Types Of Artifacts Research Articles

Tool wielding and activities at the Middle Paleolithic site of Nesher Ramla, Israel: A use-wear analysis of major tool types from unit III

This paper communicates the results of a detailed use-wear analysis of flint tools from Unit III of Nesher Ramla, central Israel, an open-air Middle Paleolithic site, dated to Marine Isotope Stage 5. The analyzed sample consists of 966 artifacts that represent major techno-typological categories; scrapers, tools with a lateral tranchet blow, naturally backed knives and other Middle Paleolithic artifact types. Most tools were associated with bone working activities, mainly scraping and cutting, suggesting both consumption and non-consumption-related practices. Results also suggest extensive butchering activities, but other applications are less common, especially the underrepresentation of armature, and plant and hide working is noteworthy. All in all, these patterns suggest a narrow range of activities. Most tools were used by their sharp edge, while the retouched edges bore weak use-related patterns. It is assumed that in some cases, the retouch served to facilitate the grip. The most widely used tools in Nesher Ramla were the naturally backed knives that according to technological studies were one of the goals of knapping at Nesher Ramla. Tools with a lateral tranchet blow, representing a cultural marker of the Nesher Ramla inhabitants, show evidence of multiple use of both retouched and non-retouched edges shaped by the lateral blow. Hafting traces are relatively rare in the analyzed sample.

OCT Angiography Artifacts in Glaucoma

To determine the prevalence of different types of artifacts seen in OCT angiography (OCTA) images of healthy and glaucoma eyes and evaluate the characteristics associated with poor-quality images. Retrospective study. A total of 649 eyes of 368 healthy, glaucoma suspect, and glaucoma patients. Angiovue (Optovue Inc) high-density (HD) and non-HD optic nerve head and macula OCTA images of participants were evaluated by 4 expert reviewers for the presence of different artifacts, including eye movement, defocus, shadow, decentration, segmentation error, blink, and Z offset in the superficial vascular layer. Each OCTA scan was designated to have good or poor quality based on the presence of artifacts. The association of demographic and ocular characteristics with the likelihood of obtaining poor-quality OCTA images was evaluated. The prevalence of OCTA artifacts and the factors associated with increased likelihood of capturing poor-quality OCTA images. A total of 5263 OCTA images were evaluated. Overall, 33.9% of the OCTA images had poor quality. The majority of images with acceptable quality scores (QS ≥ 4) had no artifacts (76.6%). Other images had 1 (13.6%) or 2 or more artifacts (9.8%). Older age (P < 0.001), male gender (P= 0.045), worse visual field mean deviation (P < 0.001), absence of eye tracking (P < 0.001), and macular scan area (P < 0.001) were associated with a higher likelihood of obtaining poor-quality images. In images with acceptable QS, the commercially available quality measures including QS and signal strength index had the area under the receiver operating characteristic curves of 0.65 (95% confidence interval [CI], 0.62-0.69) and 0.70 (95% CI, 0.68-0.73) to detect good-quality images, respectively. OCTA artifacts associated with poor-quality images are frequent, and their prevalence is affected by ocular and patient characteristics. One should not rely solely on the quantitative assessments that are provided automatically by OCTA instruments. A systematic scan review should be conducted to ensure appropriate interpretation of OCTA images. Given the high prevalence of poor-quality OCTA images, the images should be reacquired whenever an apparent and correctable artifact is present on a captured image.

