Hausdorff-Distance Enhanced Matching of Scale Invariant Feature Transform Descriptors in Context of Image Querying

Reliable and effective matching of visual descriptors is a key step for many vision applications, e.g. image retrieval. In this paper, we propose to integrate the Hausdorff distance matching together with our pairing algorithm, in order to obtain a robust while computationally efficient process of matching feature descriptors for image-to-image querying in standards datasets. For this purpose, Scale Invariant Feature Transform (SIFT) descriptors have been matched using our presented algorithm, followed by the computation of our related similarity measure. This approach has shown excellent performance in both retrieval accuracy and speed

Multicolour interphase cytogenetics: 24 chromosome probes, 6 colours, 4 layers

From the late 1980s onwards, the use of DNA probes to visualise sequences on individual chromosomes (fluorescent in-situ hybridisation - FISH) revolutionised the study of cytogenetics. Following single colour experiments, more fluorochromes were added, culminating in a 24 colour assay that could distinguish all human chromosomes. Interphase cytogenetics (the detection of chromosome copy number in interphase nuclei) soon followed, however 24 colour experiments are hampered for this application as mixing fluorochromes to produce secondary colours produces images that are not easily distinguishable from overlapping signals. This study reports the development and use of a novel protocol, new fast hybridising FISH probes, and a bespoke image capture system for the assessment of chromosome copy number in interphase nuclei. The multicolour probe sets can be used individually or in sequential hybridisation layers to assess ploidy of all 24 human chromosomes in the same nucleus. Applications of this technique are in the investigation of chromosome copy number and the assessment of nuclear organisation for a range of different cell types including human sperm, cancer cells and preimplantation embryos

Optical character recognition based-on system for automated software testing

The paper presents the development and deployment of an artificial intelligence (AI) test automation framework that allows testers to more fluidly develop scripts and carry out their day-to-day tasks. In particular, the framework aims to speed up the test automation process by enabling its users to locate elements on a webpage through the use of template-matching-based image recognition as well as optical character recognition (OCR). Indeed, test automation specialists spend much of their time creating page-object models (POMs), where they capture elements on the screen via complex locators such as cascading style sheet (CSS) or XPath. However, when webpages are updated or elements are moved around, locators become void, eventually pointing to nothing unless written in such a dynamic way as to prevent this. This heavily relies on developers providing meaningful tags to elements that they can then be located by, whereas with the introduction of an image recognition engine in our AI fr amework, this tedious and long-winded approach has been be shortened

Smart lifts:an ontological perspective

Nowadays, there is a growth of smart factories and Industry 4.0 technologies, involving Artificial Intelligence (AI) systems. These ones require interoperable solutions. In particular, ontologies have been widely used for capturing, sharing, and representing knowledge in an interoperable way, that both humans and machines can understand. Indeed, ontologies allow humans to communicate with machines in a semantic way, while machines are able to make automated reasoning about the concepts and relationships which are encoded in the ontology. For this purpose, this paper proposes the first-ever domain ontology for smart lifts. Its domain covers smart lift design, operation, and maintenance, while its scope is to aid in automating such lift services. This smart lift ontology (SLO), which contains 144 classes and 749 axioms, has been successfully developed in collaboration with the elevator industry

Muscle ultrastructural changes from exhaustive exercise performed after prolonged restricted activity and retraining in dogs

The effect of exhaustive treadmill exercise on ultrastructural changes in the quadriceps femoris muscle was studied in 7 normal, healthy dogs, before and after restricted activity (RA), and following a subsequent 2 month treadmill exercise retraining period for the 5 mo group. Mean time to exhaustion in the 2 mo group decreased from 177 + or - 22 min before to 90 + or - 32 min after RA. Retraining increased tolerance to 219 + or - 73 min; 24 pct. above the before RA and 143 pct. above the after RA time. After RA exhaustion time in the 5 mo group was 25 and 45 min. Before RA, pre-exercise muscle structure was normal and post exercise there was only slight swelling of mitochondria. After RA, pre-exercise, numerous glycogen granules and lipid droplets appeared in the muscle fibers, mitochondria were smaller, and sarcoplasmic reticulum channels widened; post exercise these changes were accentuated and some areas were devoid of glycogen, and there was fiber degradation. After 5 mo RA pre-exercise there were more pronounced changes; mitochondria were very small and dense, there were many lipid droplets, myofibrils were often separated, and the fibers appeared edematous and degenerating; post exercise the sarcoplasmic reticulum was swollen, no glycogen was present, and there was marked swelling and deformation of mitochondria. After retraining, both pre-exercise and post exercise there was still evidence of fiber degeneration. Thus, susceptibility of active skeletal muscle structures and subcellular elements, e.g., mitochondria, to the action of damaging factors occurring during exhaustive exercise is enhanced considerably by prolonged disuse

