Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust Localization for Intelligent Vehicles Based on Pole-Like Features Using the Point Cloud

Localization in the complex urban environment is an open problem for current methods. The occlusion from dynamic objects, such as vehicles and pedestrians, degenerates the precision of the localization result. This article proposes a pole-like feature-based localization framework to solve this problem. Pole-like objects, such as posts of lamps or traffic sign and tree trunks, widely exist in the urban environment and are robust to occlusion, as they are usually higher than the objects on the road. First, this type of feature is extracted from the point cloud by a robust clustering algorithm. Then, the features from different frames of data are stitched to generate a feature map. For online localization, a Monte Carlo localization (MCL) framework is used to fuse the vehicle motion data and the map-matching result. An improved version of iterative closest point (ICP) that is specifically designed for the pole-like feature association is used for map matching based on the state of every particle. With the MCL scheme, localization is robust to the local minimum or robot kidnapping problem. Experimental results in the real urban environment demonstrate the precision and robustness of the proposed method, with mean absolute errors less than 0.20 m and 0.5°. The results also show that the proposed method outperforms some state-of-the-art localization methods in the complex urban environment. Note to Practitioners—There are some works using features from the 3-D point cloud, e.g., corners, planes, and reflectance, for robot localization. Instead of the abstract features, this article presents an object-feature-based localization scheme. We propose a novel pole-like object extraction algorithm based on the spatial distribution of the 3-D points. This algorithm can extract most types of pole-like objects in the urban environment. As these objects are highly distinct from other types of objects in their surroundings, localization is achieved by associating the pole-like features in the map and the features detected in real time through maximizing the likelihood. The whole system is verified with data collected in the real world, which indicates that its accuracy can fulfill the requirements of autonomous driving. The limitation of the proposed method is that it highly depends on one specific type of feature, which may not work well in the rural environment. In future research, we will address this problem by incorporating more types of semantic features for localization.
A Dual-Polarized 2-D Monopulse Antenna Array for Conical Conformal Applications

A dual-polarized 2-D monopulse conical conformal antenna is proposed in this article. First, a method for implementing dual-polarized monopulse beams is presented. A novel array arrangement and a dual-polarized monopulse comparator suitable for conformal arrays are developed. Then, a wideband endfire element based on the double rhombic dipole is designed with directors and a reflector to obtain a stable high-gain endfire radiation. A conformal feeding network consisting of four rat-race couplers is employed to excite four conformal elements. The sum and difference beams of horizontal and vertical polarizations are realized on the azimuth and elevation planes. To verify the design concept, a prototype of the antenna array was designed, fabricated, and measured. The experimental results show that the proposed monopulse array achieves a shared bandwidth of 22.2% from 8.96 to 11.2 GHz on four ports, with the sum-beam gain of 9–11 dBi, the difference-beam gain of 5.8–7.7 dBi, and the null-depth of around −25 dB. To the best knowledge of the authors, the design concept of combining dual-polarized 2-D monopulse array with conical conformal antenna is proposed for the first time, which is a promising candidate as target detection and tracking antennas for various aircraft applications.
OsNAC300 Positively Regulates Cadmium Stress Responses and Tolerance in Rice Roots

Transcriptional regulation is involved in responding to cadmium (Cd) stress in plants. However, the molecular mechanisms of Cd stress responses regulated by transcription factors remain largely unknown in plants. In this study, a rice (Oryza sativa) NAC (no apical meristem [NAM]; Arabidopsis transcription activation factor [ATAF]; cup-shaped cotyledon [CUC]-related) family transcription factor, OsNAC300, was isolated and functionally characterized for its involvement in Cd stress responses and tolerance. OsNAC300 was localized to the nucleus. OsNAC300 was mainly expressed in roots and significantly induced by Cd treatment. Knockout of OsNAC300 resulted in increased sensitivity to Cd stress, while its overexpression lines enhanced tolerance to Cd stress. RNA-Seq analysis revealed that the mutant is impaired in regulating some important genes that were responsive to Cd stress in wild-type rice, such as the pathogenesis-related genes 10a (OsPR10a), OsPR10b, chalcone synthase 1 (OsCHS1), and several others, which was validated by reverse transcription quantitative polymerase chain reaction (RT-qPCR) analysis. Moreover, chromatin immunoprecipitation-qPCR assays and luciferase reporter assays demonstrated that OsNAC300 directly binds to the promoters of OsPR10a, OsPR10b, and OsCHS1 and activates their transcription. Overall, OsNAC300 is an important regulatory factor in Cd stress responses and tolerance in rice.
Proceedings of the Society for Computation in Linguistics Proceedings of the Society for Computation in Linguistics

