Curve Method Research Articles

APPLICATION OF DIFFERENTIAL GEOMETRY METHODS TO SLOW-FAST DYNAMIC SYSTEMS

The slow-fast autonomous two-dimensional dynamic systems are considered. Slow-fast dynamic systems describe various physical, mechanical, and other phenomena in which the gradual evolutionary accumulation of small changes over time leads to a sudden transition of the system to a new dynamic regime. The study of slow-fast dynamic systems is connected with finding the analytical equation of a slow invariant manifold, that is, a manifold where the phase trajectories of the system change slowly. This is due to the fact that the trajectory of the slow manifold divides the phase space of the dynamic system into slow and fast regions, that is, regions where the dynamics of the system slows down and accelerates, respectively. The work considers geometric approaches to finding the slow manifold of such systems, which allow writing the analytical equation of the slow manifold rather simply. The flow curve method is based on the concepts and methods of differential geometry and mechanics. Using the concept of the curvature of a curve allows one to determine the analytical equation of a slow manifold regardless of the "slow eigenvalues" of the system. The flow curvature method is applied to a slow-fast dynamic system. The analytical equation of the slow manifold of the considered system and the slow and fast regions of the phase space are determined. It was established that the equations of the slow invariant manifold of the dynamic system, obtained by the flow curvature method and the geometric singular perturbation method, are completely identical in the first order of approximation with a small parameter .

Thermodynamic adsorption mechanism of supercritical methane and application to Ordos coal

Coal, as a heterogeneous porous medium, exhibits substantial adsorption capacity for coalbed methane, highlighting the necessity to comprehend methane storage mechanisms for reserve evaluation and production optimization. To investigate the adsorption characteristics of methane, a novel approach for calculating thermodynamic parameters is developed based on phase equilibrium and fugacity principles. Isothermal adsorption experimental results are utilized to assess the influence of moisture on the adsorption mechanism, disclosing variations in enthalpy, entropy, and Gibbs free energy for supercritical methane. The findings reveal a pronounced reduction in adsorption capacity under hydrated conditions. Methane adsorption onto coal is identified as an exothermic, entropy-decreasing, non-spontaneous process dominated by microporous filling and monolayer adsorption. The supercritical Langmuir and Dubinin–Radushkevich model confirms that microporous filling accounts for over 10% of the total adsorption capacity under high-temperature and high-pressure conditions. Additionally, temperature changes within coal seams during distinct production phases, ranging from 1 to 18 K, are quantified. A predictive method for isothermal adsorption curves using thermodynamic parameters is introduced, with an accuracy within a 6% error margin. These insights offer theoretical support for modeling gas–water flow dynamics in coalbed methane reservoirs.

P-940. Diagnostic Workup of Bacteremia Post TAVR, a Single Center Experience Over a Decade

Abstract Background Prosthetic valves are considered a risk factor for endocarditis however diagnosing prosthetic valve endocarditis (PVE) is complicated by acoustic shadowing on echocardiography. In 2023, the ISCVID published an update to the Duke Criteria (Duke 2023) which intended to increase the sensitivity in diagnosing PVE. The purpose of this study was to examine how TAVR infective endocarditis (TAVR-IE) was diagnosed at our institution 90 Day Mortality Kaplan Meier Curve Methods HERON was utilized to match cases between ACC/STS databases and the EMR at The University of Kansas Health System (TUKHS). Patients with bacteremia occurring after a TAVR were reviewed. Each case was evaluated if they met rejected/possible/definitive endocarditis criteria in the Modified Duke Criteria (Duke 2005) and the Duke 2023 Criteria. To adjudicate the diagnosis, an expert panel reviewed all cases that met definitive endocarditis criteria in any edition of the Duke Criteria. Results A total of 2371 TAVRs were conducted at TUKHS from 2012 to 2023. We identified 146 cases of post procedure bacteremia. We excluded 53 cases leaving 93 in the cohort. Transeophageal echocardiography was utilized in about half of the cases (TTE 73, TEE 45). F-FDG positron emission tomography/CT was done in six patients and Cardiac CT in one patient. Cultures returning with Enterococcus spp (16). viridans group streptococci (15), and Staphylococcus spp. (15) had similar incidence. About half had either atypical organisms (40) on 2005 Duke criteria or polymicrobial growth (7). Definitive criteria were met in 18 and 21 patients for the Duke 2005 and Duke 2023 Criteria respectively. Two cases had minor microbiological criteria upgraded to major in Duke 2023. One case was promoted to definitive endocarditis based on Cardiac CT. Upon adjudication the panel agreed with Duke 2023 Criteria classification. Sensitivity was calculated 85%/100% for Duke 2005 and Duke 2023 Criteria respectively. Kaplan Meier curves calculated no significant difference of 3 month mortality between TAVR patients who had met definitive criteria and those who did not. (Figure #1) Conclusion The 2023 ISCVID Duke Criteria in this study appeared to have superior sensitivity for TAVR-IE when compared to the older Modified Duke Criteria published in 2005. Disclosures Larry M. Baddour, MD, UpToDate, Inc.: Royalty payments (authorship duties). Wissam El Atrouni, MD, ViiV Healthcare: Advisor/Consultant

