MSGD: Scalable Back-end for Indoor Magnetic Field-based GraphSLAM

Simultaneous Localisation and Mapping (SLAM) systems that recover the trajectory of a robot or mobile device are characterised by a front-end and back-end. The front-end uses sensor observations to identify loop closures; the back-end optimises the estimated trajectory to be consistent with these closures. The GraphSLAM framework formulates the back-end problem as a graph-based optimisation on a pose graph. This paper describes a back-end system optimised for very dense sequence-based loop closures. This arises when the front-end generates magnetic loop closures, among other things. Magnetic measurements are fast varying, which is good for localisation, but the requirement for high sampling rates (50 Hz+) produces many more loop closures than conventional systems. To date, however, there is no study optimising GraphSLAM back-end for sequence-based magnetic loop closures. Hence we introduce a novel variant of the Stochastic Gradient Descent-based SLAM algorithm called MSGD (Magnetic-SGD). We use high-accuracy groundtruth system and extensive real datasets to evaluate MSGD against state-of-the-art back-end algorithms. We demonstrate MSGD is at least as good as the best competitor algorithm in terms of quality, while being faster and more scalable

Telomerase activity in melanoma and non-melanoma skin cancer

Telomeres are specialized structures consisting of repeat arrays of TTAGGGn located at the ends of chromosomes. They are essential for chromosome stability and, in the majority of normal somatic cells, telomeres shorten with each cell division. Most immortalized cell lines and tumours reactivate telomerase to stabilize the shortening chromosomes. Telomerase activation is regarded as a central step in carcinogenesis and, here, we demonstrate telomerase activation in premalignant skin lesions and also in all forms of skin cancer. Telomerase activation in normal skin was a rare event, and among 16 samples of normal skin (one with a history of chronic sun exposure) 12.5% (2 out of 16) exhibited telomerase activity. One out of 16 (6.25%) benign proliferative lesions, including viral and seborrhoeic wart samples, had telomerase activity. In premalignant actinic keratoses and Bowen's disease, 42% (11 out of 26) of samples exhibited telomerase activity. In the basal cell carcinoma and cutaneous malignant melanoma (CMM) lesions, telomerase was activated in 77% (10 out of 13) and 69% (22 out of 32) respectively. However, only 25% (3 out of 12) of squamous cell carcinomas (SCC) had telomerase activity. With the exception of one SCC sample, telomerase activity in a positive control cell line derived from a fibrosarcoma (HT1080) was not inhibited when mixed with the telomerase-negative SCC or CMM extracts, indicating that, overall, Taq polymerase and telomerase inhibitors were not responsible for the negative results. Mean telomere hybridizing restriction fragment (TRF) analysis was performed in a number of telomerase-positive and -negative samples and, although a broad range of TRF sizes ranging from 3.6 to 17 kb was observed, a relationship between telomerase status and TRF size was not found

Aggressive juvenile fibromatosis of the paranasal sinuses: case report and brief review

Desmoid fibromatoses are benign, slow growing fibroblastic neoplasms, arising from musculoaponeurotic stromal elements. Desmoids are characterized by local invasion, with a high rate of local recurrence and a tendency to destroy adjacent structures and organs. Desmoid fibromatoses are rare in children, and though they may occur in the head and neck region, are extremely rare in the paranasal sinuses. Here we report a case of extraabdominal desmoid fibromatosis in a seven-year-old boy involving the sphenoid sinus, one of only six published reports of desmoid fibromatosis of the paranasal sinuses. The expansile soft tissue mass eroded the walls of the sphenoid sinus as well as the posterior ethmoid air cells extending cephalad through the base of the skull. We discuss the clinicopathologic features of this lesion, including structural and ultrastructural characteristics, and we review the literature regarding treatment and outcome

Mechanisms of human telomerase reverse transcriptase (hTERT) regulation: clinical impacts in cancer

Background Limitless self-renewal is one of the hallmarks of cancer and is attained by telomere maintenance, essentially through telomerase (hTERT) activation. Transcriptional regulation of hTERT is believed to play a major role in telomerase activation in human cancers. Main body The dominant interest in telomerase results from its role in cancer. The role of telomeres and telomere maintenance mechanisms is well established as a major driving force in generating chromosomal and genomic instability. Cancer cells have acquired the ability to overcome their fate of senescence via telomere length maintenance mechanisms, mainly by telomerase activation. hTERT expression is up-regulated in tumors via multiple genetic and epigenetic mechanisms including hTERT amplifications, hTERT structural variants, hTERT promoter mutations and epigenetic modifications through hTERT promoter methylation. Genetic (hTERT promoter mutations) and epigenetic (hTERT promoter methylation and miRNAs) events were shown to have clinical implications in cancers that depend on hTERT activation. Knowing that telomeres are crucial for cellular self-renewal, the mechanisms responsible for telomere maintenance have a crucial role in cancer diseases and might be important oncological biomarkers. Thus, rather than quantifying TERT expression and its correlation with telomerase activation, the discovery and the assessment of the mechanisms responsible for TERT upregulation offers important information that may be used for diagnosis, prognosis, and treatment monitoring in oncology. Furthermore, a better understanding of these mechanisms may promote their translation into effective targeted cancer therapies. Conclusion Herein, we reviewed the underlying mechanisms of hTERT regulation, their role in oncogenesis, and the potential clinical applications in telomerase-dependent cancers.info:eu-repo/semantics/publishedVersio

Research data supporting "Walk detection and step counting on unconstrained smartphones"

The dataset contains time-annotated sensor traces obtained from smartphones in typical, unconstrained use while walking. 27 participants were asked to walk a route at three different walk paces: starting with normal, followed by fast, and ending with slow. Each participant walked the same distance and changed her/his speed at markers installed on the path. The participant carried one or two phones placed at varying positions (in a front or back trouser pocket, in a backpack/handbag, or in a hand with or without simultaneous typing). This dataset has been used for a fair, quantitative comparison of standard algorithms for walk detection and step counting. For more details about these experiments and the obtained results please refer to the full paper on the left