CKY-type parser and Earley-type parser are two widely-used parsing algorithms for Tree Adjoining Grammar (TAG). In contrast, a standard top-down parser is not efﬁcient since the looping problem occurs during both the left and right recursion of standard TAG derivation. (Roark, 2001) combines the top-down parser for CFG with a beam search, showing that the probabilistic top-down parser yields a perplexity improvement over previous results. In this paper, we deﬁne the stochastic tree adjoining grammar and apply the probabilistic top-down parser for CFG to TAG. Comparing the parsing efﬁciency of the standard and alternative TAG derivation of the recursive adjunction, we ﬁnd that the alternative derivation is more ef-ﬁcient since it avoids the looping problem of the right recursion, increasing the parsing efﬁ-ciency of our top-down parser.
Exploring atomic quantum gases in optical lattices

In this thesis I present experiments which demonstrate a novel avenue to strongly correlated physics with atomic quantum gases. Quantum degenerate bosonic and fermionic atoms are investigated in the periodic potential of an optical lattice. The apparatus we have built during this thesis enables us to uniquely access the effects of dimensionality and interactions in both bosonic and fermionic systems. Exploiting the tight confinement provided by the optical lattice, we create the first kinematically one-dimensional atomic Bose gas. By applying an additional longitudinal periodic potential, we observe a transition from a 1D superfluid to a strongly correlated Mott insulator. Both phases are characterized by their distinct excitation spectrum. Measurements of the coherence properties reveal that the decrease of the coherent fraction in the system does not provide a direct indication when the Mott insulating phase is entered. However, in the coherence length we observe signatures for the emergence of a 1D Mott insulator at significantly smaller ratios of the interaction to the kinetic energy than the ones obtained for a three-dimensional system. This is an experimental indication of the increased fluctuations which are characteristic for 1D systems. Interacting fermionic quantum gases are essential for the understanding of solid state materials. We open a new window to these systems by creating a quantum degenerate Fermi gas in a three-dimensional optical lattice. We can directly image the Fermi surface of the atoms in the lattice and induce a dynamical transition from a strongly correlated band insulator to a ”conductive“ state. By exploiting a Feshbach resonance, we are able to tune the interactions in the gas to arbitrary values, repulsive and attractive, and thereby generate a coupling between the lowest energy bands of the lattice. Furthermore, using the tight confinement of the optical lattice, we create a tunable 1D Fermi gas. We observe confinement induced molecules which exist in a regime where bound states are absent in a 3D Fermi gas. These unique experiments demonstrate the unprecedented versatility of atomic quantum gases in optical lattices. The very controlled study of strongly correlated phases and the unparalleled direct access to low-dimensional systems opens up new perspectives onto fundamental questions of modern quantum many-body physics.
Roads, forestry, and wolves interact to drive moose browsing behavior in Scandinavia

