Metres Research Articles

Real-time optical fibre near-infrared chromatic dispersion analyser using collocated optical fibre gratings

We present what we believe to be a novel optical fibre device for real-time measurements of near-infrared chromatic dispersion of a liquid medium from 1100 nm to 1700 nm. This inline optical fibre chromatic dispersion analyser is based upon collocated fibre long-period gratings written adjacently in the core by femtosecond laser inscription yielding 8 attenuation bands associated with different cladding modes, yielding 8 independent measurements. This fibre device is tested on a series of chemical compounds associated with wines. The results for each compound yielded distinctive chromatic responses. A machine learning pipeline was developed that successfully clustered and classified spectral responses of the different chemicals to illustrate the distinctive responses. The limits of detection for these fibre devices ranged from 1×10−3 to 6×10−5 mol/L for the compounds associated with wines, demonstrating the potential usefulness of an optical fibre chromatic dispersion analyser is capable of monitoring in real-time effective chromatic dispersion that is not offered by any current technology.

Intramuscular fat % in the loin of Australian pork demonstrates a stronger relationship with computed tomography lean and fat % than abattoir measures of P2 and lean.

Intramuscular fat (IMF) % is an important measure of pork eating quality, with reduced IMF % linked to the selection of pigs with low backfat P2 thickness and more muscular genotypes over several decades. This experiment tested the association of IMF % from the M. longissimus thoracis et lumborum of 345 pigs at three abattoirs (Sites) with computed tomography (CT) determined carcass composition (% lean or fat), accredited abattoir measures of P2 backfat (mm) (Hennessy Grading Probe, AutoFom III and PorkScan Lite) and the lean % output from abattoir devices (Hennessy Grading Probe, AutoFom III and PorkScan Plus). There was a negative relationship between carcass CT lean % with IMF % at all Sites (P < 0.05), with the strength of this relationship varying between Sites. The strongest relationship was demonstrated at Site 1 (R2 0.30, RMSE 0.59), and across a 4 standard deviation range in the carcass lean % at each Site, resulted in a decrease in loin IMF % of 1.56, 0.44 and 0.80. There was a positive relationship of carcass CT fat % with IMF %, with similar, albeit slightly stronger relationship to IMF than with CT lean %. In contrast, only one of the three Sites with an accredited P2 measurement device demonstrated a significant association (P < 0.05) with IMF %. This is the first time the associations of IMF % with carcass CT composition has been assessed alongside that of P2 backfat measures from commercially deployed abattoir devices. Given P2 backfat is the key industry measure on which carcass value is determined in Australia, this experiment demonstrates the limitations that P2 has in measuring and monitoring the associations of carcass lean and fat % with IMF. Ideally, an independent measure of IMF % would allow for independent selection for lean % and IMF %, however there is currently no commercial device that can measure pork IMF %.

Using Bland-Altman plot-based harmonization algorithm to optimize the harmonization for immunoassays.

Harmonization has been recommended by theInternational Organization for Standard (ISO) to achieve equivalent results across invitro diagnostic measurement devices (IVD-MDs). We aim to evaluate the effectiveness of Bland-Altman plot-based harmonization algorithm (BA-BHA) created in this study and compare it with weighted Deming regression-based harmonization algorithm (WD-BHA) proposed in ISO 21151:2020. Eighty patient sera were used as the harmonization reference material (HRM) to develop IVD-MD-specific harmonization algorithms. Another panel of 40 patient sera was used to validate the effectiveness of harmonization algorithms. We compared regression slopes, intercepts, Bland-Altman plot layouts, percent differences, limits of agreement (LoAs), between-method coefficients of variation (CV) before and after harmonization. After harmonization by WD-BHA, acceptable slopes and intercepts between measured values and HRM targets were observed in weighted Deming regression, but not in Passing-Bablok analysis. Mean differences were-5.5 to 5.0 % and differences at specific levels were-33.9 to 23.9 %. LoAs were-64.6 to 74.6 %. Between-method CV was 22.9 % (±12.9 %). However, after harmonization by BA-BHA, both weighted Deming and Passing-Bablok regressions equations presented harmonized results. Mean differences were-0.3 to 0.2 % and differences at specific levels were-1.1 to 1.6 %. LoAs were-23.3 to 23.2 %. Between-method CV was 8.4 % (±4.0 %). The data points were evenly distributed at both sides of the mean in Bland-Altman plots. The inequivalence of test results between different methods can be improved but unacceptable analytical differences at specific levels may be hidden in terms of an acceptable slope and intercept on WD-BHA. The new protocol BA-BHA may be a viable alternative to optimize the harmonization for immunoassays.

