Miracle-dz/UniFAR-FTUs huggingface dataset:
Correspondence between the Compositional and Aromatic Diversity of Leaf and Fruit Essential Oils and the Pomological Diversity of 43 Sweet Oranges (Citrus x aurantium var sinensis L.)

Orange (Citrus x aurantium var sinensis) is the most widely consumed citrus fruit, and its essential oil, which is made from the peel, is the most widely used in the food, perfume, and cosmetics industries. This citrus fruit is an interspecific hybrid that would have appeared long before our era and would result from two natural crosses between mandarin and pummelo hybrids. This single initial genotype was multiplied by apomictic reproduction and diversified by mutations to produce hundreds of cultivars selected by men essentially based on phenotypic characteristics of appearance, spread of maturity, and taste. Our study aimed to assess the diversity of essential oil composition and variability in the aroma profile of 43 orange cultivars representing all morphotypes. In agreement with the mutation-based evolution of orange trees, the genetic variability tested with 10 SSR genetic markers was null. The oils from peels and leaves extracted by hydrodistillation were analyzed for composition by GC (FID) and GC/MS and for aroma profile by the CATA (Check All That Apply) method by panelists. Oil yield varied between varieties by a factor of 3 for PEO and a factor of 14 for LEO between maximum and minimum. The composition of the oils was very similar between cultivars and was mainly dominated by limonene (>90%). However, small variations were observed as well as in the aromatic profile, with some varieties clearly distinguishing themselves from the others. This low chemical diversity contrasts with the pomological diversity, suggesting that aromatic variability has never been a selection criterion in orange trees.
Micro-scale spatial preference and temporal cyclicity linked to foraging in harbour porpoises

: Habitat heterogeneity is a crucial driver for species distribution across scales. Har-bour porpoise Phocoena phocoena basin-wide distribution is linked to prey availability, and small-scale (kilometres to tens of kilometres) differences in distribution are prevalent. However, information on porpoise distribution and foraging-behaviour variations on a micro-scale (~100 m to kilometres) is limited. To monitor harbour porpoise distribution and foraging activity on a micro-scale, we deployed passive acoustic dataloggers, logging porpoise acoustic activity at 6 sites in a small, high porpoise-density area in southern Sweden. Data were collected for almost a year, giving detailed time series on porpoise activity. The time series were analysed using dynamic time warping to compare activity patterns between sites. Large differences were found between sites separated by only a few hundred meters, indicating micro-scale spatial preference. Spectral analysis for temporal cyclicity in activity revealed a dominant peak for 24 h cycles with higher activity at night for all sites. All sites also had a second peak for 29.5 d, linked to the lunar cycle with higher activity during full moon. Activity was overall highest during autumn and winter (September−December). Spatial and temporal patterns were linked to foraging, showing a positive correlation between porpoise presence and the percent of time present with detected foraging. The study demonstrates that harbour porpoise spatial distribution on a micro-scale should be considered in e.g. behavioural, management and conservation studies and actions. In addition, we show that time series statistical methodology is informative and appropriate for analysis of acoustic temporal data.
Block delayed Majorize-Minimize subspace algorithm for large scale image restoration

In this work, we propose an asynchronous Majorization-Minimization (MM) algorithm for solving large scale differentiable non-convex optimization problems. The proposed algorithm runs efficient MM memory gradient updates on blocks of coordinates, in a parallel and possibly asynchronous manner. We establish the convergence of the resulting sequence of iterates under mild assumptions. The performance of the algorithm is illustrated on the restoration of 3D images degraded by depth-variant 3D blur, arising in multiphoton microscopy. Significant computational time reduction, scalability and robustness are observed on synthetic data, when compared to state-of-the-art methods. Experiments on the restoration of real acquisitions of a muscle structure illustrate the qualitative performance of our approach and its practical applicability.
Assessment of the Effectiveness of Iterative Techniques for the Evaluative of the Electromagnetic Scattering By Weakly Nonlinear Dielectric Cylinders - Summary

The effectiveness of some iterative approaches to the computation of the electromagnetic scattering by nonlinear isotropic dielectric cylinders of arbitrary cross-sections is investigated in this paper. These approaches have been developed within the distorted-wave Born approximation, the classic first-order Born approximation, and the Rytov approximation. They are based on an integral equation formulation that defines an equivalent problem in which the interactions between harmonics are taken into account by coupling terms that can be made explicit, as the nonlinearity has been defined. In the case of Kerr-like nonlinearities and under the hypothesis of time-periodic transverse-magnetic incident fields, the effectiveness of these approaches is evaluated by means of several numerical simulations, concerning cylinders of different cross-sections. The results are compared with those obtained by applying an exact numerical methodology based on an optimization procedure.
Further Evidence on the Great Crash, the Oil-Price Shock, and the Unit-Root Hypothesis

