Linear Alignment Research Articles

Achieving quantitative reproducibility in label-free multisite DIA experiments through multirun alignment

DIA is a mainstream method for quantitative proteomics, but consistent quantification across multiple LC-MS/MS instruments remains a bottleneck in parallelizing data acquisition. One reason for this inconsistency and missing quantification is the retention time shift which current software does not adequately address for runs from multiple sites. We present multirun chromatogram alignment strategies to map peaks across columns, including the traditional reference-based Star method, and two novel approaches: MST and Progressive alignment. These reference-free strategies produce a quantitatively accurate data-matrix, even from heterogeneous multi-column studies. Progressive alignment also generates merged chromatograms from all runs which has not been previously achieved for LC-MS/MS data. First, we demonstrate the effectiveness of multirun alignment strategies on a gold-standard annotated dataset, resulting in a threefold reduction in quantitation error-rate compared to non-aligned DIA results. Subsequently, on a multi-species dataset that DIAlignR effectively controls the quantitative error rate, improves precision in protein measurements, and exhibits conservative peak alignment. We next show that the MST alignment reduces cross-site CV by 50% for highly abundant proteins when applied to a dataset from 11 different LC-MS/MS setups. Finally, the reanalysis of 949 plasma runs with multirun alignment revealed a more than 50% increase in insulin resistance (IR) and respiratory viral infection (RVI) proteins, identifying 11 and 13 proteins respectively, compared to prior analysis without it. The three strategies are implemented in our DIAlignR workflow (>2.3) and can be combined with linear, non-linear, or hybrid pairwise alignment.

Peptide collision cross sections of 22 post-translational modifications

Recent advances have rekindled the interest in ion mobility as an additional dimension of separation in mass spectrometry (MS)-based proteomics. Ion mobility separates ions according to their size and shape in the gas phase. Here, we set out to investigate the effect of 22 different post-translational modifications (PTMs) on the collision cross section (CCS) of peptides. In total, we analyzed ~4300 pairs of matching modified and unmodified peptide ion species by trapped ion mobility spectrometry (TIMS). Linear alignment based on spike-in reference peptides resulted in highly reproducible CCS values with a median coefficient of variation of 0.26%. On a global level, we observed a redistribution in the m/z vs. ion mobility space for modified peptides upon changes in their charge state. Pairwise comparison between modified and unmodified peptides of the same charge state revealed median shifts in CCS between −1.4% (arginine citrullination) and +4.5% (O-GlcNAcylation). In general, increasing modified peptide masses were correlated with higher CCS values, in particular within homologous PTM series. However, investigating the ion populations in more detail, we found that the change in CCS can vary substantially for a given PTM and is partially correlated with the gas phase structure of its unmodified counterpart. In conclusion, our study shows PTM- and sequence-specific effects on the cross section of peptides, which could be further leveraged for proteome-wide PTM analysis.Graphical

Evidence for baryon acoustic oscillations from galaxy–ellipticity correlations

The baryon acoustic oscillation feature in the clustering of galaxies or quasars provides a ‘standard ruler’ for distance measurements in cosmology. In this work, we report a 2–3σ signal of the baryon acoustic oscillation dip feature in the galaxy density–ellipticity cross-correlation functions using the spectroscopic sample of the Baryon Oscillation Spectroscopic Survey CMASS, combined with the deep Dark Energy Spectroscopic Instrument Legacy Imaging Surveys for precise galaxy shape measurements. We measure the galaxy–ellipticity correlation functions and model them using the linear alignment model. We constrain the distance DV/rd to redshift 0.57 to a precision of 3–5%, depending on the details of modelling. The galaxy–ellipticity measurement reduces the uncertainty of distance measurement by ~10% on top of that derived from the galaxy–galaxy correlation. More importantly, for future large and deep galaxy surveys, the independent galaxy–ellipticity measurements can help sort out the systematics in the baryon acoustic oscillation studies.

