Miracle-dz/UniFAR-FTUs huggingface dataset:
Workshop Report: Standards and Performance Metrics for On-Road Autonomous Vehicles

On-road autonomous vehicles are expected to significantly influence key aspects of everyday life. However, these complex systems can pose a safety risk in the event of unexpected system performance. Therefore, the National Institute of Standards and Technology (NIST) held the Standards and Performance Metrics for On-Road Autonomous Vehicles Workshop to solicit stakeholder feedback with respect to challenges and opportunities in developing standards and performance metrics for this complex interdisciplinary field. In addition, this workshop aimed to foster a community consisting of stakeholders from a variety of disciplines and domains in autonomous vehicles. This workshop was conducted virtually over two days (March 8 th -9 th , 2022) consisting of introductory remarks, panels, breakout sessions, and concluding remarks. This report is a summary of the technical topics discussed by participants during the workshop. to promote collaboration among federal, state, local, tribal, territorial, business, not-for-profit, and academic institutions. As a champion of advancing standards and developing measurement science solutions to challenging technical problems, NIST is well positioned to represent the federal government, drawing upon NIST’s experience in areas such as Artificial Intelligence (AI), cybersecurity, and materials- and physics-based technologies. She described the focus areas for the workshop as we aim to continue U.S. leadership in promoting an open dialogue in promoting on-road autonomous vehicle development. On behalf of the Secretary of Commerce, she thanked attendees for their participation and for their past, current, and future progress. The driving environment consists of multiple obstacles to perception (both manual and automated) including occlusion, variable reflectivity, and edge cases. This panel discusses testing conditions and metrics for evaluating sensor data and fusion techniques in autonomous vehicles.
From State Transitions to Sensory Regularity: Structuring Uninterpreted Sensory Signals From Naive Sensorimotor Experiences

How could a naive agent build some internal, subjective, notions of continuity in its sensorimotor experiences? This is a key question for all sensorimotor approaches to perception when trying to make them face realistic interactions with an environment, including noise in the perceived sensations, errors in the generation of motor trajectories, or uncertainties in the agent’s internal representation of this interaction. This article proposes a detailed formalization, but also some experimental assessments, of the structure, a naive agent can leverage from its own uninterpreted sensorimotor flow to capture a subjective sensory continuity, making it able to discover some notions of closeness or regularities in its experience. The precise role of the agent’s actions is also questioned with respect to the spatial and temporal dynamics of its exploration of the environment. On this basis, the previous authors’ contribution on sensory prediction is extended to successfully handle noisy data in the agent’s sensorimotor flow.
How do variations in dollar exchange rate impact food commodity prices in selected African countries?

Aim: Commodity exporting nations have significant terms of trade swings, making their actual exchange rate unstable. This study looked at how variations in dollar exchange rate affected food commodity prices in Africa between 1990 and 2021. Design/Research methods : The study conducted GARCH analysis for ascertaining prevalence of volatilities of exchange rates and interest rates respectively in selected African countries. Also, we estimated both static and dynamic analysis driven by panel least squares and generalized method of moments (GMM) estimators on panel data from some commodity-exporting African, namely, Ghana, Gabon, Tunisia, Nigeria, and South Africa. Findings : The dynamic GMM results reveal exchange rate and interest rate variations taken together had positive effects on commodity prices. GARCH estimates demonstrate significant volatility growth using both normal and t multivariate distributions. However, based on empirical findings, t-distribution had largest maximized log-likelihood of -8920.1 and also had a satisfactory df of 26.82 (<30). The results demonstrate that the Nigerian Naira had highest coefficient of volatility of approximately 71.2%. This was followed by the Ghanaian Cedi with a negative volatility rate of 71% and the South African rand with a coefficient of 65%. However, while all countries had negative volatility Contributions: The contribution of the study lies on its explanation of the increase of food commodity prices due to variability calculated in terms of depreciation in dollar exchange rate. Empirically, it is a confirmation of a significant structural problem, exchange rate variation as a cause of domestic inflation in selected African countries. Limitations : Results have to be interpreted with care due to the small sample size. The results are rather a working hypothesis for future research.
Determination Of Benzo[A]Pyrene Levels In Cashew Nut Shells And Kernels Processed Using Different Traditional Methods And Fuel Sources From Kilifi County, Kenya