Recently, Perron has carried out tests of the unit-root hypothesis against the alternative hypothesis of trend stationarity with a break in the trend occurring at the Great Crash of 1929 or at the 1973 oil-price shock. His analysis covers the Nelson–Plosser macroeconomic data series as well as a postwar quarterly real gross national product (GNP) series. His tests reject the unit-root null hypothesis for most of the series. This article takes issue with the assumption used by Perron that the Great Crash and the oil-price shock can be treated as exogenous events. A variation of Perron's test is considered in which the breakpoint is estimated rather than fixed. We argue that this test is more appropriate than Perron's because it circumvents the problem of data-mining. The asymptotic distribution of the estimated breakpoint test statistic is determined. The data series considered by Perron are reanalyzed using the test static. The empirical results make use of the asymptotics developed for the test statistic as well as extensive finite-sample corrections obtained by simulation. The effect on the empirical results of fat-tailed and temporally dependant innovations is investigated. In brief, by treating the breakpoint as endogenous, we find that there is less evidence against the unit-root hypothesis than Perron finds for many of the data series but stronger evidence against if for several of the series, including the Nelson–Plosser industrial-production, nominal-GNP, and real-GNP series.
Magnetic response of a hollow ellipsoid

The response of a ferrous ellipsoidal target in the presence of an applied magnetic field is studied. The ellipsoid is allowed to have two layers of contrasting magnetic permeability, and the frequency is assumed low enough to neglect any eddy currents. Because of its versatile geometry, the ellipsoid can represent several common shapes, such as discs, pancakes, cigars, and vertical or horizontal plates. Several special cases are considered in detail, including a hollow ellipsoid made of a thin, highly permeable shell. It is shown that the cross-polar component of the scattered field bears information about the ellipsoid's location.
Tracking control of a nonlinear system with input-dependent delay

A class of nonlinear systems with input dependent parameters and time delays has been considered, for which the output is oscillatory. As for /spl delta/-flat systems, the open-loop motion planning problem can be solved using an explicit parametrization of trajectories; however, it is shown that the structure of the system brings out some constraints on the input and therefore limits the possible choice of trajectories. An example is provided, in which the trajectory is piecewise polynomial, where the open loop control and the corresponding constraints are explicitly given.
Three Heads Better than One: Pure Entity, Relation Label and Adversarial Training for Cross-domain Few-shot Relation Extraction

ABSTRACT In this paper, we study cross-domain relation extraction. Since new data mapping to feature spaces always differs from the previously seen data due to a domain shift, few-shot relation extraction often perform poorly. To solve the problems caused by cross-domain, we propose a method for combining the pure entity, relation labels and adversarial (PERLA). We first use entities and complete sentences for separate encoding to obtain context-independent entity features. Then, we combine relation labels which are useful for relation extraction to mitigate context noise. We combine adversarial to reduce the noise caused by cross-domain. We conducted experiments on the publicly available cross-domain relation extraction dataset Fewrel 2.0[1]①, and the results show that our approach improves accuracy and has better transferability for better adaptation to cross-domain tasks.
Energy-Efficient Wide-Range Level Shifter With a Logic Error Detection Circuit

In this brief, an energy-efficient, wide-range level shifter (LS) with a logic error detection circuit (LEDC) is proposed. The proposed LS is designed based on a current mirror-based LS (CMLS), and a feedback pFET is added to solve the static current, which is a limitation of the CMLS. Similarly, Wilson’s CMLS (WCMLS) solves the problem of the CMLS through the feedback pFET; however, it cannot convert low supply voltage (<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {DDL}}$ </tex-math></inline-formula>) to high supply voltage (<inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {DDH}}$ </tex-math></inline-formula>) fully due to the feedback pFET. In contrast, the proposed LS can convert <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {DDL}}$ </tex-math></inline-formula> to full <inline-formula> <tex-math notation="LaTeX">$V_{\mathrm {DDH}}$ </tex-math></inline-formula> using the LEDC. To verify the performance between the proposed LS and the previously proposed LS, the postlayout simulation was performed using the 7-nm finFET model. The simulation results of the proposed LS show that the propagation delay and energy are 0.21 ns and 20.43 fJ, respectively, at a low/high voltage of 0.4/1.2 V and an input frequency of 1 MHz.
Home-Based Pilot Intervention to Improve Quality of Life and Related Outcomes among Unpaid Caregivers and Their Care-Recipients with Visual Impairments

