Miracle-dz/UniFAR-FTUs huggingface dataset:
QuatNet: Quaternion-Based Head Pose Estimation With Multiregression Loss

Head pose estimation has attracted immense research interest recently, as its inherent information significantly improves the performance of face-related applications such as face alignment and face recognition. In this paper, we conduct an in-depth study of head pose estimation and present a multiregression loss function, an <inline-formula><tex-math notation="LaTeX">$L2$</tex-math></inline-formula> regression loss combined with an ordinal regression loss, to train a convolutional neural network (CNN) that is dedicated to estimating head poses from RGB images without depth information. The ordinal regression loss is utilized to address the nonstationary property observed as the facial features change with respect to different head pose angles and learn robust features. The <inline-formula><tex-math notation="LaTeX">$L2$</tex-math></inline-formula> regression loss leverages these features to provide precise angle predictions for input images. To avoid the ambiguity problem in the commonly used Euler angle representation, we further formulate the head pose estimation problem in quaternions. Our quaternion-based multiregression loss method achieves state-of-the-art performance on the AFLW2000, AFLW test set, and AFW datasets and is closing the gap with methods that utilize depth information on the BIWI dataset.
Combination of sepsis biomarkers may indicate an invasive fungal infection in haematological patients

Abstract Background: Invasive fungal infections are a major threat to a large cohort of immunocompromised patients, including patients with chemotherapy-associated neutropenia. Early differential diagnosis with bacterial infections is often complicated, which leads to a delay in empirical antifungal therapy and increases risk for adverse outcome. Accessibility and performance of specific fungal antigen and PCR-tests are still limited, while sepsis biomarkers are more broadly used in most settings currently. Methods: Haematological patients hospitalized to receive chemotherapy with proven or probable invasive fungal infection or microbiologically proven bacterial bloodstream infection were included in the study. C-reactive protein was assessed daily during the profound neutropenia period, while procalcitonin or presepsin were measured during the first 48 hours after the onset of febrile episode. Results: There were totally 64 patients included in the study, 53 with bacterial bloodstream infections and 11 with invasive fungal infections. Combination of CRP >120 with PCT <1.25 or presepsin <170 was shown to be a possible combined biomarker for invasive fungal infections in immunocompromised patients, with areas under the ROC-curves: 0.962 (95% CI 0.868 to 0.995) for PCT-based combination and 0.907 (95% CI 0.692 to 0.990) for presepsin-based combination.
A Market-Induced Mechanism for Stock Pinning

We propose a model to describe stock pinning on option expiration dates. We argue that if the open interest on a particular contract is unusually large, delta-hedging in aggregate by floor market-makers can impact the stock price and drive it to the strike price of the option. We derive a stochastic differential equation for the stock price which has a singular drift that accounts for the price-impact of delta-hedging. According to this model, the stock price has a finite probability of pinning at a strike. We calculate analytically and numerically this probability in terms of the volatility of the stock, the time-to-maturity, the open interest for the option under consideration and a 'price elasticity' constant that models price impact.
Feasibility of Unmanned Aerial Vehicle Optical Imagery for Early Detection and Severity Assessment of Late Blight in Potato

Assessment of disease incidence and severity at farm scale or in agronomic trials is frequently performed based on visual crop inspection, which is a labor intensive task prone to errors associated with its subjectivity. Therefore, alternative methods to relate disease incidence and severity with changes in crop traits are of great interest. Optical imagery in the visible and near-infrared (Vis-NIR) can potentially be used to detect changes in crop traits caused by pathogen development. Also, cameras on-board of Unmanned Aerial Vehicles (UAVs) have flexible data collection capabilities allowing adjustments considering the trade-off between data throughput and its resolution. However, studies focusing on the use of UAV imagery to describe changes in crop traits related to disease infection are still lacking. More specifically, evaluation of late blight (Phytophthora infestans) incidence in potato concerning early discrimination of different disease severity levels has not been extensively reported. In this article, the description of spectral changes related to the development of potato late blight under low disease severity levels is performed using sub-decimeter UAV optical imagery. The main objective was to evaluate the sensitivity of the data acquired regarding early changes in crop traits related to disease incidence. For that, UAV images were acquired on four dates during the growing season (from 37 to 78 days after planting), before and after late blight was detected in the field. The spectral variability observed in each date was summarized using Simplex Volume Maximization (SiVM), and its relationship with experimental treatments (different crop systems) and disease severity levels (evaluated by visual assessment) was determined based on pixel-wise log-likelihood ratio (LLR) calculation. Using this analytical framework it was possible to identify considerable spectral changes related to late blight incidence in different treatments and also to disease severity level as low as between 2.5 and 5.0% of affected leaf area. Comparison of disease incidence and spectral information acquired using UAV (with 4-5 cm of spatial resolution) and ground-based imagery (with 0.1-0.2 cm of spatial resolution) indicate that UAV data allowed identification of patterns comparable to those described by ground-based images, despite some differences concerning the distribution of affected areas detected within the sampling units and an attenuation in the signal measured. Finally, although aggregated information at sampling unit level provided discriminative potential for higher levels of disease development, focusing on spectral information related to disease occurrence increased the discriminative potential of the data acquired.
Phased-Array Radar System Simulator (PASIM): Development and Simulation Result Assessment

