238 research outputs found

    Cassini-Huygens mission images classification framework by deep learning advanced approach

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    Developing a deep learning (DL) model for image classification commonly demands a crucial architecture organization. Planetary expeditions produce a massive quantity of data and images. However, manually analyzing and classifying flight missions image databases with hundreds of thousands of images is ungainly and yield weak accuracy. In this paper, we speculate an essential topic related to the classification of remotely sensed images, in which the process of feature coding and extraction are decisive procedures. Diverse feature extraction techniques are intended to stimulate a discriminative image classifier. Features extraction is the primary engagement in raw data processing with the purpose of data classification; when it comes across the task of analysis of vast and varied data, these kinds of tasks are considered as time-consuming and hard to be treated with. Most of these classifiers are either, in principle, quite intricate or virtually unattainable to calculate for massive datasets. Stimulated by this perception, we put forward a straightforward, efficient classifier based on feature extraction by analyzing the cell of tensors via layered MapReduce framework beside meta-learning LSTM followed by a SoftMax classifier. Experiment results show that the provided model attains a classification accuracy of 96.7%, which makes the provided model quite valid for diverse image databases with varying sizes

    Deep learning-based approach for detecting trajectory modifications of cassini-huygens spacecraft

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    There were necessary trajectory modifications of Cassini spacecraft during its last 14 years movement cycle of the interplanetary research project. In the scale 1.3 hour of signal propagation time and 1.4-billion-kilometer size of Earth-Cassini channel, complex event detection in the orbit modifications requires special investigation and analysis of the collected big data. The technologies for space exploration warrant a high standard of nuanced and detailed research. The Cassini mission has accumulated quite huge volumes of science records. This generated a curiosity derives mainly from a need to use machine learning to analyze deep space missions. For energy saving considerations, the communication between the Earth and Cassini was executed in non-periodic mode. This paper provides a sophisticated in-depth learning approach for detecting Cassini spacecraft trajectory modifications in post-processing mode. The proposed model utilizes the ability of Long Short Term Memory (LSTM) neural networks for drawing out useful data and learning the time series inner data pattern, along with the forcefulness of LSTM layers for distinguishing dependencies among the long-short term. Our research study exploited the statistical rates, Matthews correlation coefficient, and F1 score to evaluate our models. We carried out multiple tests and evaluated the provided approach against several advanced models. The preparatory analysis showed that exploiting the LSTM layer provides a notable boost in rising the detection process performance. The proposed model achieved a number of 232 trajectory modification detections with 99.98% accuracy among the last 13.35 years of the Cassini spacecraft life. © 2013 IEEE

    Brain abscess caused by trauma of the rhinobasis: an endoscopic challenge

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    Brain abscess is a rare but life-threatening infection of the brain. It often occurs as a complication of infection, trauma, or surgery. This case presents a brain abscess in a 22-month-old boy that developed after a transnasal injury with a foreign body. A minimal-invasive, transnasal, endoscopic-controlled technique was used, during which the foreign object was removed and the abscess drained. Bacteriological samples were obtained and the abscess cavity irrigated. Postoperative care included antibiotics and daily irrigation of the abscess cavity. Follow-up MRI scans showed reduction in abscess size. A spinal drain was inserted temporarily to address rhino-liquorrhoea. The patient remained asymptomatic during one-year of follow-up. This case report highlights the occurrence of a brain abscess in childhood following a transnasal injury and demonstrates a minimal-invasive, transnasal, endoscopic-controlled surgical technique. The findings underscore the importance of considering brain abscess as a potential complication in cases of head trauma, particularly in atypical presentations

    Completeness and Ambiguity of Schema Cover

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    Given a schema and a set of concepts, representative of entities in the domain of discourse, schema cover deïŹnes correspondences between concepts and parts of the schema. Schema cover aims at interpreting the schema in terms of concepts and thus, vastly simplifying the task of schema integration. In this work we investigate two properties of schema cover, namely completeness and ambiguity. The former measures the part of a schema that can be covered by a set of concepts and the latter examines the amount of overlap between concepts in a cover. To study the tradeoffs between completeness and ambiguity we deïŹne a cover model to which previous frameworks are special cases. We analyze the theoretical complexity of variations of the cover problem, some aim at maximizing completeness while others aim at minimizing ambiguity. We show that variants of the schema cover problem are hard problems in general and formulate an exhaustive search solution using integer linear programming. We then provide a thorough empirical analysis, using both real-world and simulated data sets, showing empirically that the integer linear programming solution scales well for large schemata. We also show that some instantiations of the general schema cover problem are more effective than others