The New Method for Ground Insulation Monitoring of the Secondary Circuit in Substations

When two-or-more-point grounding faults occur in the secondary circuit of a substation, they will lead to large data measurement errors in the protection, measurement, and control devices, which can easily cause protection malfunction. At present, there is a lack of an online panoramic monitoring system for the secondary circuits of substations, and it is difficult to accurately identify the faults in these secondary circuits. In order to solve this problem, this paper proposes a cloud–edge collaboration framework for the power Internet of Things (IoT), which can accurately identify faults by monitoring the secondary circuit of power grid substations with panoramic online status, reducing maintenance costs and improving overall operational efficiency. Firstly, the collection requirements of current transformer (CT) and potential transformer (PT) fault characteristics in the secondary circuit of the substation are analyzed. The platform architecture of the secondary loop panoramic monitoring system of the cloud-side cooperative substation is proposed, along with the algorithm and data wireless acquisition scheme of the edge computing, cloud computing, and cloud-side system. Furthermore, the edge computing platform and the current and voltage wireless sensors are developed. The maximum error in the accuracy test of the voltage sensor is 1.9180%, while the maximum error in the accuracy test of the current sensor is 1.3406%.

Study of Five-Hundred-Meter Aperture Spherical Telescope Feed Cabin Time-Series Prediction Studies Based on Long Short-Term Memory–Self-Attention

The Five-hundred-meter Aperture Spherical Telescope (FAST), as the world’s most sensitive single-dish radio telescope, necessitates highly accurate positioning of its feed cabin to utilize its full observational potential. Traditional positioning methods that rely on GNSS and IMU, integrated with TS devices, but the GNSS and TS devices are vulnerable to other signal and environmental disruptions, which can significantly diminish position accuracy and even cause observation to stop. To address these challenges, this study introduces a novel time-series prediction model that integrates Long Short-Term Memory (LSTM) networks with a Self-Attention mechanism. This model can hold the precision of feed cabin positioning when the measure devices fail. Experimental results show that our LSTM-Self-Attention model achieves a Mean Absolute Error (MAE) of less than 10 mm and a Root Mean Square Error (RMSE) of approximately 12 mm, with the errors across different axes following a near-normal distribution. This performance meets the FAST measurement precision requirement of 15 mm, a standard derived from engineering practices where measurement accuracy is set at one-third of the control accuracy, which is around 48 mm (according to the accuracy form the official threshold analysis on the focus cabin of FAST). This result not only compensates for the shortcomings of traditional methods in consistently solving feed cabin positioning, but also demonstrates the model’s ability to handle complex time-series data under specific conditions, such as sensor failures, thus providing a reliable tool for the stable operation of highly sensitive astronomical observations.

Research on the Technology of Improving the Compatibility of DC Measurement Devices Based on the Operation Experience of Siemens Hardware Solutions

The aim of this study was to manufacture alternative Siemens DC measurement system equipment to solve the problems of increased failure rates of foreign DC measurement equipment and the stopped production of key parts. In this paper, the overall structure and common faults of the Siemens DC measurement system are introduced, the difference between TDM signal frame structure and FT3 frame structure is detailed, and the related functional structure, chip type, and function of the Siemens distal module and merging unit (including laser function) are studied. The remote module, merging unit (including laser function), and related hardware design and software design to replace the Siemens DC measurement system were developed, and the test environment and control protection, fault recording wave for communication, and other functional tests were built. The test results show that the domestic remote module, merging unit (laser function), and other technologies communicate normally with the existing Siemens and the domestic mainstream manufacturers, and the accuracy meets the requirements of the 0.2 level.

