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283 records · Page 16

Automatic Classification of Biological Targets in a Tidal Channel Using a Multibeam Sonar

Multibeam sonars are widely used for environmental monitoring of fauna at marine renewable energy sites. However, they can rapidly accrue vast volumes of data, which poses a challenge for data processing. Here, using data from a deployment in a tidal channel with peak currents of 1–2 m s –1 , we demonstrate the data-reduction benefits of real-time automatic classification of targets detected and tracked in multibeam sonar data. First, we evaluate classification capabilities for three machine learning algorithms: random forests, support vector machines, and k-nearest neighbors. For each algorithm, a hill-climbing search optimizes a set of hand-engineered attributes that describe tracked targets. Here, the random forest algorithm is found to be most effective—in postprocessing, discriminating between biological and nonbiological targets with a recall rate of 0.97 and a precision of 0.60. In addition, 89% of biological targets are correctly classified as either seals, diving birds, fish schools, or small targets. Model dependence on the volume of training data is evaluated. Second, a real-time implementation of the model is shown to distinguish between biological targets and nonbiological targets with nearly the same performance as in postprocessing. From this, we make general recommendations for implementing real-time classification of biological targets in multibeam sonar data and the transferability of trained models.

16 TIDAL AND WAVE POWER↗

Responses of two semiarid conifer tree species to reduced precipitation and warming reveal new perspectives for stomatal regulation

Here, relatively anisohydric species are predicted to be more predisposed to hydraulic failure than relatively isohydric species, as they operate with narrower hydraulic safety margins. We subjected co-occurring anisohydric Juniperus monosperma and isohydric Pinus edulis trees to warming, reduced precipitation, or both, and measured their gas exchange and hydraulic responses. We found that reductions in stomatal conductance and assimilation by heat and drought were more frequent during relatively moist periods, but these effects were not exacerbated in the combined heat and drought treatment. Counter to expectations, both species exhibited similar gs temporal dynamics in response to drought. Further, whereas P. edulis exhibited chronic embolism, J. monosperma showed very little embolism due to its conservative stomatal regulation and maintenance of xylem water potential above the embolism entry point. This tight stomatal control and low levels of embolism experienced by juniper refuted the notion that very low water potentials during drought are associated with loose stomatal control and with the hypothesis that anisohydric species are more prone to hydraulic failure than isohydric species. Because direct association of stomatal behaviour with embolism resistance can be misleading, we advocate consideration of stomatal behaviour relative to embolism resistance for classifying species drought response strategies.

54 ENVIRONMENTAL SCIENCES↗

Organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in Cyprinidae fish: Towards hints of their arrangements using advanced classification methods

Highlights: • SOM and DT classifiers searched for relation among 25 POPs in three Cyprinidae fish. • The concentrations of indicator congeners dominated over dioxin-like PCBs. • Based on SOM, both dioxin-like and indicator PCBs differentiated the fish species. • DT assorted the samples on the levels of PCB-126, -156, -170, -28, -105, and -114. To tackle the ever-present global concern regarding human exposure to persistent organic pollutants (POPs) via food products, this study strived to indicate associations between organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) in lake-fish tissue depending on the species and sampling season. Apart from the monitoring initiatives recommended in the Global Monitoring Plan for POPs, the study discussed 7 OCPs and 18 PCB congeners determined in three Cyprinidae species (rudd, carp, and Prussian carp) from Vransko Lake (Croatia), which are widely domesticated and reared as food fish across Europe and Asia. We exploit advanced classification algorithms, the Kohonen self-organizing maps (SOM) and Decision Trees (DT), to search for POP patterns typical for the investigated species. As indicated by SOM, some of the dioxin-like and non-dioxin-like PCBs (PCB-28, PCB-74, PCB-52, PCB-101, PCB-105, PCB-114, PCB-118, PCB-156 and PCB-157), α-HCH and β-HCH caused dissimilarities among fish species, but regardless of their weight and length. To support these suggestions, DT analysis sequenced the fish species and seasons based on the concentration of heavier congeners. The presented assumptions indicated that the supplemental application of SOM and DT offers advantageous features over the usually rough interpretation of POPs pattern and over the single use of the methods.