Voice disorder classification using convolutional neural network based on deep transfer learning

Voice disorders are very common in the global population. Many researchers have conducted research on the identification and classification of voice disorders based on machine learning. As a data-driven algorithm, machine learning requires a large number of samples for training. However, due to the sensitivity and particularity of medical data, it is difficult to obtain sufficient samples for model learning. To address this challenge, this paper proposes a pretrained OpenL3-SVM transfer learning framework for the automatic recognition of multi-class voice disorders. The framework combines a pre-trained convolutional neural network, OpenL3, and a support vector machine (SVM) classifier. The Mel spectrum of the given voice signal is first extracted and then input into the OpenL3 network to obtain high-level feature embedding. Considering the effects of redundant and negative high-dimensional features, model overfitting easily occurs. Therefore, linear local tangent space alignment (LLTSA) is used for feature dimension reduction. Finally, the obtained dimensionality reduction features are used to train the SVM for voice disorder classification. Fivefold cross-validation is used to verify the classification performance of the OpenL3-SVM. The experimental results show that OpenL3-SVM can effectively classify voice disorders automatically, and its performance exceeds that of the existing methods. With continuous improvements in research, it is expected to be considered as auxiliary diagnostic tool for physicians in the future.

Linear local tangent space alignment with autoencoder

Linear local tangent space alignment (LLTSA) is a classical dimensionality reduction method based on manifold. However, LLTSA and all its variants only consider the one-way mapping from high-dimensional space to low-dimensional space. The projected low-dimensional data may not accurately and effectively “represent” the original samples. This paper proposes a novel LLTSA method based on the linear autoencoder called LLTSA-AE (LLTSA with Autoencoder). The proposed LLTSA-AE is divided into two stages. The conventional process of LLTSA is viewed as the encoding stage, and the additional and important decoding stage is used to reconstruct the original data. Thus, LLTSA-AE makes the low-dimensional embedding data “represent” the original data more accurately and effectively. LLTSA-AE gets the recognition rates of 85.10, 67.45, 75.40 and 86.67% on handwritten Alphadigits, FERET, Georgia Tech. and Yale datasets, which are 9.4, 14.03, 7.35 and 12.39% higher than that of the original LLTSA respectively. Compared with some improved methods of LLTSA, it also obtains better performance. For example, on Handwritten Alphadigits dataset, compared with ALLTSA, OLLTSA, PLLTSA and WLLTSA, the recognition rates of LLTSA-AE are improved by 4.77, 3.96, 7.8 and 8.6% respectively. It shows that LLTSA-AE is an effective dimensionality reduction method.

Endosidin 5 disruption of the Golgi Apparatus and extracellular matrix secretion in the unicellular charophyte, Penium margaritaceum.

Endosidins are a group of small molecular weight compounds, first identified by "chemical biology" screening assays, that have been used to target specific components of the endomembrane system. In this study, we employed multiple microscopy-based screening techniques to elucidate effects of Endosidin 5 (ES5) on the Golgi Apparatus and the secretion of extracellular matrix (ECM) components, Penium margaritaceum. These effects were compared with those caused by treatments with brefeldin A and concanamycin A. Penium margaritaceum's extensive Golgi Apparatus and endomembrane system make it an outstanding model organism for screening changes to the endomembrane system. Here we detail changes to the Golgi Apparatus and secretion of ECM material caused by Endosidin 5. Changes to extracellular polymeric substance (EPS) secretion and cell wall expansion were screened using fluorescence microscopy. Confocal laser scanning microscopy, and transmission electron microscopy were used to assess changes to the Golgi Apparatus, the cell wall and the vesicular network. Electron tomography was also performed in order to detail the changes to the Golgi Apparatus. While other endosidins were able to impact EPS secretion and cell wall expansion only ES5 completely inhibited EPS secretion and cell wall expansion over 24h. Short treatments of ES5 resulted in displacement of the Golgi bodies from their typical linear alignment. The number of cisternae decreased per Golgi stack and trans face cisternae in-curled to form distinct elongate circular profiles. Longer treatment resulted in a transformation of the Golgi body to an irregular aggregate of cisternae. These alterations could be reversed by removal of ES5 and returning cells to culture. ES5 alters secretion of ECM material in Penium by affecting the Golgi apparatus and does so in a markedly different way than other endomembrane inhibitors such as Brefeldin A and Concanamycin A.

A SE(2)-based transfer alignment for large installation misalignment angle

Transfer alignment is the optimal solution for initial alignment of shipborne or airborne weapons. The need for transfer alignment is increasing at large installation misalignment angles. Traditional linear models have large attitude errors at large installation misalignment angles, nonlinear algorithms are computationally intensive and difficult to be widely used, and quaternion optimization algorithms are sensitive to noise. In this paper, the Lie group theory is introduced for the first time in the study of transfer alignment. The attitude and velocity are represented as the Group of Direct Planar Isometries (SE(2)), and then the SE(2)-based error vectors are constructed by log-linearization. The SE(2)-based linear transfer alignment algorithm is developed for large installation misalignment conditions. The computational effort of the proposed algorithm is very small due to its linear structure, and it has strong engineering application value. The simulation and field test are conducted to illustrate the effectiveness of the proposed transfer alignment algorithm.

