Miracle-dz/UniFAR-FTUs huggingface dataset:
Schenkelhalsprothese Typ Cut : eine funktionell-morphologische Analyse

In contrast to other commonly employed models, the cut model femoral neck prosthesis is a cementless prosthesis of comparatively small dimensions. With the aim of investigating its functional integration in the femur radiological, densitometric and photoelastic analyses were carried out. The biomechanical reaction of the bone tissue expected on the basis of the experimental result is tested in the clinical situation.
A Distributed N-FINDR Cloud Computing-Based Solution for Endmembers Extraction on Large-Scale Hyperspectral Remote Sensing Data

In this work, we introduce a novel, distributed version of the N-FINDR endmember extraction algorithm, which is able to exploit computer cluster resources in order to efficiently process large volumes of hyperspectral data. The implementation of the distributed algorithm was done by extending the InterCloud Data Mining Package, originally adopted for land cover classification, through the HyperCloud-RS framework, here adapted for endmember extraction, which can be executed on cloud computing environments, allowing users to elastically administer processing power and storage space for adequately handling very large datasets. The framework supports distributed execution, network communication, and fault tolerance, transparently and efficiently to the user. The experimental analysis addresses the performance issues, evaluating both accuracy and execution time, over the processing of different synthetic versions of the AVIRIS Cuprite hyperspectral dataset, with 3.1 Gb, 6.2 Gb, and 15.1Gb respectively, thus addressing the issue of dealing with large-scale hyperspectral data. As a further contribution of this work, we describe in detail how to extend the HyperCloud-RS framework by integrating other endmember extraction algorithms, thus enabling researchers to implement algorithms specifically designed for their own assessment.
“A Place for Everybody”: Students’ Perspectives on Inclusive Behavior in School

Understanding students’ perspectives on inclusive behavior is important for addressing the bullying, victimization, and exclusion that many middle school and high school students, particularly marginalized students, continue to face at school. This study explored how students give meaning to inclusive behavior at school and the conditions that support inclusive behavior. Using data from 30 focus groups conducted with students, the findings expand on three primary themes: students’ broad descriptions of inclusive behavior, their understanding of the qualities and characteristics of an inclusive person, and their beliefs about what makes a school inclusive. Findings from this study can inform organizational practices to facilitate inclusive behavior in schools in a manner consistent with how students themselves view inclusivity.
A Study on Sagdeev Pseudopotential and Electrostatic Potential of Solitons in Four-Component Magnetized Dusty Plasma

The nonlinear dynamics and its wide range of applications have increased the curiosity of researchers. In short span of time, solitons have become the major interest of physicists. We investigate the nonlinear profile of plasmonic solitons with four components consisting of hot electrons, cold electrons, hot ions, and hot protons. In this framework, a couple of equations of motion are derived by invoking the reductive perturbation technique, and the resultant modified Korteweg—de Vries (m-KdV) equation is solved by the sine cosine method. Here, we analyze the effect of Sagdeev pseudopotential and the electrostatic potential with different system parameters and the characteristics of solitons are found.
Popularity-Aware Closeness Based Caching in NDN Edge Networks

By enabling name-based routing and ubiquitous in-network caching, Named Data Networking (NDN) is a promising network architecture for sixth generation (6G) edge network infrastructures. However, the performance of content retrieval largely depends on the selected caching strategy, which is implemented in a distributed fashion by each NDN node. Previous research showed the effectiveness of caching decisions based on content popularity and network topology information. This paper presents a new distributed caching strategy for NDN edge networks based on a metric called popularity-aware closeness (PaC), which measures the proximity of the potential cacher to the majority of requesters of a certain content. After identifying the most popular contents, the strategy caches them in the available edge nodes that guarantee the higher PaC. Achieved simulation results show that the proposed strategy outperforms other benchmark schemes, in terms of reduced content retrieval delay and exchanged data traffic.
Suggesting Assess Queries for Interactive Analysis of Multidimensional Data

Assessment is the process of comparing the actual to the expected behavior of a business phenomenon and judging the outcome of the comparison. The <inline-formula><tex-math notation="LaTeX">${{\sf assess}}$</tex-math><alternatives><mml:math><mml:mi mathvariant="sans-serif">assess</mml:mi></mml:math><inline-graphic xlink:href="rizzi-ieq1-3171516.gif"/></alternatives></inline-formula> querying operator has been recently proposed to support assessment based on the results of a query on a data cube. This operator requires (i) the specification of an OLAP query to determine a target cube; (ii) the specification of a reference cube of comparison (benchmark), which represents the expected performance; (iii) the specification of how to perform the comparison, and (iv) a labeling function that classifies the result of this comparison. Despite the adoption of a SQL-like syntax that hides the complexity of the assessment process, writing a complete assess statement is not easy. In this paper we focus on making the user experience more comfortable by letting the system suggest suitable completions for partially-specified statements. To this end we propose two interaction modes: progressive refinement and auto-completion, both starting from an assess statement partially declared by the user. These two modes are evaluated both in terms of scalability and user experience, with the support of two experiments made with real users.
Daimler's new full-scale, high-dynamic driving simulator - A technical overview

