Method For Removal Research Articles

Remediation of arsenic and fluoride from groundwater: a critical review on bioadsorption, mechanism, future application, and challenges for water purification.

In the past few decades, the excessive and inadequate use of technological advances has led to groundwater contamination, mainly caused by organic and inorganic pollutants, which are highly harmful to human health, agriculture, water bodies, and aquaculture. Among all toxic pollutants, As and F- play a significant role in groundwater contamination due to their excellent reactivity with other elements. To mitigate the prevalence of arsenic and fluoride within the water system, the use of biochar gives an attractive strategy for removing them mainly because of the substantial surface area, pore size, pH, aromatic structure, and functional groups inherent in biochar, which are primarily dependent upon its raw material and pyrolysis temperature. Researcher develops different methods like physiochemical and electrochemical for treating arsenic and fluoride contamination. Among all removal methods, bioadsorption using agricultural waste residues shows effective/feasible removal of As and F- due to its low cost, ecofriendly nature, readily available, and efficient reuse compared with several other harmful synthetic materials that demand costly design specifications. This study discusses current developments in bioadsorption methods for As and F- that use agricultural-based biomaterials and describes the prevailing state of arsenic and fluoride removal strategies that use biomaterials precisely.

Public engagement for inclusive and sustainable governance of climate interventions.

The need for public engagement is increasingly evident as discussions intensify around emerging methods for carbon dioxide removal and controversial proposals around solar geoengineering. Based on 44 focus groups in 22 countries across the Global North and Global South (N = 323 participants), this article traces public preferences for a variety of bottom-up and top-down engagement practices ranging from information recipient to broad decision authority. Here, we show that engagement practices need to be responsive to local political cultures and socio-technical environments, while attending to the global dimensions and interconnectedness of the issues at stake. Establishing public engagement as a cornerstone of inclusive and sustainable governance of climate-intervention technologies requires (i) recognizing the diversity of forms and intensities of engaging, (ii) considering national contexts and modes of engagement, (iii) tailoring to technological idiosyncrasies, (iv) adopting power-sensitive practices, (v) accounting for publics' prior experience, (vi) establishing trust and procedural legitimacy and (vii) engaging with tensions and value disagreements.

Review on Mercury Control during Co-Firing Coal and Biomass under O2/CO2 Atmosphere

Combining biomass co-firing with oxy-fuel combustion is a promising Bioenergy with Carbon Capture and Storage (BECCS) technology. It has the potential to achieve a large-scale reduction in carbon emissions from traditional power plants, making it a powerful tool for addressing global climate change. However, mercury in the fuel can be released into the flue gas during combustion, posing a significant threat to the environment and human health. More importantly, mercury can also cause the fracture of metal equipment via amalgamation, which is a major risk for the system. Therefore, compared to conventional coal-fired power plants, the requirements for the mercury concentration in BECCS systems are much stricter. This article reviews the latest progress in mercury control under oxy-fuel biomass co-firing conditions, clarifies the impact of biomass co-firing on mercury species transformation, reveals the influence mechanisms of various flue gas components on elemental mercury oxidation under oxy-fuel combustion conditions, evaluates the advantages and disadvantages of various mercury removal methods, and finally provides an outlook for mercury control in BECCS systems. Research shows that after biomass co-firing, the concentrations of chlorine and alkali metals in the flue gas increase, which is beneficial for homogeneous and heterogeneous mercury oxidation. The changes in the particulate matter content could affect the transformation of gaseous mercury to particulate mercury. The high concentrations of CO2 and H2O in oxy-fuel flue gas inhibit mercury oxidation, while the effects of NOx and SO2 are dual-sided. Higher concentrations of fly ash in oxy-fuel flue gas are conducive to the removal of Hg0. Additionally, under oxy-fuel conditions, CO2 and metal ions such as Fe2+ can inhibit the re-emission of mercury in WFGD systems. The development of efficient adsorbents and catalysts is the key to achieving deep mercury removal. Fully utilizing the advantages of chlorine, alkali metals, and CO2 in oxy-fuel biomass co-firing flue gas will be the future focus of deep mercury removal from BECCS systems.