As wild ungulate densities increase across Europe and North America, plant-herbivore interactions are increasingly important from ecological and economic perspectives. These interactions are particularly significant where agriculture and forestry occur and where intensive grazing and browsing by wild ungulates can result in economic losses to growing crops and trees. We studied plant-herbivore interactions in a moose (Alces alces)-dominant system where forestry is a primary economy, the primary and secondary road networks are extensive, and wolves (Canis lupus) are recolonizing. Wolves and humans use low-traffic, secondary roads, yet roadsides provide high-quality and quantity browse for moose. Foraging theory predicts that moose will respond to riskier landscapes by selecting habitats that reduce predation risk, sacrificing feeding time or food quality. As food becomes limiting, however, animals will accept higher predation risk in search of food. We predicted that road avoidance behavior would be strongest within wolf territories. In areas without wolves, moose should select roadsides for their high forage availability. To test these predictions, we measured moose browsing and counted pellet groups as a proxy for habitat use each spring in Norway and Sweden between 2008 and 2018, in areas with and without wolves and at different distances from primary and secondary roads. We used generalized linear mixed models to evaluate drivers of the probability of browsing occurrence and browsing pressure. We found that browsing occurrence increased closer to secondary roads but decreased closer to primary roads. We also found browsing patterns to vary among tree species. For Scots pine (Pinus sylvestris), the browsing occurrence was two times higher in young forests relative to non-young forests and decreased further from secondary roads. Wolf territory presence and probability had neutral or positive effect on browsing occurrence and pressure for all species. However, wolf territory presence had negative effects on browsing occurrence and pressure when interacting with secondary roads, young forest, or snow cover. We showed that roads can influence browsing patterns in Norway and Sweden. However, further research is needed, particularly in the face of continued infrastructure development in Scandinavia.
Research on Emotion Classification based on Complex Network and Ensemble Learning

Because the traditional feature extraction is based on the statistical information such as document frequency and word frequency, the selection of feature words is ignored, and the semantic correlation between words in the text is ignored. The feature selection method based on complex network takes into account the semantic association between words, but does not take into account the statistical information such as word frequency. The above methods are not satisfactory for the selection of feature words, which affects the effect of text classification. Therefore, this paper combines the two, proposes a new method for feature selection, and in order to solve the problem of low accuracy rate of single classification algorithm, USES integrated learning [1] to strengthen the classification algorithm. The results show that this method is feasible and achieves good classification effect.
Iterative learning control for multi-agent systems with impulsive consensus tracking

In this paper, we adopt D-type and PD-type learning laws with the initial state of iteration to achieve uniform tracking problem of multi-agent systems subjected to impulsive input. For the multi-agent system with impulse, we show that all agents are driven to achieve a given asymptotical consensus as the iteration number increases via the proposed learning laws if the virtual leader has a path to any follower agent. Finally, an example is illustrated to verify the effectiveness by tracking a continuous or piecewise continuous desired trajectory.
Investigation of vehicle exhaust sub-23 nm particle emissions

ABSTRACT A solid particle number limit was applied to the European legislation for diesel vehicles in 2011. Extension to gasoline direct injection vehicles raised concerns because many studies found particles below the lower size limit of the method (23 nm). Here we investigated experimentally the feasibility of lowering this size. A nano condensation nucleus counter system (nCNC) (d50% = 1.3 nm) was used in parallel with condensation particle counters (CPCs) (d50% = 3 nm, 10 nm and 23 nm) at various sampling systems based on ejector or rotating disk diluters and having thermal pre-treatment systems consisting of evaporation tubes or catalytic strippers. An engine exhaust particle sizer (EEPS) measured the particle size distributions. Depending on the losses and thermal pre-treatment of the sampling system, differences of up to 150% could be seen on the final detected particle concentrations when including the particles smaller than 23 nm in diameter. A volatile artefact as particles with diameters below 10 nm was at times observed during the cold start measurements of a 2-stroke moped. The diesel vehicles equipped with the Diesel Particulate Filter (DPF) had a low solid sub-23 nm particles fraction (<20%), the gasoline with direct injection vehicles had higher (35–50%), the gasoline vehicles with port fuel injection and the two mopeds (two and four-stroke) had the majority of particles below 23 nm. The size distributions peaked at 60–80 nm for the DPF equipped vehicles, at 40–90 nm for the gasoline vehicles with a separate nucleation mode peak at approximately 10 nm sometimes. Mopeds peaked at sizes below 50 nm when their aerosol was thermally pre-treated. © 2017 American Association for Aerosol Research
Bank’s brand, social influence, and its impact on the decision on using mobile banking services of individual customers: An empirical study