: The aim of this study was to determine BaP levels generated in cashew nut shell and kernel samples processed from two methods (roasting and sun-drying), roasted separately using different fuel sources namely: pine, mango and coconut husks and shells, when roasted for different durations using the same fuel source and the effect of the shell. In the roasted shell samples using different fuel sources, pine generated the highest BaP concentration (12.918±5.270µg/kg), followed by mango wood (5.842±2.307µg/kg) while coconut shell and husk mixture generated the least BaP (2.298±1.664µg/kg) in the cashew nut shell samples. The BaP concentrations were below the detection limit in all the 90 roasted cashew nut kernels samples. BaP levels were also below the detection limit in the 30 shell and 30 kernel samples (from 3 batches) processed through sun-drying method. BaP was not detected in all 36 roasted cashew nut kernel samples collected from the roadside vendors from the 3 towns. This could be attributed to the shell leading to 100% BaP reduction by preventing pyrolysis of the kernel and deposition of BaP by the smoke from the fuel source. The BaP non-detection in the kernel samples meant they were below the EU Maximum residual limit of 5µg/kg hence safe for human consumption.
Water vapour and ozone in the upper troposphere–lower stratosphere: global climatologies from three Canadian limb-viewing instruments

Abstract. This study presents upper troposphere–lower stratosphere (UTLS) water vapour and ozone climatologies generated from 14 years (June 2004 to May 2018) of measurements made by three Canadian limb-viewing satellite instruments: the Atmospheric Chemistry Experiment Fourier Transform Spectrometer (ACE-FTS), the Measurement of Aerosol Extinction in the Stratosphere and Troposphere Retrieved by Occultation (MAESTRO), and the Optical Spectrograph and InfraRed Imaging System (OSIRIS; ozone only). This selection of instruments was chosen to explore the capability of these Canadian instruments in representing the UTLS and to enable analysis of the impact of different measurement sampling patterns. The water vapour and ozone climatologies have been constructed using tropopause-relative potential temperature and equivalent-latitude coordinates in an effort to best represent the distribution of these two gases in the UTLS, which is characterized by a high degree of dynamic and geophysical variability. Zonal-mean multiyear-mean climatologies are provided with 5∘ equivalent latitude and 10 K potential temperature spacing and have been constructed on a monthly, seasonal (3-month), and yearly basis. These climatologies are examined in-depth for two 3-month periods, December–January–February and June–July–August, and are compared to reference climatologies constructed from the Canadian Middle Atmosphere Model 39-year specified dynamics (CMAM39-SD) run, subsampled to the times and locations of the satellite measurements, in order to evaluate the consistency of water vapour and ozone between the datasets. Specifically, this method of using a subsampled model addresses the impact of each instrument's measuring pattern and allows for the quantification of the influence of different measurement patterns on multiyear climatologies. This in turn permits a more consistent evaluation of the distributions of these two gas species, as assessed through the differences between the model and measurement climatologies. For water vapour, the average absolute relative difference between CMAM39-SD and ACE-FTS differed between the two versions of ACE-FTS by less than 8 %, while the MAESTRO climatologies were found to differ by 15 %–41 % from ACE-FTS, depending on the version of ACE-FTS and the season. When considering the ozone climatologies, those constructed from the two ACE-FTS versions agreed to within 2 % overall, and the OSIRIS ozone climatologies agreed with these to within 10 %. The MAESTRO ozone climatologies differ from those from ACE-FTS and OSIRIS by 30 %–35 % and 25 %, respectively, albeit with regions of better agreement within the UTLS. These findings indicate that this set of Canadian limb sounders yields generally similar water vapour and ozone distributions in the UTLS, with some exceptions for MAESTRO depending on the season and gas species.
Effet du stress hydrique sur quelques mécanismes physiologiques et biochimiques d’adaptation chez huit génotypes de blé dur ( Triticum Durum DESF)