The potential and problems of volumetric 3D modeling in archaeological stratigraphic analysis: A case study from Chlorakas-Palloures, Cyprus

3D digital recording technologies have become increasingly popular for rapid, cost-effective, and accurate archaeological documentation in the field. Despite improvements in 3D GIS software, three-dimensional reconstruction of archaeological stratigraphy has been slow to develop and is rarely utilized as a basis for spatial analysis post-excavation. This is partially owing to the technical and methodological challenges of creating accurate reconstructions of excavated stratigraphy, which restricts the analytical potential of 3D datasets. Volumetric 3D modeling could vastly improve how we understand and analyze archaeological deposits and stratigraphies by enabling a quantitative comparative analysis of per-volume density of artifact types between stratigraphic units.The presented case study examines the spatial articulation of the recorded stratigraphic units from three adjacent trenches excavated during the 2015–2017 field season at the Chalcolithic settlement site of Chlorakas-Palloures in Cyprus. Three vector-based 3D modeling methods using the existing 3D Analyst toolkit within the proprietary software ESRI ArcScene are evaluated for their effectiveness in volumetric representation of stratigraphy using total station (TS) data and photogrammetry models of archaeological features.The results of this study indicate that volumetric modeling can enhance the analytical potential of spatial data by visualizing and identifying patterns in excavated deposits and organizing and disseminating information about the excavation process in an intuitive, user-friendly interface. However, accurate volumetric modeling of all types of archaeological features requires a re-evaluation of conventional documentation procedures to capture the volume of excavated deposits rather than just the interfaces between them. Furthermore, efficient workflows using cost-effective and open source software must be developed to make this approach more accessible and effective for a wider archaeological community.

A new automated multi-stage system of non-local means and multi-kernel adaptive filtering techniques for EEG noise and artifacts suppression

Context. Electroencephalography (EEG) signals are contaminated with diverse types of noises and artifacts, which greatly distort EEG recording and increase the difficulty in obtaining accurate diagnosis. Objective. This paper investigates, for the first time, multi-kernel normalized least mean square with coherence-based sparsification (MKNLMS-CS) algorithm for suppressing different artifact components, and the 1D patch-based non-local means (NLM) algorithm for eliminating white and colored noises. Approach. A novel multi-stage system based on combining the NLM algorithm with the MKNLMS-CS algorithm is proposed for eliminating different noise and artifact sources by targeting each noise or artifact component in a single stage. Main Results. The proposed approach is applied to clinical real EEG data, and the results reveal the superior performance of the proposed system in removing white and colored noises, suppressing different artifact components, preserving the important and tiny features of the original EEG signal, and keeping the morphology of EEG frequency components. Significance. The proposed multi-stage design succeeds not only to suppress different artifact components and noise sources under low and high noise conditions, but also to achieve accurate sleep spindle detection from the filtered high-quality EEG signals. This demonstrates the usefulness of the proposed approach for obtaining high-resolution EEG signal from noisy and contaminated EEG recordings.

A Coarse/Fine Dual-Stage Motion Artifacts Removal Algorithm for Wearable NIRS Systems

Motivation: This paper proposes a motion artifact removal (MAR) algorithm and its evaluation method for wearable functional near infrared spectroscopy (fNIRS) system. Methods: Two types of motion artifacts (MAs) and their characteristics have been investigated, and a coarse/fine dual-stage MAR method is proposed, which can remove the MAs with different features and magnitudes to protect the original data from damage. In addition, an evaluation method is also proposed based on the classification of 4 mental tasks, which objectively quantize the performance of the MAR algorithms. Results: With the proposed MAR algorithm, the mental-task classification accuracy increased from 74.73% to 83.70% in average.

Cone-Beam Computed Tomography in Endodontics—State of the Art

Cone-beam computed tomography (CBCT) is an imaging modality with high-resolution diagnostic value that provides accurate and high-quality three-dimensional information on the elements of the maxillofacial complex. Therefore, this study aimed to present an up-to-date status of the main indications for the use of CBCT in endodontics, and to discuss its main limitations relative to diagnosis in endodontics. The data captured by CBCT devices and processed by a specific software programs create a reconstruction of the scanned volume. Thus, they allow dynamic and interactive analysis of the information, by means of simultaneously scanning the object in different anatomical planes of imaging: axial, coronal, or sagittal, and their subsequent reconstruction thereby revealing structures that are not visible in periapical radiographs. Although periapical radiographs continue to be the imaging method of choice for the evaluation of endodontic treatment, a significant leap has occurred in the growth of CBCT use Endodontics in recent years. However, the importance of recognizing the different types of artifacts generated during the image acquisition and reconstruction process is emphasized, especially in the presence of high-density endodontic materials that can compromise the quality of the diagnosis. Considering the findings of this study, and based on international guidelines, it was concluded that the possibilities of using CBCT during endodontic treatment were mainly focused on diagnosis, assessment [of existent dental conditions], and preoperative treatment; establishing the morphology, diagnosis, and treatment planning of root canal systems; evaluation of root resorption; planning and evaluation of the treatment of traumatic dental injuries, perforations, fractures, and for the preparation of endodontic guides.