Adaptive dual-domain filtering for random seismic noise removal

Random noise significantly reduces the signal-to-noise ratio (S/N) of seismic data and affects the accuracy of seismic interpretation. Traditional denoising methods typically require manual parameter tuning to increase the robustness and accuracy across various random noise levels. In this study, based on the statistical definition of random noise, we used the variance of random noise as the level of random noise and proposed an adaptive dual-domain filter (ADDF). The ADDF method estimates the random noise variance in the seismic data and uses this estimation to effectively denoise the seismic data. First, we employ a difference operator in two directions to remove useful structures from the seismic data. The processed data are then used to estimate the global random noise variance through iterative statistical processing. In the denoising process of the ADDF, seismic data are masked by a bilateral filter in the spatial domain, followed by a short-time Fourier transform with wavelet shrinkage in the frequency domain, both controlled by the adaptively estimated random noise variance. The dual-domain filter is applied iteratively for the best performance. Synthetic experiments demonstrate the robustness of the ADDF in accurately estimating the noise variance without tuning parameters, and its superior denoising performance is evident in both synthetic examples and field data when compared to two typical denoising methods: f-x deconvolution and curvelet domain thresholding. As an adaptive random noise estimation and removal method, the ADDF relies only on seismic data, making denoising random noise more objective and accurate without manual adjustment.

A Novel Method for the Highly Effective Removal of Binary Dyes from Colored Dyeing Wastewater by Periodic Reversal/Direct Current-Activated Persulfate

In recent years, electrochemical synergistic activation of persulfate (PDS) degradation technology has demonstrated significant potential in wastewater treatment applications. Given the challenges posed by the complex water quality, high COD content, and recalcitrant degradation of dyeing wastewater, this study aimed to evaluate the efficacy of iron/aluminum dual-electrode electrochemical activation of PDS for degrading simulated dyeing wastewater. The results showed that under optimal conditions, utilizing both periodic reversal and direct current electrochemical activation of PDS achieved removal rates of 99.2% and 98.3% for Reactive Black 5 (RB5) and Reactive Red X-3B (RRX-3B), respectively, demonstrating promising removal efficiency. Notably, the removal efficiency of RB5 surpassed that of RRX-3B, suggesting a dependence on initial concentration influencing reaction kinetics. Furthermore, full-spectrum scanning and quenching experiments revealed that RB5 and RRX-3B were primarily degraded through the potent oxidation action of SO4−· and ·OH, with a small number of intermediates present in the solution. Periodic reversal proved effective in mitigating electrode passivation and enhancing electrode longevity. This study provides a highly effective removal method of binary dyes from dyeing wastewater by periodic reversal Fe-Al dual-electrode electrochemical activation of PDS technology, offering valuable insights for sustainable treatment of dyeing wastewater with binary components.

Microplastics in Water: A Review of Characterization and Removal Methods

Microplastics (MPs), as an emerging persistent pollutant, exist and accumulate in the environment, which has garnered them considerable global attention. While the origin, dispersion, distribution, and impact of MPs have been extensively documented, the characterization and removal strategies for MPs present ongoing challenges. In this literature review, we introduce in detail the advantages and disadvantages of seven characterization methods, from macroscopic to microscopic, from visual observation to microscopic characterization, and discuss their scope of application. In addition, 12 treatment schemes were summarized from the three treatment directions of physics, chemistry, and biology, including filtration, adsorption, extraction, magnetic separation, oil film separation, Fenton oxidation, electrochemical oxidation, persulfate advanced oxidation, photocatalytic oxidation, coagulation, electrocoagulation, foam flotation, anaerobic–anoxic–aerobic activated sludge, enzymatic degradation, bacterial degradation, and fungal degradation. Additionally, we present a critical assessment of the advantages and drawbacks associated with these removal strategies. Building upon the findings of our research team, we propose a novel approach to degrade MPs, which combines three-dimensional electrocatalytic oxidation technology with persulfate advanced oxidation technology. This advanced oxidation technology achieves 100% degradation of antibiotics in water, can degrade large molecules into environmentally harmless small molecules, and should also be a very good strategy for the degradation of MPs. Compared with two-dimensional electrocatalytic technology, the degradation efficiency is higher and the degradation cost is lower This review intends to propel further advancements for addressing the issue of MP pollution.