In this paper, a system-specific phased-array radar system simulator was developed, based on a time-domain modeling and simulation method, mainly for system performance evaluation of the future Spectrum-Efficient National Surveillance Radar (SENSR). The goal of the simulation study was to establish a complete data quality prediction method based on specific radar hardware and electronics designs. The distributed weather targets were modeled using a covariance matrix-based method. The data quality analysis was conducted using Next-Generation Radar (NEXRAD) Level-II data as a basis, in which the impact of various pulse compression waveforms and channel electronic instability on weather radar data quality was evaluated. Two typical weather scenarios were employed to assess the simulator’s performance, including a tornado case and a convective precipitation case. Also, modeling of some demonstration systems was evaluated, including a generic weather radar, a planar polarimetric phased-array radar, and a cylindrical polarimetric phased-array radar. Corresponding error statistics were provided to help multifunction phased-array radar (MPAR) designers perform trade-off studies.
The road to accuracy: machine-learning-accelerated silicon ab initio simulations.

Ab initio simulations are capable of providing detailed information of material behavior at the nanoscale. Simulating experimentally relevant situations is, however, often computationally intense. Using hybrid approaches between ab initio methods such as density functional theory (DFT) and machine learning, new models can be constructed which retain quantum accuracy while being computationally faster by several orders of magnitude. Two examples are discussed in this paper. The first is the computational search for low energy substitutional defect complexes in silicon. The second is the construction of deep learning potentials for ab initio-level molecular dynamics simulations. The latter is applied to reproduce the 0 K equation of state and high temperature thermal expansion of Si using the same model.
A moment expansion approach to option pricing

In this paper we present a new methodology for option pricing. The main idea consists of representing a generic probability distribution function (PDF) by an expansion around a given, simpler, PDF (typically a Gaussian function) by matching moments of increasing order. Because, as shown in the literature, the pricing of path-dependent European options can often be reduced to recursive (or nested) one-dimensional integral calculations, the moment expansion (ME) approach leads very quickly to excellent numerical solutions. In this paper, we present the basic ideas of the method and the relative applications to a variety of contracts, mainly: Asian, reverse cliquet and barrier options. A comparison with other numerical techniques is also presented.
Measuring teaching quality in several European countries

Teaching quality has been observed in large representative samples from Flanders (Belgium), Lower Saxony (Germany), the Slovak Republic, and The Netherlands. This study reveals that measures of “creating a safe and stimulating climate”, “clear and activating instruction”, and “teaching learning strategies” were reliable and fully or at least partially scalar equivalent across these countries. Flemish teachers score higher, on average, on measures related to creating a safe and stimulating learning climate than do teachers in Lower Saxony, the Slovak Republic, or The Netherlands. With regard to the provision of clear and activating instruction, no significant differences arose in average scores across the 4 countries. Dutch teachers scored significantly higher on teaching learning strategies than teachers in Flanders and Lower Saxony but did not differ significantly from teachers in the Slovak Republic. Flemish and Slovak teachers earned higher average scores on teaching learning strategies than teachers in Lower Saxony.
Some Characterizations for a Quaternion-Valued and Dual Variable Curve

Quaternions, which are found in many fields, have been studied for a long time. The interest in dual quaternions has also increased after real quaternions. Nagaraj and Bharathi developed the basic theories of these studies. The Serret–Frenet Formulae for dual quaternion-valued functions of one real variable are derived. In this paper, by making use of the results of some previous studies, helixes and harmonic curvature concepts in Q D 3 and Q D 4 are considered and a characterization for a dual harmonic curve to be a helix is given.
Evaluating the Effects of Image Texture Analysis on Plastic Greenhouse Segments via Recognition of the OSI-USI-ETA-CEI Pattern

