There is evidence that physical activity (PA) is of cognitive benefit to the ageing brain, but little is known on the effect in patients with Alzheimer's disease (AD). The present pilot study ...assessed the effect of a home-based PA training on clinical symptoms, functional abilities, and caregiver burden after 12 and 24 weeks.
In an RCT thirty patients (aged 72.4±4.3 years) with AD (MMSE: 20.6±6.5 points) and their family caregivers were allocated to a home-based 12-week PA intervention program or the usual care group. The program changed between passive, motor-assisted or active resistive leg training and changes in direction on a movement trainer in order to combine physical and cognitive stimuli.
Analysis of activities of daily living in the patients (ADCS ADL total score) revealed a significant group × time interaction effect (95% CI of the difference between both groups at T2: 5.01-10.51). The control group experienced decreases in ADL performance at week 12 and 24 whereas patients in the intervention group remained stable. Analyses of executive function and language ability revealed considerable effects for semantic word fluency with a group × time interaction (95% CI of the difference between both groups at T2: 0.18-4.02). Patients in the intervention group improved during the intervention and returned to initial performance at week 12 whereas the controls revealed continuous worsening. Analyses of reaction time, hand-eye quickness and attention revealed improvement only in the intervention group. Caregiver burden remained stable in the intervention group but worsened in the control group.
This study suggests that PA in a home-based setting might be an effective and intrinsically attractive way to promote PA training in AD and modulate caregiver burden. The results demonstrate transfer benefits to ADL, cognitive and physical skill in patients with AD.
ClinicalTrials.gov NCT02196545.
Objectives
To compare targeted, transperineal magnetic resonance imaging (MRI)/ultrasound (US)‐fusion biopsy to systematic transrectal biopsy in patients with previous negative or first prostate ...biopsy and to evaluate the gain in diagnostic information with systematic biopsies in addition to targeted MRI/US‐fusion biopsies.
Patients and Methods
In all, 263 consecutive patients with suspicion of prostate cancer were investigated. All patients were evaluated by 3‐T multiparametric MRI (mpMRI) applying the European Society of Urogenital Radiology criteria. All patients underwent MRI/US‐fusion biopsy transperineally (mean nine cores) and additionally a systematic transrectal biopsy (mean 12 cores).
Results
In all, 195 patients underwent repeat biopsy and 68 patients underwent first biopsy. The median age was 66 years, median PSA level was 8.3 ng/mL and median prostate volume was 50 mL. Overall, the prostate cancer detection rate was 52% (137/263). MRI/US‐fusion biopsy detected significantly more cancer than systematic prostate biopsy (44% 116/263 vs 35% 91/263; P = 0.002). In repeat biopsy, the detection rate was 44% (85/195) in targeted and 32% (62/195) in systematic biopsy (P = 0.002). In first biopsy, the detection rate was 46% (31/68) in targeted and 43% (29/68) in systematic biopsy (P = 0.527). In all, 80% (110/137) of biopsy confirmed prostate cancers were clinically significant. For the upgrading of Gleason score, 44% (32/72) more clinically significant prostate cancer was detected by using additional targeted biopsy than by systematic biopsy alone. Conversely, 12% (10/94) more clinically significant cancer was found by systematic biopsy additionally to targeted biopsy.
Conclusions
MRI/US‐fusion biopsy was associated with a higher detection rate of clinically significant prostate cancer while taking fewer cores, especially in patients with prior negative biopsy. Due to a high portion of additional tumours with Gleason score ≥7 detected in addition to targeted biopsy, systematic biopsy should still be performed additionally to targeted biopsy.
Predictive maintenance is considered a proactive approach that capitalizes on advanced sensing technologies and data analytics to anticipate potential equipment malfunctions, enabling cost savings ...and improved operational efficiency. For journal bearings, predictive maintenance assumes critical significance due to the inherent complexity and vital role of these components in mechanical systems. The primary objective of this study is to develop a data-driven methodology for indirectly determining the wear condition by leveraging experimentally collected vibration data. To accomplish this goal, a novel experimental procedure was devised to expedite wear formation on journal bearings. Seventeen bearings were tested and the collected sensor data were employed to evaluate the predictive capabilities of various sensors and mounting configurations. The effects of different downsampling methods and sampling rates on the sensor data were also explored within the framework of feature engineering. The downsampled sensor data were further processed using convolutional autoencoders (CAEs) to extract a latent state vector, which was found to exhibit a strong correlation with the wear state of the bearing. Remarkably, the CAE, trained on unlabeled measurements, demonstrated an impressive performance in wear estimation, achieving an average Pearson coefficient of 91% in four different experimental configurations. In essence, the proposed methodology facilitated an accurate estimation of the wear of the journal bearings, even when working with a limited amount of labeled data.
