Miracle-dz/UniFAR-FTUs huggingface dataset:
Open source map matching with Markov decision processes: A new method and a detailed benchmark with existing approaches

Map matching is a widely used technology for mapping tracks to road networks. Typically, tracks are recorded using publicly available Global Navigation Satellite Systems, and road networks are derived from the publicly available OpenStreetMap project. The challenge lies in resolving the discrepancies between the spatial location of the tracks and the underlying road network of the map. Map matching is a combination of defined models, algorithms, and metrics for resolving these differences that result from measurement and map errors. The goal is to find routes within the road network that best represent the given tracks. These matches allow further analysis since they are freed from the noise of the original track, they accurately overlap with the road network, and they are corrected for impossible detours and gaps that were present in the original track. Given the ongoing need for map matching in mobility research, in this work, we present a novel map matching method based on Markov decision processes with Reinforcement Learning algorithms. We introduce the new Candidate Adoption feature, which allows our model to dynamically resolve outliers and noise clusters. We also incorporate an improved Trajectory Simplification preprocessing algorithm for further improving our performance. In addition, we introduce a new map matching metric that evaluates direction changes in the routes, which effectively reduces detours and round trips in the results. We provide our map matching implementation as Open Source Software (OSS) and compare our new approach with multiple existing OSS solutions on several public data sets. Our novel method is more robust to noise and outliers than existing methods and it outperforms them in terms of accuracy and computational speed.
Cavity-Filter-Based 3-D-Printed Gain-Filtering Transmitarray for Multibeam Applications

In this article, a full-metal transmitarray (TA) is proposed with gain-filtering characteristics. The units of the proposed TA are designed based on a square waveguide filter with different orders and cavity widths, but the same passband. The phase variation in the proposed TA is achieved by the large group velocity variation in the evanescent mode in the coupling cavity. Hence, the TA unit can achieve gain filtering and wavefront manipulation simultaneously. To verify the performance of the proposed design, a multibeam TA prototype is designed and fabricated at a center frequency of 26.0 GHz. The size of the TA is $156.0\times 156.0\times116.5$ mm3 ( $13.5\,\,\lambda \times 13.5\,\,\lambda \times 10.1\,\,\lambda$ ). The measured results show that the TA can achieve five beams with the 2-D beam-scanning range of ±28°. It can realize gain-filtering response with the out-of-band suppression levels below −19.0 dB in the main beam directions. In addition, due to the low-loss full-metal waveguide structures, the TA can achieve a maximum aperture efficiency of 45.1%. In our opinion, the high transmission coefficient, passive beam-scanning, and gain-filtering characteristics of the TA make it a good candidate for low-cost millimeter-wave communication and sensing applications.
DRIVING MODE SWITCHING MECHANISM BASED ON REINFORCEMENT LEARNING

Autonomous driving technology can improve traffic efficiency and safety, making the driving process more convenient and comfortable, thus increasing road safety and reducing environmental pollution. In this study, we explore the mode switching problem between automatic and manual driving and propose a driving mode switching mechanism based on deep reinforcement learning. First, we study the background on driving scenes based on safety degree calculation. Then, a real-time online switching mechanism based on deep reinforcement learning is presented. Finally, the proposed algorithm’s effectiveness is verified using a simulation platform. The simulation results show that based on the analysis of lateral position deviation, heading angle deviation, and safety index data, the deep RL method proposed in this project can effectively realize the switch between manual and automatic driving modes. As the results, the mode switching strategy can respond well to the vehicle’s lateral position deviation, heading angle deviation, and longitudinal safety degree and thus improve vehicle operation safety.
Crotoxin Modulates Macrophage Phenotypic Reprogramming

Macrophage plasticity is a fundamental feature of the immune response since it favors the rapid and adequate change of the functional phenotype in response to the pathogen or the microenvironment. Several studies have shown that Crotoxin (CTX), the major toxin of the Crotalus durissus terrificus snake venom, has a long-lasting antitumor effect both in experimental models and in clinical trials. In this study, we show the CTX effect on the phenotypic reprogramming of macrophages in the mesenchymal tumor microenvironment or those obtained from the peritoneal cavity of healthy animals. CTX (0.9 or 5 μg/animal subcutaneously) administered concomitantly with intraperitoneal inoculation of tumor cells (1 × 107/0.5 mL, injected intraperitoneally) of Ehrlich Ascitic Tumor (EAT) modulated the macrophages phenotype (M1), accompanied by increased NO• production by cells from ascites, and was evaluated after 13 days. On the other hand, in healthy animals, the phenotypic profile of macrophages was modulated in a dose-dependent way at 0.9 μg/animal: M1 and at 5.0 μg/animal: M2; this was accompanied by increased NO• production by peritoneal macrophages only for the dose of 0.9 μg/animal of CTX. This study shows that a single administration of CTX interferes with the phenotypic reprogramming of macrophages, as well as with the secretory state of cells from ascites, influencing events involved with mesenchymal tumor progression. These findings may favor the selection of new therapeutic targets to correct compromised immunity in different systems.
Agronomic Assessment on Paddy Field Using Aerial Imagery and Vegetation Indices: A Review