Concurrent Validity and Interunit Reliability of 25-Hz GNSS Units for Profiling Sprinting Performance.

Dennison, L, Duthie, GM, Ehrmann, F, and Psarakis, MA. Concurrent validity and interunit reliability of 25-Hz GNSS units for profiling sprinting performance. J Strength Cond Res XX(X): 000-000, 2024-Profiling sprint performance by assessing within-race velocity or time is crucial for understanding an athlete's capabilities and identifying areas for improvement. While traditional gold standard systems provide valid and reliable measurements, they are often costly, laboratory-based, or impractical for field-based settings. New Global Navigation Satellite System (GNSS) units (25 Hz) with higher sampling rates may address some of these limitations. The purpose of the project was to evaluate the concurrent validity and interunit reliability of 25-Hz GNSS units by examining their agreement with laser devices and timing gates for velocity measurements and sprint/interval times. Concurrent validity was assessed during a real track and field training session. Thirty subjects each completed 3 to 6 maximal 40-meter sprints, for a total of 106 sprints, while being assessed simultaneously through all systems. Interunit reliability was assessed by placing 3 GNSS units on a motor vehicle and completing 60 accelerations from 0 to 60 m. Low mean bias (<1%) and typical error less than <2% for all measurements demonstrate excellent agreement between GNSS and criterion devices. The units demonstrated good reliability for the 0-10 m interval time (intraclass correlation coefficient [ICC] = 0.86), excellent reliability for all remaining 10 m to 60 m intervals (ICC = 0.91-0.99), sprint times 0-60 m (ICC = 0.97), and maximal sprint velocity (ICC = 1.0). These GNSS units provide an efficient and feasible alternative to traditional measurement devices. For coaches, this technology offers a scalable method to concurrently assess the sprint performances of multiple athletes during training and competitions, enabling evidence-based decisions to guide athletic development.

Optimization, Development and Evaluation of Vegetable Seedlings Transplanter Using Inclined Magazine-Type Metering Device for Cylindrical Paper Pot Seedlings

Optimization, Development and Evaluation of Vegetable Seedlings Transplanter Using Inclined Magazine-Type Metering Device for Cylindrical Paper Pot Seedlings

Use of a Microelectromechanical Systems Sensor for Objective Measurements of Abnormal Head Posture in Congenital Superior Oblique Palsy Patients.

The purpose of this study was to design an objective method for measurement of head positions as achieved with use of a microelectromechanical systems (MEMS) sensor. In addition, to use this system to observe the abnormal head position (AHP) in patients with congenital superior oblique palsy (SOP) before and after their surgery. An MEMS sensor was designed for recording of the pitch, roll, and yaw values of the head position in real time. The MEMS sensor was then fixed on the synoptophore from -30 degrees to +30 degrees positions horizontally and vertically to test the accuracy of these measurements. Then, we tested 13 participants with AHP using the MEMS method and the photographic method and compared their correlations. Finally, the pitch, roll, and yaw values of head positions were measured using this MEMS sensor in 31 patients with congenital SOP as performed before and after their surgery. The MEMS sensor (LPMS-B2; Alubi, Guangzhou, China; 400 hertz [Hz]), as based on the theory of a gyroscope, was designed and connected to a smartphone via Bluetooth. It was able to conveniently record the patient's pitch, roll, and yaw head positions in real time, recordings which were consistent with the scales of the synoptophore (P > 0.05) and good correlations with the photographic method (P < 0.001). The main preoperative AHP in patients with SOP was roll (22/31, 71%). Pre- and postoperative vertical deviations were 16.4 ± 7.3 prism diopters (PD) and 4.1 ± 4.2 PD, respectively (P = 0.001). The AHP in patients with SOP was positively correlated with the angle of extorsion in the dominant eye (P = 0.01), rather than that of the vertical deviation. The MEMS sensor described in this report is a simple, practical, and accurate objective device for use in head position measurements. In patients with SOP, the AHP is related to the angle of extorsion in the dominant eye. The MEMS sensor was designed as a micro-wireless dynamic high-precision device for AHP measurement, which has the potential for use in a clinic.

