Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comprehensive RF Characterization and Modeling Methodology for the 5nm Technology Node FinFETs

This paper aims to provide insights into the thermal, analog, and RF attributes, as well as a novel modeling methodology, for the FinFET at the industry standard 5nm CMOS technology node. Thermal characterization shows that for a 165K change in temperature, the Sub-threshold Slope (SS) and threshold voltage vary by 69 % and ~70 mV, respectively. At room temperature, a single gate contacted n-FinFET RF device exhibits a cutoff and maximum oscillation frequency of ~100 GHz and ~170 GHz, respectively. Analog and RF Figures of Merit (FoMs) for 5 nm technology at a device level and their temperature sensitivity are also reported. The industry standard BSIM-CMG model is modified to capture the impact of self-heating (SH) and parasitics. The SH model is based on measured data, and the modeling approach renders it independent of other model parameters. To the authors’ knowledge, an iteration free approach to develop a model-card for RF applications is explained for the very first time. Excellent agreement between the measured data and the model indicates that our methodology is accurate and can be used for faster PDK development.
A new stepsize change technique for Adams methods

Abstract In this paper a new technique for stepsize changing in the numerical solution of Initial Value Problems for ODEs by means of Adams type methods is considered. The computational cost of the new technique is equivalent to those of the well known interpolation technique (IT). It is seen that the new technique has better stability properties than the IT and moreover, its leading error term is smaller. These facts imply that the new technique can outperform the IT.
Rapid Viscosity Measurement Using Arbitrary Frequency Magnetic Particle Spectrometer

Magnetic particle spectrometer (MPS) is the device for characterizing the properties of magnetic nanoparticle (MNP) suspensions, such as viscosity, temperature, and concentration. Specifically, in viscosity measurement, MPS usually works at one or several fixed frequencies. It is challenging to find the appropriate frequency for viscosity measurement of different MNP suspensions. The frequency parameter can be introduced into the measurement method to improve the measurement accuracy. Here, we developed an arbitrary frequency MPS to measure the harmonic amplitudes of the magnetization signals of MNPs, which were generated at various frequencies. A method of measuring the viscosity of MNP suspensions by harmonic ratios at different frequencies was proposed. The viscosity measurement time used in the experiment is 1 s, and the shortest measurement time available is 0.2 s. Experimental results show that the arbitrary frequency MPS can measure the viscosity of samples ranging from 0.77 mPa $\cdot \text{s}$ to 3.87 mPa $\cdot \text{s}$ , and the average measurement deviation is 2.7%. The method was validated using plasma samples from normal rabbits and high-fat diet (HFD) rabbits. Normal rabbit measurements differed from the reference by less than 4.5%, and the plasma viscosity of normal and HFD rabbits could be clearly distinguished.
Characterization of woven fabric drape based on neural networks

Previous research on fabric drape has not provided an objective and comprehensive characterization of drape characteristics. In light of this, we proposed an approach that utilizes a neural network-based framework for characterizing the umbrella drape of woven fabrics. Fabric drapes with the same macro-level mechanical characteristics can be categorized together, thereby establishing objective classification criteria. Our method involved feature extraction and classification from drape images/point clouds via neural networks, namely ResNet18 and the deep graph convolutional neural network (DGCNN). We assessed the effectiveness of both networks through supervised learning and selected the best candidate to distinguish/retrieve drape styles from unlabeled data. Moreover, a sketch down-sampling (SDS) tailored to accurately represent point clouds of umbrella-shaped drapes was devised. In all, 5160 drape meshes were collected by RGB-D cameras and GeomagicTM. Two neural networks were trained for 30 epochs using stochastic gradient descent with a momentum of 0.9. The learning rate was set to 0.1 for ResNet18 and 0.001 for the DGCNN. Experimental results demonstrated that the DGCNN coupled with the SDS method was the optimal feature extraction solution for woven fabric drapes, given that the accuracy reached 97% with the coefficient of variation of 7%. Therefore, our approach offered an objective and precise quantification of fabric drape, which provided a possible downstream application for searching fabrics based on drape similarity.
Effect of polarization force on head-on collision between multi-solitons in dusty plasma