P-372. Candida auris Outbreak in a Cardiothoracic Transplant Intensive Care Unit: Implications for Infection Prevention

Abstract Background Candida auris is a yeast that causes invasive infections such as bloodstream infections (BSIs); mortality rates for C. auris BSIs may be as high as 80%. Rates have been climbing in the U.S. Exposure to skilled nursing facilities (SNFs), long-term acute care hospitals (LTACHs), or inpatient rehabilitation facilities (IRFs) represents a known risk factor for C. auris. Our institution experienced a C. auris outbreak from September 2023 - January 2024. Figure 1: C. auris Outbreak Epidemic Curve Methods C. auris cases in the outbreak were identified from clinical specimens and admission and weekly surveillance via polymerase chain reaction (PCR). Clinical characteristics were determined through chart review. A multidisciplinary team implemented infection prevention (IP) interventions to curb nosocomial spread. Infection Prevention Interventions Results There were 20 cases of C. auris identified in our CTICU between July 2023 and January 2024 (Figure 1). Whole-genome sequencing and phylogenetic analysis based on pairwise single nucleotide polymorphism (WG-SNP) distance revealed two outbreak clusters. Of the 20 patients, 13 (65%) were solid organ transplant/acute mechanical circulatory support patients and three (15%) had prior SNF, LTACH, or IRF exposure. Four (20%) patients had C. auris BSIs and seven (35%) patients died, including all patients with BSIs. The mean duration of antibiotic use in the four patients was 67 days. IP interventions addressed potential vehicles of transmission including healthcare personnel hands, shared patient equipment, and the environment (Table 1). Conclusion Only 15% of patients had prior SNF/LTACH/IRF exposure; many were admitted from home and/or outside hospitals with risk factors including recent surgery and antimicrobial use. This suggests the epidemiology of C. auris may be changing, and it may be prudent to consider routine admission and weekly surveillance on inpatient units deemed high risk for C. auris. Effective IP interventions included interventional hand hygiene auditing, increased accountability and oversight for shared patient equipment, limiting the number of rounding providers in rooms, and auditing environmental cleaning. Sustaining these efforts is crucial to keep pace with an evolving C. auris landscape. Disclosures All Authors: No reported disclosures

Research on the Spiral Rolling Gait of High-Voltage Power Line Serpentine Robots Based on Improved Hopf-CPGs Model