Dynamics of Vortex Matter in 2D Gapless Superconducting Materials with Impurities.

The recent interest in using ultrafast single-photon detectors in research and commercial applications has garnered significant attention from the scientific community. The dynamic event in the detection process consists of a photon causing local destruction of the order parameter, and then the applied current dissipates heat, bringing the material even more out of the superconducting state and then spiking a voltage peak in a measurement device. We investigated the role of superconducting and thermal parameters of the Generalized Time-Dependent Ginzburg-Landau (GTDGL) theory within the event of the first vortex penetration and the thermal dissipation in superconductors near the critical temperature. Moreover, in the vicinity of the Bogomolny point of the static Ginzburg-Landau theory, where κ ≈ 1/√2 and T → Tc, it has been found severely different vortex profiles. We point out that within the GTDGL theory, the presence of impurities (usual or paramagnetic) influences flux penetration and enhances the dissipation of heat, causing anomalous vortex configurations.

МЕТОДИКА ВЕРОЯТНОСТНОЙ ОЦЕНКИ ЭЛЕКТРОПОТРЕБЛЕНИЯ (ВОПРОСЫ ЭНЕРГЕТИЧЕСКОЙ БЕЗОПАСНОСТИ И ПРАВОВОГО ОБЕСПЕЧЕНИЯ)

The article deals with the problem of determining the actual energy consumption of outdoor lighting in municipalities, which arises as a result of the shortcomings of the existing energy management system and leads to contradictions between electricity suppliers and the municipality. The lack of metering devices and a wide variety of types of lighting lamps leads to the fact that the standard calculation methods used by the supplier unreasonably overestimate the cost of real consumption, thus limiting the budgetary possibilities of cities. It is proposed to solve this problem through the use of rank-parametric tools, which are successfully used for evaluation and forecasting in industry.

Study on a Novel Reseeding Device of a Precision Potato Planter

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato’s motion analysis model in the seed preparation process was constructed. The analysis results indicate that the seed preparation performance is positively related to the seed preparation opening length l1 and inclination angle of the seed-returning pipe θ. Then, the potato’s motion analysis model in the reseeding process was constructed. The analysis showed that the displacement of seeding potatoes in the horizontal direction ds is influenced by the initial seeding potato’s speed , dropping height hs, and the angle between the seeding pipe and the horizontal ground βs. The horizontal moving distance xr of the reseeding potatoes is influenced by the angle between the bottom of the reseeding pipe and horizontal ground βs2, the distance from its centroid to the reseeding door d, and the dropping height of the potato hr. The analysis results indicated that the reseeding potato can be effectively discharged into the furrow. Then, a prototype of a reseeding control system was constructed based on the STM32 microcontroller, electric pushers, and through-beam laser sensors. The simulation analysis was conducted to verify the theoretical analysis by using EDEM2020 software. The simulation results indicated that with the increase in the seeding chain speed, the seed preparation success rate initially increased slowly and then decreased gradually. The seed preparation performance can be increased by increasing the seed preparation opening length or decreasing the seed-returning pipe inclination angle. The impact on the successful seed preparation rate is ranked by significance as follows: seed preparation opening length &gt; seed-returning pipe inclination angle &gt; chain speed. Then, the prototype reseeding device and the corresponding seed metering device were manufactured and a series of bench tests and field tests were conducted. The bench test results showed an average successful seed preparation rate of 93.6%. The average qualified-seeding rate, miss-seeding rate, and multi-seeding rate in the field test were 89.6%, 2.46%, and 7.94%, respectively. This study can provide a theoretical reference for the design of potato reseeding devices.