Head-on collision among dust acoustic (DA) multi-solitons in a dusty plasma with ions featuring non-Maxwellian hybrid distribution under the effect of the polarization force is investigated. The presence of the non-Maxwellian ions leads to eloquent modifications in the polarization force. Specifically, an increase in the superthermality index of ions (via κi) and nonthermal parameter (via α) diminishes the polarization parameter. By employing the extended Poincare-Lighthill-Kuo method, two sided KdV equations are derived. The Hirota direct method is used to obtain multi-soliton solutions for each KdV equation, and all of them move along the same direction where the fastest moving soliton eventually overtakes the others. The expressions for collisional phase shifts after head-on collision of two, four, and six-(DA) solitons are derived under the influence of polarization force. It is found that the effect of polarization force and the presence of non-Maxwellian ions have an emphatic influence on the phase .
Omnidirectional Depth Estimation With Hierarchical Deep Network for Multi-Fisheye Navigation Systems

Multi-fisheye System has the advantages of sufficient overlap and the ability to capture a complete 360° scene, which is beneficial for the omnidirectional depth estimation task. However, due to the severe distortion of the fisheye images, it is hard for such systems to extract and match features to predict an accurate depth. In this work, on the basis of a multi-fisheye system, we present a novel end-to-end deep learning architecture for omnidirectional depth estimation: 1) to capture the reliable features of the distorted fisheye image, a multi-scale feature extraction and aggregation module is improved, which can adaptively obtain the global context information to represent the features; 2) to leverage more aligned features, especially those in the overlap between multi-fisheye images, we construct a fusion cost volume to combine similarity and semantic information, which can enhance the feature discriminability; and 3) to refine the omnidirectional depth map efficiently, a cascaded cost regularization architecture is proposed. Instead of several costly 3D convolutions, the 3D BSConv based on intra-kernel correlations is introduced to regularize the cost. The proposed method can incrementally predict the depth map from coarse to fine, and reduce the network computational complexity significantly. The experiments in several public indoor and outdoor synthetic datasets demonstrate that the proposed method outperforms some state-of-the-art methods in terms of a synthesis of accuracy and speed, with fewer model parameters.
Pricing European options on regime-switching assets: a comparative study of Monte Carlo and finite-difference approaches

A numerical comparison of the Monte Carlo (MC) simulation and the finite-difference method for pricing European options under a regime-switching framework is presented in this paper. We consider pricing options on stocks having two to four volatility regimes. Numerical results show that the MC simulation outperforms the Crank–Nicolson (CN) finite-difference method in both the low-frequency case and the high-frequency case. Even though both methods have linear growth, as the number of regimes increases, the computational time of CN grows much faster than that of MC. In addition, for the two-state case, we propose a much faster simulation algorithm whose computational time is almost independent of the switching frequency. We also investigate the performances of two variance-reduction techniques: antithetic variates and control variates, to further improve the efficiency of the simulation. doi:10.1017/S1446181117000335
Ordinal Factor Analysis of Graded-Preference Questionnaire Data

We introduce a new comparative response format, suitable for assessing personality and similar constructs. In this “graded-block” format, items measuring different constructs are first organized in blocks of 2 or more; then, pairs are formed from items within blocks. The pairs are presented 1 at a time to enable respondents expressing the extent of preference for 1 item or the other using several graded categories. We model such data using confirmatory factor analysis (CFA) for ordinal outcomes. We derive Fisher information matrices for the graded pairs, and supply R code to enable computation of standard errors of trait scores. An empirical example illustrates the approach in low-stakes personality assessments and shows that similar results are obtained when using graded blocks of size 3 and a standard Likert format. However, graded-block designs might be superior when insufficient differentiation between items is expected (due to acquiescence, halo, or social desirability).
Inapproximability Reductions and Integrality Gaps