The increasing lifespan of the United States population has led to a rise in the prevalence of age-related chronic diseases, increasing the need for unpaid caregivers. Currently, little research is known about this specific population beyond the limited formal training unpaid caregivers receive on the caregiving process. Acquiring visual impairments (VI) later in life places a large emotional toll on both the loved one and their caregivers. The objectives of this pilot study were: (1) to implement a multimodal intervention targeted towards improving the quality of life of unpaid caregivers and their care recipients with visual impairments; (2) to evaluate the efficacy of the multimodal intervention in improving the quality of life of unpaid caregivers and their care recipients with visual impairments. A 10-week virtual intervention (e.g., tai chi, yoga, music) was implemented with 12 caregivers and 8 older adults with VI. The targeted outcomes of interest included: QoL, health, stress, burden, problem-solving, and barriers. In addition to surveys to inform the choice of the intervention, focus group interviews were conducted to obtain participants’ perspectives on the effectiveness of the intervention. Results revealed many positive outcomes in the quality of life and well-being of the participants following the 10-week intervention. Overall, these results represent a promising program for unpaid caregivers of older adults with VI.
Comparison of high-resolution NAIP and unmanned aerial vehicle (UAV) imagery for natural vegetation communities classification using machine learning approaches

ABSTRACT To map and manage forest vegetation including wetland communities, remote sensing technology has been shown to be a valid and widely employed technology. In this paper, two ecologically different study areas were evaluated using free and widely available high-resolution multispectral National Agriculture Imagery Program (NAIP) and ultra-high-resolution multispectral unmanned aerial vehicle (UAV) imagery located in the Upper Great Lakes Laurentian Mixed Forest. Three different machine learning algorithms, random forest (RF), support vector machine (SVM), and averaged neural network (avNNet), were evaluated to classify complex natural habitat communities as defined by the Michigan Natural Features Inventory. Accurate training sets were developed using both spectral enhancement and transformation techniques, field collected data, soil data, texture, spectral indices, and expert knowledge. The utility of the various ancillary datasets significantly improved classification results. Using the RF classifier, overall accuracies (OA) between 83.8% and 87.7% with kappa (k) values between 0.79 and 0.85 for the NAIP imagery and between 87.3% and 93.7% OA with k values between 0.83 and 0.92 for the UAV dataset were achieved. Based on the results, we concluded RF to be a robust choice for classifying complex forest vegetation including surrounding wetland communities.
Dual-Bit-Wise Stochastic Decoding for Polar Codes

Polar codes, being the first class of codes with provable capacity-achieving property, have aroused extensive attention. The belief propagation (BP) algorithm, which is one of the popular decoding approaches for polar codes, possesses inherent high parallelism but also high computational complexity. With low complexity and high fault tolerance, stochastic computing has been well studied and applied to BP decoding for polar codes. However, existing stochastic BP decoders suffer from high decoding latency. In this paper, firstly, a novel dual-bit-wise iterative message update method is proposed for stochastic BP, reducing the decoding latency by more than half. Based on the dual-bit-wise decoding, more special nodes in the factor graph are investigated and then fully exploited to pursue lower decoding complexity than prior arts. Moreover, a well-optimized architecture is developed for the proposed stochastic decoder, where the random number generator (RNG), tracking forecast memory (TFM), and hard decision unit are intelligently designed for reduced hardware cost. Experimental results demonstrate that the presented decoder can exhibit 61.7% lower decoding latency than the state-of-the-art works. Besides, the throughput and hardware efficiency can be improved by nearly $2.8\times$ and $2.7\times$, respectively.
The Effect of Future Time Perspective on Internet Dependence Among College Students in Pandemic Time: A Moderated Mediation Analysis

Purpose Social isolation during the COVID-19 pandemic has greatly increased the probability of Internet dependence. This study sought to examine the relation between future time perspective and college students’ Internet dependence, as well as the mediating role of boredom proneness and the moderating effect of self-control in the link between boredom proneness and Internet dependence. Materials and Methods A questionnaire survey was carried out among college students from two universities in China. A sample of 448 participants varying from freshmen to seniors completed questionnaires on future time perspective, Internet dependence, boredom proneness and self-control. Results Results indicated that college students with high future time perspective were less likely to fall into Internet dependence and boredom proneness mediated this relationship. The relation between boredom proneness and Internet dependence was moderated by self-control. Boredom proneness had a greater impact on Internet dependence for students with low self-control. Conclusion Future time perspective could influence Internet dependence through the mediating role of boredom proneness, which is moderated by self-control. The results advanced our understanding of how future time perspective affected college students’ Internet dependence, revealing that intervention strategies which could improve students’ self-control would be instrumental in reducing Internet dependence.
Observer-based fault tolerant control design for periodic piecewise time-varying systems: a fault estimation approach