Un essai de ble dur a ete conduit sous differents niveaux de stress hydrique ; l’objectif etant d’identifier quelques mecanismes physiologiques et biochimiques de tolerance. Les resultats obtenus montrent qu’il y a une diversite dans les reponses genotypiques. Celles-ci sont soit l’expression d’un ajustement osmotique a travers un certain statut hydrique, soit d’une accumulation importante d’osmoprotecteurs. Telle la proline notamment chez les varietes locales (Hoggar et Waha) ou bien d’un statut energetique important (teneurs en pigments chlorophylliens comme c’est le cas chez M.1084. Ces resultats montrent a quel point il est utile et important a la fois de proceder a des tests predictifs au stade juvenile de la plante pour l’identification de mecanismes d’adaptation ou d’accommodation. Ces resultats permettent enfin d’aborder un programme d’amelioration genetique avec en plus une connaissance fine et precise des genotypes ;la selection en depend. Mots cles : Ble dur; stress hydrique; physiologie; adaptation.
Limiting laws of linear eigenvalue statistics for Hermitian matrix models

We study the variance and the Laplace transform of the probability law of linear eigenvalue statistics of unitary invariant Matrix Models of n×n Hermitian matrices as n→∞. Assuming that the test function of statistics is smooth enough and using the asymptotic formulas by Deift et al. [ Commun. Pure Appl. Math.52, 1325–1425 (1999)] for orthogonal polynomials with varying weights, we show first that if the support of the Density of States of the model consists of q≥2 intervals, then in the global regime the variance of statistics is a quasiperiodic function of n as n→∞ generically in the potential, determining the model. We show next that the exponent of the Laplace transform of the probability law is not, in general, 1∕2× variance, as it should be if the Central Limit Theorem would be valid, and we find the asymptotic form of the Laplace transform of the probability law in certain cases.
To Vaccinate or Not to Vaccinate—Reasons of Willingness and Reluctance of Students against SARS-CoV-2 Vaccination—An International Experience

Despite the vaccine against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) being reported to be safe and effective, the unwillingness to vaccinate and doubts are still common. The aim of this international study was to assess the major reasons for the unwillingness to vaccinate in a group of students from Poland (n = 1202), Bangladesh (n = 1586), India (n = 484), Mexico (n = 234), Egypt (n = 566), Philippines (n = 2076), Pakistan (n = 506), Vietnam (n = 98) and China (n = 503). We conducted an online cross-sectional study that aimed to assess (1) the percentage of vaccinated and unvaccinated students and (2) the reasons associated with willingness/unwillingness to the vaccine. The study included 7255 respondents from 9 countries with a mean age of 21.85 ± 3.66 years. Only 22.11% (n = 1604) of students were vaccinated. However, the majority (69.25%, n = 5025) expressed a willingness to be vaccinated. More willing to vaccinate were students in informal relationships who worked mentally, used psychological/psychiatric services before the pandemic, and studied medicine. There are cultural differences regarding the reasons associated with the unwillingness to vaccinate, but some ‘universal’ might be distinguished that apply to the whole group.
Spatiotemporal Pattern of Ecosystem Respiration in China Estimated by Integration of Machine Learning With Ecological Understanding

Accurate estimation of regional and global patterns of ecosystem respiration (ER) is crucial to improve the understanding of terrestrial carbon cycles and the predictive ability of the global carbon budget. However, large uncertainties still exist in regional and global ER estimation due to the drawbacks of modeling methods. Based on eddy covariance ER data from 132 sites in China from 2002 to 2020, we established Intelligent Random Forest (IRF) models that integrated ecological understanding with machine learning techniques to estimate ER. The results showed that the IRF models performed better than semiempirical models and machine learning algorithms. The observed data revealed that gross primary productivity (GPP), living plant biomass, and soil organic carbon (SOC) were of great importance in controlling the spatiotemporal variability of ER across China. An optimal model governed by annual GPP, living plant biomass, SOC, and air temperature (IRF‐04 model) matched 93% of the spatiotemporal variation in site‐level ER, and was adopted to evaluate the spatiotemporal pattern of ER in China. Using the optimal model, we obtained that the annual value of ER in China ranged from 5.05 to 5.84 Pg C yr−1 between 2000 and 2020, with an average value of 5.53 ± 0.22 Pg C yr−1. In this study, we suggest that future models should integrate process‐based and data‐driven approaches for understanding and evaluating regional and global carbon budgets.
Phase transitional behavior in K0.5Na0.5NbO3–LiTaO3 ceramics

