Miracle-dz/UniFAR-FTUs huggingface dataset:
On optimum impedance pattern for accurate wideband noise parameter characterization

At least four source impedances are required to characterize the noise parameters of a two‐port network. The accuracy of the noise parameters depends on the configuration of the employed source impedances (pattern). The configuration of a specified pattern, generated generally by an impedance tuner, changes with frequency, and as such, the accuracy is usually degraded in a wideband characterization. To realize a low‐error wideband noise characterization, the present article thoroughly investigates the method of choosing a four‐source impedance pattern. A Monte Carlo simulation‐based approach is proposed to obtain the desired impedance patterns. The measurement and simulation results show that the noise parameters are accurately extracted when an impedance pattern is configured by a source impedance located near the center of the Smith chart and three other impedances located as close to the edge as possible with interphase separations of at least 45°. While the interphase separations remain unchanged, the impedance pattern rotation around the center of the Smith chart does not affect the accuracy of the extracted noise parameters, as demonstrated analytically here. The resultant impedance pattern realizes a wideband characterization from f0 to 3.5f0 without using an impedance tuner. The obtained accuracy is comparable to methods employing a redundant number of source impedances.
Photoluminescence of Eu(III) Doped Double Perovskite Phosphor for Red LED Application

The luminescence property of Ba2CeNbO6 has been studying by varying Eu(III) concentration. Ba2CeNbO6 doped with trivalent ions of Eu has a monoclinic phase with P21/n space group. FTIR of Ba2CeNbO6 gives information that phosphor has a nano–size perovskite structure with an edge-connected Nb-O octahedral. Photoluminescence properties of Eu(III) doped Ba2CeNbO6 have been examined with excitation wavelength 275nm and 466 nm. Luminescence emission spectra exhibited three prominent peaks around 580 nm, 596 nm, and 610nm wavelength for Eu(III). Using xenon lamp as a source and having excitation wavelength 275 and 466nm, observing that the maximum light emission yielded in the region presenting a color-correlated temperature in the range of 1500 – 2900 K.
Least Squares Boosting Ensemble and Quantum-Behaved Particle Swarm Optimization for Predicting the Surface Roughness in Face Milling Process of Aluminum Material

Surface roughness is a significant factor in determining the product quality and highly impacts the production price. The ability to predict the surface roughness before production would save the time and resources of the process. This research investigated the performance of state-of-the-art machine learning and quantum behaved evolutionary computation methods in predicting the surface roughness of aluminum material in a face-milling machine. Quantum-behaved particle swarm optimization (QPSO) and least squares gradient boosting ensemble (LSBoost) were utilized to simulate numerous face milling experiments and have predicted the surface roughness values with high extent of accuracy. The algorithms have shown a superior prediction performance over genetics optimization algorithm (GA) and the classical particle swarm optimization (PSO) in terms of statistical performance indicators. The QPSO outperformed all the simulated algorithms with a root mean square error of RMSE = 2.17% and a coefficient of determination R2 = 0.95 that closely matches the actual surface roughness experimental values.
Bridging the gaps for business growth among Indian construction companies

PurposeSuccessful handling and delivery of projects requires commensurate growth in the business capabilities of construction companies. The current scenario of exponential infrastructure boom in India necessitates scaling up to meet the challenges of competitiveness. The objectives of this study are to (1) identify the enablers of sustainable business growth among Indian construction companies, (2) identify gaps in the deployment of the enablers in comparison to competitive successful international construction companies and (3) suggest strategic initiatives to top management of companies and policymakers for promoting business growth and industry competitiveness.Design/methodology/approachA detailed literature review first identifies an adapted framework for enablers of growth and growth performance of successful international construction companies on basis of industry trends. Thereafter, a questionnaire survey was administered on the leading construction companies in India to assess the deployment of enablers and gaps thereof. A total of 108 valid responses were obtained from top management executives of the companies and analysed through descriptive statistics and hypothesis testing.FindingsStudies indicate that anticipation of new demands and capabilities; business opportunity scanning and human resource skills and capabilities are among the most important enablers of growth. The role of leadership vision and focus on development of human resources is critical to competitiveness and growth. The successful international construction companies have delivered growth utilising their ability to deploy multiple strategies, diversification and new business opportunities. These are sparingly deployed by Indian companies.Research limitations/implicationsThe study is limited to the opinion and perceptions of the top management personnel of the construction companies.Practical implicationsHigh economic growth context offers a unique opportunity for domestic Indian construction companies to leverage. The valuable insights gained from this study provide hints to the top management of these companies to draw managerial implications for facing the challenges ahead and delivering projects in the dynamic and hyper-competitive construction industry. The policymakers on their part are responsible to support and promote initiatives for sustainable growth.Originality/valueThe study suggests business growth enablers to construction companies in India to improve their international competitiveness.
Characterization of V-type asteroids orbiting in the middle and outer main belt