Digital light processing based multimaterial 3D printing: challenges, solutions and perspectives

Abstract Multimaterial (MM) 3D printing shows great potential for application in metamaterials, flexible electronics, biomedical devices and robots, since it can seamlessly integrate distinctive materials into one printed structure. Among numerous MM 3D printing technologies, digital light processing (DLP) MM 3D printing is compatible with a wide range of materials from hydrogels to ceramics, and can print MM 3D structures with high resolution, high complexity and fast speed. This paper introduces the fundamental mechanisms of DLP 3D printing, and reviews the recent advances of DLP MM 3D printing technologies with emphasis on material switching methods and material contamination issues. It also summarizes a number of typical examples of DLP MM 3D printing systems developed in the past decade, and introduces their system structures, working principles, material switching methods, residual resin removal methods, printing steps, as well as the representative structures and applications. Finally, we provide perspectives on the directions of the further development of DLP MM 3D printing technology.

Selective lipase-catalyzed hydrolysis for removal of diglyceride in palm oil

Palm-based transformer oil is an environmentally friendly and renewable alternative to mineral-based oil for use as an insulating oil. However, the crystallization of palm oil at low temperatures can cause operational issues in transformers. In this research, low diglyceride palm oil is first proposed as a promising base stock for palm-based insulating oil to overcome this issue. The research focuses on the removal of diglycerides (DG) from palm oil by selective enzymatic hydrolysis under a solvent-free system. The results indicate that the lipase GS-250G specifically catalyzes only DG molecules without hydrolyzing TG molecules, despite TG molecules being more prone to hydrolysis than DG molecules due to their higher concentration in palm oil. This unique behavior is probably attributed to steric hindrance by bulky amino acids surrounding the catalytic pocket of lipase GS-250G. Under optimum conditions (30 °C, atmospheric pressure, water content of 16 wt%, agitation speed of 850 rpm, lipase loading of 0.005 wt%, and 4 h of reaction time), the lipase GS-250G reduced the DG content in palm oil from 7 % to 0.5 % with a degree of DG hydrolysis of 95 %. After purification, the final product was composed of 99 % triglyceride (TG). The cold stability test suggested that the nucleation and crystallization rate during the crystal formation of palm oil were reduced by decreasing the DG content. The finding suggests that the proposed procedure in this work is a rapid and environmentally sustainable method for DG removal, which can solve the major problem of palm oil. This discovery opens new opportunities for palm oil to be used as a raw material only for insulating oil but also for various palm based products.

Design and Implementation of DSLMS Algorithm Based Photoelectric Detection of Weak Signals

Accurately extracting weak signals is extremely important for overall performance and application in optoelectronic imaging and optical communication systems. While weak signals are susceptible to noise, adaptive filtering is a commonly used noise removal method. Still, its convergence speed is slow, the steady-state error is large, and the anti-interference ability is weak. To solve the above problems, this paper proposes a new type of variable-step-length adaptive filtering algorithm (DSLMS) based on the minutiae function, which effectively reduces the noise component in error through its combination with the pair cancelation system, utilizing the low correlation property of the noise signal, to improve the anti-noise interference ability of the adaptive filter. Using FPGA and Matlab (2018b) for experimental verification, the results show that this algorithm shows significant advantages in noise suppression, accelerated algorithm convergence, and low steady-state error, and it has effectiveness and application potential for the optoelectronic detection of weak signal processing.

Highly efficient electrocatalysis of oxygen to hydroxyl radical by FeN2O2 single-atom catalyst for refractory organic pollutant removal

The heterogeneous electro-Fenton (Hetero-EF) provides an effective and environmentally friendly method for refractory pollutants removal by strongly oxidative •OH. However, the •OH generation shows an insufficient activity in activating H2O2 to •OH due to the too strong H2O2 binding on the catalytic site. Here, an iron single-atom FeN2O2 catalyst anchored on hollow spherical porous carbon (FeN2O2-HPC) was designed to enhance •OH production by modulating the H2O2 binding. The FeN2O2-HPC Hetero-EF system showed a •OH production rate of 25.0 μmol h−1 and kinetic rate constant of 2.06 h−1 for phenol removal, which exceeded the FeN4 catalyst (the most reported iron single-atom). Density function theory calculations revealed that FeN2O2 could lower the H2O2 adsorption energy and energy barrier of H2O2 activation to •OH compared with FeN4, thus enhancing •OH production. This work gives a new insight into the •OH generation enhancement of Hetero-EF by modulating single-atom coordination environment for refractory pollutants removal.