54 ENVIRONMENTAL SCIENCES↗

Leveraging intermediate resonances to probe CP violation at colliders

We explore the phenomenological impact of interference in tree-level contributions to three-body final states in $2\rightarrow 3$ scattering processes. This work introduces a novel search strategy leveraging asymmetries to enable sensitivity to CP-violating effects in less well-explored regions of phase space. Analytically, we demonstrate the effectiveness of this observable in probing interference between Standard Model charged-current decays and effective left-handed vector interactions, illustrated in a toy model featuring a scalar leptoquark, $S_1 \sim (3, 1, -\,1/3)$. Numerically, we apply this framework to studying the process $pp\rightarrow b \tau \nu $; unlike traditional high-$p_T$ searches or “bump hunts”, this approach utilizes an intermediate energy regime – where new physics is neither light enough to be produced on shell or heavy enough to justify an effective field theory treatment. A proof-of-principle analysis at parton level demonstrates a percent-level asymmetry, with sensitivity also to BSM weak-CP phase. While the specific phase sensitivity is diminished at particle level due to showering and detector effects, a machine learning classifier can recover sensitively to the presence of SM-BSM interference, significantly outperforming standard analysis methods. Notably discrimination between BSM signal and SM background could be achieved at the 2$\sigma $ level for the current LHC dataset and 8$\sigma $ at the High-Luminosity LHC. Moreover, this asymmetry observable as defined can also be more broadly applied to other searches for CP-violation in $2\rightarrow 3$ processes in present and future collider environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Comparative genomic analysis of thermophilic fungi reveals convergent evolutionary adaptations and gene losses

Thermophily is a trait scattered across the fungal tree of life, with its highest prevalence within three fungal families (Chaetomiaceae, Thermoascaceae, and Trichocomaceae), as well as some members of the phylum Mucoromycota. We examined 37 thermophilic and thermotolerant species and 42 mesophilic species for this study and identified thermophily as the ancestral state of all three prominent families of thermophilic fungi. Thermophilic fungal genomes were found to encode various thermostable enzymes, including carbohydrate-active enzymes such as endoxylanases, which are useful for many industrial applications. At the same time, the overall gene counts, especially in gene families responsible for microbial defense such as secondary metabolism, are reduced in thermophiles compared to mesophiles. We also found a reduction in the core genome size of thermophiles in both the Chaetomiaceae family and the Eurotiomycetes class. The Gene Ontology terms lost in thermophilic fungi include primary metabolism, transporters, UV response, and O-methyltransferases. Comparative genomics analysis also revealed higher GC content in the third base of codons (GC3) and a lower effective number of codons in fungal thermophiles than in both thermotolerant and mesophilic fungi. Furthermore, using the Support Vector Machine classifier, we identified several Pfam domains capable of discriminating between genomes of thermophiles and mesophiles with 94% accuracy. Using AlphaFold2 to predict protein structures of endoxylanases (GH10), we built a similarity network based on the structures. We found that the number of disulfide bonds appears important for protein structure, and the network clusters based on protein structures correlate with the optimal activity temperature. Thus, comparative genomics offers new insights into the biology, adaptation, and evolutionary history of thermophilic fungi while providing a parts list for bioengineering applications.

59 BASIC BIOLOGICAL SCIENCES↗

Graph-based machine learning improves just-in-time defect prediction

The increasing complexity of today’s software requires the contribution of thousands of developers. This complex collaboration structure makes developers more likely to introduce defect-prone changes that lead to software faults. Determining when these defect-prone changes are introduced has proven challenging, and using traditional machine learning (ML) methods to make these determinations seems to have reached a plateau. In this work, we build contribution graphs consisting of developers and source files to capture the nuanced complexity of changes required to build software. By leveraging these contribution graphs, our research shows the potential of using graph-based ML to improve Just-In-Time (JIT) defect prediction. We hypothesize that features extracted from the contribution graphs may be better predictors of defect-prone changes than intrinsic features derived from software characteristics. We corroborate our hypothesis using graph-based ML for classifying edges that represent defect-prone changes. This new framing of the JIT defect prediction problem leads to remarkably better results. We test our approach on 14 open-source projects and show that our best model can predict whether or not a code change will lead to a defect with an F1 score as high as 77.55% and a Matthews correlation coefficient (MCC) as high as 53.16%. This represents a 152% higher F1 score and a 3% higher MCC over the state-of-the-art JIT defect prediction. We describe limitations, open challenges, and how this method can be used for operational JIT defect prediction.