Article history: Received: September 28, 2020 Received in revised format: December 28 2020 Accepted: December 28, 2020 Available online: January 15, 2021 In the context of fintech and industrial revolution 4.0, the banking system worldwide has significantly developed mobile banking services at a great pace in order to promote economic performance. The aim of this analysis is to estimate factors that impact on the customers' use of mobile-banking services in the typical case in Vietnam nowadays. Using a sample data of 420 questionnaires covering in 2020, the results indicate that brand and social influence have greatly impacted on the customers' use of mobile-banking services. A greater bank’s brand and social influence is positively related to a greater the customers' use of mobile-banking services. In addition, transaction risk has a negative impact on decisions to use mobile-banking services. Vietnam should enhance the risk management in the banking sector in order to maintain sustainable development in the long run. © 2021 by the authors; licensee Growing Science, Canada
HPLC METHOD DEVELOPMENT AND VALIDATION FOR QUANTITATION OF TRIGONELLINE FROM MIRABILIS JALAPA LINN. LEAVES AND ENHANCEMENT IN EXTRACTION YIELD FROM ULTRA FINE POWDER

Objective: Development and validation of a simple and reliable HPLC method for determination of an alkaloid, trigonelline, in the methanolic extract of Mirabilis jalapa Linn. leaves and comparing the extraction yields of trigonelline from micro powder and ultrafine powder. Methods: The quantitation of trigonelline was carried out on a Phenomenex (Luna 5 U RP C8 (2) column, 25 cm x 4.6 mm, i.d. 5 µm), using mobile phase comprising of distilled water containing HCl (pH adjusted to 3.5) and methanol in the volume ratio of 70:30, which was delivered at the flow rate of 0.5 ml per min, at 35 °C column temperature. The detection and quantitation of trigonelline were carried out using PDA detector at the wavelength λ=264 nm. Ultra-fine powder of M irabilis jalapa Linn. was prepared using simple stepwise powdering method. The dried leaves of Mirabilis jalapa Linn. were ground using ice jacketed domestic mixer. This powder was sieved through a BSS 85 mesh sieve and considered as a micro powder. Further fine grinding was done by jet milling, followed by ball milling. This powder was considered as an ultra-fine powder. Results: The proposed HPLC method for quantitation of trigonelline from dried leaf powder of Mirabilis jalapa Linn. is rapid, simple, accurate and precise. Conclusion: The amount of trigonelline obtained using methanolic extracts of Mirabilis jalapa Linn. Ultra-fine powder and the micro powder was found to be 1.1103 mg/g and 0.7258 mg/g respectively.
Analysis and Design of Interleaved DCM Buck–Boost Derived Three-Phase PFC Converter for MEA

In more-electric aircraft (MEA), the synchronous generators are connected directly to the turbo engine to develop a constant-voltage variable-frequency (CVVF) ac supply bus. In addition, the MEA has adopted a high-voltage dc bus in its power system to cater to the various categories of load used by aircraft. Therefore, this change in power paradigm has created a requirement for ac–dc power factor correction (PFC) converters to convert CVVF ac to constant dc with high power quality in a reliable manner. In this article, a three-phase interleaved buck–boost-derived PFC converter is operated in discontinuous current conduction mode to realize the inherent unity power factor (UPF) operation for MEA wide range of supply frequency. The benefits of the proposed converter are higher power density, efficiency, and reliability. The advantages of the proposed converter are demonstrated by performing an analytical comparison with the single-cell three-phase buck–boost derived PFC converter and presented the relevant results. The experimental results from a 2.0-kW laboratory concept-proof hardware prototype have been provided to confirm the proposed converter UPF operation for a wide range of supply frequencies. A low input power factor of 0.9996 and a minimum current THD of 2.52% are recorded from the developed prototype.
A CIRCULARLY POLARIZED QUAD-BAND ANNULAR RING ANTENNA WITH ASYMMETRIC GROUND PLANE USING THEORY OF CHARACTERISTIC MODES