Objective
Our aim was to assess and compare trends of urinary diversion (UD) for patients receiving radical cystectomy for the treatment of bladder cancer in the US and Germany, and to investigate ...decisive predictors for the choice of UD.
Methods
We analyzed the nationwide German hospital billing database and the Nationwide Inpatient Sample (NIS) from 2006 to 2014. Cases with a bladder cancer diagnosis combined with RC were included, and trends in the choice of UD, transfusion rates, length of stay, and mortality were assessed.
Results
From 2006 to 2014, the total number of RCs recorded within the NIS were 17,711, with a varying annual caseload of 1666–2009, while RC numbers increased from 5627 to 7390 in Germany (
p
< 0.001 for trends), with a total of 60,447 cases. The share of incontinent UD in the US remained stable at 93%, while increasing from 63.2 to 70.8% in Germany. Multivariate models indicated age and sex were the most important factors associated with the choice of UD in both countries, while hospital caseload and teaching status were less relevant factors in the US. In-hospital mortality was lower in the US compared with Germany (1.9% vs. 4.6%;
p
< 0.001), with significantly shorter hospital stays (10.7 days in the US vs. 25.1 days in Germany;
p
< 0.001).
Conclusions
The increasing age of patients with presumably higher comorbidity in recent years led to increased use of incontinent UD in Germany, while continent UD appears to be underused in the US. Mortality and transfusion rates were significantly lower in the US within a shorter hospital stay.
This paper introduces a robust deposition model designed for exploring the growth dynamics of deposits on surfaces under practical conditions. The study addresses the challenge of characterizing the ...intricate morphology of deposits, exhibiting significant visual variations. A generative approach is deployed to create diverse natural and engineered surface textures, governed by probabilistic principles. The model’s formulation addresses key questions related to deposition initiation, nucleation point behaviour, spatial scaling, deposit growth rates, spread dynamics, and surface mobility. A versatile algorithm, relying on six parameters and employing nested loops and Gaussian sampling, is developed. The algorithm’s efficacy is examined through extensive simulations, involving variations in nucleation scaling densities, aggregate scaling scenarios, spread factors, and diffusion rates. Surface statistics are computed for simulated deposits and analyzed using Fast Fourier Transform (FFT). The resulting database enables quantitative comparisons of surfaces generated with different parameters, where the database-derived parallel coordinates offer guidance for selecting optimal model parameters to achieve desired surface morphologies. The proposed approach is validated against urea-derived deposits, exhibiting statistical consistency and agreement with experimental observations. Overall, the model’s adaptable framework holds promise for understanding and predicting deposit growth on surfaces in diverse practical scenarios.
Mapping with laser scanners is the state-of-the-art method applied in service, industrial, medical, and rescue robotics. Although a lot of research has been done, maps still suffer from interferences ...caused by transparent and specular reflective objects. Glass, mirrors, shiny or translucent surfaces cause erroneous measurements depending on the incident angle of the laser beam. In past experiments the Mirror Detector Approach was implemented to determine such measurements with a multi-echo laser scanner. Recognition values are based on their differences in recorded measurements in regard to the distance of the echoes. This paper describes the research to distinguish between reflective and transparent objects. The implemented Mirror Detector was specifically modified for recognition of said objects for which four experiments were conducted; one experiment to show the map of the original Mirror Detector; two experiments to investigate intensity characteristics based on angle, distance, and material; and one experiment to show an applied discrimination with the extended version of the Mirror Detector, the Reflection Classifier Approach. To verify the results, a comparison with existing models was performed. This study showed that shiny metals, like aluminium, etc., provide significant characteristics, while mirrors are to be characterized by a mixed model of glass and shiny metal. Transparent objects turned out to be challenging because their appearance in the sensor data strongly depends on the background. Nevertheless, these experiments show that discrimination of transparent and reflective materials based on the reflected intensity is possible and feasible.
•The need for discrimination between specular reflective and transparent objects for environmental mapping is demonstrated.•The characteristics identified in the measurements of different objects based on distance, angle, and material are investigated.•It is shown that shiny metallic materials provide significant characteristics, while mirrors are to be characterized by a mixed model (between glass and shiny metal).•Mapping transparent objects turned out to be challenging because of the dependency on the object behind the surface.•The problem of mapping transparent and specular reflective objects is treated with an extended version of the Mirror Detector Approach, named Reflection Classifier Approach. It demonstrates the solvability of this problem.
In lung cancer, randomized trials assessing hyperfractionated or accelerated radiotherapy seem to yield conflicting results regarding the effects on overall (OS) or progression-free survival (PFS). ...The Meta-Analysis of Radiotherapy in Lung Cancer Collaborative Group decided to address the role of modified radiotherapy fractionation.