We present new spectral observations using ground-based telescopes of 23 putative V-type asteroids, selected according to colour surveys in the visible from the Moving Objects Catalogue of the Sloan Digital Sky Survey and near-infrared from the Moving Objects VISTA catalogue. 10 asteroids are orbiting in the middle main belt, while five in the outer part of the main asteroid belt. For the observed asteroids, we assign a taxonomical classification and confirm the basaltic nature for 16 of them. The high-quality spectra in the UV range, obtained with the X-Shooter spectrograph at ESO, allowed the identification of the Fe2+ forbidden transition of pyroxene for 10 asteroids. This band is centred at 506.5 nm, and it is diagnostic of the Ca-content in the pyroxene form. We determined a low Fe-content composition for asteroids (2452) Lyot, (5758) Brunini, (7675) Gorizia, (9197) Endo, (22308) 1990 UO4, (36118) 1999 RE135, (66905) 1999 VC160, and (189597) 2000 WG119, and a composition more rich in Fe for asteroids (75661) 2000 AB79 and (93620) 2000 UQ70. We also present a dynamical investigation of V-type asteroids in the middle and outer main belt. The principal finding of these simulations is that the middle and outer V-types are more likely to be associated with some families, which were considered as possibly originated from the break up of a partially or totally differentiated parent body by diverse studies. This reinforces the hypothesis that the identified V-type in the region were not originated from (4) Vesta and that the number of differentiated objects in the middle and outer main belt must have been much larger than previously assumed.
Evolution of convective characteristics during tropical cyclogenesis

Four idealized, high‐resolution (500 m horizontal grid spacing), numerical simulations are used to investigate the evolution of convective structures during tropical cyclogenesis. The simulations all begin with a weak initial axisymmetric cloud‐free vortex in a quiescent environment, but differ in the moisture level of the initial sounding and whether or not ice microphysical processes are considered. Irrespective of experimental setup, there is only a short period where shallow or congestus clouds dominate. The shallow cloud phase is slightly extended with the drier initial environmental sounding. The composite structure of the convective elements sampled changes markedly throughout the genesis period. For much of the genesis phase, vertical profiles of the mean convective cell show significant amounts of anticyclonic vorticity produced in cells in the inner core. Towards the end of the genesis phase, there is a large increase in the production of cyclonic vertical vorticity in inner‐core convection, and cyclonic vorticity becomes dominant at low‐mid levels. The evolution from roughly equal strength vertical profiles of cyclonic/anticyclonic vorticity at low‐mid levels to profiles where cyclonic vorticity dominates occurs at relatively low system wind speeds (Vmax less than 10 m·s−1). This finding indicates a change in the structure of vortical convection prior to rapid intensification. In outer‐core convection, there are roughly equal strength vertical vorticity dipoles produced throughout the genesis period.
Supervision/Coaching in der Lehrer*innenbildung: Einblicke in die Inanspruchnahme aus psychometrischer und hermeneutisch-rekonstruktiver Perspektive

Die Inanspruchnahme von Supervsision/Coaching dient in vielen Berufsfeldern als Moglichkeit der Professionalierung, z.B. auch in der Lehrer*innenausbildung. In der vorliegen Studie wird die Intention von Junglehrer*innen unstersucht, in ihrem Berufsleben Supervision/Coaching in Anspruch zu nehmen. Basierend auf der Theorie des geplanten Verhaltens (Theory of planned Bevaviour) wurde ein reliaber und valider Fragebogen zu dieser Thematik entwickelt, der von 132 Leher*innen berbeitet wurde. Es zeigte sich, dass die Intention Supervison/Coaching in Anspruch zu nehmen in erster Linie von den Einstellungen und der (beruflichen) sozialen Norm der Proband*innen abhing. Die empfundene soziale Norm der Stichprobe war gering ausgepragt, hingegen waren die Einstellungen zur Supervision/zum Coachimg der Stichprobe positiv. Trotzdem war die Bereitschaft, an einer Supervison/einem Coaching teilzunehmen nur im durchschnittlichen Bereich verortet. Die statistischen Befunde der vorliegenden Untersuchung werden vor dem Hintergrund einer hermeneutisch-rekonstruktiven Perspektive diskutiert, insbesondere die beobachtete „Attitude-Intention-Gap“. Zudem wird das Verhaltnis Supervison/Coaching und Schule perspektivisch beleuchtet.
Novel Hierarchical Structure of MoS2/TiO2/Ti3C2Tx Composites for Dramatically Enhanced Electromagnetic Absorbing Properties