The efficiency of helical locomotion in snake-like robots along high-voltage transmission lines is often hindered by low motion efficiency, high joint signal noise, and challenges in traversing obstacles. This study aims to address these issues by proposing a gait generation method that leverages a standardized Central Pattern Generator (CPG). We modify the traditional Hopf-CPG model by incorporating constraint functions and a frequency-tuning mechanism to regulate the oscillator, which allows for the generation of asymmetric waveform signals for deflection joints and facilitates rapid convergence. The method begins by determining initial and obstacle-crossing state parameters, such as deflection angles and helical radii of the snake-like robot, using the backbone curve method and the Frenet–Serret framework. Subsequently, a CPG neural network is constructed based on Hopf oscillators, with a limit cycle convergent speed adjustment factor and amplitude bias signals to establish a fully connected matrix model for calculating multi-joint output signals. Simulation analysis using Simulink–CoppeliaSim evaluates the robot’s obstacle-crossing ability and the optimization of deflection joint signal noise. The results indicate a 55.70% increase in the robot’s average speed during cable traversal, a 57.53% reduction in deflection joint noise disturbance, and successful crossing of the vibration damper. This gait generation method significantly enhances locomotion efficiency and noise suppression in snake-like robots, offering substantial advantages over traditional approaches.

Age group classification based on optical measurement of brain pulsation using machine learning

Optical techniques, such as functional near-infrared spectroscopy (fNIRS), contain high potential for the development of non-invasive wearable systems for evaluating cerebral vascular condition in aging, due to their portability and ability to monitor real-time changes in cerebral hemodynamics. In this study, thirty-six healthy adults were measured by single channel fNIRS to explore differences between two age groups using machine learning (ML). The subjects, measured during functional magnetic resonance imaging (fMRI) at Oulu University Hospital, were divided into young (age ≤ 32) and elderly (age ≥ 57) groups. Brain pulses were extracted from fNIRS using a single 830 nm wavelength. Four feature sets were derived from log-normal parameters estimated by pulse decomposition algorithm. ML experiments utilized support vector machines and random forest learners, along with maximum relevance minimum redundancy and principal component analysis for feature selection. Performance with increasing sample size was estimated using learning curve method. The best mean balanced accuracies for each feature set were over 75% (75.9%, 76.4%, 79.3%, 76.9%), indicating the pulse features containing age related information. Learning curves indicated stable classification performance with increasing sample size. The results demonstrate the potential of using single channel fNIRS in the analysis of aging.

Laparoscopic Pudendal Nerve Release at the Level of Sacrospinous Ligament.

Pudendal nerve release can be managed by the laparoscopic approach for pudendal nerve entrapment. This is a case report of a stepwise demonstration of the technique with narrated video footage. A 71-year-old woman, gravid 7, parity 3, abortion 4, live births 3 vaginal delivery, complained of pain while sitting. She had been having vaginal and vulvar pain on the left side for 3years. At vaginal examination, she had pain over the sacrospinous ligament with palpation. Tinel's sign (+) on the left side. Left side pudendal nerve block relieves pain for 1h. Using a laparoscopic approach for a left pudendal nerve release at the level of sacrospinous ligament, the dissection started at the level of medial to the infundibulopelvic ligament, after visualization of obliterated umbilical artery and obturator nerve and vessels, dissection continued deeper to the pelvic floor visualizing the obturator internus muscle, then pudendal nerve and vessels are identified and the coccygeus muscle and sacrospinous ligament are observed. The sacrospinous ligament is cut all the way to the entrance of Alcock's canal. The operation was finished without any complication and the patient was discharged after the operation day. Pain decreased on her postoperative examination. Follow-up visits will be continued at 3 and 6 months. Laparoscopic pudendal nerve release is reproducible, effective, safe, and has a steep learning curve method for the management of pudendal nerve entrapment.

Association between novel anthropometric indices and overactive bladder: a population-based study.