Compared to multispectral or panchromatic bands, fusion imagery contains both the spectral content of the former and the spatial resolution of the latter. Even though the Estimation of Scale Parameter (ESP), the ESP 2 tool, and some segmentation evaluation methods have been introduced to simplify the choice of scale parameter (SP), shape, and compactness, many challenges remain, including obtaining the natural border of plastic greenhouses (PGs) from a GaoFen-2 (GF-2) fusion imagery, accelerating the progress of follow-up texture analysis, and accurately evaluating over-segmentation and under-segmentation of PG segments in geographic object-based image analysis. Considering the features of high-resolution images, the heterogeneity of fusion imagery was compressed using texture analysis before calculating the optimal scale parameter in ESP 2 in this study. As a result, we quantified the effects of image texture analysis, including increasing averaging operator size (AOS) and decreasing greyscale quantization level (GQL) on PG segments via recognition of a proposed Over-Segmentation Index (OSI)-Under-Segmentation Index (USI)-Error Index of Total Area (ETA)-Composite Error Index (CEI) pattern. The proposed pattern can be used to reasonably evaluate the quality of PG segments obtained from GF-2 fusion imagery and its derivative images, showing that appropriate texture analysis can effectively change the heterogeneity of a fusion image for better segmentation. The optimum setup of GQL and AOS are determined by comparing CEI and visual analysis.
Sensitivity of Landsat-8 OLI and TIRS Data to Foliar Properties of Early Stage Bark Beetle (Ips typographus, L.) Infestation

In this study, the early stage of European spruce bark beetle (Ips typographus, L.) infestation (so-called green attack) is investigated using Landsat-8 optical and thermal data. We conducted an extensive field survey in June and the beginning of July 2016, to collect field data measurements from several infested and healthy trees in the Bavarian Forest National Park (BFNP), Germany. In total, 157 trees were selected, and leaf traits (i.e. stomatal conductance, chlorophyll fluorescence, and water content) were measured. Three Landsat-8 images from May, July, and August 2016 were studied, representing an early stage, advanced stage, and post-infestation, respectively. Spectral vegetation indices (SVIs) sensitive to the measured traits were calculated from the optical domain (VIS, NIR, and SWIR), and canopy surface temperature (CST) was calculated from the thermal infrared band using the mono-window algorithm. The leaf traits were used to examine the impact of bark beetle infestation on the infested trees and to explore the link between these traits and remote sensing data (CST and SVIs). The differences between healthy and infested samples regarding measured leaf traits were assessed using Student’s t test. The relative importance of the CST and SVIs for estimating measured leaf traits was evaluated based on the variable importance in projection (VIP) obtained from the partial least squares regression (PLSR) analysis. A temporal comparison was then made for SVIs with a VIP > 1, including CST, using statistical significance tests. The clustering method using a principal components analysis (PCA) was used to examine visually how well the two groups of sample plots (healthy and infested) are separated in 2-D space based on principal component scores. Finally, linear regression (LR) was used to generate the leaf traits maps using the SVI that have highest VIP score and then used to produce a stress map for the study area. The results revealed that all measured leaf traits were significantly different (p < 0.05) between healthy versus infested samples. Moreover, the study showed that CST was superior to the SVIs in detecting subtle canopy changes due to bark beetle infestation for the three months considered in this study. The results showed that CST is an essential variable for estimating measured leaf traits with VIP > 1, improving the results of clustering when used with other SVIs. Likewise, the stress map produced by CST and leaf traits well presented the infestation areas at the green attacked stage. The new insight offered by this study is that the stress induced by the early stage of bark beetle infestation is more pronounced by Landsat-8 thermal bands than the SVIs calculated from its optical bands. The potential of CST in detecting the green attack stage would have positive implications for forest practice.
Observations About the Projective Tensor Product of Banach Spaces, Iii – LP [0, 1] ⊗ X, 1 < P < ∞

Let X be a complex Banach space and 1 < p < ∞. Then the projective tensor product L p [0, 1]⊗ X has the analytic Radon-Nikodym property (respectively, the near Radon-Nikodym property) if and only if X does. Also, L p[0, 1]⊗ X does not contain a copy of c 0 if and only if X does not contain a copy of c 0.
On a universal mechanism for long-range volatility correlations

We propose a general interpretation for long-range correlation effects in the activity and volatility of financial markets. This interpretation is based on the fact that the choice between 'active' and 'inactive' strategies is subordinated to random-walk-like processes. We numerically demonstrate our scenario in the framework of simplified market models, such as the Minority Game model with an inactive strategy. We show that real market data can be surprisingly well accounted for by these simple models.
An Extensible Search Engine Platform for Efficiency Research