A fast and scalable framework for automated artifact recognition from EEG signals represented in scalp topographies of Independent Components

Background and objectivesElectroencephalography (EEG) measures the electrical brain activity in real-time by using sensors placed on the scalp. Artifacts due to eye movements and blinking, muscular/cardiac activity and generic electrical disturbances, have to be recognized and eliminated to allow a correct interpretation of the Useful Brain Signals (UBS). Independent Component Analysis (ICA) is effective to split the signal into Independent Components (IC) whose re-projection on 2D topographies of the scalp (images also called Topoplots) allows to recognize/separate artifacts and UBS. Topoplot analysis, a gold standard for EEG, is usually carried out offline either visually by human experts or through automated strategies, both unenforceable when a fast response is required as in online Brain-Computer Interfaces (BCI). We present a fully automatic, effective, fast, scalable framework for artifacts recognition from EEG signals represented in IC Topoplots to be used in online BCI. MethodsThe proposed architecture, optimized to contain three 2D Convolutional Neural Networks (CNN), divides Topoplots in 4 classes: 3 types of artifacts and UBS. The framework architecture is described and the results are presented, discussed and indirectly compared with those obtained from state-of-the-art competitive strategies. ResultsExperiments on public EEG datasets showed overall accuracy, sensitivity and specificity greater than 98%, taking 1.4 s on a standard PC for 32 Topoplots, i.e. for an EEG system with at least 32 sensors. ConclusionsThe proposed framework is faster than other automatic methods based on IC analysis and fast enough to be used in EEG-based online BCI. In addition, its scalable architecture and ease of training are necessary conditions to apply it in BCI, where difficult operating conditions caused by uncontrolled muscle spasms, eye rotations or head movements, produce specific artifacts that need to be recognized and dealt with.

Foundational ontologies, ontology‐driven conceptual modeling, and their multiple benefits to data mining

AbstractFor many years, the role played by domain knowledge in all stages of knowledge discovery has been recognized. However, the real‐world semantics embedded in data is often still not fully considered in traditional data mining methods. In this article, we argue that the quality of data mining results is directly related to the extent that they reflect important properties of real‐world entities represented therein. Analyzing and characterizing the nature of these entities is the very business of the area of formal ontology. We briefly elaborate on two particular types of artifacts produced by this area: foundational ontologies and ontology‐driven conceptual modeling languages grounded on them. We then elaborate on the benefits they can bring to several activities in a data mining process.This article is categorized under: Fundamental Concepts of Data and Knowledge &gt; Knowledge Representation Fundamental Concepts of Data and Knowledge &gt; Data Concepts

Current Limitations of Intraoperative Ultrasound in Brain Tumor Surgery.

While benefits of intraoperative ultrasound (IOUS) have been frequently described, data on IOUS limitations are relatively sparse. Suboptimal ultrasound imaging of some pathologies, various types of ultrasound artifacts, challenging patient positioning during some IOUS-guided surgeries, and absence of an optimal IOUS probe depicting the entire sellar region during transsphenoidal pituitary surgery are some of the most important pitfalls. This review aims to summarize prominent limitations of current IOUS systems, and to present possibilities to reduce them by using ultrasound technology suitable for a specific procedure and by proper scanning techniques. In addition, future trends of IOUS imaging optimization are described in this article.

