Complexity Reduction Research Articles

Effect of “corona-core” structuring of poly(1-vinyl-1,2,4-triazole)–poly(acrylic acid)-Ag(I) interpolymer complexes on the radiation-induced preparation and stability of silver nanoparticles

Interpolymer complexes (IPC) of water-soluble polymers can be promising matrices for the synthesis of metal colloids. In this work, silver nanoparticles were obtained via radiation-induced reduction (under X-ray irradiation) of complexes based on poly (1-vinyl-1,2,4-triazole) (PVT) and poly (acrylic acid) (PAA) containing Ag+ ions. Particular attention was paid to the role of the supramolecular structure in the formation of nanoparticles. Combined dynamic light scattering and electrophoretic mobility measurements have revealed that, in pH range 5.5–7, micro-scale aggregates of the initial PVT-PAA-Ag(I) IPC transform into nano-sized particles consisting of a PVT-Ag(I) core electrostatically stabilized by PAA loops and tails forming a corona. It was explicitly demonstrated for the first time that such transformation of IPC aggregates can significantly enhance the efficiency of AgNPs formation. In particular, using UV-VIS spectroscopy and transmission electron microscopy, we have shown that at pH 7.0 the core of the “corona-like” form of the PVT-PAA-Ag(I) complex ensures the radiation-induced generation of AgNPs with a narrow size distribution due to the strong affinity of triazole groups to the metal surface. At the same time, the localization of the excessive negatively charged carboxylate groups in the outer part of the complex provides a long-term colloidal stability of the prepared AgNPs.

Complexity Reduction in Intra Prediction of HEVC Using a Modified Convolutional Neural Network Model Incorporating Depth Map and RGB Texture

Complexity Reduction in Intra Prediction of HEVC Using a Modified Convolutional Neural Network Model Incorporating Depth Map and RGB Texture

Intelligent switching gain based sliding mode control for optimization of power consumption in cooperative manipulators

AbstractCooperative manipulators, vital for intricate tasks, are gaining widespread attention across industries. Recognizing their impact on power consumption, costs, and task outcomes, this paper emphasizes the critical study of control methods, actuator power consumption, and manipulator accuracy. Addressing these challenges, we propose a neural network‐sliding mode controller (NN‐SMC) to optimize actuator power consumption and minimize errors in cooperative manipulators. Operating in trajectory and point‐to‐point modes, the NN‐SMC dynamically generates real‐time switching mode controller (SMC) gains (L and K) for precise control. Stability is ensured by maintaining gains within permissible ranges. In point‐to‐point mode, the NN orchestrates an optimal path generation, along with tailored gains. To evaluate performance accurately, a novel control performance index is introduced. Experimental results on 3‐DOF cooperative manipulators demonstrate a remarkable 28% increase in the control performance index for the trajectory mode and a substantial reduction in computational complexity for both modes. This work not only addresses inherent challenges in cooperative manipulators but also signifies a methodological advancement through the integration of neural network‐based control, promising enhanced efficiency and stability.

Two-torsion subgroups of some modular Jacobians

We give a practical method to compute the 2-torsion subgroup of the Jacobian of a non-hyperelliptic curve of genus [Formula: see text], [Formula: see text] or [Formula: see text]. The method is based on the correspondence between the 2-torsion subgroup and the theta hyperplanes to the curve. The correspondence is used to explicitly write down a zero-dimensional scheme whose points correspond to elements of the [Formula: see text]-torsion subgroup. Using [Formula: see text]-adic or complex approximations (obtained via Hensel lifting or homotopy continuation and Newton–Raphson) and lattice reduction we are then able to determine the points of our zero-dimensional scheme and hence the [Formula: see text]-torsion points. We demonstrate the practicality of our method by computing the [Formula: see text]-torsion of the modular Jacobians [Formula: see text] for [Formula: see text]. As a result of this we are able to verify the generalized Ogg conjecture for these values.

