness extrapolation method was applied to remove the contact resistance at the Al/LiFePO4 and probe/LiFePO4 interfaces. We discovered that while 2 wt% C65 is sufficient for thin electrodes (<50 μm), at least 5 wt% C65 is required to maximize the rate performance of thicker electrodes (>100 μm), see Figure 1a&b. Further study reveals the existence of a critical electrical conductivity : the electrode’s rate capability increases with the conductivity at but saturates above (Figure 1c). The optimal amount of conductive additive is thus determined by . For electrodes thicker than 100 μm, we discovered that is independent of electrode thickness and comparable to the ionic conductivity of the electrodes. For thinner electrodes, however, increases monotonically with the electrode thickness L. We show that this phenomenon could be explained by the competition between three types of resistance present in the electrode: charge transfer (RCT), electrical (Relec) and ionic (Rion) resistances. Our prediction of the curve agrees with experiments, which could serve as a general guidance to the optimization of conductive additives for thick electrodes. Our study also reveals that the critical electrical conductivity could be most effectively achieved for thick electrodes via a combination of C65 and VGCF thanks to their complementary morphologies. While the fiber-shaped VGCF provides long-range pathways for electron conduction across the electrodes, the contact between particulate C65 and active materials facilitates the short-range electrical wiring. As a result, only 3 wt% of hybrid additives (2wt% C65 + 1wt% VGCF) is needed to reach , as opposed to 5 wt% of C65 only. Figure 1. Rate performance of electrode with different carbon amount (a) Thin electrode and (b) 150 μm electrodes. (c) Rate capability of electrode with different electrical conductivity. Acknowledgement This work is supported by Shell International Exploration and Production, Inc. Reference Kuang, Y.; Chen, C.; Kirsch, D.; Hu, L., Thick Electrode Batteries: Principles, Opportunities, and Challenges. Advanced Energy Materials 2019, 9 (33). Ju, Z.; Zhang, X.; King, S. T.; Quilty, C. D.; Zhu, Y.; Takeuchi, K. J.; Takeuchi, E. S.; Bock, D. C.; Wang, L.; Marschilok, A. C.; Yu, G., Unveiling the dimensionality effect of conductive fillers in thick battery electrodes for high-energy storage systems. Applied Physics Reviews 2020, 7 (4). Tian, R.; Alcala, N.; O’Neill, S. J. K.; Horvath, D. V.; Coelho, J.; Griffin, A. J.; Zhang, Y.; Nicolosi, V.; O’Dwyer, C.; Coleman, J. N., Quantifying the Effect of Electronic Conductivity on the Rate Performance of Nanocomposite Battery Electrodes. ACS Appl Energ Mater 2020, 3 (3), 2966-2974. Lee, B.-S.; Wu, Z.; Petrova, V.; Xing, X.; Lim, H.-D.; Liu, H.; Liu, P., Analysis of Rate-Limiting Factors in Thick Electrodes for Electric Vehicle Applications. J Electrochem Soc 2018, 165 (3), A525-A533. Figure 1

Endless Dirac nodal lines and high mobility in kagome semimetal Ni3In2Se2 : a theoretical and experimental study

Kagome-lattice crystal is crucial in quantum materials research, exhibiting unique transport properties due to its rich band structure and the presence of nodal lines and rings. Here, we investigate the electronic transport properties and perform first-principles calculations for Ni3In2Se2kagome topological semimetal. First-principles calculations of the band structure without the inclusion of spin-orbit coupling (SOC) shows that three bands are crossing the Fermi level (EF), indicating the semi-metallic nature. With SOC, the band structure reveals a gap opening of the order of 10 meV.Z2index calculations suggest the topologically nontrivial natures (ν0;ν1ν2ν3) = (1;111) both without and with SOC. Our detailed calculations also indicate six endless Dirac nodal lines and two nodal rings with aπ-Berry phase in the absence of SOC. The temperature-dependent resistivity is dominated by two scattering mechanisms:s-dinterband scattering occurs below 50 K, while electron-phonon (e-p) scattering is observed above 50 K. The magnetoresistance (MR) curve aligns with the theory of extended Kohler's rule, suggesting multiple scattering origins and temperature-dependent carrier densities. A maximum MR of 120% at 2 K and 9 T, with a maximum estimated mobility of approximately 3000 cm2V-1s-1are observed. Ni3In2Se2is an electron-hole compensated topological semimetal, as we have carrier density of electron (ne) and hole (nh) arene≈nh, estimated from Hall effect data fitted to a two-band model. Consequently, there is an increase in the mobility of electrons and holes, leading to a higher carrier mobility and a comparatively higher MR. The quantum interference effect leading to the two dimensional (2D) weak antilocalization effect (-σxx∝ln(B)) manifests as the diffusion of nodal line fermions in the 2D poloidal plane and the associated encircling Berry flux of nodal-line fermions.