In addition to x-ray diffraction, Raman spectrum measurements provide direct evidence of the tetragonal and orthorhombic phases coexistence in lead-free ceramics (1−x)K0.5Na0. 5NbO3 (KNN)–xLiTaO3 when x equals 5mol%. This is caused by the phase transition temperature between tetragonal and orthorhombic decreasing to around room temperature due to the Li and Ta doping in KNN, and not by constituting a region of morphotropic phase boundary as presented by most published papers. The results indicate that although this kind of ceramic displays good properties, it needs further study to verify if it is suitable to be used in a varying temperature environment.
Planting time, first‐year mowing, and seed mix design influence ecological outcomes in agroecosystem revegetation projects

The conversion of tallgrass prairie to agriculture has negatively affected provisioning of ecosystem services. Successful restoration of ecosystem services could depend on management decisions applied during revegetation projects. We examined the effects of three management decisions (seed mix design, planting time, and first‐year mowing) on targeted ecosystem services (erosion control, weed resistance, and pollinator resources). We tested three seed mixes of varying diversity and grass‐to‐forb seeding ratios: Economy mix (21 species, 3:1 grass:forb), Pollinator mix (38 species, 1:3), and Diversity mix (71 species, 1:1). We established plots at two planting times (dormant‐season and spring) with or without first‐year mowing. To assess ecosystem services, we measured stem density, canopy cover, and floral density and richness of sown species in the second year after planting. The Economy mix had the highest stem density and cover but lowest floral density and richness. The Pollinator mix had the lowest stem density and cover but highest floral density. The Diversity mix had comparable stem density and cover to the Economy mix and comparable floral density and richness to the Pollinator mix. Mowing accelerated native plant establishment in all seed mixes. Dormant‐season planting improved establishment of spring and fall forbs and favored cool‐season graminoids over warm‐season grasses. All three management decisions influenced ecosystem outcomes, and comparison to a previous study revealed these effects to be robust to variation in site and climatic conditions. We recommend a diverse, balanced seed mix design, first‐year mowing, and dormant‐season planting to improve multifunctionality of conservation projects.
Preparation and Characterization of Protein Molecularly Imprinted Poly (Ionic Liquid)/Calcium Alginate Composite Cryogel Membrane with High Mechanical Strength for the Separation of Bovine Serum Albumin

In order to improve the mechanical strength and imprinting efficiency, a novel bovine serum albumin (BSA) molecularly imprinted poly(ionic liquid)/calcium alginate composite cryogel membrane (MICM) was prepared. The results of the tensile test indicated that the MICM had excellent mechanical strength which could reach up to 90.00 KPa, 30.30 times higher than the poly (ionic liquid) membrane without calcium alginate; the elongation of it could reach up to 93.70%, 8.28 times higher than the poly (ionic liquid) membrane without calcium alginate. The MICM had a very high welling ratio of 1026.56% and macropore porosity of 62.29%, which can provide effective mass transport of proteins. More remarkably, it had a very high adsorption capacity of 485.87 mg g−1 at 20 °C and 0.66 mg mL−1 of the initial concentration of BSA. Moreover, MICM also had good selective and competitive recognition toward BSA, exhibiting potential utility in protein separation. This work can provide a potential method to prepare the protein-imprinted cryogel membrane with both high mechanical strength and imprinting efficiency.
More viable parameter space for leptogenesis