Abdominal obesity is recognized as a key risk factor for developing OAB. However, traditional measures of obesity, such as the waist-to-height ratio (WHtR), waist circumference, and body mass index (BMI), may not sufficiently capture fat distribution in the body. This study aims to evaluate the relationship between novel anthropometric indices and OAB, providing a more accurate assessment of obesity-related risk factors. The National Health and Nutrition Examination Survey (NHANES) data from 2007 to 2018 were utilized, comprising 27,560 participants. To assess the association and discriminative ability of novel anthropometric indices, including the Body Roundness Index (BRI), A Body Shape Index (ABSI), Waist-to-Weight Index (WWI), and Relative Fat Mass (RFM), with OAB, we employed multivariable logistic regression, restricted cubic spline (RCS) analysis, subgroup analysis, and receiver operating characteristic (ROC) curve methods. Multivariable logistic regression analysis indicated that higher levels of novel anthropometric indices were positively associated with OAB prevalence. One z-score increase in WWI, BRI, RFM, and ABSI was associated with a 16, 31, 57, and 5% higher likelihood of OAB, respectively. RCS analysis revealed a non-linear relationship between RFM and OAB. ROC analysis indicated that WWI (AUC = 0.680) and RFM (AUC = 0.661) provided better diagnostic accuracy than traditional measures such as BMI (AUC = 0.599). Subgroup analyses supported the robustness of these findings. Novel anthropometric indices were positively associated with OAB prevalence. WWI and RFM demonstrated significantly better diagnostic value for OAB than BMI and WHtR. Future studies should investigate the potential of combining multiple anthropometric indices to improve predictive accuracy and conduct prospective studies to determine causality.

Quantitative Review of Critical Plane Criteria and Stress Analysis Approaches for Multiaxial Fatigue of Welded Joints

ABSTRACTThis quantitative review evaluates the effectiveness of stress‐based critical plane criteria, specifically Findley's criterion, the approach due to Carpinteri–Spagnoli (CS), and the Modified Wöhler Curve Method (MWCM), in assessing fatigue strength in aluminum and steel welded joints subjected to constant amplitude (CA) and variable amplitude (VA) multiaxial loading. These criteria were analyzed alongside stress analysis approaches, including nominal stress (NS), hot‐spot stress (HSS), effective notch stress (ENS), and the Theory of Critical Distances–Point Method (TCD PM). Results confirm that all criteria effectively estimate fatigue life for steel welded joints under CA loading, with MWCM combined with HSS proving most accurate. For aluminum joints, estimations showed greater conservatism and scatter, highlighting the need for further experimental data to improve accuracy. Experimentally calibrated constants significantly enhanced prediction reliability. Future research should refine these criteria for diverse aluminum grades and thicknesses, ensuring accurate estimations and robust alternatives to established codes.

Using Machine Learning to Predict Suspended Sediment Transport under Climate Change

Abstract Sediment transport, an important element of the erosion‒sedimentation cycle, can be very high during extreme flood events and can cause hydromorphological changes within river networks. Therefore, improved sediment transport predictions are needed to establish sediment management at the catchment scale. A machine learning model (i.e., XGBoost) and a sediment rating curve method were tested for predicting the suspended sediment load in the Sora River catchment in Slovenia. The evaluation of the models based on the historical data for 2016–2021 revealed that XGBoost outperformed the sediment rating curve model and resulted in a lower bias (i.e., approximately 15%). The XGBoost model was used to predict future suspended sediment load dynamics. Three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) and several climate change models were used. The rainfall–runoff model was set up, calibrated, validated and applied to simulate future daily discharge data, as this was the required input for the XGBoost and sediment rating curve models. The simulation results indicate that suspended sediment load is expected to increase in the future in the range 15–20% under both the RCP4.5 and RCP8.5 scenarios. Additionally, the number of days with a suspended sediment concentration (SSC) greater than 25 mg/l, which is often used an indicator of inadequate water quality, is expected to increase by 2–4%, whereas some models indicate an increase of up to 8%. Erosion and sediment management mitigation measures need to be applied in the future to ensure adequate water quality and good ecological status of the river.

