Miracle-dz/UniFAR-FTUs huggingface dataset:
Microwave radiation absorption and Shubnikov: de Haas oscillations in semi-metal InAs/GaSb/AlSb composite quantum wells

Strong Shubnikov – de Haas (SdH) oscillations were observed in the derivative of microwave absorption (f = 10 GHz) in the InAs/GaSb/AlSb composite quantum wells (CQWs) using electron-paramagnetic-resonance spectroscopy at low temperatures (2.7–20 K) and in the magnetic field up to 14 kOe. CQWs were grown on the n-GaSb:Te(100) and n- InAs:Mn(100) substrates with various width of QWs by MOVPE. Predominance contribution of the bulk n-GaSb substrate in SdH oscillations was manifested. Two frequencies of the SdH oscillations were found from Fourier analysis, which is connected to warping of the Fermi surface of GaSb. Unusual angular indicatrix was observed in dependence on orientation of the samples in the magnetic field. Obtained results can be explained by inversion asymmetry, which is a feature of the substances with lack of inversion centres. For CQWs grown on n-InAs:Mn (ns = 1.1 × 1017 cm-3) substrate, only several SdH oscillations with higher period were observed. Taking into account isotropic Fermi surface of bulk InAs, we succeeded to extract a contribution of the 2D carriers of InAs QW ~ H⊥,where H⊥= HconstcosΘ, from bulk substrate oscillations using special spline interpolation from angular dependence of SdH oscillatory amplitudes in the angle range 0–90°. 2D electron concentration in the InAs QW ns ≈ 1 – 3 × 1011 cm-2 was evaluated from oscillatory period.
Artificial Intelligence Techniques Used to Extract Relevant Information from Complex Social Networks

Social networks constitute an almost endless source of social behavior information. In fact, sometimes the amount of information is so large that the task to extract meaningful information becomes impossible due to temporal constrictions. We developed an artificial-intelligence-based method that reduces the calculation time several orders of magnitude when conveniently trained. We exemplify the problem by extracting data freely available in a commonly used social network, Twitter, building up a complex network that describes the online activity patterns of society. These networks are composed of a huge number of nodes and an even larger number of connections, making extremely difficult to extract meaningful data that summarizes and/or describes behaviors. Each network is then rendered into an image and later analyzed using an AI method based on Convolutional Neural Networks to extract the structural information.
Method to determine attribute weights based on subjective and objective integrated

The multi-attribute decision-making problems is studyed,in which the information about attribute weights is completely unknown and the attribute values are numeric.Firstly,the shortcomings of two existed methods are analysed and a rule to estimate the rationality of methods for determining objective weight is set up.Secondly,a new method is proposed based on entropy of attributes,which can adjust the weight value and is more adaptable to the real problem.Furthermore,the subjective weight and the objective weight are integrated into general weight by trade-off coefficients,which can reflect both subjective factors and objective factors.Finally,an example demonstrates the practicability and validity of this approach.
Marxist sociology in East Berlin (1949–1989): A field-spatial analysis

The main objective of the paper is to identify the logic of the sociological field in the GDR, looking at how it was spatialized in the city of East Berlin. In this regard, I am less interested in providing an overview of the different research streams of the main sociologists operating in the scientific and academic institutes located in Berlin than in reconstructing some crucial dynamics at work there and highlighting their effects at the social and symbolic levels. The underlying idea is that, especially in East Berlin, the sociological knowledge produced was less homogeneous than it has been represented in the existing literature. Without negating the existence of shared aspects characterizing Marxist-Leninist sociology, also superimposed on the political elite, a field analysis enables us to see how the different positions and trajectories of GDR-sociologists had an impact on their approaches to theoretical, epistemological, and methodological questions, and on their understanding and uses of concepts deriving from both Marxist-Leninist and “bourgeois” sociology. In the analysis, I will first compare the social trajectories of two of my interview-partners as paradigmatic of two different sociological habitus depending on their different academic/political socialization, networks, and positions in the field. As a second step, I will present a sketch of the sociological field drawn from 63 curricula of sociologists active in East Berlin in an attempt to pinpoint, on a larger scale, the homologies between the social and symbolic spaces of the field. Thus, the underlying idea is to examine the intersection of the “quasi-structural properties” of the field with its “phenomenological aspects” concerning the “feel for the game. ” While the two understandings of field are interdependent, it is in the second one that the physical space as a localized social space played a crucial role in defining the material, social, and cultural constraints and opportunities actors faced which, in turn, influenced their practices and choices.
Early outcomes of “low-risk” patients undergoing lung resection assessed by cardiopulmonary exercise testing: Single-institution experience