59 BASIC BIOLOGICAL SCIENCES↗

Photovoltaic Inverter Failure Mechanism Estimation Using Unsupervised Machine Learning and Reliability Assessment

This article introduces a data-driven approach to assessing failure mechanisms and reliability degradation in outdoor photovoltaic (PV) string inverters. The manufacturer's stated PV inverter lifetime can vary due to the impact of operating site conditions. To address limitations in degradation estimation through accelerated testing, condition monitoring, or degradation modeling, we propose a machine learning (ML) oriented approach. Utilizing data from a 1.4 MW PV power plant operational since 2016, with 46 string PV inverters tied to the grid, we employ the unsupervised one-class support vector machine ML technique to analyze inverter and sensor data, capable of classifying humidity cycling and temperature fluctuations as dominant failure mechanisms. Utilizing the anomaly alert relationship and alert details specific to the inverter, the level of PV inverter output is considered as its availability or available reliability. Subsequently, a continuous Markov model is applied to six-month alert data, revealing an average stated reliability of 20% after 20 years of continuous operation. These results support recommendations for time-bound preventive measures to enhance PV inverter reliability under diverse outdoor conditions. Furthermore, the approach provides a nondestructive, top–down, and generalized method for analyzing any commercial PV inverter exposed to outdoor conditions, contingent on the availability of relevant data.

14 SOLAR ENERGY↗

Temporal mismatches in flight activity patterns between Pipistrellus kuhlii and Prays oleae in olive farms: Implications for biocontrol services potential

Abstract Biocontrol services are widely recognized to provide key incentives for bat conservation. However, we have virtually no information on whether and how disruptions in bat‐mediated biocontrol services are driven by mismatches between the temporal activity patterns of insectivorous bats and insect pests. We investigated the temporal relationship between the nightly activity patterns of the common pipistrelle bat ( Pipistrellus kuhlii ) and the olive fruit moth ( Prays oleae ). Temporal mismatches between species pairs were estimated as the time difference (expressed as a percentage of the night) at which P. kuhlii and P. oleae reached 50% of their abundance. The study was carried out during spring, summer, and fall between 2017 and 2019 in 60 olive farms representing increasing levels of structural simplification (as a surrogate of agricultural intensification). Olive farms were classified as exhibiting high (i.e. HIGH olive farms; n = 27), intermediate (MID; n = 18), and low (LOW; n = 15) structural complexity. Temporal mismatches between the activity levels of P. kuhlii and P. oleae varied between seasons and types of olive farms, being comparatively lower in summer than in spring and fall. Furthermore, summer was the only season in which temporal mismatches between species pairs differed between types of olive farms, with higher temporal mismatches found in LOW than in HIGH and MID olive farms. Overall, our work demonstrates the existence of temporal mismatches between the nightly activity patterns of P. kuhlii and P. oleae . Furthermore, it demonstrates that the structural simplification of olive farms increases temporal mismatches between species pairs, particularly in summer when bat‐mediated biocontrol services are most needed. Synthesis and applications . Future research should consider mismatches between the temporal activity patterns of insectivorous bats and insect pests. Otherwise, the actual impact of agricultural intensification on bat‐mediated biocontrol services as well as the economic impact of their loss on the agriculture industry might be underestimated. To enhance biocontrol services, we propose increasing the availability of suitable roosting and foraging sites as well as conserving areas of remnant native woodland and scattered hollow‐bearing trees.

Herrera, José M.↗

Removal of Antibiotics from Swine Wastewater Using an Environmentally Friendly Biochar: Performance and Mechanisms

Antibiotics used in the swine industry to treat diseases and improve animal growth are poorly absorbed by swine and have been classified as micropollutants due to their occurrence in surface water, wastewater, and soil. This study investigated the capacity of biochar produced from eastern red cedar to remove target antibiotics that have been extensively used in the swine industry. Biochar was produced by pyrolysis from eastern red cedar at 450 °C. The sorption tests were performed by mixing biochar and a solution (1:10 ratio) containing each antibiotic in 100, 300, 600, and 900 μg L –1 concentrations. The results indicate that red cedar biochar was able to effectively remove up to 99.93% tetracycline, 96.23% oxytetracycline, 98.28% chlortetracycline, 76.4% sulfadiazine, and 78.6% sulfamethazine at the lowest concentrations. The removal efficiencies at higher concentrations declined up to 83.52, 47.23, 64.16, 69.8, and 58.4% for tetracycline, oxytetracycline, chlortetracycline, sulfadiazine, and sulfamethazine, respectively. The biochar exhibited stronger adsorption capacity for chlortetracycline and sulfamethazine compared to the other antibiotics. The likely adsorption mechanisms driving the removal of tetracyclines and sulfonamides are hydrogen-bonding and π–π electron-donor–acceptor, supported by FTIR analyses of the biochar itself. Overall, the results highlighted the potential utilization of eastern red cedar biochar for practical applications, mitigating antibiotic residues from swine wastewater in a cost-effective and environmentally friendly manner due to its relatively low pyrolysis temperature (450 °C) and sustainable repurposing of an invasive tree species.