In this thesis we prove intractability results for several well studied problems in combinatorial optimization. Closest Vector Problem with Pre-processing (CVPP): We show that the pre-processing version of the well known Closest Vector Problem is hard to approximate to an almost polynomial factor (2 1− ) unless NP is in quasi polynomial time. The approximability of CVPP is closely related to the security of lattice based cryptosystems. Pricing Loss Leaders: We show hardness of approximation results for the problem of maximizing profit from buyers with single minded valuations where each buyer is interested in bundles of at most k items, and the items are allowed to have negative prices (“Loss Leaders”). For k = 2, we show that assuming the Unique Games Conjecture, it is hard to approximate the profit to any constant factor. For k ≥ 2, we show the same result assuming P 6= NP . Integrality gaps: We show Semi-Definite Programming (SDP) integrality gaps for Unique Games and 2-to-1 Games. Inapproximability results for these problems imply inapproximability results for many fundamental optimization problems. For the first problem, we show “approximate” integrality gaps for super constant rounds of the powerful Lasserre hierarchy. For the second problem we show integrality gaps for the basic SDP relaxation with perfect completeness.
Ultra culture-ultra reality: a content analysis of YouTube depictions of ultra endurance sport and comparisons to scientific literature

Introduction Interest in ultra endurance sport (UES) is increasing, with relevant events growing in popularity. However, these activities may encompass more complex characteristics and demands that do not correspond to scientifically validated correlations between physical activity and improved health. It is unknown whether high volume training for UES can have adverse implications, although certain sociocultural aspects of western society, such as an emphasis on autonomy and self-directed success, may encourage participation as a representation of personal achievement. As media depictions of UES can be highly influential, we aimed to explore prominent messages to better comprehend the values and aspirations of established and aspiring ultra endurance athletes (UEA). Methods Using qualitative, conventional content analysis techniques, we evaluated n = 15 popular YouTube videos on various UES to synthesize the most common themes. A YouTube search was conducted, and videos were selected based on sport and relevance. Subsequently, videos were analyzed and coded to discern the most frequently repeated themes. Results Five recurring themes were identified: discussion of the mental aspects of UES participation; the adoption of folk-tale storytelling; dietary habits of UEA; a focus on pain and suffering; the use of words associated with mental illness as a colloquial descriptor of UES/UEA. Discussion YouTube depictions of UES participation appear to accentuate suffering and co-occurring phenomena as attractive qualities. These resonate with sociocultural ideologies in western contexts, which emphasize fitness and personal success, but appear inconsistent with evidence around potentially adverse health-related implications of UES. Conclusion Discrepancies between popular portrayals of UES and scientific evidence suggest a need for greater community education and information sharing about sport-specific risk factors for physical and mental health conditions and appropriate training protocols. Further research is also required to better define the relationship between motivations for UES participation and overall health using interdisciplinary approaches.
Termination of Priority Rewriting - Extended version

Introducing priorities on rules increases the expressive power of rewriting and helps to limit computations. Priority rewriting is used as a com- putation model for the functional paradigm. Termination of priority rewriting then warrants that programs give a result. We describe in this paper an induc- tive proof method for termination of priority rewriting, lying on an inductive mechanism on the termination property. It works by generating proof trees, using abstraction and narrowing. As it speciﬁcally handles priorities on the rules, our technique allows proving termination of rewrite systems that would diverge without priorities.
On multifield inflation, adiabaticity and the speed of sound of the curvature perturbations