Rice is consumed by the majority of Southeast Asians, particularly in Malaysia itself. As years pass by, rice production has not to inclined to align with a number of populations in Malaysia that keeps growing, thus the self-sufficiency level (SSL) of 100% is not achieved until today. The intention of the government in expanding the granary areas for rice farming by concerning the SSL target to be achieved. Despite that, crop management specifically paddy farming is tedious and requires a lot of manpower. However, as the technology develops and gets sophisticated these days, a discipline that helps in crop management has been introduced over the years called remote sensing. Remote sensing is undoubtedly showed significant application in crop management. The vegetation indices (VIs) algorithm is a branch in remote sensing that enables researchers to evaluate vegetative covers on the ground from aerial view by using spectral measurements either qualitatively or quantitatively. The VIs obtains from the spectral response of the ground areas from the aerial view commonly composed of vegetation areas, soil brightness, various vegetation on the ground, canopy, environmental effects, shadow, and moisture level of soil and plants. Nonetheless, the favourable of remote sensing is the spatial-temporal which helps in determining changes of vegetation over a certain period. This also includes rice farming. Thus, this paper discusses and summarizes the VIs algorithm that was relevant in the application of rice planting. It proposes the popularity and relevance of the VIs algorithm in rice crop management.
A Novel Approach of Satellite Image Enhancement Using DWT Based on 2-Type Fuzzy Logic

: This study proposes a new approach to enhance the dark and low-contrast satellite images captured under poor illumination. Images are converted from RGB to HSV color space in order to separate the Hue (H), Saturation (S), and luminance (V) components. Enhancement is achieved in saturation and luminance components using Discrete Wavelet Transform (DWT) and 2-type fuzzy logic. DWT breaks the images into high and low-frequency sub-bands and results in approximation and detailed coefficients. The approximation coefficient consists of low-frequency components, which are further modified using the 2-type Fuzzy Logic technique. Fuzzy logic is basically a point operation-based technique based on the fact that human perceived brightness characteristic is not linear. Inverse Wavelet Transform is used to achieve the enhanced saturation components. The luminance component (V) is passed through class-limited adaptive histogram equalization. All the enhanced components are then combined to get the enhanced image and finally reconverted to RGB color space. The proposed scheme significantly works well for enhancing and sharpening dark and low-contrast satellite images. The experimental results obtained by the proposed method show improved performance in terms of PSNR, MSE, mean, and variance.
Integrated Modeling of Causes and Consequences of Forward-Looking Information Disclosure in Annual Reports

The forward-looking information disclosure presents the information that enables the beneficiaries to evaluate a company's future that might involve financial forecasts and uncertainty. This affects the company's performance and decreases the stock return volatility. The present research aims at integrated modeling of the causes and consequences of forward-looking information disclosure. This study is an applied descriptive correlational research. The sample included 93 companies listed on the Tehran stock exchange from 2013 to 2019. The impact of all the causes of forward-looking information disclosure and its consequences was extracted by applying the structural equation
Production and performance assessment of a SARS-CoV-2 biomimetic in a verification program for pandemic readiness

During the early stages of the Covid-19 pandemic in South Africa, one of many challenges included availability of control material proficiency testing programs. Control material utilising live SARS-CoV-2 or RNA extracted from cell culture was either biohazardous and costly, particularly in resource limited settings. Here, we report the development and application of a non-infectious SARS-CoV-2 biomimetic Mycobacterium smegmatis strain that mimics a positive result in the GeneXpert SARS-CoV-2 Xpert Xpress cartridge. Nucleotide sequences located in genes encoding the RNA-dependent RNA polymerase, the nucleocapsid and the envelope proteins were used. The resulting biomimetic was prepared as a Quality Control specimen and distributed to laboratories in South Africa for validation prior to testing of clinical specimens. Between April 2020 and December 2020, a total of 151 instruments were validated to bring Covid-19 mass testing online. These instruments capacitated the country to perform tests in 2532 modules. False negative or false positive findings reflected issues such as workflow/technician error or other related technical issues. This non-infectious, easily scalable control material became available within two months after the start of the pandemic in South Africa and represents a useful approach to consider for other diseases and future pandemics.
An Experimental and Numerical Study of Crosstalk Effects in PMUT Arrays