We performed an individual patient data meta-analysis in patients with nonmetastatic lung cancer, which included trials comparing modified radiotherapy with conventional radiotherapy.
In non-small-cell lung cancer (NSCLC; 10 trials, 2,000 patients), modified fractionation improved OS as compared with conventional schedules (hazard ratio HR = 0.88, 95% CI, 0.80 to 0.97; P = .009), resulting in an absolute benefit of 2.5% (8.3% to 10.8%) at 5 years. No evidence of heterogeneity between trials was found. There was no evidence of a benefit on PFS (HR = 0.94; 95% CI, 0.86 to 1.03; P = .19). Modified radiotherapy reduced deaths resulting from lung cancer (HR = 0.89; 95% CI, 0.81 to 0.98; P = .02), and there was a nonsignificant reduction of non-lung cancer deaths (HR = 0.87; 95% CI, 0.66 to 1.15; P = .33). In small-cell lung cancer (SCLC; two trials, 685 patients), similar results were found: OS, HR = 0.87, 95% CI, 0.74 to 1.02, P = .08; PFS, HR = 0.88, 95% CI, 0.75 to 1.03, P = .11. In both NSCLC and SCLC, the use of modified radiotherapy increased the risk of acute esophageal toxicity (odds ratio OR = 2.44 in NSCLC and OR = 2.41 in SCLC; P < .001) but did not have an impact on the risk of other acute toxicities.
Patients with nonmetastatic NSCLC derived a significant OS benefit from accelerated or hyperfractionated radiotherapy; a similar but nonsignificant trend was observed for SCLC. As expected, there was increased acute esophageal toxicity.
The formation of pollutant emissions in jet engines is closely related to the fuel distribution inside the combustor. Hence, the characteristics of the spray formed during primary breakup are of ...major importance for an accurate prediction of the pollutant emissions. Currently, an Euler–Lagrangian approach for droplet transport in combination with combustion and pollutant formation models is used to predict the pollutant emissions. The missing element for predicting these emissions more accurately is well defined starting conditions for the liquid fuel droplets as they emerge from the fuel nozzle. Recently, it was demonstrated that the primary breakup can be predicted from first principles by the Lagrangian, mesh-free, Smoothed Particle Hydrodynamics (SPH) method. In the present work, 2D Direct Numerical Simulations (DNS) of a planar prefilming airblast atomizer using the SPH method are presented, which capture most of the breakup phenomena known from experiments. Strong links between the ligament breakup and the resulting spray in terms of droplet size, trajectory and velocity are demonstrated. The SPH predictions at elevated pressure conditions resemble quite well the effects observed in experiments. Significant interdependencies between droplet diameter, position and velocity are observed. This encourages to employ such multidimensional interdependence relations as a base for the development of primary atomization models.
Flash vacuum thermolysis (FVT) of 3-methylidenefuran-2(3H)-ones 3 causes cheletropic extrusion of CO with formation of allenyl ketones 4. o-Chloro- and o-bromophenylmethylidenefuranones also afford ...allenyl ketones upon flash vacuum thermolysis, but in addition, 3-ethynylcoumarins 6 are formed via E/Z isomerization of the methylidenefuranones, cyclization, halogen atom migration, and HCl (HBr) elimination. The presence of strongly electron-withdrawing groups (nitroaryl or acetyl) on the acylallene moiety causes rearrangement to give 2-arylfurans 10 and 13 as well as 2-furylfurans and 2-furylthiophenes 16 by cyclization of the allenyl ketones. The reaction mechanisms are supported by calculations at the M06-2X/6-311+G(d,p) level of theory.
With the increasing demand for efficient and accurate numerical simulations of spray combustion in jet engines, the necessity for robust models to enhance the capabilities of spray models has become ...imperative. Existing approaches often rely on ad hoc determinations or simplifications, resulting in information loss and potentially inaccurate predictions for critical spray characteristics, such as droplet diameters, velocities, and positions, especially under extreme operating conditions or temporal fluctuations. In this study, we introduce a novel approach to modeling multivariate spray characteristics using Gaussian mixture models (GMM). By applying this approach to spray data obtained from numerical simulations of the primary atomization in air-blast atomizers, we demonstrate that GMMs effectively capture the spray characteristics across a wide range of operating conditions. Importantly, our investigation reveals that GMMs can handle complex non-linear dependencies by increasing the number of components, thereby enabling the modeling of more complex spray statistics. This adaptability makes GMMs a versatile tool for accurately representing spray characteristics even under extreme operating conditions. The presented approach holds promise for enhancing the accuracy of spray combustion modeling, offering an improved injection model that accurately captures the underlying droplet distribution. Additionally, GMMs can serve as a foundation for constructing meta models, striking a balance between the efficiency of low-order approaches and the accuracy of high-fidelity simulations.
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