H κατοικία στην επικράτεια της Κορίνθου από την Αρχαϊκή έως και την Ελληνιστική περίοδο. Μια πρώτη κριτική προσέγγιση

H κατοικία στην επικράτεια της Κορίνθου από την Αρχαϊκή έως και την Ελληνιστική περίοδο. Μια πρώτη κριτική προσέγγιση

AUTOMATIC COIL WINDING MACHINE

The article deals with the design of a fully automated coil winding machine for stator winding of a motor used in submersible pumps. The conventional coil winding machine winds copper wire onto a former (winding fixture). The former is attached to the sliding arm which is actuated manually. However this machine usually has material tension limitations, operator intervention and low productivity and as motors are the basic need for all operation requiring automation, the stator winding becomes the growing and essential process in automation solutions. The machine winds the coil within the slots of the former. The length of the former is 9.2 cm. The number of slots and windings per slot are customized. The winding is done by suitable methodology using various components. The three phase geared induction motor actuates the rotation of sliding arm with suitable belt and pulley arrangement. Proximity sensor is used to count the number of turns of the sliding arm. The machine winds the coil of 110 turns per minute at 120 rpm. Shifter assembly consists of series of nylon pulleys to maintain tension and linear alignment. The ball screw mechanism is used for precise slot shifting, and it is driven by stepper motor. The machine is controlled by the PIC16F877A microcontroller. The required number of turns and slots is given as input through a keypad which is displayed in a LCD. After the process is over, it is notified through a buzzer. The approximate cost of the developed machine is reduced very much.

Gravitational wave fossils in nonlinear regime: Halo tidal bias and intrinsic alignments from gravitational wave separate universe simulations

We investigate impacts of long-wavelength gravitational waves (GWs) on nonlinear structure formation by utilizing the tidal separate universe simulations. Based on the equivalence of a long-wavelength GW to a uniform tidal field in a local frame, we provide a way to incorporate a long-wavelength GW into the tidal separate universe simulation as an effective anisotropic expansion. This methodology enables us to study effects of GWs on large-scale structure efficiently. We measure the anisotropic imprint in the local power spectrum from the tidal separate universe simulations with GWs, which corresponds to the scalar-scalar-tensor bispectrum in squeezed limit or the so-called power spectrum response to GWs. We also detect the halo tidal bias induced by GWs from the response of the halo-matter cross-power spectrum to GWs, as well as the linear shape bias (or the linear alignment coefficient) induced by GWs from the one-point function of the halo ellipticity. In contrast to the case of the tidal field induced by scalar perturbations, we discover that the wavenumber dependence of the temporal evolution of GWs naturally causes these biases to be scale-dependent. We also find that this scale dependence is well approximated by the second-order density induced by the coupling between scalar and tensor perturbation. This highlights that the structure formation, especially the process to determine the halo shape, is nonlocal in time. Our findings lay the foundation for predicting the impact of GWs on large-scale structure.

Comparison between Two Time Synchronization and Data Alignment Methods for Multi-Channel Wearable Biosensor Systems Using BLE Protocol

Wireless wearable sensor systems for biomedical signal acquisition have developed rapidly in recent years. Multiple sensors are often deployed for monitoring common bioelectric signals, such as EEG (electroencephalogram), ECG (electrocardiogram), and EMG (electromyogram). Compared with ZigBee and low-power Wi-Fi, Bluetooth Low Energy (BLE) can be a more suitable wireless protocol for such systems. However, current time synchronization methods for BLE multi-channel systems, via either BLE beacon transmissions or additional hardware, cannot satisfy the requirements of high throughput with low latency, transferability between commercial devices, and low energy consumption. We developed a time synchronization and simple data alignment (SDA) algorithm, which was implemented in the BLE application layer without the need for additional hardware. We further developed a linear interpolation data alignment (LIDA) algorithm to improve upon SDA. We tested our algorithms using sinusoidal input signals at different frequencies (10 to 210 Hz in increments of 20 Hz-frequencies spanning much of the relevant range of EEG, ECG, and EMG signals) on Texas Instruments (TI) CC26XX family devices, with two peripheral nodes communicating with one central node. The analysis was performed offline. The lowest average (±standard deviation) absolute time alignment error between the two peripheral nodes achieved by the SDA algorithm was 384.3 ± 386.5 μs, while that of the LIDA algorithm was 189.9 ± 204.7 μs. For all sinusoidal frequencies tested, the performance of LIDA was always statistically better than that of SDA. These average alignment errors were quite low-well below one sample period for commonly acquired bioelectric signals.