Many widely used open source projects for full-text searching are available for industry and academic use. Although they have implemented plenty of optimized strategies and technologies to improve performance of specific phases during text searching, only a few of them have been well-designed to form a complete and extensible search engine platform. Especially for efficiency research, many previous works which utilize parallel mechanism in modern computer system, such like SIMD and GPU, can not be directly integrated in most existing open source projects since they were written in Java. To improve this, we expand NBLucene, which is written in C++, for efficiency research purpose. We build an extensible platform with application programming interfaces for users to implement algorithms and strategies readily. The complete platform consists of three typical components, namely web server, index server and document server. Each component is designed to be extensible so as to accommodate new methods without significant development effort. We also expand original project for taking use of parallelism in GPU to speed-up lists intersection of query process.
Book reviews

Roger Backhouse has long been known for providing the economics community with insightful historical scholarship wrapped in elegant prose. His Economists and the Economy (1992) and A History of Modern Economic Analysis (1985) both exemplify this and are excellent treatments of their respective topics. It thus comes as no surprise that Backhouse has given us an excellent ‘popular’ history in The Ordinary Business of Life: a History of Economics from the Ancient World to the Twenty-First Century. (The book was originally published in the United Kingdom in 2002 as The Penguin History of Economics.) As its subtitle implies, the book takes us from the Greeks to the present – from Homer and Hesiod to endogenous growth theory and transaction cost economics. The discussion is broken up into 14 chapters averaging just over 20 pages in length, with a prologue and an epilogue wrapped around them. Chapters 1–5 take us up to the Scottish Enlightenment and the beginnings of the classical period. Chapters 6–10 bring the story up to 1939, treating the classical school, historicism, the marginal revolution, the eclecticism of American economics in the late 19th and early 20th centuries, and developments in macroeconomics and monetary analysis from Wicksell to Keynes. Chapters 11–14 survey developments to the present day, including the rise of mathematical and econometric formalism, socialism and welfare economics, macroeconomics and macroeconomic policy, and the expanding boundaries of economic analysis. The book also includes nearly 20 pages of a lightly annotated bibliography that serves as a useful guide to further reading in the primary and secondary literatures. What is particularly refreshing is the extent of Backhouse’s treatment of preclassical, or pre-Smithian, economics. In a volume that runs to 328 pages of text, we do not meet Dr Smith until page 121. Prior to this meeting, the reader is introduced to the usual figures – e.g. Aristotle, Aquinas, Mun, and Cantillon – but also the early Christian fathers, Islamic writers, the Judaic tradition, the Reformers, Machiavelli, Child, and North, among many others. It is not unusual to meet some – and occasionally even all – of these characters in a treatise on the history of economic ideas, although the tendency to treat material written before 1776 as an afterthought, apart from the fodder that the mercantilists provided for Smith, is all too prevalent. What is surprising is to find this breadth of treatment in a book that also gives a great deal of play to the 19th and 20th centuries. Review of Political Economy, Volume 18, Number 2, 271–293, April 2006
Learning from Users: an Elicitation Study and Taxonomy for Communicating Small Unmanned Aerial System States Through Gestures

This paper presents a gesture set for communicating states to novice users from a small Unmanned Aerial System (sUAS) through an elicitation study comparing gestures created by participants recruited from the general public with varying levels of experience with an sUAS. Previous work in sUAS flight paths sought to communicate intent, destination, or emotion without focusing on concrete states such as Low Battery or Landing. This elicitation study uses a participatory design approach from human-computer interaction to understand how novice users would expect an sUAS to communicate states, and ultimately suggests flight paths and characteristics to indicate those states. We asked users from the general public $(\mathbf{N}=20)$ to create gestures for seven distinct sUAS states to provide insights for human-drone interactions and to present intuitive flight paths and characteristics with the expectation that the sUAS would have general commercial application for inexperienced users. The results indicate relatively strong agreement scores for three sUAS states: Landing (0.455), Area of Interest (0.265), and Low Battery (0.245). The other four states have lower agreement scores, however even they show some consensus for all seven states. The agreement scores and the associated gestures suggest guidance for engineers to develop a common set of flight paths and characteristics for an sUAS to communicate states to novice users.
A Survey of Recent Advances in Fractional Order Control for Time Delay Systems

Several papers reviewing fractional order calculus in control applications have been published recently. These papers focus on general tuning procedures, especially for the fractional order proportional integral derivative controller. However, not all these tuning procedures are applicable to all kinds of processes, such as the delicate time delay systems. This motivates the need for synthesizing fractional order control applications, problems, and advances completely dedicated to time delay processes. The purpose of this paper is to provide a state of the art that can be easily used as a basis to familiarize oneself with fractional order tuning strategies targeted for time delayed processes. Solely, the most recent advances, dating from the last decade, are included in this review.