Applicability of optical coherence tomography angiography (OCTA) imaging in Parkinson\u2019s disease

To evaluate the significance of motion artifacts in optical coherence tomography angiography (OCTA) images of patients with Parkinson’s disease (PD) and healthy controls. In this prospective, cross-sectional study subjects with medicated PD (ON) and healthy, age- and gender-matched volunteers were recruited. Participants underwent specific ophthalmological examinations, including OCTA. Angiograms of the superficial retinal capillary plexus were evaluated for the type and frequency of artifacts using a validated motion artifact score (MAS). A total of 30 PD patients (60 eyes), average disease duration of 9.61 ± 5.55 years, and 30 matched, healthy controls (60 eyes) were recruited. Twenty percent of all eyes had an eye disease, unknown to the participant, with a significant impact on OCTA results. After cleansing the dataset by excluding subjects with confounding ocular comorbidities 42 eyes of 28 PD patients and 53 eyes of 29 healthy controls were further evaluated. Overall MAS and all five subtypes of motion artifacts were comparable without significant differences between groups. OCTA can be used in treated PD patients (ON) without a significant increase in motion artifacts. Nevertheless, special attention should be paid to image quality during the acquisition of OCTA data, for which an experienced OCTA operator is useful.

Morphological Subtypes of Tumor Spread Through Air Spaces in Non-Small Cell Lung Cancer: Prognostic Heterogeneity and Its Underlying Mechanism.

BackgroundTumor spread through air spaces (STAS) has three morphologic subtypes: single cells, micropapillary clusters, and solid nests. However, whether their respective clinical significance is similar remains unclear.MethodsWe retrospectively reviewed 803 patients with resected non-small cell lung cancer (NSCLC) from January to December 2009. Recurrence-free survival (RFS) and overall survival (OS) were compared among patients stratified by STAS subtypes. We also performed a prospective study of NSCLC resection specimens to evaluate the influence of a prosecting knife on the presence of STAS subtypes during specimen handling (83 cases).ResultsSTAS was found in 370 NSCLCs (46%), including 47 single cell STAS (13%), 187 micropapillary cluster STAS (50%), and 136 solid nest STAS (37%). STAS-negative patients had significantly better survival than patients with micropapillary cluster STAS (RFS: P < 0.001; OS: P < 0.001) and solid nest STAS (RFS: P < 0.001; OS: P < 0.001), but similar survival compared with those with single cell STAS (RFS: P = 0.995; OS: P = 0.71). Multivariate analysis revealed micropapillary cluster (RFS: P < 0.001; OS: P < 0.001) and solid nest STAS (RFS: P = 0.001; OS: P = 0.003) to be an independent prognostic indicator, but not for single cell STAS (RFS: P = 0.989; OS: P = 0.68). Similar results were obtained in subgroup analysis of patients with adenocarcinoma. The prospective study of NSCLC specimens suggested that 18 cases were considered as STAS false-positive, and most were singe cell pattern (13/18, 72%).ConclusionsSingle cell STAS was the common morphologic type of artifacts produced by a prosecting knife. A precise protocol of surgical specimen handling is required to minimize artifacts as much as possible.

FMRI and Artifact computation and Analysis

Over the years, the field of Medical Imagology has gained considerable importance. The number of neuroimaging studies conducted using functional magnetic resonance imaging (fMRI) has been exploding in recent years. fMRI survey gives to rise to large amounts of noisy data with a complex spatiotemporal correlation structure. Statistics play great role in clarifying the features of the data and gain results that can be used and explain by neuroscientists. Several types of artifacts can happen through a functional magnetic resonance imaging (fMRI) scanner Because of software or hardware problems, physical limitation or human physiologic phenomenon. Several of them can negatively affect diagnostic image goodness, and confused with various pathology. Artificial Characteristics is show in an image not found in the real actual object it is the necessary to recognize these artifacts according to a basic perception of their origin, especially those simulating pathology, as they can be sing to wrong diagnostic medical. As a result, it causes dangerous effects on the patient’s health. We discuss the study of fMRI data in this paper; we highlight important and significant problems where statistics already play a major role. It is include a sequence of programs for processing, analysing, and offer fMRI data. Of special regard to statisticians might be its use of functions from the statistical software package. The conventional methods are FSL and SPM. The most generally applied software is SPM (Statistical Parametric Mapping), which include groups of MATLAB functions for pre-processing, analysing, and display fMRI data.