09 BIOMASS FUELS↗

Diffusion and perfusion MR parameters to assess preoperative short-course radiotherapy response in locally advanced rectal cancer: a comparative explorative study among Standardized Index of Shape by DCE-MRI, intravoxel incoherent motion- and diffusion kurtosis imaging-derived parameters

Purpose: To assess preoperative short-course radiotherapy (SCR) tumor response in locally advanced rectal cancer (LARC) by means of Standardized Index of Shape (SIS) by dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters derived from diffusion-weighted MRI (DW-MRI). Materials and methods: Thirty-four patients with LARC who underwent MRI scans before and after SCR followed by delayed surgery, retrospectively, were enrolled. SIS, ADC, IVIM parameters [tissue diffusion (D{sub t}), pseudo-diffusion (D{sub p}), perfusion fraction (f{sub p})] and DKI parameters [mean diffusivity (MD), mean of diffusional kurtosis (MK)] were calculated for each patient. IVIM parameters were estimated using two methods, namely conventional biexponential fitting (CBFM) and variable projection (VARPRO). After surgery, the pathological TNM and tumor regression grade (TRG) were estimated. For each parameter, percentage changes between before and after SCR were evaluated. Furthermore, an artificial neural network was trained for outcome prediction. Nonparametric sample tests and receiver operating characteristic curve (ROC) analysis were performed. Results: Fifteen patients were classified as responders (TRG ≤ 2) and 19 as not responders (TRG > 3). Seven patients had TRG 1 (pathological complete response, pCR). Mean and standard deviation values of pre-treatment CBFM D{sub p} and mean value of VARPRO D{sub p} pre-treatment showed statistically significant differences to predict pCR. (p value at Mann–Whitney test was 0.05, 0.03 and 0.008, respectively.) Exclusively SIS percentage change showed significant differences between responder and non-responder patients after SCR (p value << 0.001) and to assess pCR after SCR (p value << 0.001). The best results to predict pCR were obtained by VARPRO Fp mean value pre-treatment with area under ROC of 0.84, a sensitivity of 96.4%, a specificity of 71.4%, a positive predictive value (PPV) of 92.9%, a negative predictive value (NPV) of 83.3% and an accuracy of 91.2%. The best results to assess after treatment complete pathological response were obtained by SIS with an area under ROC of 0.89, a sensitivity of 85.7%, a specificity of 92.6%, a PPV of 75.0%, a NPV of 96.1% and an accuracy of 91.2%. Moreover, the best results to differentiate after treatment responders vs. non-responders were obtained by SIS with an area under ROC of 0.94, a sensitivity of 93.3%, a specificity of 84.2%, a PPV of 82.4%, a NPV of 94.1% and an accuracy of 88.2%. Promising initial results were obtained using a decision tree tested with all ADC, IVIM and DKI extracted parameter: we reached high accuracy to assess pathological complete response after SCR in LARC (an accuracy of 85.3% to assess pathological complete response after SCR using VARPRO D{sub p} mean value post-treatment, ADC standard deviation value pre-treatment, MD standard deviation value post-treatment). Conclusion: SIS is a hopeful DCE-MRI angiogenic biomarker to assess preoperative treatment response after SCR with delayed surgery. Furthermore, an important prognostic role was obtained by VARPRO F{sub p} mean value pre-treatment and by a decision tree composed by diffusion parameters derived by DWI and DKI to assess pathological complete response.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Ectomycorrhizal fungal associates of Pinus contorta in soils associated with a hot spring in Norris Geyser Basin, Yellowstone National Park, Wyoming