Based on 25 years experience with the optimization and successful operation of driving simulators as efficient tools for the development and assessment of driver assistant and chassis system for passenger cars, trucks and busses, we have built up a new driving simulator center at Daimler's main research and development location in Sindelfingen. Beside three fixed-based simulators and a ride simulator a completely new designed high dynamic moving-base simulator was constructed. The new driving simulator center was taken into operation in the first half of 2010 and will be officially opened end of September. This paper gives an overview of the hard- and software components as well as of the performance of the new simulators.
Reduced Gain and Shortened Time Constant of Vestibular Velocity Storage as a Source of Balance and Movement Sensitivities in Gravitational Insecurity

Gravitational insecurity (GrI) involves lifetime movement and balance concerns whose pathophysiological origins are unclear. We tested whether balance symptoms in mild GrI might involve anomalies in vestibular velocity storage (VVS), a brainstem/cerebellar circuit that amplifies gain and prolongs the persistence of weak vestibular signals from small/slow head movements. A Provisional Gravitational Insecurity Index (PGrI) was developed, evaluated for psychometrics/demographics, and used to identify otherwise healthy adults with life-long balance challenges as well as sex, age, and ethnicity-matched comparison adults without such challenges. Balance confidence, sensory hypersensitivities, spatial orientation, anxiety, and hearing loss were self-reported. Standing balance under visual/proprioceptive restrictions and perrotary vestibulo-ocular nystagmus were evaluated. The PGrI showed approximated test-retest reliability and convergent and discriminant validity. When only vestibular input was available, mild GrI participants on a tilting platform used effortful hip strategies for balance significantly more than did comparison participants. Rotation testing revealed that mild GrI participants had significantly less low frequency gain and shortened VVS persistence. Combined, these two parameters correlated significantly with PGrI. The PGrI also correlated with problematic spatial orientation, but surprisingly, not to anxiety. Balance/movement issues in GrI are likely due to VVS deficiencies. Additional mechanisms may account for other GrI symptoms. Better understanding of GrI's pathophysiological basis will be useful in informing the larger health-provider community about this condition.
Contract functions in service exchange governance: evidence from logistics outsourcing

Abstract The logistics outsourcing literature emphasises relational governance mechanisms and has underplayed the role of formal contractual provisions. This paper empirically examines the multiple functions that contracts perform in the governance of service exchanges. Codification, safeguarding, coordination and adaptation functions are linked to contract specification schedules, payment mechanisms, (early) termination rights, performance review and communication provisions, service variations clauses and renegotiation provisions. Contracts may also embody exchange- or partner-specific learning, albeit to a limited extent. Overall, the empirical findings lend support to the functional view of contracting. The functionality of contracts extends beyond safeguarding against opportunism and financial losses. In addition to offering economic and legal safeguards, contracts are used to coordinate and adapt service exchanges in the face of complexity and uncertainty.
Study on Modeling and Simulation of SVCs in Wind Farms Based on PSS/E Software

Simulation and modeling of state var compensators(SVCs) in wind farms are important for integration of large-scale wind power into a local grid. Standard models of reactive dynamic compensation devices in PSS/E software were introduced in detail in the paper, and user-defined modeling methods and skills of SVC controller were summarized. Based on an actual wind farm in northern Hebei, a user-defined model of SVC controllers with constant voltage or reactive power control objectives was established for typical wind farms. Comparison of the simulation and field testing results shows that the user-defined model is accurate and sufficient. Besides, the PSS/E customized modeling method mentioned above is equally applicable to other FACTS' devices in power systems.
MESON: A Platform for Optimized Cross-Slice Communication on Edge Computing Infrastructures

In the dawn of the 6G era, evolving service ecosystems raise the need for cross-service interactions. Existing resource/service orchestration frameworks are oblivious to such cross-service interactions, since they tend to orchestrate services independent to each other. In this respect, we stress on the need for optimized crossservice communication, and more specifically, for optimized cross-slice communication (CSC). To this end, we present a CSC orchestration platform, namely MESON, which fulfills all main CSC requirements, such as the discovery of CSC-enabled services, the selection of the most suitable (edge) computing infrastructure, and also the establishment and configuration of CSC in a secure and policy-compliant manner. MESON has been designed and built as an extension of the ETSI NFV MANO framework. Relying on MESON as a proof-of-concept for CSC, we present evaluation results from various performance and scalability tests, and further uncover significant gains from optimized CSC in relation to video streaming and Industry 4.0 use cases.
Examination of Amorphous Calcium Carbonate on the Inflammatory and Muscle Damage Response in Experienced Resistance Trained Individuals