RBF-based partition of unity methods for two-dimensional time-dependent PDEs: Numerical and theoretical aspects

This article discusses standard Radial Basis Function (RBF) partition of unity method and an enhanced version known as the direct RBF partition of unity method. We introduce the framework of these methods for the effective and accurate numerical analysis of certain two-dimensional time-dependent Partial Differential Equations (PDEs). Additionally, we conduct a convergence analysis of these methods and establish error bounds for local approximations. These error bounds are determined based on conditions associated with the eigenvalues of the Laplacian operator matrices generated by the proposed methods. To validate the accuracy and reliability of these approaches, we provide several numerical examples. We assess the consistency between theoretical and numerical results. The localized techniques introduced in this research demonstrate a significant reduction in computational cost and algorithmic complexity, achieved through the direct local procedure. Despite this computational advantage, both versions of the RBF partition of unity method exhibit a similar level of accuracy. Finally, we conduct a comparative analysis between the RBF partition of unity local methods and the RBF-generated finite differences method, offering valuable insights into the strengths and limitations of each approach.

White matter and cortical gray matter microstructural abnormalities in new daily persistent headache: a NODDI study

BackgroundNew daily persistent headache (NDPH) is a rare primary headache with unclear pathogenesis. Neuroimaging studies of NDPH are limited, and controversy still exists. Diffusion tensor imaging (DTI) is commonly used to study the white matter. However, lacking specificity, the potential pathological mechanisms of white matter microstructural changes remain poorly understood. In addition, the intricacy of gray matter structures impedes the application of the DTI model. Here, we applied an advanced diffusion model of neurite orientation dispersion and density imaging (NODDI) to study the white matter and cortical gray matter microstructure in patients with NDPH.MethodsThis study assessed brain microstructure, including 27 patients with NDPH, and matched 28 healthy controls (HCs) by NODDI. The differences between the two groups were assessed by tract-based spatial statistics (TBSS) and surface-based analysis (SBA), focusing on the NODDI metrics (neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)). Furthermore, we performed Pearson’s correlation analysis between the NODDI indicators and clinical characteristics.ResultsCompared to HCs, patients with NDPH had a reduction of density and complexity in several fiber tracts. For robust results, the fiber tracts were defined as comprising more than 100 voxels, including bilateral inferior fronto-occipital fasciculus (IFOF), left superior longitudinal fasciculus (SLF) and inferior longitudinal fasciculus (ILF), as well as right corticospinal tract (CST). Moreover, the reduction of neurite density was uncovered in the left superior and middle frontal cortex, left precentral cortex, and right lateral orbitofrontal cortex and insula. There was no correlation between the NODDI metrics of these brain regions and clinical variables or scales of relevance after the Bonferroni correction.ConclusionsOur research indicated that neurite loss was detected in both white matter and cortical gray matter of patients with NDPH.

A hybrid Monte Carlo, discontinuous Galerkin method for linear kinetic transport equations

We present a hybrid method for time-dependent particle transport problems that combines Monte Carlo (MC) estimation with deterministic solutions based on discrete ordinates. For spatial discretizations, the MC algorithm computes a piecewise constant solution and the discrete ordinates use bilinear discontinuous finite elements. From the hybridization of the problem, the resulting problem solved by Monte Carlo is scattering free, resulting in a simple, efficient solution procedure. Between time steps, we use a projection approach to “relabel” collided particles as uncollided particles. From a series of standard 2-D Cartesian test problems we observe that our hybrid method has improved accuracy and reduction in computational complexity of approximately an order of magnitude relative to standard discrete ordinates solutions.

Repurposed 3D Printer Allows Economical and Programmable Fraction Collection for Proteomics of Nanogram Scale Samples.

In this work, we describe the construction and application of a repurposed 3D-printer as a fraction collector. We utilize a nano-LC to ensure minimal volumes and surfaces although any LC can be coupled. The setup operates as a high-pH fractionation system capable of effectively working with nanogram scales of lysate digests. The 2D RP-RP system demonstrated superior proteome coverage over single-shot data-dependent acquisition (DDA) analysis using only 5 ng of human cell lysate digest with performance increasing with increasing amounts of material. We found that the fractionation system allowed over 60% signal recovery at the peptide level and, more importantly, we observed improved protein level intensity coverage, which indicates the complexity reduction afforded by the system outweighs the sample losses endured. The application of data-independent acquisition (DIA) and wide window acquisition (WWA) to fractionated samples allowed nearly 8000 proteins to be identified from 50 ng of the material. The utility of the 2D system was further investigated for phosphoproteomics (>21 000 phosphosites from 50 μg starting material) and pull-down type experiments and showed substantial improvements over single-shot experiments. We show that the 2D RP-RP system is a highly versatile and powerful tool for many proteomics workflows.