Abstract PO-076: Unsupervised learning of image embeddings enables new opportunities to extract novel information from digital pathology H&amp;E images

Abstract Introduction: In digital pathology, large amounts of time and money are spent annotating whole slide images (WSIs). By using an AI algorithm trained on thousands of WSIs, it is possible to remove the process of annotating from the workflow whilst simultaneously finding potential imaging features that correlate with drug response, molecular phenotypes, histologic features (e.g. Tertiary Lymphoid Structures), inflammation at the tumor-stroma interface, artifacts, etc. Method: A pipeline was constructed for ingesting WSI from the set of diagnostic slides available in the cancer genome archive (TCGA). The WSIs were masked for tissue areas and divided into patches extracted at multiple magnification levels. These patches were used to train a U-Net (initialised with a pre-trained ResNet34) to complete a self-supervised in-painting task and evaluated with perceptual loss using VGG16. After training, embeddings were extracted from the bottleneck layer of the U-Net, and these were evaluated for their capacity to cluster according to tissue type and magnification level. Results: The trained embeddings showed strong clustering by tissue type, magnification level, and separation of artefacts. The results were qualitatively evaluated by pathologist with consensus and exceeded the performance of a baseline pre-trained ImageNet model. Conclusion: These results highlight a novel methodology for AI algorithm development that removes the need for numerous pathologists to annotate pathology images by hand and converts their role to reviewing and quality-checking images. AI algorithms based on this approach can have a significant impact in the pathologic evaluation of tissue for oncology clinical trials by extracting a richer set of features than glass microscopy alone would permit. Furthermore, self-supervised methods, such as in-painting allow for the training of embeddings that encapsulate a richer understanding of the data and are consequently more repurposable than supervised/labelled approaches. Citation Format: Jason Hipp, Mona Xu, Lucas Bordeaux, Feng Gu, Carlos Pedrinaci, Khan Baykaner. Unsupervised learning of image embeddings enables new opportunities to extract novel information from digital pathology H&amp;E images [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-076.

Open access resources on motion artifact in adult dentomaxillofacial CBCT: illustrated pictorial review of medical literature

Objective: to know how much open access/open knowledge reference figures were available on motion artifacts in CBCT dentomaxillofacial imaging, and to describe and to categorize clinical variation of motion artifacts related to diverse types of head motion retrospectively observed during CBCT scanning time.&#x0D; Material and methods: a search equation was performed on Pubmed database. We found 56 articles. The 45 articles were out of scope, and 7 articles were excluded after applying exclusion and inclusion criteria. Only 4 articles were finally freely accessible and selected for this review. Moreover, we retrospectively used our department CBCT database to search examinations with motion artifacts. We also checked retrospectively for radiological protocols as the type of motion artifact was described when occurred during the CBCT scanning time by the main observer. We had obtained the approval from the Ethical committee for this study.&#x0D; Results: The accessibility of free figures on motion artifact in dentomaxillofacial CBCT is limited to 13 figures not annotated, and to one annotated figure presenting a double contour around cortex of bony orbits. We proposed to categorize the&#x0D; motion artifacts into three levels: low, intermediary, and major. Each level was related to: 1) progressive image quality degradation, 2) distortion of anatomy, and 3) potential possibility of performing clinical diagnosis. All 45 figures were annotated.&#x0D; Conclusions: There exists a scarce open access literature on motion artifacts in CBCT. In our pictorial review we found that low level motion artifacts were more related to head rotation in axial plane (rolling). Rolling and lateral translation were responsible of intermediary level motion artifacts. Major level motion artifacts were created by complex motion with multiple rotation axes, multiple translation directions, and by anteroposterior translation. The main limitation of this study is related to retrospectively report empirical observation of patient motion during CBCT scanning and to compare these observations with motion artifacts found on clinical images. More robust methodology should be further developed using a virtual simulation of various types of head movements and associated parameters to consolidate the open knowledge on motion artifacts in dentomaxillofacial CBCT.&#x0D;

