Miracle-dz/UniFAR-FTUs huggingface dataset:
Review on Lane Detection and Tracking Algorithms of Advanced Driver Assistance System

Autonomous vehicles and advanced driver assistance systems are predicted to provide higher safety and reduce fuel and energy consumption and road traffic emissions. Lane detection and tracking are the advanced key features of the advanced driver assistance system. Lane detection is the process of detecting white lines on the roads. Lane tracking is the process of assisting the vehicle to remain in the desired path, and it controls the motion model by using previously detected lane markers. There are limited studies in the literature that provide state-of-art findings in this area. This study reviews previous studies on lane detection and tracking algorithms by performing a comparative qualitative analysis of algorithms to identify gaps in knowledge. It also summarizes some of the key data sets used for testing algorithms and metrics used to evaluate the algorithms. It is found that complex road geometries such as clothoid roads are less investigated, with many studies focused on straight roads. The complexity of lane detection and tracking is compounded by the challenging weather conditions, vision (camera) quality, unclear line-markings and unpaved roads. Further, occlusion due to overtaking vehicles, high-speed and high illumination effects also pose a challenge. The majority of the studies have used custom based data sets for model testing. As this field continues to grow, especially with the development of fully autonomous vehicles in the near future, it is expected that in future, more reliable and robust lane detection and tracking algorithms will be developed and tested with real-time data sets.
Effect of Excess Atomic Volume on Crack Evolution in a Deformed Iron Single Crystal

This paper presents a molecular dynamics study of how the localization and transfer of excess atomic volume by structural defects affects the evolution and self-healing of nanosized cracks in bcc iron single crystals under different mechanical loading conditions at room temperature. It is shown that deformation is initially accompanied by a local growth of the atomic volume at the crack tips. The crack growth behavior depends on whether the excess atomic volume can be transferred by structural defects from the crack tips to the free surface or other interfaces. If an edge crack is oriented with respect to the loading direction so that dislocations are not emitted from its tip or only twins are emitted, then the sample undergoes a brittle-ductile fracture. The transfer of the excess atomic volume by dislocations from the crack tips prevents the opening of edge cracks and is an effective healing mechanism for nanocracks in a mechanically loaded material.
Une approche pour la sélection de variables stables : application à l’encodage des diagnostics secondaires

R ESUME Dans cet article, nous proposons une approche pour sélectionner des variables stables dans le contexte de prédiction des diagnostiques secondaires en partant d’une base de données médico-économique, en l’occurrence le PMSI. Les résultats de prédiction se présentent sous forme de guides pour l’activité d’encodage des diagnostiques secondaires dans les départements d’information médicale (DIM). L’approche que nous proposons dans ce papier consiste à exploiter les paradigmes ensemblistes sur les sources de données réduites et équilibrées pour déduire un ensemble stable et fiable de variables utiles à la prédiction . Cet ensemble est construit de façon très indépendante par rapport à l’échantillon de données utilisé pour l’apprentissage du modèle. La qualité des variables est déduite en fonction de la qualité de prédiction des algorithmes de ML. L’évaluation de notre approche sur les données de PMSI montre le réel intérêt de cette proposition et ouvre le débat sur l’applic ation de ces méthodes à ces sources de données très
Trophic mediation and ecosystem stability: An assessment using qualitative network models

Nontrophic interactions can contribute to negative and positive feedbacks within a community, thus affecting likelihood of regime shifts; however, assessing the nature and importance of these effects in a network remains challenging, especially for pelagic ecosystems. Here, we present a qualitative modeling approach for assessing the importance of different effects and resultant feedbacks for community stability, using a Southern Ocean example. A potentially important positive feedback in the Southern Ocean ecosystem involves production of a chemical cue, dimethyl sulfide (DMS), by some phytoplankton. Production of DMS can promote phytoplankton growth by attracting predators of phytoplankton‐grazers, and nutrients released as feces from those predators help fertilize the water column. We explored how uncertainties in the nature of this feedback affect community stability in a set of small, community models. We found that stability varied substantially depending on how the community was modeled, but that the interactions most important for determining stability were consistent across all models. Model stability was sensitive to the strength of phytoplankton competition, controls on phytoplankton, DMS production and release, and predator attraction to DMS, suggesting that the community could be destabilized by perturbation affecting these interactions. Incorporating DMS‐mediated feedbacks into a larger Southern Ocean network had a moderate impact on stability characteristics and altered the trophic level at which the system would be most vulnerable to perturbation.
Fast digital multi-beam search method for active phased array antenna system with full azimuth beam steering

This paper proposes a multi-beam search method based on an active phased array antenna system using digital beamforming. It includes initial beamforming, valid beam selection, and beam angle estimation using phase comparison mono pulses for multi-channel signals. To verify DoA estimation error, simulation and measurement are performed using the proposed antenna system. As a result, we confirm the performance of estimating each channel's angle and the beam directional error within 0.5°.
The Dynamic Change of Immune Checkpoints and CD14+ Monocytes in Latent Tuberculosis Infection