Herein a theory of characteristic mode (TCM)-based design of circularly-polarized (CP) quad-band compact microstrip antenna is proposed. It involves one annular ring radiator having eight symmetrical slots along its boundary and three circular closed ring resonators (CRRs) on the bottom side of the substrate. Initially, CM analysis was carried out for the radiator without a feeding structure, to determine the modal currents and their corresponding modal fields (radiation patterns) of existing modes. This helped in recognizing the symmetric modes to be selectively excited by the feed to furnish CP and gave direction for selecting an asymmetric CPW-fed structure as the feed of choice. Evolution process of the antenna geometry shows that the eight symmetrical slots in tandem with the CRRs generate wide impedance bandwidth (IBW), while measured quad CP bands are obtained through uses of an asymmetric ground plane resonating at 5.63 GHz (120 MHz), a cross-shaped slit at 7.69 GHz (650 MHz), a rectangular open loop at 9.91 GHz (1200 MHz), and a tuning stub in the feeding structure at 12.09 GHz (160 MHz). Series of parasitic strips augmented CP radiation and eliminate ripples in the radiation pattern. Measured findings relate satisfactorily with simulations done using Ansys HFSS 2020 R1. A low cost FR-4 substrate is used to fabricate the antenna with an optimized dimension of 35 × 30 × 1.6 mm3. The measured IBW ranges from 4.36–4.82 GHz, 5.50–5.78 GHz, and 5.95–beyond 14 GHz. The proposed antenna may find suitable applications in C band, X band, and 5GHz WLAN devices.
1 Don ’ t Accept Candy from Strangers: An Analysis of Th ird-Party Mobile SDKs

Mobile application (app) developers oft en include third-party Soft ware Development Kits (SDKs) in their soft ware to integrate services and features off ered by other companies, like online payments or social network integration, or to monetise their apps through advertisements. As a result, SDKs play a key role in the soft ware supply chain. Th eir integration in apps is practically mandatory if developers aim at producing soft ware that integrates smoothly in the current ecosystem of internet services. Unfortunately, these common soft ware development practices might come at a privacy cost to end users since many third-party library providers implement data-driven business models that allow them to off er their services to developers free of monetary payment. In this chapter, we provide an overview of the third-party library ecosystem for the Android platform and we discuss its privacy implications for mobile end users due to limitations present in the permission system of today ’ s mobile platforms, and the overall lack of transparency in the industry. We apply soft ware analysis techniques and manual analysis to: (1) compare the eff ectiveness and limitations of state-of-the-art SDK detection tools; (2) manually classify SDKs by their purpose and compare the classifi cation capabilities of current auditing tools; and (3) gain empirical insights about their behaviour and data collection practices. We discuss diff erent ways to tackle the limitations present in current detection tools to increase developers ’
WiFi-Sleep: Sleep Stage Monitoring Using Commodity Wi-Fi Devices

Sleep monitoring is essential to people’s health and wellbeing, which can also assist in the diagnosis and treatment of sleep disorder. Compared with contact-based solutions, contactless sleep monitoring does not attach any device to the human body; hence, it has attracted increasing attention in recent years. Inspired by the recent advances in Wi-Fi-based sensing, this article proposes a low-cost and nonintrusive sleep monitoring system using commodity Wi-Fi devices, namely, WiFi-Sleep. We leverage the fine-grained channel state information from multiple antennas and propose advanced fusion and signal processing methods to extract accurate respiration and body movement information. We introduce a deep learning method combined with clinical sleep medicine prior knowledge to achieve four-stage sleep monitoring with limited data sources (i.e., only respiration and body movement information). We benchmark the performance of WiFi-Sleep with polysomnography, the gold reference standard. Results show that WiFi-Sleep achieves an accuracy of 81.8%, which is comparable to the state-of-the-art sleep stage monitoring using expensive radar devices.