Search Results (7)

Background: Patellar motion trajectory (PMT) is a key kinematic parameter for evaluating patellofemoral joint (PFJ) stability, but traditional static imaging indices are unable to capture the dynamic six-degrees-of-freedom (6-DOF) characteristics of patellar motion throughout the entire knee flexion–extension cycle. Four-dimensional computed tomography (4D-CT) facilitates in vivo dynamic imaging of the PFJ, while the systematic classification of PMT in asymptomatic populations has remained underexplored. Methods: A retrospective cross-sectional study was performed on 64 asymptomatic and functionally normal knees that underwent 4D-CT dynamic scanning from March 2021 to December 2025. Patellar 6-DOF kinematic data during 0° to 90° of knee flexion–extension were extracted through manifold optimization, automatic segmentation, and spatial registration. Following standardization of the motion cycle, unsupervised K-means clustering was employed to classify PMT phenotypes, with nonparametric tests used to analyze intergroup kinematic differences and evaluate clustering quality. Results: Three distinct PMT types were identified based on clustering validity indices, including a silhouette score of 0.381, a Davies-Bouldin index of 0.916, and a Calinski–Harabasz index of 44.06: Type 1 (7.81%, 35.11 ± 6.56 mm), Type 2 (56.25%, 15.67 ± 6.59 mm), and Type 3 (35.94%, 2.82 ± 2.41 mm). Lateral translation (Tx) served as the dominant determinant for PMT typing (p < 0.001), whereas non-lateral DOF parameters exhibited no consistent intergroup differences. Postural DOFs exhibited coupled fluctuations with Tx but had no independent stratification effect. Traditional static imaging parameters demonstrated no consistent correlation with these dynamic subtypes. Conclusions: Functionally asymptomatic knees exhibited three in vivo patellar 6-DOF motion trajectory phenotypes dominated by lateral translation amplitude. This 4D-CT-based typing framework provides a dynamic kinematic baseline for PFJ stability evaluation and lays a foundation for individualized optimization of ligament reconstruction and pathophysiological research of patellofemoral disorders. Full article

The transverse beam size is a key parameter for characterizing the performance of synchrotron radiation sources. Accurate measurement of the transverse beam size is crucial for assessing beam quality. In this study, a fiber array-photomultiplier tube (PMT) beam measurement system was developed to enable high-precision sampling of beam profile information for beam-size measurement. Furthermore, a hybrid method integrating nonlinear least squares (NLLS) fitting and Gaussian basis-function fitting was proposed to reconstruct the beam intensity profile from discrete sampling data. Before performing NLLS fitting, a median absolute deviation (MAD)-based threshold filter is employed to remove outliers and suppress random noise, thereby improving the stability and robustness of the parameter estimation. The filtered data are then fitted using NLLS to obtain the reconstructed distribution. To capture potential high-order modal features in the beam profile, a Gaussian basis-function fitting model was also introduced for comparison, and its performance was evaluated under complex intensity distributions. Additionally, the relationship between the full width at half maximum (FWHM) and beam intensity was experimentally verified while accounting for measurement effects in the system. The results demonstrate that the proposed hybrid algorithm improves reconstruction accuracy and robustness, enabling precise recovery of the beam-intensity profile in the fiber-array PMT system. Full article

Crop water use (ET_c) is typically estimated as the product of crop evapotranspiration (ET_o) and a crop coefficient (K_c). However, the estimation of ET_o requires various meteorological data, which are often unavailable or of poor quality, particularly in countries such as Guinea-Bissau, where the maintenance of weather stations is frequently inadequate. The present study aimed to assess alternative approaches, as outlined in the revised FAO56 guidelines, for estimating ET_o when only temperature data is available. These included the use of various predictors for the missing climatic variables, referred to as the Penman–Monteith temperature (PMT) approach. New approaches were developed, with a particular focus on optimizing the predictors at the cluster level. Furthermore, different gridded weather datasets (AgERA5 and MERRA-2 reanalysis) were evaluated for ET_o estimation to overcome the lack of ground-truth data and upscale ET_o estimates from point to regional and national levels, thereby supporting water management decision-making. The results demonstrate that the PMT is generally accurate, with RMSE not exceeding 26% of the average daily ET_o. With regard to shortwave radiation, using the temperature difference as a predictor in combination with cluster-focused multiple linear regression equations for estimating the radiation adjustment coefficient (k_Rs) yielded accurate results. ET_o estimates derived using raw (uncorrected) reanalysis data exhibit considerable bias and high RMSE (1.07–1.57 mm d⁻¹), indicating the need for bias correction. Various correction methods were tested, with the simple bias correction delivering the best overall performance, reducing RMSE to 0.99 mm d⁻¹ and 1.05 mm d⁻¹ for AgERA5 and MERRA-2, respectively, and achieving a normalized RMSE of about 22%. After implementing bias correction, the AgERA5 was found to be superior to the MERRA-2 for all the studied sites. Furthermore, the PMT outperformed the bias-corrected reanalysis in estimating ET_o. It was concluded that PMT-ET_o can be recommended for further application in countries with limited access to ground-truth meteorological data, as it requires only basic technical skills. It can also be used alongside reanalysis data, which demands more advanced expertise, particularly for data retrieval and processing. Full article