INCREASING OR DECREASING FRUGALITY: THE CONNECTION BETWEEN DIGITALISATION AND FRUGAL INNOVATION

Within wider debates on sustainability and digitalisation, frugal innovation (FI) scholars largely assume that digital technologies are important for FI in realising more sustainable outcomes. However, very few studies interrogate this causality. To tackle this challenge, we connect FI with digitalisation. Thereto, we conceptualise digital technologies as and within FIs and discuss three frugality dimensions to analyse three empirical case studies of digitally-enabled FIs. We use these cases to introduce new nuances on how digitalisation affects frugality and scaling. Our results unveil that digitalisation can increase frugality by enabling more accessible and affordable solutions through new flexible funding schemes and pay-as-you-go models. However, our evidence also implies decreasing frugality by an increase in end-user costs and digital exclusion. Likewise, increasing frugality through complexity reduction seems mainly to benefit intermediaries and frugal innovators themselves, whereas benefits of digitalisation in terms of complexity reduction for end-users seem to be limited. Digitalisation can even increase complexity for end-users, thus suggesting decreasing frugality. Finally, just like with non-digital innovations, scaling of digitally enabled innovations is dependent on the quality of logistical infrastructure and local adaptation practices. Moreover, scaling of digitally-enabled innovations is limited to users in regions with a proper ICT infrastructure.

SAT-based Decision Tree Learning for Large Data Sets

Decision trees of low depth are beneficial for understanding and interpreting the data they represent. Unfortunately, finding a decision tree of lowest complexity (depth or size) that correctly represents given data is NP-hard. Hence known algorithms either (i) utilize heuristics that do not minimize the depth or (ii) are exact but scale only to small or medium-sized instances. We propose a new hybrid approach to decision tree learning, combining heuristic and exact methods in a novel way. More specifically, we employ SAT encodings repeatedly to local parts of a decision tree provided by a standard heuristic, leading to an overall reduction in complexity. This allows us to scale the power of exact SAT-based methods to comparatively very large data sets. We evaluate our new approach experimentally on a range of real-world instances that contain up to several thousand samples. In almost all cases, our method successfully decreases the complexity of the initial decision tree; often, the decrease is significant.

MICOS Complex Loss Governs Age-Associated Murine Mitochondrial Architecture and Metabolism in the Liver, While Sam50 Dictates Diet Changes.

The liver, the largest internal organ and a metabolic hub, undergoes significant declines due to aging, affecting mitochondrial function and increasing the risk of systemic liver diseases. How the mitochondrial three-dimensional (3D) structure changes in the liver across aging, and the biological mechanisms regulating such changes confers remain unclear. In this study, we employed Serial Block Face-Scanning Electron Microscopy (SBF-SEM) to achieve high-resolution 3D reconstructions of murine liver mitochondria to observe diverse phenotypes and structural alterations that occur with age, marked by a reduction in size and complexity. We also show concomitant metabolomic and lipidomic changes in aged samples. Aged human samples reflected altered disease risk. To find potential regulators of this change, we examined the Mitochondrial Contact Site and Cristae Organizing System (MICOS) complex, which plays a crucial role in maintaining mitochondrial architecture. We observe that the MICOS complex is lost during aging, but not Sam50. Sam50 is a component of the sorting and assembly machinery (SAM) complex that acts in tandem with the MICOS complex to modulate cristae morphology. In murine models subjected to a high-fat diet, there is a marked depletion of the mitochondrial protein SAM50. This reduction in Sam50 expression may heighten the susceptibility to liver disease, as our human biobank studies corroborate that Sam50 plays a genetically regulated role in the predisposition to multiple liver diseases. We further show that changes in mitochondrial calcium dysregulation and oxidative stress accompany the disruption of the MICOS complex. Together, we establish that a decrease in mitochondrial complexity and dysregulated metabolism occur with murine liver aging. While these changes are partially be regulated by age-related loss of the MICOS complex, the confluence of a murine high-fat diet can also cause loss of Sam50, which contributes to liver diseases. In summary, our study reveals potential regulators that affect age-related changes in mitochondrial structure and metabolism, which can be targeted in future therapeutic techniques.