More neck pain, less spinal mobility, altered sitting posture: Sagittal spinal alignment and mobility in women with chronic neck pain

BackgroundIncreasing evidence suggests that people with chronic neck pain (CNP) may display altered biomechanics beyond the cervical spine. However, whether spinal alignment and mobility are associated with neck pain is not clarified. ObjectivesTo investigate whether there is a significant association between neck pain intensity and sagittal spinal alignment and mobility in people with CNP, and to examine whether sagittal spinal alignment and mobility differ according to pain intensity. DesignA cross-sectional study. MethodForty-four women with CNP were included. The neck pain intensity at rest and during neck movements was assessed with the visual analogue scale (VAS). A skin-surface measurement device was used to assess sagittal alignment and mobility while sitting and standing. Linear regression analysis was used to assess associations. Participants were divided into two groups according to the pain intensity as group with mild pain (VAS≤4.4 cm) and group with moderate to severe pain (VAS>4.4 cm) and compared using the analysis of covariance. ResultsGreater resting pain was associated with a more forward trunk during sitting (Beta = 0.433, p < 0.05). Greater pain during neck movements was associated with increased lumbar lordosis during sitting (Beta = −0.376, p < 0.05). Classified by pain intensity at rest, trunk mobility while sitting was lower and forward trunk inclination and sacral kyphosis while sitting were higher in those with moderate/severe pain (η2p = 0.093–0.119, p < 0.05). By pain intensity during neck movements, women with moderate/severe pain exhibited lower sacral mobility while sitting (η2p = 0.129, p < 0.05). ConclusionsAddressing the entire spine in the assessment and management of CNP may help reduce pain.

Analysis of contamination and jamming characteristics of fuel metering device based on OMEGA theory

In order to obtain the quantitative law of the influence of pollution particles in fuel on the working characteristics of fuel metering devices and explore an analytical method for the pollution sticking characteristics of non-standard fuel components, the effect of pollution particles on fuel components is converted into sticking force based on the OMEGA theory, and the dynamic model of fuel components and devices under fuel pollution conditions is established. The working characteristics of the fuel metering device when the solid contamination level is GJB450B-7/8/9 is simulated, and the influence of each grade of fuel on the performance of its key components is obtained. The results show that the load flow response obtained by the servo valve contamination sticking model is basically consistent with the results of the standard servo valve contamination sticking model. The maximum sticking force of the metering valve in the 9-grade fuel is about 140 N, the response time is more than twice that of the non-polluting state, and the maximum relative error of the metered fuel quantity increases by more than 4 times. The method proposed in this paper can provide a reference for the pollution sticking modeling of non-standard fuel components and systems.

Silicon-based quantum random number generator with untrusted sources and uncharacterized measurements

Random numbers are essential resources in science and engineering, with indispensable applications in simulation, cybersecurity, and finance. Quantum random number generators (QRNGs), based on the principles of quantum mechanics, ensure genuine randomness and unpredictability. Silicon photonics enables the large-scale deployment of integrated QRNGs due to its low cost, miniaturization, and compatibility with CMOS technology. However, current integrated QRNGs are typically based on perfect or partially perfect device models, deviating from real-world devices, which compromises the unpredictability of quantum random numbers. In this study, we implemented a silicon-based QRNG that makes no assumptions about the source and only uses trusted but uncharacterized measurement devices. In experimental demonstration, we show that our setup can generate secure random numbers with different choices of intensities of laser light, and achieve an optimized random number generation rate of up to 4.04 Mbps. Our work significantly advances the security, practicality, and commercial development of QRNGs by employing imperfect devices.