The effect of 3 weeks of amorphous calcium carbonate (ACC) supplementation (2000 mg per day) was examined on the recovery response to resistance exercise. Thirty men were randomized into a supplement (ACC) or placebo (PL) group. Following supplementation, participants performed six sets of 10 repetitions in the bench press (BP) and incline BP exercises, using 80% of maximal strength. Participants returned 24 (T4) and 48 h (T5) later and performed six sets of the BP exercise. Significant decreases in the number of repetitions (p < 0.001), peak power (p < 0.001), and mean power (p = 0.009) were noted over time, but no significant interactions were observed (p > 0.05). Magnitude-based inference analysis (MBI) indicated that the change in repetitions was possibly beneficial for ACC at T4 and likely beneficial at T5. No significant interaction was noted for general soreness (p = 0.452), but a trend toward an interaction was observed in upper body soreness (p = 0.089). Confidence intervals for mean percent change scores indicated significant differences between the groups at T4 and T5, and MBI analysis indicated that ACC was very likely or likely to be beneficial for reducing soreness at those time points. In conclusion, ACC supplementation may have a potential beneficial effect in attenuating the decline in performance, which is possibly due to the carbonate component.
Disinformation Propagation Trend Analysis and Identification Based on Social Situation Analytics and Multilevel Attention Network

Digital disinformation, such as those occurring on online social networks (OSNs), can influence public opinion, create mistrust and division, and impact decision- and policy-making. In this study, we propose a disinformation diffusion trend analysis and identification method, which uses social situation analytics and a multilevel attention network. First, we present a division and feature representation approach of social user circle based on the content sequence (internal driving factor) and social contextual information (external driving factor) of users associated with disinformation. Second, disinformation content feature, crowd response feature, and time-series feature are represented using embedding layer and bidirectional long short-term memory neural networks (Bi-LSTMs). We also present an attention mechanism model based on multifeature fusion, which can dynamically adjust the weight of each feature. On this foundation, the fused features are fed into the multilayer perceptron to identify the propagation quantity trend. According to the experimental results of real-world OSNs and social situation metadata, we conclude that while disinformation occurs across OSN platforms, the disinformation is more likely to spread widely in the original OSN platform. We also identify four typical disinformation propagation trends based on propagation patterns and propagation peak times. Findings from our experiments demonstrate that our proposed approach accurately identifies and predicts the diffusion trend of disinformation, which can then be used to inform mitigation strategy.
Fourier phase retrieval algorithm based on deep denoiser network

Fourier phase recovery techniques focus on how to reconstruct object information from phaseless measurement. Generally, such model-based phase recovery algorithms are difficult to obtain high-quality reconstructions in the presence of noise interference. Hence, we proposed a phase retrieval algorithm with deep denoiser networks. Firstly, an optimization model is constructed for the phase retrieval problem, then the alternating direction method of multipliers method is used to solve optimization problem iteratively. Besides, a well-trained deep neural network act as plug-and-play denoiser to participate the process of algorithm. Our method combines the model information of traditional phase retrieval algorithm and the fitting ability of the deep neural network, experiments show that it can achieve higher reconstruction result in the face of noisy image, and the generalization ability is also improved compared to end-to-end method.
Estimation of Seaweed Biomass Based on Multispectral UAV in the Intertidal Zone of Gouqi Island

UAV remote sensing inversion is an efficient and accurate method for obtaining information on vegetation coverage, biomass and other parameters. It is widely used on forest, grassland and other terrestrial vegetation. However, it is rarely used on aquatic vegetation, especially in intertidal zones and other complex environments. Additionally, it is mainly used for inversion of coverage, and there have been few studies thus far on biomass assessment. In this paper, we applied multispectral UAV aerial photography data to evaluate the biomass of seaweed in an intertidal zone. During the ebb tide, UAV aerial photography and in situ sampling data were collected in the study area. After optimizing the spectral index and performing a multiple linearity test, the spectral parameters were selected as the input of the evaluation model. Combined with two machine learning algorithms, namely random forest (RF) and gradient boosting decision tree (GBDT), the biomasses of three species of seaweed (Ulva pertusa, Sargassum thunbergii and Sargassum fusiforme) in the intertidal zone were assessed. In addition, the input parameters of the machine learning algorithms were optimized by one-way ANOVA and Pearson’s correlation analysis. We propose a method to assess the biomass of intertidal seaweed based on multispectral UAV data combined with statistics and machine learning. The results show that the two machine learning algorithms have different accuracies in terms of biomass evaluation using multispectral images; the gradient boosting decision tree can evaluate the biomass of seaweed in the intertidal zone more accurately.
Coverage and Meta Distribution Analysis in Ultra-Dense Cellular Networks with Directional Antennas