Predictive risk model of mild cognitive impairment in patients with malignant haematological diseases after haematopoietic stem cell transplantation

ObjectiveThis study is to develop and validate a robust risk prediction model for mild cognitive impairment (MCI) in patients with malignant haematological diseases after haematopoietic stem cell transplantation (HSCT).MethodsIn this study, we analysed the clinical data of the included patients. Logistic regression analysis was used to identify independent risk factors for cognitive impairment after HSCT in patients with malignant haematological diseases, and a risk prediction model was constructed. Multiple cohorts of patients with haematological malignancies after HSCT (282 cases) from the Affiliated Hospital of Xuzhou Medical University and the First People’s Hospital of Yancheng City between April 2019 and February 2022, and patients from the Affiliated Huaian No.1 People’s Hospital of Nanjing Medical University between March 2022 and July 2023 were used for external validation. Logistic regression analysis was performed to develop the predictive model. The predictive value and consistency of the model were evaluated using the area under the curve (AUC) and calibration method, respectively. Decision curve analysis (DCA) was performed to access the utility of the model.ResultsApproximately half (52.26%) of the patients in the study developed mild cognitive impairment (MCI). Older age, allogeneic HSCT, anxiety, graft-versus-host disease, and longer hospital stay were associated with a higher risk of developing MCI. ROC curve analysis confirmed the sound performance of the predictive model and external validation, with AUC of 0.897 and 0.789 respectively. The direction of the calibration curves of the training and validation sets is closer to the diagonal (ideal curve), indicating good model consistency; the DCA curves also show that the model has good predictive ability and stability.ConclusionsWe conclude that it is possible to predict mild cognitive impairment with readily available, mostly pretransplant predictors. The accuracy of the risk prediction models can be improved for use in clinical practice, possibly by adding pretransplant patient-reported functioning and comorbidities.

Correct characteristics curves of Vlasov equation, fully respecting Maxwell equations in plasma kinetic simulation in lagrangian approach

Abstract We strictly demonstrate that the conflict between ordinary differential equations (ODEs) converted, through characteristic curve method, from one of coupled partial differential equations (PDEs) in Vlasov-Maxwell system and other coupled PDEs arises from inappropriate and habitual choice of one of two classes of characteristic curves and can be overcome by choosing another class. More comprehensive consideration on the characteristic curves of Vlasov equation can warrant kinetic simulation in Lagrangian approach getting rid of a well-known downside which refers to violation of Maxwell equations and continuity equation. This yields a sound/robust scheme of kinetic simulation in Lagrangian approach applicable to study a variety of topics. PACS: 52.65.-y.

The association between blood cadmium levels and bone mineral density in U.S. adolescents aged 12-19years.

To investigate the associations between blood cadmium (B-Cd) levels and bone mineral density (BMD) in adolescents. On the basis of the National Health and Nutrition Examination Survey (NHANES) database spanning from 2011 to 2018, we used weighted multiple regression, a generalized weighted model and smoothed curve methods to investigate the associations between B-Cd levels and BMD in adolescents. Subgroup analyses were also conducted to examine potential differences across age, sex, race, tobacco exposure status and other relevant variables. Among the 2427 participants, 52% were males, and 48% were females. In this study, multistage sampling data from the NHANES database were analysed, and the positive association between B-Cd levels and BMD shifted to a negative association after adjustment for age, sex and race. Subgroup analyses revealed a more pronounced association among females (β = - 0.07, 95% CI: - 0.09, - 0.04, P < 0.001), other Hispanic individuals (β = - 0.08, 95% CI: - 0.14, - 0.02, P = 0.012) and individuals exposed to tobacco (β = - 0.04, 95% CI: - 0.06, - 0.01, P = 0.016). The findings revealed a negative association between B-Cd levels and BMD in multivariable adjusted models.

Settlement of piles with negative skin friction: design approaches according to part 3 of Eurocode 7

Piles offer an effective solution for supporting structures in challenging ground conditions. However, ground settlement around deep foundations can induce negative skin friction, adding complexity to the geotechnical analysis and requiring careful consideration in both the pile settlement evaluation and structural integrity design. The article discusses the general recommendations provided by the informative annex of the revised Eurocode 7 version for designing piles subjected to negative skin friction. Using the Fellenius unified pile design concept, we provide a practical design framework for piles subjected to negative skin friction that extends the load-settlement curve methods proposed by Masopust, representing the standard pile design approaches in the Czech Republic. For examples presented, the introduced practical approach, also suitable for manual calculations, is in very good agreement with a refined calculation providing a nonlinear load-settlement curve.