Phase Transformation of Arsenic, Antimony and Lead in High-Grade Copper Matte Converting

The duration of the high-grade matte converting process is short, the amount of slag is small, and it is difficult for the original impurity removal operation in the low-grade matte converting process to meet the current production demand. Because the removal method for impurity elements during high-grade matte converting is unclear, the phase transformation of impurity elements during this process is investigated in this study. The results show that arsenic exists mainly in the form of FeAsO4 and As2O5, antimony in the form of Sb and Sb2O5, and lead in the form of PbS and PbO in high-grade matte. During the converting process, arsenic and antimony mainly exist in the melt in the form of oxides and gradually aggregate into large particles with increasing copper content in the melt. Lead exists in matte in the form of PbS until the end of the converting process, and PbS is not completely oxidized until the matte converted to blister copper phase. The phase transformation characteristics of copper, iron, sulfur and impurity elements in the process of high-grade matte converting were revealed. This study provides a theoretical reference for the formulation of an efficient impurity removal scheme for the converting process.

Stacking with Recursive Feature Elimination-Isolation Forest for classification of diabetes mellitus.

Diabetes Mellitus is one of the oldest diseases known to humankind, dating back to ancient Egypt. The disease is a chronic metabolic disorder that heavily burdens healthcare providers worldwide due to the steady increment of patients yearly. Worryingly, diabetes affects not only the aging population but also children. It is prevalent to control this problem, as diabetes can lead to many health complications. As evolution happens, humankind starts integrating computer technology with the healthcare system. The utilization of artificial intelligence assists healthcare to be more efficient in diagnosing diabetes patients, better healthcare delivery, and more patient eccentric. Among the advanced data mining techniques in artificial intelligence, stacking is among the most prominent methods applied in the diabetes domain. Hence, this study opts to investigate the potential of stacking ensembles. The aim of this study is to reduce the high complexity inherent in stacking, as this problem contributes to longer training time and reduces the outliers in the diabetes data to improve the classification performance. In addressing this concern, a novel machine learning method called the Stacking Recursive Feature Elimination-Isolation Forest was introduced for diabetes prediction. The application of stacking with Recursive Feature Elimination is to design an efficient model for diabetes diagnosis while using fewer features as resources. This method also incorporates the utilization of Isolation Forest as an outlier removal method. The study uses accuracy, precision, recall, F1 measure, training time, and standard deviation metrics to identify the classification performances. The proposed method acquired an accuracy of 79.077% for PIMA Indians Diabetes and 97.446% for the Diabetes Prediction dataset, outperforming many existing methods and demonstrating effectiveness in the diabetes domain.

A Method of Skin Disease Detection Using Image Processing and Machine Learning

Skin conditions are prevalent health issues globally. The dangers posed by these infections are unseen, leading to physical discomfort and mental anguish. In severe cases, skin diseases can even progress to skin cancer. Consequently, the identification of skin diseases from clinical images remains a significant challenge in medical image analysis. Furthermore, manual diagnosis by medical professionals is time-consuming and subjective. Therefore, there is a need for automated skin disease prediction to expedite treatment planning for both patients and dermatologists. These studies presents a digital hair removal method and de-blurs or denoise the images. To extract essential patterns from the skin imagesand statistical features techniques are utilized. Two efficient machine learning algorithms, namely Support Vector Machine (SVM), and Convolutional Neural Network (CNN) classifiers, are employed with the extracted features to accurately classify skin images as melanoma (MEL), melanocytic nevus (NV), basal cell carcinoma (BCC), actinic keratosis (AK), benign keratosis (BKL), dermatofibroma (DF), vascular lesion (VASC), and Squamous cell carcinoma (SCC). The models are validated using the ISIC 2019 challenge and HAM10000 datasets, with SVM demonstrating slightly superior performance compared to the other classifiers. Furthermore, a comparison with state-of-the-art methods is conducted to evaluate the effectiveness of the proposed approach.

Recent Advances in Technologies for Removing Nanoparticles from Water

Abstract:: Nanoparticles are widely used in manufacturing, daily life applications, and other fields because of their unique properties. However, the nanoparticles that end up in surface water are difficult to break down naturally and cause environmental hazards that cannot be ignored. In this paper, the migration mode of nanoparticles in the environment was proposed, and the factors affecting the removal efficiency of nanoparticles mainly include ionic strength, natural organic matter, surface properties, etc. The common methods for removing nanoparticles mainly include coagulation precipitation methods, activated sludge methods, membrane filtration methods, and adsorption methods. In addition, new technologies such as photothermal removal and electro-adsorption have also been applied to remove nanoparticles in water. In future research, combining the advantages of different removal methods and using different methods interactively to remove nanoparticles in water could become a new research direction.