Host-virus coevolution drives soil microbial function succession along a millennium land reclamation chronosequence

IntroductionGene exchange between viruses and hosts plays an important role in driving virus-host coevolution, enabling adaptation of both viruses and hosts to environmental changes. However, the mechanisms and functional significance of virus-host gene exchanges over long-term scales remain largely unexplored. ObjectiveThe present study aimed to gain insights into the role of viruses in virus-host interactions and coevolution by monitoring virome dynamics along a millennium-long land reclamation chronosequence. MethodsWe collected 24 soil samples from 8 stages of a millennium-long land reclamation chronosequence, including non-reclamation, and reclamation periods of 10, 50, 100, 300, 500, 700, and 1000 years. We characterized their metagenomes, and identified DNA viruses within these metagenomes. ResultsOur findings reveal a significant shift in viral community composition after 50 years of land reclamation, but soil viral diversity reached a stable phase approximately 300 years after the initial reclamation. Analysis of the virus-host network showed a scale-free degree distribution and a reduction in complexity over time, with generalist viruses emerging as key facilitators of horizontal gene transfer. ConclusionThese findings highlight the integral role of viruses, especially generalist types, in mediating gene exchanges between viruses and hosts, thereby influencing the coevolutionary dynamics in soil ecosystems over significant timescales. This study offers novel insights into long-term virus-host interactions, showing how the virome responds to environmental changes, driving shifts in various microbial functions in reclaimed land.

Diagnosis of Arrhythmia from Compressively Sensed ECG Signals Using Machine Learning Algorithms

Cardiovascular diseases (CVDs) represent a significant health concern in the present era, with Electrocardiogram (ECG) serving as a crucial bio-signal for their detection. Efficient health monitoring necessitates rapid and precise diagnosis, thereby mandating the utilization of Compressive Sensing (CS) alongside Machine Learning (ML) algorithms. CS functions as a sensing methodology that reduces sample numbers by capturing sparse or compressible representations, simplifying and expediting the acquisition process. In this proposed study, ECG signals are compressively sensed and preprocessed using CS reconstruction algorithms, followed by the application of various ML algorithms for diagnostic purposes. The assessment of the reconstructed ECG signal entails the assessment of Peak Signal-to-Noise Ratio (PSNR) values and Percentage Root-mean-square Difference (PRD). Concurrently, ML algorithms are evaluated based on metrics including accuracy, specificity, and sensitivity. This work demonstrates exceptional performance in terms of acquisition time and computational complexity through the application of CS technology. Comparative analysis with the existing methodologies for CVD diagnosis reveals the proposed approach’s remarkable efficacy. Notably, the reduction in data volume and hardware complexity serves as a significant advantage over conventional methods. The integration of CS and ML algorithms in the proposed methodology proves highly effective in diagnosing CVDs, achieving a classification accuracy of 94.7%. These results underscore the methodology’s ability to deliver both speed and accuracy in diagnosis, positioning it as a promising approach for health monitoring.

Dynamic synergies in cable-driven exosuits for gait assistance

Exosuits for the lower limb have developed rapidly as an affordable, light, and more cost-effective alternative to the bulkier, traditional exoskeletons. The synergy-based approach aims at further emphasizing such advantages, providing even lighter and cheaper solutions, thanks to its reduction in actuators and the subsequent simplification of the actuation unit. In this paper, a design approach based on dynamic synergies is proposed to reduce the number of required actuators, thus decreasing the price and weight of walking-assistance exosuits. Also, in this work, we propose a methodology to calculate motor torque output and cable forces during assisted gait. Mechanical designs for the actuation unit are proposed along with experimental and computer-based testing and simulation. Lastly, actuation units with one and two motors are studied and compared, regarding control, mechanical complexity, and metabolic cost reduction. The results show that dynamic synergies can indeed contribute to the design of these assistive devices, with its own set of advantages and disadvantages when compared to the previously proposed postural synergies: while the latter led to a higher cumulative variance of the first principal component and the transmission system is simpler, control may be more unpredictable and forces upon the system, harder to estimate. With dynamic synergies, more related to muscle synergies, metabolic benefit on users may be more significant.