Collective decision-making and spatial patterns in orientation of an endemic ungulate on the Tibetan Plateau.

Group living animals form striking aggregation patterns and display synchronization, polarization, and collective intelligence. Though many collective behavioral studies have been conducted on small animals like insects and fish, research on large animals is still rare due to the limited availability of field collective data. We used drones to record videos and analyzed the decision-making and behavioral spatial patterns in orientation of Kiang (Tibetan wild ass, Equus kiang). Leadership is unevenly distributed among Kiang, with the minority initiating majority behavior-shift decisions. Decisions of individual to join are driven by imitation between group members, and are largely dependent on the number of members who have already joined. Kiang respond to the behavior and position of neighbors through different strategies. They strongly polarize when moving, therefore adopting a linear alignment. When vigilant, orientation deviation increases as they form a tighter group. They remain scattered while feeding and, in that context, adopt a side-by-side alignment. This study reveals partially-shared decision-making among Kiang, whereby copying neighbors provides the wisdom to thrive in harsh conditions. This study also suggests that animals' spatial patterns in orientation depend largely on their behavioral states in achieving synchronization.

Crystallographic controlled exsolution and metal partitioning in magmatic sulfide deposits

Magmatic sulfide liquids are effective at concentrating a range of metals. Within magmatic sulfide systems pentlandite, an exsolution product of monosulfide solid solution (MSS), is the primary host of Ni, Co and significant concentrations of Pd. Over the last decade, LA-ICP-MS mapping has revealed non-uniform metal distributions and complexity to the metal patterns such as zonation and the linear alignment of elements. Whereas the compatibility and partitioning behavior of chalcophile elements during sulfide fractionation are well constrained, there is little knowledge on the crystallographic control exerted on metal distributions.In this study, LA-ICP-MS mapping of globular sulfides from the Crystal Lake Intrusion, Ontario (Canada), is complimented by EBSD analysis, revealing a strong crystallographic control on both the concentration of metals and pentlandite exsolutions. Elements considered incompatible in the high temperature monosulfide solid solution (MSS) phase (e.g., Cr, V, As, Pb, Ag, Bi and Pd) are preserved as a microfabric, showing preferential concentration in association with the (0001) basal plane of pyrrhotite and adjacent pentlandite. Where the [0001] axis is viewed perpendicular to the cut surface, the microfabric is considered to be an intersection lineation between the basal (0001) plane and the surface of the cut section.Pentlandite textures described in magmatic sulfide deposits include granular, fan and laths/blades. Our observations indicate that marginal pentlandite exsolutions, are in optical continuity with granular exsolutions, providing insights into the growth of pentlandite at MSS grain boundaries. We conclude that all pentlandite forms are crystallographically controlled by the hexagonal mineral system of MSS/pyrrhotite, with the [0001] c-axis of pyrrhotite corresponding to the 〈111〉 axis of pentlandite. This axis also acts as a twinning rotation axis for the two identified pentlandite orientations. Fan and lath textured exsolutions are considered geometrically equivalent structures, being reconstructed as flat disc–shapes developed parallel to the basal (0001) plane of pyrrhotite, which acts as a preferred nucleation site. A network of low-angle grain boundaries are recognized as hexagonal or rectangular structures within pyrrhotite, with the morphology shown to be dependent on the orientation of the crystals. As these features are again geometric equivalents, they can be reconstructed as intragrain hexagonal prisms. We speculate due to their localized development, that they could represent a plastic response of the pyrrhotite to accommodate the increase in volume suggested to be associated with late pentlandite exsolutions and thus are the result of static lattice recovery.The microstructural and trace element observations presented here provide new context to some of the common textural features of magmatic sulfide deposits, while importantly highlighting the strong crystallographic control on both metal distributions and sulfide textures. This study also importantly recognizes the dominance of hexagonal pyrrhotite within the ores of the Crystal Lake Intrusion and likely other magmatic sulfide deposits. This has implications for mineral processing as its non-magnetic properties can result in dilution of Ni-Cu-PGE ores and thus requires special attention for the flotation strategy.