This paper proposes a one-tier ultra-dense cellular network framework based on the characteristics of directional beamforming to explore the downlink signal-to-interference ratio (SIR) performance. The features of the proposed cellular network include: small base stations (SBSs) are equipped with directional antennas; the beam boresight directions of antennas are adaptively adjusted with the locations of users on the two-dimensional horizontal plane while the boresight directions are perfectly aligned with their associated users. In addition, an angle fading model, which follows from the exponential distribution, is developed to simulate the signals attenuation of interference links. The angle fading of the interference signals depends on the angle offset between the locations of users and the beam boresight directions of their interfering SBSs. With the assistance of stochastic geometry, the analytical expressions of coverage probability and average ergodic rate are derived by combining with the probability density function of angle offset variable. Then, the meta distribution of SIR is obtained to capture the performance changes of individual links for users. The numerical results indicate that the performance advantages of the proposed directional network obviously exceed that of the conventional isotropic antennas case. Monte-Carlo simulations validate the correctness of numerical results.
Sustained and Microenvironment-Accelerated Release of Minocycline from Alginate Injectable Hydrogel for Bacteria-Infected Wound Healing

During wound healing, bacterial infection is one of the main limiting factors for the desired efficiency. Wound dressing-mediated antibiotics therapies could overcome this problem to a great extent due to sustained drug release and controllable dose. Here, we designed a kind of alginate injectable hydrogel loaded with minocycline (SA@MC) as a dressing for staphylococcus aureus-infected wound healing. SA@MC hydrogel possessed good injectability and can be injected by syringes. MC participated in the gel formation, causing the microstructure change based on the morphology characterization. The element mapping and FT-IR spectra further confirmed the successful loading of MC in SA hydrogel. Interestingly, MC was released more efficiently in a weakly alkaline condition (pH 7–8) than in a weakly acidic condition (pH 4–6) from SA@MC injectable hydrogel, which means that there is an accelerated release to respond to the weakly alkaline wound microenvironment. Meanwhile, SA@MC injectable hydrogel had high biocompatibility and excellent antibacterial activity due to the sustained release of MC. Further, in vivo experiment results demonstrated that SA@MC injectable hydrogel promoted staphylococcus aureus-infected wound healing efficiently. In summary, the injectable composite hydrogel can serve as an ideal dressing to prevent bacterial infection and promote wound healing.
Screen-Printed Carbon Electrodes with Macroporous Copper Film for Enhanced Amperometric Sensing of Saccharides

A porous layer of copper was formed on the surface of screen-printed carbon electrodes via the colloidal crystal templating technique. An aqueous suspension of monodisperse polystyrene spheres of 500 nm particle diameter was drop-casted on the carbon tracks printed on the substrate made of alumina ceramic. After evaporation, the electrode was carefully dipped in copper plating solution for a certain time to achieve a sufficient penetration of solution within the polystyrene spheres. The metal was then electrodeposited galvanostatically over the self-assembled colloidal crystal. Finally, the polystyrene template was dissolved in toluene to expose the porous structure of copper deposit. The morphology of porous structures was investigated using scanning electron microscopy. Electroanalytical properties of porous copper film electrodes were evaluated in amperometric detection of selected saccharides, namely glucose, fructose, sucrose, and galactose. Using hydrodynamic amperometry in stirred alkaline solution, a current response at +0.6 V vs. Ag/AgCl was recorded after addition of the selected saccharide. These saccharides could be quantified in two linear ranges (0.2–1.0 μmol L−1 and 4.0–100 μmol L−1) with detection limits of 0.1 μmol L−1 glucose, 0.03 μmol L−1 fructose, and 0.05 μmol L−1 sucrose or galactose. In addition, analytical performance of porous copper electrodes was ascertained and compared to that of copper film screen-printed carbon electrodes, prepared ex-situ by the galvanostatic deposition of metal in the plating solution. After calculating the current densities with respect to the geometric area of working electrodes, the porous electrodes exhibited much higher sensitivity to changes in concentration of analytes, presumably due to the larger surface of the porous copper deposit. In the future, they could be incorporated in detectors of flow injection systems due to their long-term mechanical stability.