Updating direct methods II. Reduction of the structural complexity when triplet invariants are estimated via the Patterson map

Direct methods have practically solved the phase problem for small–medium-size molecules but have substantially failed in macromolecular crystallography. They have two main limitations: a strong dependence on structural complexity and the need to work with atomic-resolution data. Many attempts have been made to broaden their field of applicability, for example the use of some a priori information to make the estimate of the triplet invariant phases more effective. Unfortunately none of these new approaches allowed the successful application of direct methods to proteins and nucleic acids. Direct methods are still a niche tool in macromolecular crystallography. In a recent publication [Giacovazzo (2019). Acta Cryst. A75, 142–157] the method of joint probability distributions has been modified to take into account new sources of prior information, one of which is relevant to this article: the Patterson map. In practice, it has been shown that with prior knowledge of the interatomic vectors one is able to modify the classic Cochran reliability parameter for estimating the triplet invariant phases. The article was essentially theoretical in nature, and no attempt was described to test the practical usefulness of the new probabilistic formulas. This work is therefore the first application of the new method. It is shown that the use of the Patterson map as prior information substantially improves the Cochran estimate of triplet phases; the phase error distribution for the new estimates, even if it is related to macromolecular structures, becomes similar to that obtained for medium-size structures. In some ways, it is as if the use of the Patterson information reduces the structural complexity, thus allowing a more general use of direct methods in macromolecular crystallography. Atomic resolution no longer seems to be a necessary ingredient for the applicability of direct methods; tests show that the apparent reduction in structural complexity also occurs in macromolecular structures with experimental data having a resolution of 2.3 Å. A number of test structures have been used to show the potential of the new technique.

Real-time coordination of integrated transmission and distribution systems: Flexibility modeling and distributed NMPC scheduling

This paper proposes a real-time distributed operational architecture to coordinate integrated transmission and distribution systems (ITD). At the distribution system level, the distribution system operator (DSO) calculates the aggregated flexibility of all controllable devices by power-energy envelopes and provides them to the transmission system operator (TSO). At the transmission system level, a distributed nonlinear model predictive control (nmpc) approach is proposed to coordinate the economic dispatch of multiple TSOs, considering the aggregated flexibility of all distribution systems. The subproblems of the proposed approach are associated with different TSOs and individual time periods. In addition, the aggregated flexibility of controllable devices in distribution networks is encapsulated, re-calculated, and communicated through the power-energy envelopes, facilitating a reduction in computational complexity and eliminating redundant information exchanges between TSOs and DSOs, thereby enhancing privacy and security. The framework’s effectiveness and applicability in real-world scenarios are validated through simulated operational scenarios on a summer day in Germany, highlighting its robustness in the face of significant prediction mismatches due to severe weather conditions.

Visual function and retinal thickness in children with type 1 diabetes mellitus

ABSTRACT Clinical Relevance The possibility that changes in blue–yellow visual thresholds and some retinal thickness measures in children with diabetes mellitus may be observed before any visible fundus changes points to the possibility of these measures being a useful predictor that the risks of diabetic retinopathy are higher in some children than in others. Introduction Previous studies showed mixed results on chromatic and achromatic contrast sensitivity early in the course of diabetes mellitus, and the findings of these studies may have been influenced by a lack of experimental sensitivity to visual deficits, a bias towards tritan-like errors or the cognitive demands of the tests and variations in sample composition. The purpose of this study was to evaluate colour and contrast thresholds and retinal thickness in children with type 1 diabetes mellitus compared with age-matched controls. Methods A prospective case–control study was carried out on 9–14-year-old children with type 1 diabetes mellitus (49 cases) and age matched controls (49) in which isoluminant red–green and blue–yellow and achromatic luminance contrast thresholds were measured. Fundus photography was used to grade diabetic retinopathy. Retinal thickness parameters were measured using optical coherence tomography. Data on the duration of diabetes mellitus, glycaemic control (HbA1c), blood glucose level, body mass index, blood pressure and blood oxygenation at the time of testing were obtained. Results The cases mostly had poorly controlled diabetes, HbA1c 8.6% (6.4–12.8%), for an average (range) duration of 5 (0.4–12) years. The cases had significantly higher blue–yellow thresholds (p = 0.02) and greater total retinal and inner retinal thickness (p < 0.05) than controls. No cases had diabetic retinopathy. Within the cases, poorer visual function and systemic health measures were associated with thinner retinal structures and greater global loss volume percentage in the ganglion cell complex. Conclusion Blue–yellow thresholds of cases were raised compared to normal. Within the cases, higher luminance contrast thresholds were also associated with, mostly, ganglion cell complex reductions.