Development and mechanical properties of soy protein fibrils-chitin nanowhiskers complex gel

To enrich the use of protein-polysaccharide complex gel as texture assistance, we introduced a soy protein fibrils-chitin nanowhiskers complex gel system. Firstly, a stable positively charged chitin nanowhiskers (CNW) suspension and amyloid-like soy protein fibrils (SPF) were fabricated. We found that the self-assembled SPF and CNW formed complex with each other at pH 5.0–8.0 due to attractive interactions caused by their carrying opposite electrical charges. Then, the MTGase-induced SPF-CNW complex gel were formed and investigated by instrumental analysis. The results showed that the presence of CNW significantly increased the β-Sheet structure in complex gel and the rheological modules of complex gel were pH-dependent and showing G' > G" at all pHs. The SPF-CNW complex gel showed a strong and elastic textural property during compression test at pH 6.0. Meanwhile, the frequency scan showed that the SPF-CNW system is less dependent on the frequency and belonged to the typical physical gel. According to the results of SEM and CLSM images, the SPF, CNW and complex gel presented spherical shape, rod shape and linear alignment microstructure, respectively. We inferred that the CNW provided a framework for gel formation and introduced rigidity to the SPF gel. Thanks to the attractive interactions, the SPF molecules were attached to the growth of CNW to form a longer fiber structure. After the gelation process, the aggregates further interacted with each other and finally form complex gel with linear, ordered and compact microstructure.

Manifold Learning via Linear Tangent Space Alignment (LTSA) for Accelerated Dynamic MRI With Sparse Sampling.

The spatial resolution and temporal frame-rate of dynamic magnetic resonance imaging (MRI) can be improved by reconstructing images from sparsely sampled k -space data with mathematical modeling of the underlying spatiotemporal signals. These models include sparsity models, linear subspace models, and non-linear manifold models. This work presents a novel linear tangent space alignment (LTSA) model-based framework that exploits the intrinsic low-dimensional manifold structure of dynamic images for accelerated dynamic MRI. The performance of the proposed method was evaluated and compared to state-of-the-art methods using numerical simulation studies as well as 2D and 3D in vivo cardiac imaging experiments. The proposed method achieved the best performance in image reconstruction among all the compared methods. The proposed method could prove useful for accelerating many MRI applications, including dynamic MRI, multi-parametric MRI, and MR spectroscopic imaging.

Weighted Linear Local Tangent Space Alignment via Geometrically Inspired Weighted PCA for Fault Detection

Principal component analysis (PCA) is widely adopted in local tangent space alignment to estimate local tangent spaces. These estimates are only accurate when uniformly distributed data lies in or is close to linear subspaces. In practice, such conditions are rarely satisfied. Therefore, this approach fails to reveal manifold intrinsic features, resulting in degraded fault detection accuracy. Considering the drawbacks, weighted linear local tangent space alignment (WLLTSA), a manifold learning method is put forward. First, weighted PCA is adopted to provide local tangent space estimates. The parameter selection criterion for the weight matrix is established by taking the context of geometric preservation into account. Second, global low dimensional coordinates are formed by aligning local coordinates with global feature space. Finally, the fault detection model is developed, and kernel density estimation is utilized to approximate confidence bounds for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mathrm{T}^{\mathrm{2}}$</tex-math></inline-formula> and SPE statistics. Simulation results are presented to illustrate the superior feature extraction and fault detection performance of WLLTSA.