Molecular methods and comparisons of fruiting patterns (i.e., presence or absence of fungal fruiting bodies in different soil types) were used to determine ectomycorrhizal (EM) associates of Pinus contorta in soils associated with a thermal soil classified as ultra-acidic to extremely acidic (pH 2 to 4). EM were sampled by obtaining 36 soil cores from six paired plots (three cores each) of both thermal soils and forest soils directly adjacent to the thermal area. Fruiting bodies (mushrooms) were collected for molecular identification and to compare fruiting body (above-ground) diversity to below-ground diversity. Our results indicate (i) that there were significant decreases in both the level of EM infection (130 +/- 22 EM root tips/core in forest soil; 68 +/- 22 EM root tips/core in thermal soil) and EM fungal species richness (4.0 +/- 0.5 species/core in forest soil; 1.2 +/- 0.2 species/core in thermal soil) in soils associated with the thermal feature; (ii) that the EM mycota of thermal soils was comprised of a small set of dominant species and included very few rare species, while the EM mycota of forest soils contained a few dominant species and several rare EM fungal species; (iii) that Dermocybe phoenecius and a species of Inocybe, which was rare in forest soils, were the dominant EM fungal species in thermal soils; (iv) that other than the single Inocybe species, there was no overlap in the EM fungal communities of the forest and thermal soils; and (v) that the fungal species forming the majority of the above-ground fruiting structures in thermal soils (Pisolithus tinctorius, which is commonly used in remediation of acid soils) was not detected on a single EM root tip in either type of soil. Thus, P. tinctorius may have a different role in these thermal soils. Our results suggest that this species may not perform well in remediation of all acid soils and that factors such as pH, soil temperature, and soil chemistry may interact to influence EM fungal community structure. In addition, we identified at least one new species with potential for use in remediation of hot acidic soil.