Objective Cardiopulmonary exercise testing (CPET) is currently recommended for all patients undergoing lung resection with either respiratory comorbidities or functional limitations. The main parameter evaluated is oxygen consumption at peak (VO2peak). Patients with VO2peak above 20 ml/kg/min are classified as low risk surgical candidates. The aims of this study were to evaluate postoperative outcomes of low-risk patients, and to compare their outcomes with those of patients without pulmonary impairment at respiratory function testing. Methods Retrospective monocentric observational study was designed, evaluating outcomes of patients undergoing lung resection at San Paolo University Hospital, Milan, Italy, between January 2016 and November 2021, preoperatively assessed by CPET, according to 2009 ERS/ESTS guidelines. All low-risk patients undergoing any extent surgical lung resection for pulmonary nodules were enrolled. Postoperative major cardiopulmonary complications or death, occurring within 30 days from surgery, were assessed. A case-control study was nested, matching 1:1 for type of surgery the cohort population with control patients without functional respiratory impairment consecutively undergoing surgery at the same centre in the study period. Results A total of 80 patients were enrolled: 40 subjects were preoperatively assessed by CPET and deemed at low risk, whereas 40 subjects represented the control group. Among the first, 4 patients (10%) developed major cardiopulmonary complications, and 1 patient (2.5%) died within 30 days from surgery. In the control group, 2 patients (5%) developed complications and none of the patients (0%) died. The differences in morbidity and mortality rates did not reach statistically significance. Instead, age, weight, BMI, smoking history, COPD incidence, surgical approach, FEV1, Tiffenau, DLCO and length of hospital stay resulted significantly different between the two groups. At a case-by-case analysis, CPET revealed a pathological pattern in each complicated patient, in spite of VO2peak above target for safe surgery. Conclusions Postoperative outcomes of low-risk patients undergoing lung resections are comparable to those of patients without any pulmonary functional impairment; nonetheless the formers represent a dramatically different category of individuals from the latter and may harbour few patients with worse outcomes. CPET variables overall interpretation may add to the VO2peak in identifying higher risk patients, even in this subgroup.
An overall survival predictive nomogram to identify high-risk patients among locoregionally advanced nasopharyngeal carcinoma: Developed based on the SEER database and validated institutionally

Objective Locoregionally advanced nasopharyngeal carcinoma (LA-NPC) patients, even at the same stage, have different prognoses. We aim to construct a prognostic nomogram for predicting the overall survival (OS) to identify the high-risk LA-NPC patients. Materials and methods Histologically diagnosed WHO type II and type III LA-NPC patients in the Surveillance, Epidemiology, and End Results (SEER) database were enrolled as the training cohort (n= 421), and LA-NPC patients from Shantou University Medical College Cancer Hospital (SUMCCH) served as the external validation cohort (n= 763). Variables were determined in the training cohort through Cox regression to form a prognostic OS nomogram, which was verified in the validation cohort, and compared with traditional clinical staging using the concordance index (C-index), Kaplan–Meier curves, calibration curves and decision curve analysis (DCA). Patients with scores higher than the specific cut-off value determined by the nomogram were defined as high-risk patients. Subgroup analyses and high-risk group determinants were explored. Results Our nomogram had a higher C-index than the traditional clinical staging method (0.67 vs. 0.60, p<0.001). Good agreement between the nomogram-predicted and actual survival were shown in the calibration curves and DCA, indicating a clinical benefit of the nomogram. High-risk patients identified by our nomogram had worse prognosis than the other groups, with a 5-year overall survival (OS) of 60.4%. Elderly patients at advanced stage and without chemotherapy had a tendency for high risk than the other patients. Conclusions Our OS predictive nomogram for LA-NPC patients is reliable to identify high-risk patients.
Permitted Fe II emission in Seyfert 1 galaxies and QSOs. II. The excitation mechanism

The excitation of optical permitted Fe II emission in Seyfert 1 galaxies and certain QSOs is considered in light of recent spectrophotometric observations. The Fe II emission is too strong to be explained by recombination. Collisional excitation by itself does not appear capable of producing the observed intensity either. Resonance fluorescence can probably account for the emission, although almost complete conversion of the ultraviolet resonance-line photons to optical emission is required. This implies large optical depths in the resonance lines.Optically thin resonance-fluorescence and collisional excitation models fail to reproduce the observed relative intensities of the optical Fe II lines. Optically thick resonance-fluorescence calculations which allow for noncoherent scattering effects give much better matches to the observations. Opitcal depths in the resonance lines 500 or approx. =0.35 QSOs show detectable Fe II emission, suggesting that these QSOs represent a different class of objects than the Fe II Seyfert 1 galaxies and QSOs. « less
Radar HRRP Open Set Recognition Based on Extreme Value Distribution