Theoretical and Methodological Approaches to Ecological Changes, Social Behaviour and Human Intergroup Tolerance 300,000 to 30,000 BP

Archaeological evidence suggests that important shifts were taking place in the character of human social behaviours 300,000 to 30,000 years ago. New artefact types appear and are disseminated with greater frequency. Transfers of both raw materials and finished artefacts take place over increasing distances, implying larger scales of regional mobility and more frequent and friendlier interactions between different communities. Whilst these changes occur during a period of increasing environmental variability, the relationship between ecological changes and transformations in social behaviours is elusive. Here, we explore a possible theoretical approach and methodology for understanding how ecological contexts can influence selection pressures acting on intergroup social behaviours. We focus on the relative advantages and disadvantages of intergroup tolerance in different ecological contexts using agent-based modelling (ABM). We assess the relative costs and benefits of different ‘tolerance’ levels in between-group interactions on survival and resource exploitation in different environments. The results enable us to infer a potential relationship between ecological changes and proposed changes in between-group behavioural dynamics. We conclude that increasingly harsh environments may have driven changes in hormonal and emotional responses in humans leading to increasing intergroup tolerance, i.e. transformations in social behaviour associated with ‘self-domestication’. We argue that changes in intergroup tolerance is a more parsimonious explanation for the emergence of what has been seen as ‘modern human behaviour’ than changes in hard aspects of cognition or other factors such as cognitive adaptability or population size.

Modeling of artifacts in the wrist photoplethysmogram: Application to the detection of life-threatening arrhythmias

ObjectiveA model for simulating motion-induced artifacts in the wrist photoplethysmogram (PPG) is proposed for the purpose to improve realism of PPG models. MethodsThe database of day-long PPGs, acquired during cardiac rehabilitation, is used to extract artifact characteristics, which further serve as a basis for modeling artifacts in simulated PPGs with life-threatening arrhythmias. ResultsDepending on the recording, 14–49% of the PPG duration is corrupted by artifacts, mostly due to device displacement, forearm and hand motion. The artifact type influence on the performance of a life-threatening arrhythmia detector shows that the sensitivity drops by 45–48% for extreme bradycardia and by 13–32% for ventricular tachycardia. Poor contact causes 2–4 times more false alarms of ventricular tachycardia compared to the other artifact types under investigation. ConclusionSimulation of realistic artifacts encountered in activities of daily living allows to comprehensively investigate arrhythmia detectors and understand the artifact types most negatively affecting detection performance. SignificanceThe proposed PPG artifact model is of importance for developing and testing artifact-robust arrhythmia detectors.

The southern Levantine earthquake of 418/419 AD and the archaeology of Byzantine Petra

This article provides a critical review of the archaeological, geological and historical evidence concerning the southern Levantine earthquake of 418/419 AD, specifically its effects on Petra. Historical accounts indicate that the earthquake caused destruction in Jerusalem and elsewhere, but archaeological evidence is sparse. Numerous destruction layers at sites in the Galilee were attributed to the 418/419 earthquake, but these attributions have all been questioned due to the presence of material in these layers post-dating the early 5th century AD. To the south, the attribution of the destruction of the Spätrömisch II phase at al-Zantur, in Petra, to this earthquake has largely been accepted. This paper reviews the published evidence and determines that this, too, has been dated too early. Based on this evidence, I suggest that the destruction of al-Zantur Spätrömisch II occurred in the 6th century and argue that the 418/419 earthquake was a relatively minor event, primarily affecting the Jerusalem region. This has bearing on the dating of diagnostic artifact types found in this phase, notably the Negev wheel-made lamp, which I argue should be considered a reliable indicator of dates in the 6th–7th century AD. This, in turn, has implications for the dating of other sites, notably the Petra Church.