Many German cities, municipalities and transport associations are expanding their bike-sharing systems (BSS) to offer citizens a cost-effective and climate-friendly means of transport and an alternative to private motorized transport (PMT). However, operators face the challenge of generating high-quality predictive analyses and time series forecasts. In particular, the prediction of demand is a key component to foster data-driven decisions. To address this problem, an Unobserved Component Model (UCM) has been developed to predict the monthly rentals of a BSS, whereby the station-based BSS VRNnextbike, including over 2000 bikes, 297 stations and 21 municipalities, is employed as an example. The model decomposes the time series into trend, seasonal, cyclical, auto-regressive and irregular components for statistical modeling. Additionally, the model includes exogenous factors such as weather, user behavior (e.g., traveled distance), school holidays and COVID-19 relevant covariates as independent effects to calculate scenario based forecasts. It can be shown that the UCM calculates reasonably accurate forecasts and outperforms classical time series models such as ARIMA(X) or SARIMA(X). Improvements were observed in model quality in terms of AIC/BIC (2.5% to 22%) and a reduction in error metrics from 15% to 45% depending on the considered model. Full article

Herbal medicine and nutritional supplements are suggested to treat premenstrual somatic and psycho-behavioural symptoms in clinical guidelines; nonetheless, this is at present based on poor-quality trial evidence. Hence, we aimed to design a systematic review and meta-analysis for their effectiveness in alleviating premenstrual symptoms. The published randomized controlled trials (RCTs) were extracted from Google scholar, PubMed, Scopus and PROSPERO databases. The risk of bias in randomized trials was assessed by Cochrane risk-of-bias tool. The main outcome parameters were analysed separately based on the Premenstrual Symptom Screening Tool and PMTS and DRSP scores. Secondary parameters of somatic, psychological, and behavioural subscale symptoms of PSST were also analysed. Data synthesis was performed assuming a random-effects model, and standardized mean difference (SMDs) was analysed using SPSS version 28.0.0 (IBM, Armonk, NY, USA). A total of 754 articles were screened, and 15 RCTs were included (n = 1211 patients). Primary results for participants randomized to an intervention reported reduced PSST (n = 9), PMTS (n = 2), and DSR (n = 4) scores with (SMD = −1.44; 95% CI: −1.72 to −1.17), (SMD = −1.69; 95% CI: −3.80 to 0.42) and (SMD = 2.86; 95% CI: 1.02 to 4.69) verses comparator with substantial heterogeneity. Physical (SMD = −1.61; 95% CI = −2.56 to −0.66), behavioural (SMD = −0.60; 95% CI = −1.55 to 0.35) and mood (SMD = 0.57; 95% CI = −0.96 to 2.11) subscale symptom groupings of PSST displayed similar findings. Fifty-three studies (n = 8) were considered at low risk of bias with high quality. Mild adverse events were reported by four RCTs. Based on the existing evidence, herbal medicine and nutritional supplements may be effective and safe for PMS. Full article

It is well established that every living organism spontaneously emits photons referred to as ultra-weak photon emission (synonym biophotons or low-level chemiluminescence) which inherently embodies information about the wellbeing of the source. In recent years, efforts have been made to use this feature as a non-invasive diagnostic tool related to the detection of food quality, agriculture and biomedicine. The current study deals with stress resulting from wounding (mechanical injury) on Arabidopsis thaliana and how it modifies the spontaneous ultra-weak photon emission. The ultra-weak photon emission from control (non-wounded) and stressed (wounded) plants was monitored using different modes of ultra-weak photon emission measurement sensors like charge-coupled device (CCD) cameras and photomultiplier tubes (PMT) and the collected data were analyzed to determine the level of stress generated, photon emission patterns, and underlying biochemical process. It is generally considered that electronically excited species formed during the oxidative metabolic processes are responsible for the ultra-weak photon emission. In the current study, a high-performance cryogenic full-frame CCD camera was employed for two-dimensional in-vivo imaging of ultra-weak photon emission (up to several counts/s) and the spectral analysis was done by using spectral system connected to a PMT. The results show that Arabidopsis subjected to mechanical injury enhances the photon emission and also leads to changes in the spectral pattern of ultra-weak photon emission. Thus, ultra-weak photon emission can be used as a tool for oxidative stress imaging and can pave its way into numerous plant application research. Full article

The use of Personal Mobile Terrestrial System (PMTS) has increased considerably for mobile mapping applications because these systems offer dynamic data acquisition with ground perspective in places where the use of wheeled platforms is unfeasible, such as forests and indoor buildings. PMTS has become more popular with emerging technologies, such as miniaturized navigation sensors and off-the-shelf omnidirectional cameras, which enable low-cost mobile mapping approaches. However, most of these sensors have not been developed for high-accuracy metric purposes and therefore require rigorous methods of data acquisition and data processing to obtain satisfactory results for some mapping applications. To contribute to the development of light, low-cost PMTS and potential applications of these off-the-shelf sensors for forest mapping, this paper presents a low-cost PMTS approach comprising an omnidirectional camera with off-the-shelf navigation systems and its evaluation in a forest environment. Experimental assessments showed that the integrated sensor orientation approach using navigation data as the initial information can increase the trajectory accuracy, especially in covered areas. The point cloud generated with the PMTS data had accuracy consistent with the Ground Sample Distance (GSD) range of omnidirectional images (3.5–7 cm). These results are consistent with those obtained for other PMTS approaches. Full article