The role of peptides in bone healing and regeneration: A systematic review

Background: Bone tissue engineering and the research surrounding peptides has expanded significantly over the last few decades. Several peptides have been shown to support and stimulate the bone healing response and have been proposed as therapeutic vehicles for clinical use. The aim of this comprehensive review is to present the clinical and experimental studies analysing the potential role of peptides for bone healing and bone regeneration. Methods: A systematic review according to PRISMA guidelines was conducted. Articles presenting peptides capable of exerting an upregulatory effect on osteoprogenitor cells and bone healing were included in the study. Results: Based on the available literature, a significant amount of experimental in vitro and in vivo evidence exists. Several peptides were found to upregulate the bone healing response in experimental models and could act as potential candidates for future clinical applications. However, from the available peptides that reached the level of clinical trials, the presented results are limited. Conclusion: Further research is desirable to shed more light into the processes governing the osteoprogenitor cellular responses. With further advances in the field of biomimetic materials and scaffolds, new treatment modalities for bone repair will emerge

Treatment of residual periodontal pockets using a hyaluronic acid-based gel: A 12 month multicenter randomized triple-blinded clinical trial

The aim of the present study was to evaluate the adjunctive effect of hyaluronic acid (HA) gel in the treatment of residual periodontal pockets over a 12-month period. Periodontal patients presenting at least one residual periodontal pocket 5–9 mm of depth in the anterior area were recruited from six university-based centers. Each patient was randomly assigned to subgingival instrumentation (SI) with the local adjunctive use of HA for test treatment or adjunctive use of local placebo for control treatment at baseline and after 3 months. Clinical parameters probing depth (PD), bleeding on probing (BoP), plaque index (PI), recession (REC), clinical attachment level (CAL)) and microbiological samples for the investigation of the total bacterial count (TBC) and presence of specific bacterial species (Porphyromonas gingivalis, Treponema denticola, Tannerella forsythia, Fusobacterium nucleatum) were taken at baseline and every 3 months, until study termination. PD was determined as the primary outcome variable. From a total of 144 enrolled, 126 participants (53 males, 73 females) completed the entire protocol. Both treatments resulted in statistically significant clinical and microbiological improvements compared to baseline. Although the local application of HA showed a tendency for better results, there was a lack of statistically significant differences between the groups

Tailoring complexity metrics for simulink models

The size and complexity of Simulink models is constantly increasing, just as the systems which they represent. Therefore, it is beneficial to control them already at the design phase. In this paper we establish a set of complexity metrics for Simulink models to capture diverse aspects of complexity by proposing new and redefining existing metrics. To evaluate the applicability of our metrics, we compare them with the closed-source metric proposed by Mathworks. Moreover, through a case study from the automotive domain, we relate such metrics to quality attributes as determined by domain experts, and correlate them to known faults. Preliminary assessment suggests that complexity is closely related to analysability, understandability, and testability

The Immune System in Stroke

Stroke represents an unresolved challenge for both developed and developing countries and has a huge socio-economic impact. Although considerable effort has been made to limit stroke incidence and improve outcome, strategies aimed at protecting injured neurons in the brain have all failed. This failure is likely to be due to both the incompleteness of modelling the disease and its causes in experimental research, and also the lack of understanding of how systemic mechanisms lead to an acute cerebrovascular event or contribute to outcome. Inflammation has been implicated in all forms of brain injury and it is now clear that immune mechanisms profoundly influence (and are responsible for the development of) risk and causation of stroke, and the outcome following the onset of cerebral ischemia. Until very recently, systemic inflammatory mechanisms, with respect to common comorbidities in stroke, have largely been ignored in experimental studies. The main aim is therefore to understand interactions between the immune system and brain injury in order to develop novel therapeutic approaches. Recent data from clinical and experimental research clearly show that systemic inflammatory diseases -such as atherosclerosis, obesity, diabetes or infection - similar to stress and advanced age, are associated with dysregulated immune responses which can profoundly contribute to cerebrovascular inflammation and injury in the central nervous system. In this review, we summarize recent advances in the field of inflammation and stroke, focusing on the challenges of translation between pre-clinical and clinical studies, and potential anti-inflammatory/immunomodulatory therapeutic approaches