In order to prevent the microwave leakage and mutual interference, more and more microwave absorbing devices are added into the design of electronic products to ensure its routine operation. In this work, we have successfully prepared MoS2/TiO2/Ti3C2Tx hierarchical composites by one-pot hydrothermal method and focused on the relationship between structures and electromagnetic absorbing properties. Supported by comprehensive characterizations, MoS2 nanosheets were proved to be anchored on the surface and interlayer of Ti3C2Tx through a hydrothermal process. Additionally, TiO2 nanoparticles were obtained in situ. Due to these hierarchical structures, the MoS2/TiO2/Ti3C2Tx composites showed greatly enhanced microwave absorbing performance. The MoS2/TiO2/Ti3C2Tx composites exhibit a maximum reflection loss value of −33.5 dB at 10.24 GHz and the effective absorption bandwidth covers 3.1 GHz (13.9–17 GHz) at the thickness of 1.0 mm, implying the features of wide frequency and light weight. This work in the hierarchical structure MoS2/TiO2/Ti3C2Tx composites opens a promising door to the exploration of constructing extraordinary electromagnetic wave absorbents.
Observations on the Distribution and Status of Selected Nebraska Mammals

Information on the distribution and current status of 25 species or subspecies of mammals occurring in Nebraska are presented. The species covered include one shrew, an armadillo, eight bats, 10 rodents (including two subspecies of one species), three carnivores, and one artiodactyl. Distributional information reported includes the first state record for one species (Sorex nanus) and new county records for 18 species. In Nebraska, we know that mammals are shifting their geographic ranges with some extending populations into the state, whereas others are expanding their geographic ranges within the state. The current status of six additional mammalian taxa in Nebraska is documented, providing knowledge important to the conservation of these species during this time of shifting environmental conditions. The concern is that some mammals have suffered population declines since the 1940s and may have a contracting geographic range as well in the state. These species would be endangered and could be lost to the mammalian fauna of the state. Extensive data on reproduction in these mammals are presented and the taxonomy of species is updated from the 1964 Mammals of Nebraska by Jones.
Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey

Background: In the development of artificial intelligence in ophthalmology, the ophthalmic AI-related recognition issues are prominent, but there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. This survey aims to assess medical workers’ and other professional technicians’ familiarity with, attitudes toward, and concerns about AI in ophthalmology.Methods: An electronic questionnaire was designed through the app Questionnaire Star, and was sent to participants through WeChat, China’s version of Facebook or WhatsApp. The participation was voluntary and anonymous. The questionnaire consisted of four parts, namely the participant’s background, their basic understanding of AI, their attitudes toward AI, and their concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form.Results: A total of 562 participants completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 1/3 of the participants understood AI and ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that AI in ophthalmology would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with AI in ophthalmology application experiences (30.6%), above 70% of participants held a full acceptance attitude toward AI in ophthalmology. The participants expressed medical ethics concerns about AI in ophthalmology. And among the participants who understood AI in ophthalmology, almost all the people said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field.Conclusions: The survey results revealed that the medical workers had a higher understanding level of AI in ophthalmology than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI but generally had a relatively high acceptance level of AI in ophthalmology, and there was a need to strengthen research into medical ethics issues of the field.
Influence of Biochar Derived Nitrogen on Cadmium Removal by Ryegrass in a Contaminated Soil

Little is known about the effect of nitrogen (N) application via biochar on the removal of trace elements by crops, and the effects with chemical fertilizers are inconsistent. We determined, from a previous study, the influence of increased N addition via biochars produced from switchgrass (SGB) and poultry litter (PLB) on cadmium (Cd) removal by ryegrass. The biochar rates of 0, 0.5, 1, 2, and 4% w/w were applied to a Cd-contaminated soil before seeding in a potting experiment with a complete randomized block design (CRBD). Ryegrass yield and N and Cd removed by harvest were strongly related (p < 0.05). The ryegrass yields increased up to 1% of PLB, and Cd removal was also the highest at 1% of PLB. The biomass of ryegrass roots increased with Cd accumulation (p < 0.05). Overall, the Cd transfer factor (TF) from ryegrass roots to shoots increased when up to 206 ± 38 kg N ha−1 was removed in ryegrass shoots (p < 0.0001). The application of PLB up to 1% might be a viable option since it is a practical rate for handling operations requiring less volume of material than SGB. Additionally, the Cd concentration in the aboveground forage remained acceptable for grazing cattle. Future studies are encouraged to evaluate different sources of N fertilizers affecting Cd uptake on cash crops.
Multi-class Classification Method of Support Vector Machine Based on Error Correction Coding

In the space radiation environment, there will be many errors in the multi-classification results of support vector machine which caused by single event flipping , the ability of correcting classification errors through error correction coding is studied in this paper, results of simulation confirm that error correction coding can increase the accuracy ,which is beneficial for anti-single event flip.
Learning to Drive Like Human Beings: A Method Based on Deep Reinforcement Learning