Accurate and 30-plus days reliable cuffless blood pressure measurements with 9-minutes personal photoplethysmograph data and mixed deduction learning

Cuffless blood pressure (BP) measurements have long been anticipated, and the PPG (Photoplethysmography)-only method is the most promising one since already embedded in many wearable devices. To further meet the clinical accuracy requirements, PPG-only BP predictions with personalized modeling for overcoming personal deviations have been widely studied, but all required tens to hundreds of minutes of personal PPG measurements for training. Moreover, their accurate test periods without calibration practice were not reported. In this work, we collected records of PPG data from our recruited subjects in real-life scenarios instead of relying on the openly available MIMIC dataset obtained from intensive care unit (ICU) patients. Since our objective is commercial application and a substantial reduction in training data, we tailored our model training to closely mimic real-world usage. To achieve this, we developed a training approach that only requires 9-minutes of personal PPG signal recordings and mixed with other PPG data from our recruited 364 subjects. The modeling is conducted with two-channel paired inputs to the convolutional neural network (CNN)-based model, which we called Mixed Deduction Learning (MDL). The test results of 88 samples from 15 subjects, under testing period up to 30-plus days without extra calibration, revealed that MDL meets most of the standards of AAMI, BHS, and IEEE 1708–2014 (for static test only) for BP measurement devices, which indicates MDL’s long-term stability and consistency. Furthermore, we found that the model with two-channel inputs presents a trend of improving performance as the pool of mixed training data increased, while the conventional one-channel input revealed degraded performance. The outperformance of MDL is attributed to many significant features remained in the first CNN layer even when mixing personal 9-minutes data with the other 364 subjects. Consequently, PPG-only with MDL introduces a new avenue for overcoming challenges in training due to personal physiological variations. Given our consideration of real-life usage, this technology can be seamlessly translated to commercial applications.

Comparison of Machine Learning Approaches for The Modelling of Non-Invasive Optical-Based Hemoglobin Measurement Device

This paper discusses the comparison of several machine learning approaches to build a model for our developed non-invasive optical-based hemoglobin measurement device. Optical data for hemoglobin prediction was obtained from 120 volunteering patients taken in two different time periods, i.e., experiment 1 and experiment 2. The gold standard of these data for model training was taken from laboratory hemoglobin tests conducted at IPB University’s Policlinic. The two experiments suggest that univariate feature selection and Multi-Variable Linear Regression (MVLR) are promising for model building. Simulation results for several features show that a total of 30 features were able to produce the best model with Mean Absolute Error (MAE) = 1.25 g/dL, Mean Squared Error (MSE) = 2.56 and an R-squared (R2) = 0.24. This means that the 30 coefficients obtained for the 30 most important features can be embedded in the developed non-invasive optical-based hemoglobin measurement device. However, more data is needed to produce a better model.

Streamlining Barkhausen effect measurements: A simplified apparatus approach

The application of the Barkhausen Effect technique is hindered by the complexity and need for standardization in Barkhausen measurement devices. These devices typically comprise several modules for excitation, measurement, conditioning, and signal acquisition/processing, making them more complex than simpler methods such as Eddy Current or Magnetic Flux Leakage. Variations in device parameters among researchers can affect result consistency and interpretation. To address this issue, we propose a streamlined Barkhausen device consisting of a low-complexity measurement-excitation unit directly connected to the power grid. In the proposed device, nearly all signal conditioning and processing are transitioned from hardware, as used in the classic Barkhausen setup, to digital processing. This transition significantly enhances the standardization of the resultant Barkhausen signal. Comparative analysis between this simplified device and a traditional setup revealed no significant differences in signal parameters. The proposed device could function as a portable solution for preliminary tests to determine the feasibility of using the Barkhausen measurement technique. Adopting this simplified device could enhance the utility of the Barkhausen technique across various applications.

A new method to evaluate fluoroscopic system collimator performance.

Fluoroscopy uses collimators to limit the radiation field size. Collimators are often evaluated annually during equipment performance evaluations to maintain compliance with regulatory and/or accreditation bodies. A method to evaluate and quantify fluoroscopy collimator performance was developed. A radiation field and displayed image measurement device consisting of radiopaque rulers and radiochromic film strips was placed on the x-ray source assembly exit window to evaluate fluoroscopy collimator performance. This method was used to evaluate collimator performance on 79 fluoroscopic imaging systems including fixed C-arms, mobile C-arms, mini C-arms, and radiographic fluoroscopic systems. The excess length (EL), excess width (EW), and sum EL + EW of the radiation field relative to the displayed image were measured and compared to the limits specified in 21CFR1020.32. Four systems exceeded these limits. Placing the radiation measurement device at the x-ray source assembly exit window relative to the image receptor cover increased the film exposure rate by a factor up to 14.6. The time required to set up and complete the fluoroscopy collimator performance measurements using this method ranged from 5 to 10 min. This method provides an easily implemented quantitative measure of fluoroscopy system collimator performance that satisfies regulatory and accreditation body requirements.