Lepton flavor asymmetries generated at the onset of the oscillations of sterile neutrinos with masses above the electroweak scale can be large enough to partly survive washout and to explain the baryon asymmetry of the Universe. This opens up new regions of parameter space, where leptogenesis is viable within the type-I seesaw framework. In particular, we find it possible that the sterile neutrino masses are substantially below ${10}^{9}\text{ }\text{ }\mathrm{GeV}$, while not being degenerate. However, the required reheat temperature that is determined by the beginning of the oscillations lies some orders of magnitude above the sterile neutrino mass scale.
Multicolor localization microscopy by deep learning

Deep learning has become an extremely effective tool for image classification and image restoration problems. Here, we apply deep learning to microscopy, and demonstrate how neural networks can exploit the chromatic dependence of the point-spread function to classify the colors of single emitters imaged on a grayscale camera. While existing single-molecule methods for spectral classification require additional optical elements in the emission path, e.g. spectral filters, prisms, or phase masks, our neural net correctly identifies static as well as mobile emitters with high efficiency using a standard, unmodified single-channel configuration. Furthermore, we demonstrate how deep learning can be used to design phase-modulating elements that, when implemented into the imaging path, result in further improved color differentiation between species.
A study of lambda Bootis type stars in the wavelength region beyond 7000 Å

The group of Bootis type stars comprises late B- to early F-type, Population I objects which are basically metal weak, in particular the Fe group elements, but with the clear exception of C, N, O and S. One of the theories to explain the abundance pattern of these stars involves circumstellar or interstellar matter around the objects. Hence, we have compiled all available data from the literature of well established members of the Bootis group redward of 7000 A in order to find evidence for matter around these objects. Furthermore, we present unpublished ISO as well as submillimeter continuum and CO (2-1) line measurements to complete the data set. In total, measurements for 34 (26 with data redward of 20m) well established Bootis stars are available. There is evidence for an infrared excesses in six stars (HD 31295, HD 74873, HD 110411, HD 125162, HD 198160/1 and HD 210111) and two are doubtful cases (HD 11413 and HD 192640) resulting in a percentage of 23% (excluding the two doubtful cases). Dust models for these objects show fractional dust luminosities comparable to the Vega-type stars and slightly higher dust temperatures. ISO-SWS spectroscopy for HD 125162 and HD 192640 resulted in the detection of pure stellar Hi lines ruling out an active accretion disk (as found for several Herbig Ae/Be stars) around these objects. The submillimeter measurements gave only upper limits for the line and continuum fluxes.
Geometric quantum discord through the Schatten 1-norm

It has recently been pointed out that the geometric quantum discord, as defined by the Hilbert-Schmidt norm (2-norm), is not a good measure of quantum correlations, since it may increase under local reversible operations on the unmeasured subsystem. Here, we revisit the geometric discord by considering general Schatten $p$-norms, explicitly showing that the 1-norm is the only $p$-norm able to define a consistent quantum correlation measure. In addition, by restricting the optimization to the tetrahedron of two-qubit Bell-diagonal states, we provide an analytical expression for the 1-norm geometric discord, which turns out to be equivalent to the negativity of quantumness. We illustrate the measure by analysing its monotonicity properties and by considering the ground state of quantum spin chains.
A cloud-edge collaborative scheme for surface defect recognition based on KubeEdge

With the expansion of smart devices in 5G, Internet of Things, mobile Internet and other technical scenarios, the number of devices on the edge of the network has increased dramatically. In the edge computing scene, there are a large number of heterogeneous devices, each of which has its own unique characteristics and attributes. For the edge scene, due to the increasing requirements of massive data on the timeliness, security and network dependence of computing facilities, the current cloud platform with Kubernetes as the core is not fully applicable. Therefore, many open source frameworks came into being, and KubeEdge [1] is one of the representatives. Aiming at KubeEdge, this paper proposes a cloud-edge collaboration scheme, which deploys the surface defect recognition algorithm based on YOLOv5 network to cloud edge devices to realize surface defect recognition and node autonomy in edge scenes, and provides a solution for cloud edge collaboration scenes.