In this paper, a new framework for path tracking is proposed through learning to drive like human beings. Firstly, the imitation algorithm (behavior cloning) is adopted to initialize the deep reinforcement learning (DRL) algorithm through learning the professional drivers’ experience. Secondly, a continuous, deterministic, model free deep reinforcement learning algorithm is adopted to optimize our DRL model on line through trial and error. By combining behavior cloning and deep reinforcement learning algorithms, the DRL model can learn an effective policy quickly for path tracking using some easy-to-measure vehicle state parameters and environment information as inputs. Actor-Critic structure is adopted in the DRL algorithm. In order to speed up the convergence rate of the DRL model and improve the learning effect, we propose a dual actor networks structure for the two different action outputs (steering wheel angle and vehicle speed), and a chief critic network is built to guide the updating process of dual actor networks at the same time. Based on this dual actor networks structure, we can pick out some more important state information as state inputs for different action outputs. Besides, a kind of reward mechanism is also presented for autonomous driving. Finally, simulation training and experiment test are carried out, and the results confirm that the framework proposed in this paper is more than data efficient than the original algorithm, and the trained DRL model can track the reference path with accuracy and has the generalization ability for different roads.
Distributed static output feedback control for interconnected systems in finite‐frequency domain

Funding information National Natural Science Foundation of China, Grant/Award Number: 61673218 Abstract This paper aims at designing a distributed static output feedback (DSOF) controller for the interconnected system in finite-frequency domain. Motivated by the fact that the signal transmitting process is usually affected by surrounding environments, the interconnection communication between subsystems are assumed to be non-ideal. By introducing some dilated multipliers into the extended condition that guarantees the well-posedness, stability and finite-frequency ∞ performance of non-ideally interconnected systems, a new equivalent condition is derived, which is more effective for parameterizing the DSOF controller. A two-stage approach is then developed for constructing a DSOF controller: design an initial distributed full information (DFI) controller first and then derive a desired DSOF from the DFI controller. Moreover, two iterative linear matrix inequality based algorithms are proposed to improve the solvability of the DFI controller and DSOF controller design problems. Finally, an example is given to show the effectiveness of the proposed two-stage DSOF controller design method.
The fifty most cited publications in shoulder arthroplasty research

Introduction Frequency of citation provides one quantitative metric of the impact that an article has on a given field. The purpose of this study was to evaluate characteristics of the 50 most cited publications on shoulder arthroplasty. Methods The Web of Science database was used to determine the 50 most frequently cited shoulder arthroplasty articles. Articles were evaluated for several factors including type of arthroplasty, citation frequency and rate, source journal, country of origin, study type, and level of evidence. Results The most common countries of origin were the United States (60%) followed by France (24%) and Switzerland (6%). A total of 27 (54%) articles included anatomic total shoulder arthroplasty (TSA), 18 (36%) included reverse total shoulder arthroplasty (RTSA), and 15 (30%) included hemiarthroplasty. Articles including RTSA had the greatest number of citations compared to those on TSA (p = 0.037) and hemiarthroplasty (p = 0.035). Citations per year were also greatest with RTSA compared to TSA and hemiarthroplasty (p ≤ 0.001). Discussion This citation analysis includes many of the landmark studies that shaped, and continue to impact, the field of shoulder arthroplasty. This list provides a group of influential articles that provide a foundation for future research in shoulder arthroplasty.
Emphasising spatial structure in geosocial media data using spatial amplifier filtering

In this article, a new method called spatial amplifier filtering is proposed. The presented method is related to Moran eigenvector filtering and allows the accentuation of spatial structures in heterogeneous data sets. The spatial amplifier filtering technique is based on the inclusion of certain eigenvectors of a spatial weights matrix into a regression model. The application of this method can be seen as a pre-processing step prior to subsequent analyses, and to separate different types of spatially correlated components in a data set. For this purpose, three different types of the so-called spatial amplifiers are proposed, each consisting of different subsets of eigenvectors of the weights matrix. These amplifiers can either emphasise the positive or negative spatial autocorrelation, or spatial structuring in general. In this way, it is possible to make desired spatial structures more visible, especially in spatially highly mixed data sets, whereby the focus here is on geosocial media data. In the empirical part of the article, it is first shown why georeferenced social media data are difficult to handle from a spatial analysis perspective, motivating the need for the method proposed. Subsequently, the technique of amplifier filtering is applied to two data sets: a census data set from Brazil and Twitter data from London. The results obtained show that the method is capable of strengthening existing spatial structures and mitigating potentially disturbing spatial randomness patterns and other nuisances. This facilitates the interpretation especially of the Twitter data used. While the analysis of the unfiltered Twitter data with established methods reveals little information about possible spatial structures in the tweets, the filtered data offer a much clearer picture with distinguishable clusters. In addition, the method also provides insights into the internal irregularity of spatial clusters and thus complements the toolbox for investigating spatial heterogeneity.