Integrated Video and Acoustic Emission Data Fusion for Intelligent Decision Making in Material Surface Inspection System.

In the field of intelligent surface inspection systems, particular attention is paid to decision making problems, based on data from different sensors. The combination of such data helps to make an intelligent decision. In this research, an approach to intelligent decision making based on a data integration strategy to raise awareness of a controlled object is used. In the following article, this approach is considered in the context of reasonable decisions when detecting defects on the surface of welds that arise after the metal pipe welding processes. The main data types were RGB, RGB-D images, and acoustic emission signals. The fusion of such multimodality data, which mimics the eyes and ears of an experienced person through computer vision and digital signal processing, provides more concrete and meaningful information for intelligent decision making. The main results of this study include an overview of the architecture of the system with a detailed description of its parts, methods for acquiring data from various sensors, pseudocodes for data processing algorithms, and an approach to data fusion meant to improve the efficiency of decision making in detecting defects on the surface of various materials.

Machine Learning and 3D Reconstruction of Materials Surface for Nondestructive Inspection.

During the steel pipeline installation, special attention is paid to the butt weld control performed by fusion welding. The operation of the currently popular automated X-ray and ultrasonic testing complexes is associated with high resource and monetary costs. In this regard, this work is devoted to the development of alternative and cost-effective means of preliminary quality control of the work performed based on the visual testing method. To achieve this goal, a hardware platform based on a single board Raspberry Pi4 minicomputer and a set of available modules and expansion cards is proposed, and software whose main functionality is implemented based on the systemic application of computer vision algorithms and machine learning methods. The YOLOv5 object detection algorithm and the random forest machine learning model were used as a defect detection and classification system. The mean average precision (mAP) of the trained YOLOv5 algorithm based on extracted weld contours is 86.9%. A copy of YOLOv5 trained on the images of control objects showed a mAP result of 96.8%. Random forest identifying of the defect precursor based on the point clouds of the weld surface achieved a mAP of 87.5%.

Antifungal Thiazolidines: Synthesis and Biological Evaluation of Mycosidine Congeners.

Novel derivatives of Mycosidine (3,5-substituted thiazolidine-2,4-diones) are synthesized by Knoevenagel condensation and reactions of thiazolidines with chloroformates or halo-acetic acid esters. Furthermore, 5-Arylidene-2,4-thiazolidinediones and their 2-thioxo analogs containing halogen and hydroxy groups or di(benzyloxy) substituents in 5-benzylidene moiety are tested for antifungal activity in vitro. Some of the synthesized compounds exhibit high antifungal activity, both fungistatic and fungicidal, and lead to morphological changes in the Candida yeast cell wall. Based on the use of limited proteomic screening and toxicity analysis in mutants, we show that Mycosidine activity is associated with glucose transport. This suggests that this first-in-class antifungal drug has a novel mechanism of action that deserves further study.

Strength of word-specific neural memory traces assessed electrophysiologically.

Memory traces for words are frequently conceptualized neurobiologically as networks of neurons interconnected via reciprocal links developed through associative learning in the process of language acquisition. Neurophysiological reflection of activation of such memory traces has been reported using the mismatch negativity brain potential (MMN), which demonstrates an enhanced response to meaningful words over meaningless items. This enhancement is believed to be generated by the activation of strongly intraconnected long-term memory circuits for words that can be automatically triggered by spoken linguistic input and that are absent for unfamiliar phonological stimuli. This conceptual framework critically predicts different amounts of activation depending on the strength of the word's lexical representation in the brain. The frequent use of words should lead to more strongly connected representations, whereas less frequent items would be associated with more weakly linked circuits. A word with higher frequency of occurrence in the subject's language should therefore lead to a more pronounced lexical MMN response than its low-frequency counterpart. We tested this prediction by comparing the event-related potentials elicited by low- and high-frequency words in a passive oddball paradigm; physical stimulus contrasts were kept identical. We found that, consistent with our prediction, presenting the high-frequency stimulus led to a significantly more pronounced MMN response relative to the low-frequency one, a finding that is highly similar to previously reported MMN enhancement to words over meaningless pseudowords. Furthermore, activation elicited by the higher-frequency word peaked earlier relative to low-frequency one, suggesting more rapid access to frequently used lexical entries. These results lend further support to the above view on word memory traces as strongly connected assemblies of neurons. The speed and magnitude of their activation appears to be linked to the strength of internal connections in a memory circuit, which is in turn determined by the everyday use of language elements.

Muscle contraction force and fatigue: effects on mismatch negativity.

Muscle load can affect the performance of concurrent cognitive task. This effect is often explained by limited resources in the voluntary attention system. To examine whether earlier stages of cognitive information processing might be affected, we recorded the mismatch negativity component (MMN) of the auditory event-related brain potential before, during and after sustained handgrip at 7 and 30% of maximal voluntary contraction. MMN is an index of automatic detection of a deviating auditory event. MMN was not affected by force level. However, its amplitude at fronto-central sites decreased during the fatiguing 30% contraction, while it tended to increase during the light 7% work. Thus, muscle fatigue may affect auditory information processing at preattentive and preconscious stages, which could modify cognitive performance.

The evolutionary origin of man can be traced in the layers of defunct ancestral alpha satellites flanking the active centromeres of human chromosomes.

Alpha satellite domains that currently function as centromeres of human chromosomes are flanked by layers of older alpha satellite, thought to contain dead centromeres of primate progenitors, which lost their function and the ability to homogenize satellite repeats, upon appearance of a new centromere. Using cladistic analysis of alpha satellite monomers, we elucidated complete layer patterns on chromosomes 8, 17, and X and related them to each other and to primate alpha satellites. We show that discrete and chronologically ordered alpha satellite layers are partially symmetrical around an active centromere and their succession is partially shared in non-homologous chromosomes. The layer structure forms a visual representation of the human evolutionary lineage with layers corresponding to ancestors of living primates and to entirely fossil taxa. Surprisingly, phylogenetic comparisons suggest that alpha satellite arrays went through periods of unusual hypermutability after they became "dead" centromeres. The layer structure supports a model of centromere evolution where new variants of a satellite repeat expanded periodically in the genome by rounds of inter-chromosomal transfer/amplification. Each wave of expansion covered all or many chromosomes and corresponded to a new primate taxon. Complete elucidation of the alpha satellite phylogenetic record would give a unique opportunity to number and locate the positions of major extinct taxa in relation to human ancestors shared with extant primates. If applicable to other satellites in non-primate taxa, analysis of centromeric layers could become an invaluable tool for phylogenetic studies.

Interspersed repeats are found predominantly in the "old" alpha satellite families.

The biased distribution of dispersed repeat insertions in various types of primate specific alpha satellites (AS) is being discussed in the literature in relation to the modes of AS evolution and their possible roles in maintenance and disruption of functional centromeres. However, such a bias has not been properly documented on a genome-wide scale so far. In this work, using a representative sample of about 100 insertions we show that the "old" AS contains at least 10 times more dispersed repeats than the "new" one. In the new arrays insertions accumulate mostly in poorly homogenized areas, presumably in the edges, and in the old AS, throughout the whole array length. Dating of L1 insertions in the old AS revealed that their massive accumulation started at or after the time when the new AS emerged and expanded in the genome and the centromere function had shifted to the new AS arrays.