This study provides a comprehensive characterization of a 4 $\times $ 4 piezoelectric micromachined ultrasonic transducer (PMUT) array suited for in-air applications. Crosstalk can be viewed as a lack of isolation among the transducers, with possible reasons, including the electrical, acoustic, and structural coupling among the transducers. This study focuses on acoustic coupling as the primary cause of crosstalk, since the influence of electrical and structural coupling on crosstalk is shown to be negligible by comparing experimental tests and numerical analysis conducted in vacuum and in air. It is expected that acoustic coupling among diaphragms occurs due to air-connected cavities. Consequently, several scenarios are investigated in which the cavities are either partially or completely acoustically disconnected. The computed response spectra of the PMUTs demonstrate that the presence of secondary peaks, which indicated the presence of crosstalk, is diminished when the PMUTs are decoupled partially or completely as compared with an open cavity. The conducted acoustic tests also demonstrated that crosstalk impacts the intensity and directivity of the acoustic wave produced by the array.
Time-lapse simulator-to-seismic study - Forties field, North Sea.

Summary A Simulator-to-Seismic (S-to-S) study is conducted over the Forties field, North Sea, by combining petrophysical, engineering and geophysical data into an integrated workflow. Based on a calibrated rock physics model, static and dynamic properties from a reservoir model are converted into time-lapse synthetic seismic attributes that can be used in conjunction with conventional seismic attributes to get more insights into the interpreted 4D anomalies. The aim of the study is to better understand the drainage patterns of the reservoir and help validate the planned position of additional producer wells to ultimately reduce drilling risks.
The Las Salinas palaeo-lagoon in the Sechura Desert (Peru): Evolution during the last two millennia

The Sechura Desert provides a unique example of a vast palaeo-lagoon system on the Peruvian coast that was active during the first millennium AD. Reconstruction of coastal evolution is made possible by the good resolution of the sedimentary records of the Las Salinas Noroeste coastal plain. Evidence from morphostratigraphy and sedimentary facies indicates marked environmental diversity between the 3rd and the 8th centuries AD and a wide variability of sedimentary dynamics: lagoon foreshores received alternately fine distal marine sediments and coarser continental sediments in pro-deltaic sheets. Evaporation phases periodically occurred in these foreshores causing the formation of salt crusts. After a last high water level in the 8th century AD, the lagoon ultimately dried out and remains dry today. The malacofauna and sedimentary facies indicate that marine marshes bordered by vegetation, perhaps mangrove, developed in the higher parts of these lagoons. This palaeogeography is explained by the progressive build-up of a sand bar which started at least in the middle Holocene. From the 3rd to 8th centuries AD, the lagoon had limited connection to the sea in its northern end and hosted a warm-water and productive ecosystem that was exploited by pre-Hispanic populations. Wetter conditions in the Andes and occasional El Niño rainfalls maintained the lagoon during this period. The freshwater input likely stopped in the 8th century AD, which led to the closing of the shore bar under the influence of the longshore drift rapidly followed by the drying up of the lagoon, and the abandonment of the archaeological site.
Remote sensing image semantic segmentation method based on small target and edge feature enhancement

Abstract. Semantic segmentation of high-resolution remote sensing images based on deep learning has become a hot research topic and has been widely applied. At present, based on the structure of the convolutional neural network, when extracting target features through multiple layer convolutional layers, it is easy to cause the loss of small target features and fuzzy boundary of ground object classification. Therefore, we propose a remote sensing image semantic segmentation method P-Net to detect small target and enhance edge feature. The proposed network was based on an Encoder-Decoder structure. The decoder included the following components: a progressive small target feature enhancement network (IFEN), a boundary thinning module (BRM), and a feature aggregation module (FIAM). Firstly, the dense side output features of the encoder network were utilized to learn and acquired small target feature information and target edge features. Secondly, the pyramid segmentation attention module was introduced to effectively extract fine-grained and multi-scale spatial information. This module enhanced the feature expression of small targets and obtained high-level semantic feature information. The boundary refinement module was designed to refine the low-level spatial feature information extracted by the encoder. Finally, in order to improve the accuracy of remote sensing image object segmentation boundaries, skip connections were used to fuse high-level semantic information and low-level spatial information acrossed layers. These skip connections had the same spatial resolution but different semantic information. In this paper, six evaluation indices including mean intersection over union, frequency weighted intersection over union, pixel accuracy, F1, recall, and precision were used to verify on two public datasets of high-resolution remote sensing images, Gaofen image dataset (GID) and wuhan dense labeling dataset (WHDLD). In the GID dataset, each index reached 78.90%, 78.87%, 87.76%, 87.74%, 87.51%, and 88.04%, respectively; in the WHDLD dataset, each index reached 63.21%, 75.20%, 84.67%, 75.79%, 76.56%, and 75.45%, respectively. The results show that the performance of proposed method is better than that of DeepLabv3+, U-NET, PSPNet, and DUC_HDC methods. More precisely, the recognition performance of small target features is better, and the boundary obtained between object categories is clearer.
Characteristics of Fenghuoshan Group's material and its era discussion