Direct utilisation of impulse response data in reduction index assessment without intermediate reverberation time estimation (L).

An approach is proposed for reduction index measurement where impulse response data are utilised directly without relying on intermediate reverberation time estimation. The theoretical framework is presented and the main result is substantiated by shown equivalence to the conventional method for ideal exponential decay curves of acoustic energy. Additionally, the study introduces a formula for estimating effective reverberation time in cases of non-exponential decay curves. Further formulas for determining effective values of reverberation time and absorption area for general decay curve shapes are also suggested.

A Direct Discretization Method of Backbone Curve for Snake Robots With Multiple Roll Joints

A Direct Discretization Method of Backbone Curve for Snake Robots With Multiple Roll Joints

Soil structural stability improvement using arbuscular mycorrhizal fungi and biochar in water repellent and non‐water repellent soil

AbstractSoil hydrophobicity has increased in recent years due to the expansion of arid lands. In these lands soil inoculation with arbuscular mycorrhizal fungi (AMF) and application of biochar are two soil improvement strategies. The formation and stability of soil aggregates can be significantly influenced by these management practices. In the present study, the simultaneous effect of sugarcane biochar (0%, 1% and 2%) and AMF (+AMF and −AMF) on the improvement of water repellent (WR) and non‐water repellent (NWR) soil structure was investigated under corn cultivation in greenhouse. Incorporation of 2% biochar into NWR soil increased soil organic carbon by 155% and 94% in AMF and non‐AMF treatments, respectively, compared to the control (without biochar). However, this increase was less pronounced in WR soil. The difference in soil carbohydrate concentration between AMF and non‐AMF treatments enhanced with increasing biochar application level from 25% to 144% in non‐water repellent soil and from 51% to 147% in water repellent soil. The results indicated that the interaction between AMF and biochar had a significant positive effect on both soil microbial respiration and glomalin concentration. To measure the soil aggregate stability, the high‐energy soil moisture characteristic curve (HEMC) method was used. The positive effects of biochar and AMF on soil structural stability indices were observed in both studied soils. However, these positive effects were influenced by their interactive effects. Two percent biochar application in non‐water repellent soil, limited the positive effect of AMF on soil stability improvement by 73%. While, in water repellent soil, structural stability indices improved with 1% and 2% biochar application by 13.4% and 19.7% respectively, due to soil wettability improvement and consequently better microbial activities. Finally, in addition to the interactive effects of microbial activities and biochar on soil structural characteristics, the level of soil hydrophobicity is also effective in improving soil structure under these studies managements.

Comparison of external calibration and isotope dilution methods for iodine determination in foods by inductively coupled plasma mass spectrometry.

This study sought to validate the external calibration curve (CAL) method for iodine analysis in 26 selected foods and then to compare the test result with the isotope dilution mass spectrometry (IDMS). Iodine was extracted by tetramethylammonium hydroxide (TMAH) and determined by ICP-MS using CAL and IDMS methods. The results showed that iodine determination using the IDMS method had higher precision than the CAL method (LOD of the method were 0.01 and 0.02mg/kg, respectively). However, both methods showed good accuracy and precision for all SRM and the 26 food samples. Test results from both methods had a strong correlation (R2>0.998) and no significant difference between the determination methods, even within test sample sectors based on the distribution in the AOAC food triangle (p>0.970). 129I spiked into the sample before or during alkaline extraction showed no significant difference in the test results (p=0.989).

Bioavailability of rumen-protected histidine, lysine, and methionine assessed using different in vivo methods.