Controlling latent tuberculosis infection (LTBI) is important for preventing tuberculosis (TB). However, the immune regulation of LTBI remains uncertain. Immune checkpoints and CD14+ monocytes are pivotal for immune defense but have been scarcely studied in LTBI. We prospectively enrolled participants with LTBI and controls from January 2017 to December 2019. We measured their CD14+ monocytes and the expression of immune checkpoints, including programmed death-1 (PD-1), cytotoxic T-lymphocyte-associated protein 4 (CTLA-4), and T cell immunoglobulin mucin domain-containing-3 (TIM3) on T lymphocytes in peripheral blood mononuclear cells before and after LTBI treatment. A total of 87 subjects were enrolled, including 29 IGRA-negative healthy controls (HC), 58 in the LTBI group (19 without chronic kidney disease (non-CKD), and 39 with end-stage renal disease (ESRD)). All PD-1, CTLA-4, and TIM3 on lymphocytes and monocytes were higher in the LTBI group than that in the HC group. Total CD14+ monocytes were higher and PD-L2+CD14+ over monocytes were lower in patients with LTBI-non-CKD than that in the HC group. After LTBI treatment, CD14+ monocytes, TIM3+ on CD4+ and monocytes, and CTLA-4 on lymphocytes decreased significantly. Multivariable logistic regression indicated that CD14+ monocytes was an independent factor for LTBI-non-CKD from the HC group, whereas PD-L2+CD14+ monocytes and TIM3+ monocytes were significant for LTBI-ESRD from the HC group. In conclusion, LTBI status was associated with increasing CD14+ monocytes plus low PD-L2 expression. By contrast, increased expression of immune checkpoints over all immune cells might be due to Mycobacterium tuberculosis related immune exhaustion, which decreased after treatment.
Pistis: Issuing Trusted and Authorized Certificates with Distributed Ledger and TEE

The security of HTTPS fundamentally relies on SSL/TLS certificates issued by Certificate Authorities (CAs), which, however, are vulnerable to be compromised to issue unauthorized certificates (i.e., certificates issued without domains' permission). Current countermeasures such as Certificate Transparency (CT) can only detect unauthorized certificates rather than preventing them. In this paper, we present Pistis, a framework for issuing authorized and trusted certificates with the distributed ledger and Trusted Execution Environment (TEE) technology. In Pistis, TEE nodes validate whether the domain in a requested certificate passes the domain ownership validation (i.e., under corresponding applicants' control) and submit attested results to a smart contract in the distributed ledger. The smart contract issues the certificate to the applicant when an attested result shows a pass. Therefore, Pistis can ensure its issued certificates are authorized due to the domain ownership validation mechanism in the TEE. Furthermore, as the issued certificates are stored in a Merkle Patricia Tree (MPT) in Pistis, they are trusted and can be verified by a normal user easily. The security of Pistis is formally proved in the Universally Composable (UC) framework. Compared with state of the art, Pistis avoids potential damages by preventing unauthorized certificates from issuing.
Metal-Based Additive Manufacturing Condition Monitoring: A Review on Machine Learning Based Approaches

The metal-based additive manufacturing (MAM) processes have great potential in wide industrial applications, for their capabilities in building dense metal parts with complex geometry and internal characteristics. However, various defects in the MAM process greatly affect the precision, mechanical properties and repeatability of final parts. These defects limit its application as a reliable manufacturing process, especially in the aerospace and medical industries where high quality and reliability are essential. MAM process monitoring provides a technical basis for avoiding and eliminating defects to improve the build quality. Based on of the nature of the MAM build defects, this article conducts a thorough investigation of monitoring methods, and proposes a machine learning (ML) framework for process condition monitoring. According to the structure of ML models, they are divided into shallow ML-based and deep learning-based methods. The state-of-the-art ML monitoring approaches, as well as the advantages and disadvantages of their algorithmic implementations, are discussed. Finally, the prospects of ML based process monitoring researches are summarized and advised.
North Atlantic air pressure and temperature conditions associated with heavy rainfall in Great Britain