In this thesis we study some aspects of the very early Universe. We focus on the period of inflation, and show how the presence of many fields during this period can affect its low energy description. We focus on the predictions for the two and three point correlation functions of the curvature perturbations, in the case in which apart from the inflaton field there is a very heavy isocurvature field participating in the dynamics. We also treat briefly the case in which the isocurvature field is light, in particular applied to the case of so-called natural inflation.
Impact of the peripheral blood inflammatory indices and modified nomogram-revised risk index on survival of Extranodal Nasal-Type Natural Killer/T-Cell lymphoma

BACKGROUND: At present, peripheral blood markers are easily accessible information and clinically valuable prognostic indicators in extranodal nasal-type natural killer/T-cell lymphoma (ENKTCL). Nevertheless, the role of its comprehensive score in ENKTCL remains to be determined. OBJECTIVE: Therefore, this study aimed to investigate the prognostic effect of the peripheral inflammation score on ENKTCL. METHODS: The retrospective study included 183 patients with ENKTCL. Univariate Cox regression analyses and least absolute shrinkage and selection operator (LASSO) Cox regression were used to construct the inflammation-related prognostic index named Risk. Univariate and multivariate Cox regression analyses and regression adjustment with propensity score matching (PSM) were used to evaluate the prognostic ability of risk. The performance of the modified nomogram-revised risk index (NRI) by integrating risk was evaluated with the area under the time-dependent receiver operating characteristic (ROC) curve (AUC), decision curve analysis (DCA), and integrated Brier score (IBS). RESULTS: The risk cut-off value, constructed by the lymphocyte count, platelet count, albumin level, LMR, and PNI, was -1.3486. Before PSM, multivariate analysis showed that risk was significantly associated with OS (HR = 2.577, 95% CI = 1.614–4.114, P< 0.001) and PFS (HR = 2.679, 95% CI = 1.744–4.114, P< 0.001). After PSM adjustment, risk was still an independent factor for OS (HR = 2.829, 95% CI = 1.601–5.001, P< 0.001) and PFS (HR = 2.877, 95% CI = 1.735–4.770, P< 0.001). With the NRI, the modified NRI by integrating risk increased the AUC and clinical net benefit and decreased the IBS. CONCLUSIONS: Risk is an easily accessible and inexpensive indicator that may be used as a prognostic marker and could improve NRI predictive power in patients with ENKTCL.
Local Buckling Analysis of T-Section Webs with Closed-Form Solutions

This paper reports on approaches to estimate the critical buckling loads of thin-walled T-sections with closed-form solutions. We first develop a model using energy conservation approach under the assumption that there is no correlation between the restraint coefficient and buckling half-wavelength. Secondly, we propose a numerical approach to estimate the critical buckling conditions under the more realistic torsional stiffener constraint condition. A dimensionless parameter correlated with constraint conditions is introduced through finite element (FE) analysis and data fitting technique in the numerical approach. The critical buckling coefficient and loads can be expressed as explicit functions of the dimensionless parameter. The proposed numerical approach demonstrates higher accuracy than the approach under noncorrelation assumption. Due to the explicit expression of critical buckling loads, the numerical approach presented here can be easily used in the design, analysis, and precision manufacture of T-section webs.
Comparative study of three satellite image time-series decomposition methods for vegetation change detection

ABSTRACT Satellite image time-series (SITS) methods have contributed notably to detection of global change over the last decades, for instance by tracking vegetation changes. Compared with multi-temporal change detection methods, temporally highly resolved SITS methods provide more information in a single analysis, for instance on the type and consistency of change. In particular, SITS decomposition methods show a great potential in extracting various components from non-stationary time series, which allows for an improved interpretation of the temporal variability. Even though many case studies have applied SITS decomposition methods, a systematic comparison of common algorithms is still missing. In this study, the seasonal trend loess (STL), breaks for additive season and trend (BFAST) and multi-resolution analysis-wavelet transform (MRA-WT) were explored in order to evaluate their performance in modelling, monitoring and detecting land-cover changes with pronounced seasonal variations from simulated normal difference vegetation index time series. The selected methods have all proven their ability to characterize the non-stationary vegetation dynamics along with different physical processes driving the vegetation dynamics. Our results indicated that BFAST is the most accurate method for the examined simulated dataset in terms of RMSE, whereas MRA-WT showed a great potential for the extraction of multi-level vegetation dynamics. Considering the computational efficiency, both STL and MRA-WT outperformed BFAST.
Medium band gap polymer based solution-processed high-κ composite gate dielectrics for ambipolar OFET