ABSTRACT This study tackles the fault estimation issue for a continuous-time periodic piecewise time-varying systems (PPTVSs) with delays, fault signal and external disturbances. In particular, the PPTVSs are conjured up by segmenting the fundamental period of the periodic system into a finite number of subintervals. Moreover, fault estimator is designed in line with periodic piecewise observer systems to estimate the immeasurable states of the PPTVSs and the fault signal, simultaneously. Subsequently, in accordance with the estimated values of the fault signal and state dynamics, a fault-tolerant controller is devised. Moreover, by utilising Lyapunov stability theory and matrix polynomial lemma, sufficient criteria are procured in context of linear matrix inequalities to affirm the uniform boundedness of the undertaken system and error system. Further, relying on the acquired constraints, the precise configuration of the fault-tolerant control and observer gain matrices are proffered. Eventually, by offering two illustrative examples including mass-spring-damper system, the utility and potential of presented theoretical insights are validated.
Discovering spatiotemporal flow patterns: where the origin–destination map meets empirical orthogonal function decomposition

ABSTRACT Flows are usually represented as vector lines from origins to destinations and can reflect the movements of individuals or groups in space and time. Revealing and analyzing the spatiotemporal flow patterns are conducive to understanding information underlying movements. This paper proposes a new method called the OD – EOF (Origin – Destination – Empirical Orthogonal Function) to discover important spatiotemporal flow patterns on the premise of maintaining the pairwise connections between origins and destinations. We first construct a spatiotemporal flow matrix that contains connection information between origins and destinations and temporal flow information by adding a temporal dimension to the OD map. Then, we decompose the spatiotemporal flow matrix into spatial modes and corresponding time coefficients by EOF decomposition. The decomposition results depict the prominent spatial distribution of and temporal variation in flows, with most of the spatiotemporal characteristics highly concentrated into the first few spatial modes. The method is evaluated by five synthetic datasets and a user study and subsequently applied to analyze the impact of the COVID-19 pandemic on the spatiotemporal patterns of human mobility in China during the Spring Festival travel rush in 2020 and 2021. The results show the prominent spatiotemporal patterns of human mobility during these periods under the influence of the COVID-19 pandemic outbreak and the normalization of pandemic prevention and control.
Evaluating the Effects of Virtual Reality Environment Learning on Subsequent Robot Teleoperation in an Unfamiliar Building

Using a map in an unfamiliar environment requires identifying correspondences between elements of the map's allocentric representation and elements in egocentric views. Aligning the map with the environment can be challenging. Virtual reality (VR) allows learning about unfamiliar environments in a sequence of egocentric views that correspond closely to the perspectives and views that are experienced in the actual environment. We compared three methods to prepare for localization and navigation tasks performed by teleoperating a robot in an office building: studying a floor plan of the building and two forms of VR exploration. One group of participants studied a building plan, a second group explored a faithful VR reconstruction of the building from a normal-sized avatar's perspective, and a third group explored the VR from a giant-sized avatar's perspective. All methods contained marked checkpoints. The subsequent tasks were identical for all groups. The self-localization task required indication of the approximate location of the robot in the environment. The navigation task required navigation between checkpoints. Participants took less time to learn with the giant VR perspective and with the floorplan than with the normal VR perspective. Both VR learning methods significantly outperformed the floorplan in the orientation task. Navigation was performed quicker after learning in the giant perspective compared to the normal perspective and the building plan. We conclude that the normal perspective and especially the giant perspective in VR are viable options for preparing for teleoperation in unfamiliar environments when a virtual model of the environment is available.
Characterizing behaviors of territorial-dispute-related mapping in OpenStreetMap

ABSTRACT OpenStreetMap (OSM) as one of the most successful projects of Volunteered Geographical Information (VGI) has attracted millions of contributors to work together and produces massive open geographical data. However, the co-work does not always run smoothly since mapping can involve conflicted understandings of the reality. In this paper, we investigate behaviors of mapping related to territorial disputes to reveal the characteristics of contributions and examine the contradictions between ground truth as the vision of OSM and the theory of critical cartography. We perform our experiments from the perspectives of entities, changesets, and contributors using the full history data of OSM. The experiments show that territorial-dispute-related contributions have substantially different characteristics from various aspects but they cannot be treated as outliers either, considering that most contributors do not focus on disputed boundaries. Interpreting OSM data as a converging state to ground truth or equally opinions can both be inaccurate. We also find that mapping disputes may not be absolutely negative in a VGI project. Key policy highlights We perform quantitative, large-scale (global) analysis of dispute-related mapping. The results show that territorial-dispute-related contributions and contributors are different from contributions and contributors in general. Territorial-dispute-related mapping is not an independent phenomenon for OSM. The contributors make much more disputes-unrelated contributions. Dispute-related entities have more (divergent) versions than normal boundaries, attract more participants, and are more semantically complete, especially for names. Dispute-related changesets generally attract more discussions. The spatial distribution of the dispute-related changesets is consistent with real-world territorial disputes and very different from that of all boundary-related changesets and all changesets. Contributors who participate in dispute-related contributions are generally more active. These users tend to have a special interest in boundaries but most of them do not focus on disputed boundaries.