Urinary L-FABP Assay in the Detection of Acute Kidney Injury following Haematopoietic Stem Cell Transplantation.

Background: Acute Kidney Injury (AKI) is a condition that affects a significant proportion of acutely unwell patients and is associated with a high mortality rate. Patients undergoing haemopoietic stem cell transplantation (HSCT) are in an extremely high group for AKI. Identifying a biomarker or panel of markers that can reliably identify at-risk individuals undergoing HSCT can potentially impact management and outcomes. Early identification of AKI can reduce its severity and improve prognosis. We evaluated the urinary Liver type fatty acid binding protein (L-FABP), a tubular stress and injury biomarker both as an ELISA and a point of care (POC) assay for AKI detection in HSCT. Methods: 85 patients that had undergone autologous and allogenic HSCT (35 and 50, respectively) had urinary L-FABP (uL-FABP) measured by means of a quantitative ELISA and a semi-quantitative POC at baseline, day 0 and 7 post-transplantation. Serum creatinine (SCr) was also measured at the same time. Patients were followed up for 30 days for the occurrence of AKI and up to 18 months for mortality. The sensitivity and specificity of uL-FABP as an AKI biomarker were evaluated and compared to the performance of sCr using ROC curve analysis and logistic regression. Results: 39% of participants developed AKI within 1 month of their transplantation. The incidence of AKI was higher in the allogenic group than in the autologous HTSC group (57% vs. 26%, p = 0.008) with the median time to AKI being 25 [range 9-30] days. This group was younger (median age 59 vs. 63, p < 0.001) with a lower percentage of multiple myeloma as the primary diagnosis (6% vs. 88%, p < 0.001). The median time to AKI diagnosis was 25 [range 9-30] days. uL-FABP (mcg/gCr) at baseline, day of transplant and on the 7th day post-transplant were 1.61, 5.39 and 10.27, respectively, for the allogenic group and 0.58, 4.36 and 5.14 for the autologous group. Both SCr and uL-FABP levels rose from baseline to day 7 post-transplantation, while the AUC for predicting AKI for baseline, day 0 and day 7 post-transplant was 0.54, 0.59 and 0.62 for SCr and for 0.49, 0.43 and 0.49 uL-FABP, respectively. Univariate logistic regression showed the risk of AKI to be increased in patients with allogenic HSCT (p = 0.004, 95%CI [0.1; 0.65]) and in those with impaired renal function at baseline (p = 0.01, 95%CI [0.02, 0.54]). The risk of AKI was also significantly associated with SCr levels on day 7 post-transplant (p = 0.03, 95%CI [1; 1.03]). Multivariate logistic regression showed the type of HSCT to be the strongest predictor of AKI at all time points, while SCr levels at days 0 and 7 also correlated with increased risk in the model that included uL-FABP levels at the corresponding time points. The POC device for uL-FABP measurement correlated with ELISA (p < 0.001, Spearman 'correlation' = 0.54) Conclusions: The urinary biomarker uL-FABP did not demonstrate an independent predictive value in the detection of AKI at all stages. The most powerful risk predictor of AKI in this setting appears to be allograft recipients and baseline renal impairment, highlighting the importance of clinical risk stratification. Urinary L-FAPB as a POC biomarker was comparable to ELISA, which provides an opportunity for simple and rapid testing. However, the utility of LFABP in AKI is unclear and needs further exploration. Whether screening through rapid testing of uL-FABP can prevent or reduce AKI severity is unknown and merits further studies.