The authors present a novel ambipolar organic filed-effect transistors (OFETs) composed of a hybrid dielectric thin film of Ta2O5:PMMA nanocomposite material, and solution processed poly(selenophene, benzotriazole and dialkoxy substituted [1,2-b:4, 5-b′] dithiophene (P-SBTBDT)-based organic semiconducting material as the active layer of the device. We find that the Ta2O5:PMMA insulator shows n-type conduction character, and its combination with the p-type P-SBTBDT organic semiconductor leads to an ambipolar OFET device. Top-gated OFETs were fabricated on glass substrate consisting of interdigitated ITO electrodes. P-SBTBDT-based material was spin coated on the interdigitated ITO electrodes. Subsequently, a solution processed Ta2O5:PMMA nanocomposite material was spin coated, thereby creating the gate dielectric layer. Finally, as a gate metal, an aluminum layer was deposited by thermal evaporation. The fabricated OFETs exhibited an ambipolar performance with good air-stability, high field-induced current and relatively high electron and hole mobilities although Ta2O5:PMMA nanocomposite films have slightly higher leakage current compared to the pure Ta2O5 films. Dielectric properties of the devices with different ratios of Ta2O5:PMMA were also investigated. The dielectric constant varied between 3.6 and 5.3 at 100 Hz, depending on the Ta2O5:PMMA ratio.
Rigorous full-vectorial optical analysis of VCSEL using FDFD method

In this paper, the optical problem of the Vertical Cavity Surface Emitting Laser (VCSEL) is analyzed in details. Taking advantage of the VCSEL layer structure, Maxwell’s equation is discretized on uniform Yee grid, and the rigorous full vectorial Finite Difference Frequency Domain (FDFD) method was used to formulate and solve the complex eigenvalue problem. The full vectorial solver is well suited for the fundamental as well as the higher-order modes and includes different field polarization. The method is demonstrated for advanced VCSEL incorporating the surface reliefs and the oxide layer. In order to compare with the experimental structure, a superposition of the VCSEL modes is used to construct the Linearly Polarized (LP) mode.
Semileptonic B-Meson decays at Belle II

The Belle II experiment is the upgrade of the Belle experiment, performed at the SuperKEKB asymmetric electron-positron-collider, located in Tsukuba, Japan. With an design instantaneous luminosity of $8\cdot 10^{35}\rm{cm}^{-2}\rm{s}^{-1}$ a dataset of $50\ \rm{ab}^{-1}$ will be collected. The clean collision environment of the experiment and the large dataset yields the ability to perform high precision measurements of physics mediated by the weak force, such as semileptonic $B$-meson decays. Of special focus of this document are magnitudes of the CKM matrix elements $\rm{V_{\rm{ub}}}$ and $\rm{V_{\rm{cb}}}$ measured in $B\to D^{(\star)} l \nu$ and $B\to \pi l \nu$, where $l = e,\mu$, as well as the ratio of the branching fractions, $R_{D^{(\star)}} := \mathcal{B} (B\to D^{(\star)} \mu \nu) / \mathcal{B} (B\to D^{(\star)} e \nu) $ and $R_{\tau} := \mathcal{B} (B\to D^{(\star)} \tau\nu) / \mathcal{B} (B\to D^{(\star)} l \nu) $ , of lepton couplings in these decays. Some of these have shown persistent tension with the Standard Model and are therefore of primary interest towards a better understanding of the weak force carriers and potential new physics couplings.