Severe flooding in the United Kingdom is often linked to the occurrence of heavy rainfall events, which can be characterized by the synoptic scale meteorological conditions over the North Atlantic region. Seasonal heavy rainfall events (summer and winter 1‐day maxima) were extracted from 125 locations across Great Britain over the period 1950–2017. For each event, anomaly sea‐level pressure and 2 m air temperature conditions across the North Atlantic sector were extracted. In contrast to earlier studies, these two datasets were combined and clustered to identify how the pressure and temperature conditions co‐vary within each half‐year to produce heavy rainfall events. Distinctly different spatial patterns were found for four classes in summer and for three classes in winter. For all classes there is a negative sea‐level pressure anomaly centred over or near the British Isles. However, whereas in summer the low pressures are associated with either predominantly cold or warm anomalies over most of the North Atlantic, in winter two phases of a smaller‐scale four‐pole temperature pattern emerges. Nevertheless, for one of the winter classes the cold anomaly over the northwest Atlantic is so deep, persistent and widespread that, unusually for the winter season, a significant relationship between the class's frequency of occurrence and the Atlantic Multidecadal Oscillation (AMO) index is found (r = −.39). Further, for both seasons heavy rainfall occurs when the AMO and the North Atlantic Oscillation (NAO) are in opposing phases. Particularly, positive NAO and negative AMO result in heavy rainfall in western Britain. Two classes in each season are consistent with positive and negative phases of the NAO, and the two non‐NAO summer classes are associated with a northward extension of the subtropical high pressure and heavy rainfall in the southeast. The association between heavy rainfall and large‐scale circulation and temperature drivers can find application in, for example, weather generators.
Developing the Smart Sorting Screw System Based on Deep Learning Approaches

The deep learning technique has turned into a mature technique. In addition, many researchers have applied deep learning methods to classify products into defective categories. However, due to the limitations of the devices, the images from factories cannot be trained and inferenced in real-time. As a result, the AI technology could not be widely implemented in actual factory inspections. In this study, the proposed smart sorting screw system combines the internet of things technique and an anomaly network for detecting the defective region of the screw product. The proposed system has three prominent characteristics. First, the spiral screw images are stitched into a panoramic image to comprehensively detect the defective region that appears on the screw surface. Second, the anomaly network comprising of convolutional autoencoder (CAE) and adversarial autoencoder (AAE) networks is utilized to automatically recognize the defective areas in the absence of a defective-free image for model training. Third, the IoT technique is employed to upload the screw image to the cloud platform for model training and inference, in order to determine if the defective screw product is a pass or fail on the production line. The experimental results show that the image stitching method can precisely merge the spiral screw image to the panoramic image. Among these two anomaly models, the AAE network obtained the best maximum IOU of 0.41 and a maximum dice coefficient score of 0.59. The proposed system has the ability to automatically detect a defective screw image, which is helpful in reducing the flow of the defective products in order to enhance product quality.
DRESSING IN OTHER PEOPLE’S CLOTHES. CHANGES IN CLOTHING DURING EVANGELIZATION OF RAPA NUI: A DIALOGIC EXPRESSION (1864-1877)

In all human societies, textiles play important roles in social, economic, and religious life. As in other Polynesian societies, on Rapa Nui (Easter Island) in the second half of the 19 th century, textiles were important locally and served, above all, as objects of exchange with foreign visitors. This article examines cultural transformations that occurred on Rapa Nui, as reflected in the use and signification of textiles, particularly in the use of introduced cloth and clothing during the times of the first missions and the first colonial agents. Our analysis is based on information taken from missionary writings and from the reports of travelers and explorers who visited the island during that period. Understanding that material culture cannot be separated from the cultural practices in which it is embedded, our analysis will focus on accounts referring to material objects as elements that reflect the social and cultural transformations of the historic context in which they were created. We argue that the islanders redefined Western textiles that were introduced, using them in ritual contexts appropriate to the island’s culture. European textiles acted as status markers within a new social organization, and also served as sociopolitical markers among island groups (Christian converts and non-converts).
Laying the Foundation of Medical Professionalism among Pre-clinical Students: Importance of Reflection

This article was migrated. The article was marked as recommended. Introduction: The escalating problem of unprofessionalism calls for teaching medical professionalism in a manner that should lead to deeper learning. Early clinical exposure (ECE) to an Intensive Care Unit (ICU) presents the issues pertaining to medical professionalism to the students in a more explicit and emotionally challenging manner. And reflection note writing evokes the critical process of thought and analysis required for learning. We conducted the present study to sensitize the pre-clinical students towards medical professionalism using these two tools, ECE and Reflection. Methods: Two hundred students of 1st MBBS were given an Objective Structured Clinical Examinations (OSCE). The students were then taken for ECE to an ICU. There, the students observed different ongoing activities and critical patients, a doctor discussed some cases with them, and they also interacted with the relatives of patients admitted in the ICU. Thereafter, students wrote a ‘reflection’ note describing what did you see? so what? and now what? Students were again given an OSCE, similar to the one given before the ECE, for assessing any change in their professional behaviour.Analysis of reflection notes was done thematically and of OSCE scores using paired t-test (p<0.05). Results: The analysis of reflection notes revealed the budding of different elements of professionalism among the students. Post-visit OSCE scores also showed significant improvement. Conclusion: Incorporation of reflection note writing along with ECE is helpful in laying the foundation of medical professionalism among pre-clinical students.
Full Length Transcriptome Highlights the Coordination of Plastid Transcript Processing