Smoke deposition and extraction in compartment fires with different ignition sources

The paper presents the experimental research findings on the characteristics of smoke emission and deposition during compartment fires with different ignition sources: an open flame, a heated surface, local heating sources and exposed electrical conductors. The research involved the interior design and construction materials typical of residential and industrial premises: wood, linoleum and cardboard. Adaptive approaches were proposed to the creation of smoke deposition conditions at incipient fire stages using limited volumes of liquid. The foaming agent emulsion was found to be very effective for smoke suppression. The efficiency of several methods of smoke extraction using supply and exhaust ventilation was investigated. Efficient combined techniques of smoke extraction and deposition were identified. Smoke extraction was found to be most efficient at an air velocity of less than 3 m/s. The alternation of intermittent activation of the spraying system and supply and exhaust ventilation system is the most efficient method of smoke removal. Mathematical equations were derived to predict the characteristics of sprinkler and ventilation systems, providing effective smoke deposition and extraction.

Efficient photocatalytic removal of ciprofloxacin through in-situ growth of g-C3N4 on the surface of clinoptilolite

Natural mineral clinoptilolite has many advantages such as porous structure, stability, low price, environmental protection, and simple modification process, making it an ideal choice for wastewater treatment materials. Loading photocatalysts on the surface of zeolite can effectively exert adsorption degradation synergy in wastewater treatment, improve pollutant removal and mineralization capabilities, and further reduce the harm of wastewater to the environment. In this work, g-C3N4 was in-situ grown on the surface of clinoptilolite using a one-step calcination method for efficient photocatalytic removal of the pollutant ciprofloxacin from water. In-situ growth of g-C3N4 on clinoptilolite enables the catalyst to have strong adsorption capacity for pollutants. At the same time, the large specific surface area and extended photo-generated carrier lifetime make the composite photocatalyst exhibit excellent visible light adsorption degradation ability. The CN/CLI-60 with the best photocatalytic performance showed a removal rate of over 90 % of ciprofloxacin within 60 min, much higher than pure g-C3N4 and clinoptilolite. In addition, the pH value, pollutant concentration, catalyst quantity, and cycle stability have all been investigated to evaluate the practical application potential of this catalyst. This work can provide industrial guidance for the rational design of low-cost and high-efficiency photocatalysts using natural clinoptilolite.

Selective electrocatalytic oxidation of ammonia to nitrogen by using titanium dioxide nanorod array decorated with ultrasmall Ir nanoparticles and non-noble metal Fe nanoparticles

Electrochemical ammonia oxidation process through active chlorine has been proposed as a potentially effective method for ammonia removal. Currently, most of the anodes require to use high-stable TiO2 loaded with large particles of noble metal Ru or Ir, which have low activity and high cost. Herein, we prepare ultrasmall and uniform metal nanoparticles of Ir on TiO2 to remove ammonia. Moreover, we use non-noble metal Fe to replace noble metals. The ammonia removal efficiency of Fe/TiO2 under 2 VVS Ag / AgCl during 2 h is 100 % and 94 % of ammonia is converted to N2. The Fe/TiO2 anodes not only have higher catalytic activity but also show excellent stability and reusability. Fe/TiO2 anodes still exhibit excellence activity and selectivity after 1 year. As a common metal, Fe will have more application space than iridium in ammonia removal for its low cost and selectively high efficiency.