Radar automatic target recognition (RATR) based on high-resolution range profile (HRRP) has attracted more attention in recent years. In fact, the actual application environment of RATR is open set environment rather than closed set environment. However, previous works mainly focus on closed set recognition, which classifies the known classes by dividing hyperplanes in the feature space, and it will cause classification errors in an open set environment. Therefore, open set recognition is proposed to solve this problem, which needs to determine a closed classification boundary for the identification of the known and unknown targets simultaneously. To accomplish this purpose, this article proposes and proves the extreme value boundary theorem, which demonstrates that the maximum distance from the known features to the cluster center follows the generalized extreme value distribution. According to the proposed theorem, the closed classification boundary of the cluster is easily determined to distinguish between the known and unknown classes. Finally, extensive experiments on measured HRRP data verify the validity of the proposed theorem and the effectiveness of the proposed method.
Plasma wave resonant detection of femtosecond pulsed terahertz radiation by a nanometer field-effect transistor

We report on the room-temperature, resonant detection of femtosecond pulsed terahertz radiation obtained by optical rectification in a ZnTe crystal. The detection was realized using a 250nm gate length GaAs∕AlGaAs heterostructure field-effect transistor. We show that physical mechanism of the detection is related to the plasma waves excited in the transistor channel. The detection is strongly enhanced by increasing the drain current and driving the transistor into the plasma wave instability region. Our results clearly show that plasma wave nanometer transistors can be efficient and fast detectors for terahertz spectroscopic imaging based on the femtosecond pulsed THz sources.
A Kind of Hybrid Particle Swarm Optimization Algorithm for Solving 0-1 Knapsack Problems

Aimed at the 0-1 knapsack problems,the article proposes a kind of hybrid intelligence algorithm combining with the adjusting strategy,the greedy algorithm and the binary particle swarm optimization algorithm.Results of numerical tests show that the algorithm can avoid precocious phenomena to a certain extent and it has higher rate of convergence.Therefore,the hybrid intelligence algorithm is effective to solve 0-1 knapsack problems.
Estimación en tiempo real de torque y velocidad en un motor trifásico.

Internal induction motor variables estimators are highly required in field applications [3]. They are the entrance to modern control techniques for induction machines. Even though there is a huge range of variables or parameters which can be estimated, load torque and rotor speed are prior in sensorless control techniques because most industrial applications require control of these variables. To estimate rotor speed is neccesary to estimate rotor and stator currents or fluxes (depending on the model used) as well. As consequence with an estimator is possible to know and control almost all the performance in an induction machine in sensorless way. One of the most known and used estimator is the Kalman filter and its extended version for parameter estimation, not only states in non-linear systems [10]. Theory regarding this estimator applied to induction machines is well known and authors have proposed different techniques and models [11, 12, 2] to approach. However, all the algorithms need stator voltages and currents measurements to work. Stator voltage measurements are used to calculate the states in the model and stator currents measurements are used to calculate the error between estimated and measured outputs in most of the models. All the estimation is based on the error mentioned above. To reduce computation requirements some authors have proposed alternative algorithms for Kalman estimation [13, 14], but they are usually restricted to particular problems or models. H1 filter is less known and there is no much information about real-problem implementations, but this filter was specifically developed for robustness. H1 filters are robust filters that minimizes the worst-case error (bounded peak error gain). Perturbations are assumed to be energy-bounded signals without specific statistics. H1 filters do not make assumptions about error statistics and are robust to uncertain in the model parameters or errors in covariance matrices tunning. This articule presents an estimation for both variables, speed and load torque by using a sixth order extended Kalman Filter and an extended H1 Filter. In the case of the H1 filter the cost function to be minimizated will be limited to rotor speed and load torque error estimation to reduce computation required. The space state model for the motor is writen as function of machine magnetic fluxes because it reduces significantly the number of non constant terms in the model and also reduces the number of computations perform by the DSP in real implementation.
Viscosity Approximation Methods for Strong Vector Equilibrium Problems and Fixed Point Problems