Pseudomonas aeruginosa impairs mitochondrial function and metabolism during infection of corneal epithelial cells.

Pseudomonas aeruginosa (PA) is a gram-negative opportunistic pathogen that can infect the cornea as a result of trauma or contact lens wear. In addition to their known energy producing role, mitochondria are important mediators of immune signaling and host defense. While certain pathogens have developed strategies to evade host defenses by modulating host mitochondrial dynamics and metabolism, the ability of PA to harness host cell mitochondria during corneal infection is unknown. Using a combination of biochemical and imaging techniques, we show that PA infection of corneal epithelial cells induced mitochondrial fission in a DRP1-dependent manner that preceded PINK1/Parkin and FUNDC1-mediated mitophagy. PA also impaired NADH-linked respiration through a reduction in complex 1. This corresponded to a decrease in metabolic pathways related to glycolysis and the TCA cycle. Metabolomics analysis further demonstrated an upregulation of the pentose phosphate pathway, arginine, purine, and pyrimidine metabolism in PA infected cells. These pathways may provide a key source of nucleotides, amino acids, and nitrogen for both the host cell and PA, in addition to antioxidant functions. Following treatment with gentamicin to kill all extracellular bacteria, metabolic flux analysis showed that corneal epithelial cells were able to restore mitochondrial function despite the continued presence of intracellular PA. Taken together, these data demonstrate that mitochondrial dysfunction and metabolic rewiring in host cells is triggered by extracellular PA, but once inside, PA requires healthy mitochondria to ensure host cell survival.

Force Fluctuations During Role-Differentiated Bimanual Movements Reflect Cognitive Impairments in Older Adults: A Cohort Sequential Study.

During role-differentiated bimanual movements (RDBM), an object is typically stabilized with 1 hand and manipulated with the other. RDBM require coupling both hands for coordinated action (achieved through interhemispheric connections), but also inhibition of crosstalk to avoid involuntary movements in the stabilizing hand. We investigated how healthy cognitive aging and mild cognitive impairments (MCI) affect force stabilization during an RDBM in a cohort sequential study design with up to 4 measurement points over 32 months. In total, 132 older adults (>80 years) participated in this study, 77 were cognitively healthy individuals (CHI) and 55 presented with MCI. Participants performed a visuomotor bimanual force-tracking task. They either produced a constant force with both hands (bimanual constant) or a constant force with 1 and an alternating force with the other hand (role-differentiated). We investigated force fluctuations of constant force production using the coefficient of variation (CV), detrended fluctuation analysis (DFA), and sample entropy (SEn). Results showed higher CV and less complex variability structure (higher DFA and lower SEn) during the role-differentiated compared to the bimanual constant task. Furthermore, CHI displayed a more complex variability structure during the bimanual constant, but a less complex structure during the role-differentiated task than MCI. Interestingly, this complexity reduction was more pronounced in CHI than MCI individuals, suggesting different changes in the control mechanisms. Although understanding these changes requires further research, potential causes might be structural deteriorations leading to less efficient (intra- and interhemispheric) networks because of MCI, or an inability to appropriately divert the focus of attention.

Digital Aided Analog Data Acquisition for Telemetry

This paper tackles the limitations in the current data acquisition system through the integration of a equiripple Finite Impulse Response (FIR) filter. The inclusion of this digital filter eliminates the necessity for physical component alterations, thereby increasing the system’s adaptability and versatility in telemetry applications. The FIR filter’s ability to adjust passband, stopband, and sampling frequencies allows for seamless reconfiguration without the need for hardware modifications, representing a substantial enhancement compared to the constraints of the previous system. Additionally, the equiripple design guarantees minimal variations in passband and stopband ripples, thereby optimizing overall filter performance. An important aspect of the proposed solution is the implementation of shift-and-add multiplier architecture for the FIR filter, which contributes to a reduction in hardware complexity and resource requirements, ultimately leading to a more efficient system. The adoption of MATLAB’s robust filter design tools, coupled with subsequent verification through SIMULINK simulations, has played a pivotal role in successfully realizing the proposed design. To sum up, this project has efficiently addressed the identified issues by introducing a reconfigurable FIR filter solution that not only enhances the flexibility, performance, and user friendliness of the data acquisition system in telemetry applications but also showcases the potential for broader applications in various signal processing domain.