Evaluation of Factors of Soil Resistivity in the Niger Delta

Soil conductivity is responsible for its aggressive behavior to metallic objects either in contact or buried in the ground. Rapid deterioration and eventual rupture of pipelines leading ultimately to crude oil spillages have been of economic as well as environmental concern. Although many factors contribute to soil resistivity, these relationships have hardly been quantitatively expressed. This paper explores the factors affecting soil resistivity firstly by matching the spatial regional distribution with each of the identified factors of influence, including ground elevation soil type, depth to water table and undrained strength. 183 Vertical Electrical Sounding VES with the ABEM SAS 1000, using Schlumberger electrode configuration were carried out along a pipeline route to generate resistivity distribution across a linear alignment that traverses three geomorphic sub-environments in the Niger Delta Region. The apparent resistivity values averaged over depths of 3 m and 10 m were plotted against the co-ordinates using Surfer-16 and overlaid on Google earth Pro to produce a spatial distribution with enhanced location visibility. The results show that apparent resistivity is influenced by depth to water table with lower values in areas of shallow water table occurrence. Furthermore, it is shown that changes in resistivity below the water table are more due to variation in soil type. Within a soil type above the water table, soil resistivity increases monotonically with depth until the depth of probe extends to a different soil horizon. Results of this study provide guidance as to what ground resistivity to expect in different part of the delta as well as provide valuable information to assess the risks to assets either as a means of prioritizing maintenance or of improving design for new installations in the Niger Delta Region.

Fault diagnosis model based on adaptive generalised morphological filtering and LLTSA-ELM

It is difficult for a single feature to contain all the information needed to describe the running state of the equipment. Though multi-features can contain more information about running state, the redundancy between high-dimension features can easily reduce the accuracy of the classifier. Aimed at that, a fault diagnosis method for rolling bearings combining adaptive generalised morphological filter, linear local tangent space alignment and extreme learning machine (LLTSA-ELM) is proposed. Firstly, the rolling bearing vibration signals are filtered by an adaptive generalised morphological filter. Secondly, the multi-domain features are extracted from filtered signal to construct high-dimensional features set of bearing. Thirdly, the dimension of high-dimensional features is reduced by maximum likelihood estimation (MLE) and LLTSA. Finally, the bearing condition monitoring model based on ELM is constructed by the reduced dimension features, and then is used to analyse and diagnose the running state of bearing. Experiments show that this method can effectively filter noise, reduce the redundancy caused by high-dimensional features, and improve the recognition accuracy of the running state of bearings.

SINS/DVL Linear Initial Alignment based on Lie Group SE3 (3)

This paper investigates the strapdown inertial navigation system (SINS) initial alignment aided by Doppler velocity log (DVL). A linear Kalman filtering method is proposed using the theory of Lie group, which is immune to the initial misalignment. The dead-reckoning position based on the body velocity provided by DVL and attitude provided by SINS is used as measurement. The SINS calculated attitude, velocity, position and DVL dead-reckoning position are formulated together as the elements of Lie group SE <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> (3). Since the dead-reckoning position is a type of left-invariant measurement, the corresponding linear error-state model is derived based on the left-invariant group error definition. Although the Lie group state model is not group affine, thesmall attitude error assumption does not introduce accuracy degeneracy in deriving the linear error-state model. This is the core reason why the derived linear error-state model is still applicable for cases with large initial misalignment. Experiments are conducted to verify the feasibility and effectiveness of the proposed methods. The test results show that the proposed method has higher accuracy and faster convergence speed as compared with the existing methods.

DFT calculations and giant dielectric responses in (Ni1/3Nb2/3)xTi1-xO2.

The origins of dielectric responses in Ni2+ and Nb5+ co-doped TiO2 were explored considering intrinsic and extrinsic effects. DFT calculations demonstrated that Ni2+ doping induced oxygen vacancies, while Nb5+ doping generated free electrons. Theoretical predictions indicated complex defect dipoles forming in the rutile structure, contributing to overall dielectric responses. Theoretical calculations also showed a possible linear alignment of Ni2+-2Nb5+ without oxygen vacancies, especially in high doping concentrations. Experimentally, (Ni1/3Nb2/3)xTi1-xO2 ceramics (x = 1%, 2.5%, and 10%) were synthesized. The substantial dielectric response at room temperature, attributed to factors like defect dipoles and grain boundary/surface barrier layer capacitor (GBLC/SBLC) effects, increased with higher doping levels. However, in a temperature range where GBLC/SBLC effects were suppressed, the dielectric response decreased with increased doping, likely due to self-charge compensation between Ni2+-2Nb5+. Notably, (Ni1/3Nb2/3)xTi1-xO2 with x = 2.5% exhibited a high dielectric permittivity of 104 and a low loss tangent of 0.029 at 1 kHz. Moreover, the dielectric permittivity changed by less than ±15% (compared to 25 °C) at 150 °C. This work provides an understanding of the origins of dielectric responses in co-doped TiO2 and optimizes the doping concentration to achieve the best dielectric performance.