Древняя металлургия Восточного Синьцзяна

This paper examines the form and chemical composition of metal artifacts of three successive cultures of the Hami region. The metal artifacts of the Tianshanbeilu culture are rather diverse in both type and material; body ornaments are dominant, whereas tools and weapons are quantitatively modest. The typological composition and the predominance of body ornaments made of tin bronze, pure copper, and arsenic copper are reminiscent of the Karasuk culture in the Minusinsk Basin and the Siba culture in the Hexi Corridor. Apart from the bulk metal types, there are gold, lead, and antimonial copper. The metal artifacts of the succeeding culture of Yanbulake are morphologically derived from Tianshanbeilu. In the subsequent Heigouliang culture, apart from old types of metal artifacts inherited from the Yanbulake culture, there are a number of new types of artifacts that are morphologically derived from nomadic cultures in the Eurasian steppe. In the cultures of Yanbulake and Heigouliang, the use of tin bronze, arsenic copper, and pure copper prevailed. The source of minerals, especially tin, which is used throughout the three successive cultures, awaits further investigation. Keywords: Xinjiang, Bronze Age, Early Iron Age, metallurgy, Eurasia

Multi-Task Learning Framework for Motion Estimation and Dynamic Scene Deblurring.

Motion blur, which disturbs human and machine perceptions of a scene, has been considered an unnecessary artifact that should be removed. However, the blur can be a useful clue to understanding the dynamic scene, since various sources of motion generate different types of artifacts. Motivated by the relationship between motion and blur, we propose a motion-aware feature learning framework for dynamic scene deblurring through multi-task learning. Our multi-task framework simultaneously estimates a deblurred image and a motion field from a blurred image. We design the encoder-decoder architectures for two tasks, and the encoder part is shared between them. Our motion estimation network could effectively distinguish between different types of blur, which facilitates image deblurring. Understanding implicit motion information through image deblurring could improve the performance of motion estimation. In addition to sharing the network between two tasks, we propose a reblurring loss function to optimize the overall parameters in our multi-task architecture. We provide an intensive analysis of complementary tasks to show the effectiveness of our multi-task framework. Furthermore, the experimental results demonstrate that the proposed method outperforms the state-of-the-art deblurring methods with respect to both qualitative and quantitative evaluations.

Вещественная (материальная) культура как конструкция и функциональная органопроекция

The article defines the specifics and structure of things as a type of cultural artefacts. The author considers the thing to be the result of the practical construction of the world, where construction is expressed as the transformation of nature into culture. The construction in question is carried out on the basis of two generative models — the value model and the utilitarian one. Both models are aimed at creating a world acceptable to humans, but do it in different ways. The value model connects the transformed world with the meaning of human life. The utilitarian model, in contrast, adapts the world to the objective and specific requirements of a person so that to allow him to exist in this world, while a person himself adapts to the objective conditions of the world in which he begins to live. The role of the value model varies in different time periods but never ceases to exist. The utilitarian model, however, always has the primary importance. It is shown that material culture exists in the form of a means for solving certain tasks facing a person and posed by him. The morphology of material culture is based on a functional understanding of its organoprojective nature. The category of organoprojection is defined as the totality of means for increasing the effectiveness of an organ of the human body. The nature of the connection between a body organ and a material instrument is considered as the functional dependence of the latter on the former. The article identifies six key functions of organoprojection: access to the world, surface transformation of the world, deep transformation of the world, protection from the world, replenishment of energy and restoration of the human body, and reproduction. Each function has been studied as the specifics of one or another type of artefacts of material culture: communicative technology and transport, landscape and domestics, utensils and implements, costume, housing and weapons, diet and medicines.