The paper about the age of Fenghuoshan group was a debated focus all along, based on the document, there are two different standpoints on it. The one regards that it belongs to Cretaceous period, and the other think that it belongs to Eogene period. According to Fenghuoshan group′s geological characteristics, geologic horizon contact relation, geomorphological characteristics, metamorphic characteristics, the age of fossil and relative age of intrusive body in 1∶250000 areal geological survey, we decide to put it in Late Cretaceous epoch.
Influence of distance from conspecific and heterospecific co-flowering plants on pollination and fecundity in the nectarless orchid Dactylorhiza sambucina

ABSTRACT Background The relative influence of both conspecific and heterospecific plant density on the fecundity of generalist rewardless plants is unclear. Aims To test whether distance from both conspecific and heterospecific plants influence pollen removal, deposition, and fruit set in the nectarless orchid, Dactylorhiza sambucina that co-flowers with the rewarding Ranunculus apenninus. Methods I experimentally translocated D. sambucina inflorescences and measured pollen removal and deposition rates. I measured plant height and distance to D. sambucina and R. apenninus plants in 30 D. sambucina patches of varying density. I quantified the proportion of pollen removed, pollinia deposited, and fruit set and tested whether these vary according to plant height and distance to both D. sambucina and R. apenninus. Results Translocated inflorescences outside the population had a higher proportion of pollen removal than control plants within the population, while pollinia deposition rates did not differ. Increased D. sambucina height increased pollen removal rates, while increasing distance from R. apenninus resulted in both increased pollen deposition and fruit set. Conclusion Pollination and fecundity of a nectarless orchid may increase with increasing distance from rewarding heterospecifics. This study improves our understanding of how the fecundity of rewardless plants is influenced by co-flowering plants.
CENTRIFUGAL MODELING OF REINFORCED EMBANKMENTS ON SOFT CLAY

The geosynthetic reinforcing techniques have been widely used nowadays in the design of embankments and foundations on soft clay to maintain stability during or immediately after the construction of the embankment. However,the behaviour of reinforcements on soft clay is far from clear. The objective is to investigate the behaviours of reinforced embankment on soft clay using the technique of centrifugal modelling and to provide a rigorous basis for optimum design of embankments. A series of centrifuge model tests for both unreinforced and reinforced foundations are conducted and behaviours of the subsoil are observed. Based on these tests,the distributions of the horizontal displacement and vertical displacement as well as the dissipation of the excess pore pressure in the clay foundation are obtained. In particular,the effectiveness of the base reinforcement is examined by comparing its behaviour with that of an unreinforced clay foundation. A new technique for measuring the tension induced in the reinforcement was developed and used in centrifuge tests. It is found that a geosynthetic reinforcement is effective in preventing the lateral displacement of the clay foundation,and therefore,may contribute towards the stability of the embankment. In general,the extension of the reinforcement and the settlement of the embankment are consistent,and in the present study,the mobilization of the tension reaches around 52% of the tensile strength.
Nesting of Data Assimilation Cycles into the Recursive Model Predictions

The paper addresses the important problem of model errors impact on attempts for realistic modelling of pollution propagation in the atmosphere. The mathematical model always remains only a simplification of the complex physical phenomena and a significant extent of the uncertainties involved can degrade credibility of the model predictions. The article itemizes particular sources of the model errors and illustrates the influence of variability of the most important meteorological inputs. Stochastic character of the task calls for introduction of advanced statistical assimilation techniques based on merging of all available associated information including real observations incoming from terrain.
The Mesopotamian Delta in the First Millennium, B.C.

Reconstitution de la geographie du Delta mesopotamien pendant le premier millenaire, a la lumiere des donnees historiques et archeologiques: notamment a l'epoque de Sennacherib (ca. 696 av. J.-C.), a l'epoque d'Alexandre.