Pinus/microbiology↗

AN ACID BAKING APPROACH TO ENHANCE RARE EARTH ELEMENT RECOVERY FROM BITUMINOUS COAL SOURCES

Rare earth elements (REE) are a group of 17 elements typically classified as light and heavy rare earth elements, which play a crucial role in developing the latest technologies for energy, defense, and medical sectors. Even though REEs have been found in more than 200 minerals, only bastnaesite, monazite and xenotime are commercially exploited for REE extraction. However, the recent exponential increase in REE demand has spurred countries such as the United States into research for the extraction of REEs from secondary sources such as coal, acid mine drainage, and coal ash. Several coal sources (e.g., Fire Clay seam coal) across the United States have been identified to contain elevated concentrations of rare earth elements (>600 ppm), and various researchers have investigated the feasibility of both physical and hydrometallurgical extraction techniques for rare earth concentration and subsequent extraction. However, both physical and direct leaching were concluded to be inefficient for RE beneficiation and extraction due to low recoveries. Alternatively, thermal treatment provides promising means for RE recovery from bituminous coal sources. The positive impact of thermal treatment/calcination was established to be due to the decarbonization and dehydroxylation of the clays, which released entrapped rare earth elements within the dominant minerals and converted them into an acid-soluble form. Nonetheless, the improvement in recovery was limited to the light REEs (LREEs) with an insignificant increase in the heavy REEs (HREE). It was demonstrated that the light and heavy REEs in the material were associated with difficult-to-leach minerals such as monazite, xenotime, and zircon, which were not decomposed by simple calcination due to their high thermal stability. Hence, roasting in the presence of chemicals was necessary to ensure the decomposition of those REE-containing minerals. As such, this study was focused on the acid baking treatment of bituminous coals with an aim to enhance REE recovery, especially HREEs. Based on the presence of REE minerals like monazite and xenotime, three pre-leach treatment methods, i.e., 1) roasting, 2) direct acid baking, and 3) acid baking after roasting were investigated. Roasting tests at 600 ⁰C revealed that the recovery of light REEs (LREEs) was enhanced while the recovery of HREEs remained relatively unaffected. LREE and HREE recovery values of 38.3% and 21.3%, respectively, were achieved using a 50 g/L sulfuric acid solution at 5% solid concentration and a solution temperature of 75 ⁰C for 2 hours. Comparatively, direct acid baking at 250 °C provided substantial increased LREE and HREE recovery values to approximately 49.4% and 53.0%, respectively, using an equivalent acid dosage. Recoveries were maximized to 77.0% and 79.6% for LREE and HREE, respectively, by roasting followed by acid baking. Similar results were obtained from the treatment of a second bituminous coal source. Due to strong correlations between REE and Al recovery values, tests were performed on kaolinite and illite, which were prominent clay minerals within the source coals. These experiments revealed that the REE recovery improvements were likely a result of dehydroxylation of clays and subsequent release and decomposition of REE-bearing minerals such as monazite, xenotime and zircon. Subsequently, a parametric study was conducted to identify the impact of acid baking parameters on rare earth element recovery. The factors investigated using a three-level statistical experimental program were acid baking time, acid solution concentration, baking temperature, and acid solution-to-solids ratio which were found to significantly impact REE and contaminant element (Al, Fe, and Ca) recovery. An increase in baking temperature up to around 250 ⁰C improved the light and heavy REE recovery values by more than 50 absolute percentage points relative to performances achieved when direct leaching. As aforementioned, acid baking was needed to both decompose the clay minerals and liberate the REE minerals, which allowed access for the acid to solubilize the REEs. Acid concentration of the solution used for acid baking was studied as a means of minimizing the amount of acid needed to achieve a target REE recovery. However, thermo-gravimetric and differential scanning calorimetry analysis (TGA-DSC) of sulfuric acid under oxidizing atmosphere revealed that the addition of water decreased the evaporation temperature, which explains the lower REE recovery values obtained when using acid concentrations less than 100%. Using pure sulfuric acid at an acid-to-solid ratio of 0.8:1 resulted in recovery values of around 70% for both LREEs and HREEs. The decomposition reaction time was relatively quick with 65% of the TREEs recovered within the first 10 minutes. Following the identification of optimum operating conditions through the parametric study, a systematic leaching study was carried out to examine the impact of leaching parameters, such as solid-to-liquid (S/L) ratio, temperature, and time, on REE recovery using acid baking conditions of 1:1 acid to solids ratio at 250 °C for 30 minutes. The solid-to-liquid ratio was varied from 1-20% by weight at 25 °C, 50 °C, and 75 °C solution temperatures. The results indicated that reaction time and solution temperature considerably impacted the recovery of heavy and light REEs. Interestingly, LREE recovery reduced from 68% at 5% S/L to 58% at 20%S/L, whereas HREE recovery of 78% remained unaffected. The decrease in the LREE recovery was determined to be due to La and Ce precipitation, likely through isomorphic substitution with calcium in gypsum. The kinetic data indicated that 67% LREE and 77% HREE recovery could be obtained within the first 15 minutes of the reaction, suggesting fast reaction kinetics. Furthermore, raising the solution temperature from 25 °C to 75 °C increased the LREE and HREE recovery from 60% and 32% to 67% and 79%, respectively. The kinetic modeling results demonstrated that the rate-limiting step in the LREE dissolution was diffusion and chemical reaction, whereas the HREE extraction was controlled by only chemical reaction. The leaching study concluded that using 20% S/L at 75 °C for 15 minutes maximized LREE and HREE recovery. The lab-scale precipitation study showed that Fe and Al in solution could be removed at pH 4.5 followed by REE precipitation at pH 6.0 using 6 mol/L NaOH. Finally, the bench-scale data was used to develop a process flowsheet for REE recovery from low-grade bituminous coal sources using acid baking. Finally, based on the proposed flowsheet, a concentrated RE-cake obtained through selective precipitation at pH 6.5 was re-leached using HCl at pH 1.5. The resultant leachate was used to identify the impact of various operating parameters on REE recovery and purity with an aim to maximize REE precipitation efficiency while minimizing the oxalic acid dosage. The operating parameters for this investigation were oxalic acid dosage, iron (III) contamination, solution pH and temperature. The resultant model suggested that oxalic acid dosage and reaction pH are the most significant factors for the REE precipitation efficiency, followed by the interaction of oxalic dosage and Fe concentration. Test results indicated that increasing the oxalic acid concentration from 0g/L to 80g/L improved the REE precipitation efficiency from approximately 4.2% to 95.0%. Furthermore, raising the solution pH from 0.5 to 2.5 considerably enhanced the precipitation efficiency from 0.0% to 98.9%. A solution temperature elevation decreased REE recovery, which indicated an exothermic reaction between REEs and oxalate anions. Finally, a high level of Fe contamination adversely impacted REE precipitation efficiency. The speciation analysis revealed that the dominant iron species in the solution system were Fe-(C₂O₄)₃³⁻, Fe-(C₂O₄)²⁻, and Fe-(C₂O₄)⁺, which consumed the majority of the oxalate anions

rare earth elements, acid baking, high-temperature↗