In this paper,we study the problem of finding a common element of the set of solutions of a strong vector equilibrium problem and the set of fixed points of a nonexpansive mapping in Hilbert space.We first give the auxiliary problem for the strong vector equilibrium problem and obtain some results of existence and uniqueness of solutions of the auxiliary problem under suitable conditions.Then,by virtue of these results,we propose a viscosity iterative scheme for finding a common element of the set of solutions of the strong vector equilibrium problem and the set of fixed points of the nonexpansive mapping.Furthermore,we prove that,under suitable conditions,the sequences generated by this iterative scheme converge strongly to a common element of the set of solutions of the strong vector equilibrium problem and the set of fixed points of the nonexpansive mapping.
Optimizing pharmacotherapy regimens in adult patients receiving extracorporeal membrane oxygenation: A narrative review for clinical pharmacists

Extracorporeal membrane oxygenation (ECMO) is a complex therapy aimed at providing mechanical support for patients with severe, life‐threating cardiac and/or respiratory failure. Research has demonstrated variability in pharmacokinetic changes in the critically ill patient population receiving ECMO. There is a need to understand the complexity of these pharmacokinetic changes to provide optimal pharmacotherapeutic regimens thereby maximizing effectiveness and mitigating harm. However, the number of pharmacokinetic studies in patients receiving ECMO remains small, and very few prospective studies have been published addressing optimal analgesic, sedative, or antimicrobial therapy. Anticoagulation is an additional important component of ECMO therapy but the preferred agent as well as dosing and monitoring strategy are unclear. The purpose of this narrative review is to discuss analgesia and sedation, antimicrobial, and anticoagulation management strategies in adult patients receiving ECMO.
Multidisciplinary education through faculty members’ conceptualisations of and experiences in engineering education

ABSTRACT Engineering education has become increasingly multidisciplinary in order to prepare future experts to transcend disciplinary boundaries and to co-construct solutions to solve grand challenges. However, faculty members’ perspectives and experiences have been largely ignored in the literature. To understand and support faculty members, the present study investigated faculty members’ conceptualisations of multi-, inter-, and transdisciplinary education. We conducted semi-structured interviews with 13 faculty members from engineering, business, art and design with varied experiences with multidisciplinary teaching, course design, and programme management. We found that while some faculty members conceptualised multidisciplinary education as an encompassing concept, most used disciplinary integration to distinguish multi-, inter-, and transdisciplinary education. However, their conceptualisations of the differences between multi-, inter-, and transdisciplinary education were nuanced. Summarising the perceived nuances in different aspects of course design, we propose a typology to demonstrate the variety of types in faculty members’ course design. By identifying the diversity and complexities of faculty members’ conceptualisations, this study attempts to help faculty members achieve an in-depth understanding of their conceptualisations and practices, as well as support engineering educators in designing courses with disciplinary integration.
Cooperative Lane-Change Motion Planning for Connected and Automated Vehicle Platoons in Multi-Lane Scenarios

Multi-vehicle motion planning (MVMP) has become an emerging paradigm in connected and automated vehicles (CAVs). The cooperative lane-change movements with the coexistence of platoons and CAVs are typical scenarios on the muti-lane roads. This paper proposes an optimal control framework with the advantages of completeness and universality for platoons and CAVs’ cooperative lane-change motion planning in different task scenarios. Two typical cooperative scenarios are designed for the subsequent study of optimal modeling. The platoons’ reconfiguration and original shape maintenance are considered to reflect the universality of moving objects and the diversity of cooperative tasks. Approximately geometric contour models, dynamic externally tangent rectangle and inflated rectangle, are utilized to describe the platoon’s profile. Analytical complete collision avoidance constraints among different motion objects are constructed effectively. Other necessary constraints and the weighted cost function that minimizes lane-change time and motion energy are comprehensively considered. The optimal control models are established for the desired scenarios. Moreover, a numerical solution method combined with the simultaneous direct collocation method based on the trapezoidal rule and the barrier function method is proposed to obtain the optimal schemes. Simulation and contrast experiments are conducted for two scenarios. The results indicate that the cost function’s weight coefficients and specific lane-change tasks influence the cooperative motion planning effects and verify that the proposed optimal control framework is of reasonability, effectiveness, and unification.
The research of lightweight method for the electric and electronic systems’ BIM model

In view of the problems of BIM model, low data transmission efficiency, cumbersome data conversion and poor BIM rendering, An optimized and improved method is proposed to realize the lightweight of electric &electronic systems’ BIM model. This method uses RevitAPI to generate a custom GLTF model, split and preprocess the overall model, use the optimized model simplification method to ensure the details of the model, generate the custom GLTF data format, complete the lightweight of BIM model. Taking the model in the electric &electronic systems’ project as an example, a high-speed railway station and components were selected for this experiment to verify and compare the proposed method. The results show that the lightweight method of BIM model effectively reduces the model data quantity, improves the real-time rendering efficiency and optimizes the loading effect.