The objective of this experiment was to estimate the bioavailability (BA) of rumen-protected (RP) His, RPLys, and 2 RPMet products using 3 in vivo methods: area under the curve (AUC), plasma dose-response (PDR), and fecal free AA (FFAA) methods. We used 8 rumen-cannulated cows in a replicated 4 × 4 Latin square experiment with 16-d periods. Treatments were (1) abomasal infusion of water (control), (2) abomasal infusion of free His, Lys, and Met (FAA), (3) administration of RPHis + RPLys + RPMet1 (rumen-protected methionine protected with ethyl cellulose; RPAA1), and (4) administration of RPHis + RPLys + RPMet2 (rumen-protected methionine protected with a pH-sensitive polymer; RPAA2). On d 7 of each experimental period, a pulse-dose of water (control) or FAA were infused into the abomasum of the cows, or RPAA were placed directly in the rumen, and blood samples were taken from the jugular vein through a catheter 11 times over a 24-h period for the AUC method. Following the AA pulse-dose, infusion lines were installed into the abomasum for continuous infusion of FAA for the PDR method, or RPAA were fed from d 12 to d 16 and cows were fitted with urinary catheters for total collection of feces for the FFAA method. Fecal collection and blood sampling were conducted from d 14 to 16. Due to technical issues likely leading to unrealistic BA estimates, data for the PDR method are reported in the supplemental material. Relative BA based on the AUC method (computed as AUC of RPAA treatment plasma AA concentration divided by AUC of FAA treatment plasma AA concentration) was lower for RPMet1 compared with RPMet2 (43% vs. 61%) and was 45% (SEM = 3.35) and 72% (SEM = 5.99), for RPHis and RPLys, respectively. Rumen escape fractions of RPAA, estimated in a previous study using an in situ method, and digestibility data from the current study were used for calculations of BA for the FFAA method. Bioavailability based on the FFAA method was lower for RPMet1 (67%) compared with RPMet2 (91%) and was 87% (SEM = 0.71) and 75% (SEM = 2.75) for RPHis and RPLys, respectively. The relative differences in estimated BA based on both the AUC and FFAA methods between the RPMet products were as expected, based on literature, and data for all 4 RPAA products corresponded well with previously estimated BA using the FFAA method. The unrealistic data for the PDR method were likely caused by technical deviations from the original method (e.g., once-daily dosing of RPAA and inability to capture representative plasma concentration data with the sampling time points). Therefore, comparison of the PDR method with the AUC and FFAA methods were not possible in this study. Further comparisons are needed without deviations from the original PDR method. Variability in BA data and differences in estimated BA between the in vivo methods highlight the current challenges for accurate measurements of relative in vivo BA of RPAA products. Different protection technologies may call for different methodology to be used for BA estimations. Further research and standardization of in vivo BA methods are warranted.

LANDSLIDE SUSCEPTIBILITY ZONATION USING WEIGHT OF EVIDENCE METHOD IN MERTELU AND TEGALREJO, GEDANGSARI, GUNUNGKIDUL, SPECIAL REGION OF YOGYAKARTA, INDONESIA

Mertelu and Tegalrejo are situated in the Gedangsari Subdistrict, Gunungkidul Regency, Special Region of Yogyakarta, Indonesia. Located in the northern Baturagung Range, Southern Mountains Zone of East Java, with much hilly topography and mountainous areas with steep slopes, Mertelu and Tegalrejo are prone to landslides. The purpose of this research is to produce a landslide susceptibility zone using the weight of evidence (WoE) method. There were 73 landslide data taken from December 2022 to January 2023. As much as 80% of the data were used as a training dataset for weighting and generating the model map, while the remaining 20% were used as a test dataset. Parameters used in this research include slope angle, lithology, distance to faults, distance to rivers, and land use. Each parameter was weighted using the WoE method, and then the map of each parameter was overlaid to produce a map of landslide susceptibility zones. The accuracy of the map was calculated using the area under curve (AUC) method, including the success rate curve (SRC) and prediction rate curve (PRC). Based on the research results, the landslide susceptibility zone in the research area can be categorized: (1) very low, covering 6.34% of the total research area, (2) low, covering 24.15% of the total research area, (3) moderate, covering 44.46% of the total research area, and (4) high, covering 25.05% of the total research area. The landslide susceptibility map shows that the research location is predominantly characterized by areas with medium to high susceptibility to landslides. The medium and high susceptibility zones are close to the rivers that serve as the alignment of the faults. The accuracy calculations result in an SRC value of 0.753 and a PRC value of 0.780, both can be classified as “good” performance.