Photocatalytic degradation of linezolid antibiotic from aqueous solution by magnetically separable nanoheterostructure Fe3O4/ MgAl2O4/BiOBr0.5Cl0.5 synthesized Composite catalyst

The photocatalytic system has been emerging as a practical method for antibiotic removal in an aqueous medium. In this study, novel MgAl2O4/BiOBr0.5Cl0.5 heterojunction was synthesized by the decoration of different mass percentages of MgAl2O4 nanoparticles (10, 20, and 30 %) on the BiOBr0.5Cl0.5 solid solution and used for the photocatalytic degradation of linezolid antibiotic. Also, to facilitate easy separation of 10 % MgAl2O4/BiOBr0.5Cl0.5 from the solution after use, it was magnetized by Fe3O4 as 2 % Fe3O4/10 % MgAl2O4/BiOBr0.5Cl0.5. Synthesized photocatalysts were characterized by XRD, XPS, Raman, FESEM, TEM, EDX, BET-BJH, DRS, PL, Mott–Schottky, VSM, and pHpzc analyses to specify the synthesized photocatalysts and determine their chemical and physical properties. In addition, the influence of experimental parameters, including pH of the initial solution, the dosage of photocatalyst, and linezolid concentration on the performance of photocatalyst in linezolid removal, were elucidated in this study. The results showed that 10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was the optimal sample with a maximum removal efficiency of 95.59 % within 90 min under optimal experimental parameters (1 g/L catalyst, 10 mg/L linezolid, pH = 6.5). The kinetic studies revealed that the degradation rate of 10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was approximately 1.8, 2.7, 2.0, and 6.3 times faster than 20 % MgAl2O4/BiOBr0.5Cl0.5, 30 % MgAl2O4/BiOBr0.5Cl0.5, BiOBr0.5Cl0.5 photocatalyst and photolysis, respectively. Scavenger tests conducted in the same process operation revealed that h+ and •O2− play the predominant roles in linezolid photocatalytic degradation. The 2 % Fe3O4/10 % MgAl2O4/BiOBr0.5Cl0.5 photocatalyst was easily collected by magnet after each use for the next run, and its activity after five runs has reached 90 %.

Air-water interfacial properties of perfluorosulfonic acid salts with different chain lengths

Perfluorosulfonic acids (PFSA) are a class of per- and polyfluoroalkyl substances (PFAS), which have been extensively used in numerous applications. The toxicity and bioaccumulation of PFAS have become a serious worldwide problem. Foam fractionation has been suggested as a promising remediation method for PFAS removal owing to the amphiphilic nature of most of the currently existing PFAS in the environment, allowing them to migrate to the air-water interface during the foaming process. Nevertheless, the current challenge for widespread utilization of foam fractionation is its low removal efficiency, especially for short-chain PFAS. Foam fractionation performance depends on the air-water interfacial properties as well as the ability for PFAS to adsorb at the air-water interface. In the present study, therefore, we investigate surface tensions of PFSA with long and short chain lengths. Different adsorption models are studied to estimate maximum surface excess concentrations for various PFSA. Our results indicate that long-chain PFSA have lower surface tensions, higher surface activities, and form more rigid air-water interfaces. This study marks the first investigation of dilatational interfacial rheology of PFAS, as well as addressing the gap in understanding PFAS interfacial rheology by focusing on the quantification the storage and loss interfacial moduli, which are known to play a significant role in the foaming process.

Enzymatic removal of Numts from Panthera tigris DNA samples

Forensic mitochondrial DNA analysis is a vital investigative tool for wildlife casework, but numts continue to complicate DNA analysis. A major goal of wildlife forensic DNA analysis is to identify non-human biological evidence to its taxonomic source. Species identification is accomplished by sequencing genetic markers on the mitochondrial genome and comparing evidentiary sequence data to published reference sequences. Due to the high level of sequence similarity between mitochondrial genes and numts, current sequencing methods result in co-amplification of the target gene marker and non-target numt. Co-amplification of target and non-target loci results in ambiguous nucleotide calls in sequence data. Reducing the influence of numts during sequence analysis will provide a technique that will maximize accuracy and minimize error in taxonomic identifications. To overcome the analytical burden of numts, we studied the enzymatic removal of numts using exonuclease V. To evaluate the feasibility of exonuclease V as a numt removal method, total Panthera tigris DNA was extracted from blood and liver and divided into three treatment groups: untreated, 1st digest, and 2nd digest. For the untreated sample, 7.6 % of the 620 bp sequence data was classified as ambiguous. Following treatment, all samples demonstrated a reduction in ambiguous calls: liver-1st digest (48 h): 6.6 %, liver-2nd digest (48 h + 16 h): 1.8 %, and blood-1st digest (48 h): 0 %. Based on this preliminary study, exonuclease V treatment effectively removed numts before sequencing analysis. While exonuclease V treatment has demonstrated potential, additional studies are required to optimize the reaction and fully validate the methodology.