Plastid gene expression involves many post-transcriptional maturation steps resulting in a complex transcriptome composed of multiple isoforms. Although short-read RNA-Seq has considerably improved our understanding of the molecular mechanisms controlling these processes, it is unable to sequence full-length transcripts. This information is crucial, however, when it comes to understanding the interplay between the various steps of plastid gene expression. Here, we describe a protocol to study the plastid transcriptome using nanopore sequencing. In the leaf of Arabidopsis thaliana, with about 1.5 million strand-specific reads mapped to the chloroplast genome, we could recapitulate most of the complexity of the plastid transcriptome (polygenic transcripts, multiple isoforms associated with post-transcriptional processing) using virtual Northern blots. Even if the transcripts longer than about 2500 nucleotides were missing, the study of the co-occurrence of editing and splicing events identified 42 pairs of events that were not occurring independently. This study also highlighted a preferential chronology of maturation events with splicing happening after most sites were edited.
Homomorphic Encryption: The ‘Holy Grail’ for Big Data Analytics and Legal Compliance in the Pharmaceutical and Healthcare Sector?

The pharmaceutical and healthcare sector is a prime target for cybercriminals around the world. These cyber-attacks represent significant challenges in the context of data protection and data security. The General Data Protection Regulation (GDPR) imposes strict rules regarding the processing and analysis of personal data. In conventional approaches, data analysts request data from various sources. Then, they anonymise or pseudonymise the data using various tools and techniques. These methods often use powerful algorithms to ensure a high level of security. However, these methods tend to either reduce the quality of data for further analysis or they expose the data while decrypting it for analysis. Ho-momorphic Encryption (HE) has recently been touted as the ‘Holy Grail’ of cryptography since it allows the analysis of big data sets without ever needing to decrypt and thus compromising the confidentiality of the data. This provides a whole new layer of protection and at the same time allows the processing of data for secondary use and scientific research. While HE is not a new technology, it is still in the early stages of development. In this piece, we will introduce a new automated tool for searching and analysing encrypted data using HE techniques, which is being developed within the scope of the EnergyShield project. 1
National Business Cultures: Research Methodology, Content and Role in Provision of International Entrepreneurship

Characterization of national business cultures on the basis of identifying the most typical consumer strata in the frames of individual countries and describing the cultural codes of countries by disclosing the contents of the selected triad “Logical Emotionality” The object of analysis is a complex of methodological principles of economic comparative studies: the studies of national business cultures. The evolution of managerial, communicative and marketing approaches in their consideration is being comprehended. The definition of “national business cultures” is substantiated and the essential phenomena, processes and developmental trends that are reflected in the definition are revealed.
Editor’s Introduction

Editor’s Introduction v on the revitalization of downtown neighborhoods in the Middle Susquehanna River valley in Pennsylvania. Victoria Chanse examines the contribution of TDAR perspectives for organizing and managing multiple volunteer groups in a regional watershed stewardship initiative in Contra Costa County, California. Three of the cases occur in rural settings. Christine Carlson, John Koepke, and Mirja Hanson from the University of Minnesota offer TDAR perspectives on their efforts to organize and coordinate the activities of the Laurentian Vision Partnership in reframing iron ore mining as a tool to make future ecologies and economies on the Mesabi Iron Range in northern Minnesota. In Entlebuch, Switzerland, Olaf Schroth, Ulrike Wissen Hayek, Eckart Lange, Stephen R. J. Sheppard, and Willy A. Schmid of the Institute for Spatial and Landscape Planning, ETH Zurich and the University of British Columbia examine the contribution of interactive landscape visualizations for constructing transdisciplinary knowledge, dialogue, and consensus building in the search for solutions to rural landscape planning problems. Working with the Wisconsinbased Green Communities and Green Affordable Housing in Indian Country Initiative, Susan Thering integrates a grounded theory approach informed by social science literature to document and evaluate the intangible outcomes of transdisciplinary partnerships with Native American communities. Finally, two of the cases are statewide in their geographic focus. Cheryl Doble and Maren King of the State University of New York College of Environmental Science and Forestry discuss lessons learned from the creation and operation of a statewide partnership to address remediation and redevelopment of small city waterfronts throughout New York State. Through his work with the Pennsylvania Advocates for Nutrition and Activity, Michael Rios, of the University of California, Davis, demonstrates the utility of social ecological approaches sensitive to various scales of social and spatial production to inform the development and evaluation of transdisciplinary approaches in the context of an obesity prevention initiative in Pennsylvania. We welcome the addition of Nicole Peterson to our editorial staff as an editorial assistant. Before commencing her graduate studies in Landscape Architecture at the University of Minnesota, Nicole was an English and Media Studies major at St. Olaf College in Northfi eld, MN.