    SMART: A tool for analyzing and reconciling schema matching networks

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    Schema matching supports data integration by establishing correspondences between the attributes of independently designed database schemas. In recent years, various tools for automatic pair-wise matching of schemas have been developed. Since the matching process is inherently uncertain, the correspondences generated by such tools are often validated by a human expert. In this work, we go beyond the state-of-the-art of matching pairs of schemas and consider scenarios in which attribute correspondences are identified in a network of schemas. Here, correspondences between different schemas are interrelated, so that incomplete and erroneous matching results propagate in the network and the validation of a correspondence by an expert has ripple effects. To analyse and reconcile such matchings in schema networks, we present the Schema Matching Analyzer and Reconciliation Tool (SMART). It allows for the definition of network-level integrity constraints for the matching and, based thereon, detects and visualizes inconsistencies of the matching. The tool also supports the reconciliation of a matching by guiding an expert in the validation process and by offering semi-automatic conflict-resolution techniques

    Antiproliferative efficacies but minor drug transporter inducing effects of paclitaxel, cisplatin, or 5-fluorouracil in a murine xenograft model for head and neck squamous cell carcinoma

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    Drug-induced multidrug resistance (MDR) has been linked to overexpression of drug transporting proteins in head and neck squamous cell carcinoma (HNSCC) in vitro. The aim of this work was to reassess these findings in a murine xenograft model. NOD-SCID mice xenotransplanted with 106 HNO97 cells were treated for four consecutive weeks with weekly paclitaxel, biweekly cisplatin (both intraperitoneal), or 5-fluorouracil (5-FU, administered by osmotic pump). Tumor volume and body weight were weekly documented. Expression of drug transporters and Ki-67 marker were examined using quantitative real-time polymerase chain reaction and/or immunohistochemistry. Both paclitaxel and cisplatin significantly reduced tumor volumes after 2–3 weeks. 5-FU-treated animals had significantly lower body weights after 2 or 4 weeks of chemotherapy. None of the drugs affected expression of drug transporters at the mRNA level. However, P-glycoprotein (Pgp) protein expression was increased by paclitaxel (P < 0.01). Ki-67 expression did not change during treatment irrespective of the drug applied. Paclitaxel and cisplatin are effectively tumor volume reducing drugs in a murine xenograft model of HNSCC. Paclitaxel enhanced Pgp expression at the protein level, but not at the mRNA level suggesting transcriptional induction to be of minor relevance. In contrast, posttranscriptional mechanisms or Darwinian selection of intrinsically drug transporter overexpressing MDR cells might lead to iatrogenic chemotherapy resistance in HNSCC.Fil: Theile, Dirk. UniversitĂ€t Heidelberg; AlemaniaFil: Gal, Zoltan. UniversitĂ€t Heidelberg; AlemaniaFil: Warta, Rolf. UniversitĂ€t Heidelberg; AlemaniaFil: Rigalli, Juan Pablo. UniversitĂ€t Heidelberg; Alemania. Consejo Nacional de Investigaciones CientĂ­ficas y TĂ©cnicas; ArgentinaFil: Lahrmann, Bernd. UniversitĂ€t Heidelberg; AlemaniaFil: Grabe, Niels. UniversitĂ€t Heidelberg; AlemaniaFil: Herold Mende, Christel. UniversitĂ€t Heidelberg; AlemaniaFil: Dyckhoff, Gerhard. UniversitĂ€t Heidelberg; AlemaniaFil: Weiss, Johanna. UniversitĂ€t Heidelberg; Alemani

    Genetic landscape of early-onset dementia in Hungary

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    Introduction: Early-onset dementias (EOD) are predominantly genetically determined, but the underlying disease-causing alterations are often unknown. The most frequent forms of EODs are early-onset Alzheimer's disease (EOAD) and frontotemporal dementia (FTD). Patients: This study included 120 Hungarian patients with EOD (48 familial and 72 sporadic) which had a diagnosis of EOAD (n = 49), FTD (n = 49), or atypical dementia (n = 22). Results: Monogenic dementia was detected in 15.8% of the patients. A pathogenic hexanucleotide repeat expansion in the C9ORF72 gene was present in 6.7% of cases and disease-causing variants were detected in other known AD or FTD genes in 6.7% of cases (APP, PSEN1, PSEN2, GRN). A compound heterozygous alteration of the TREM2 gene was identified in one patient and heterozygous damaging variants in the CSF1R and PRNP genes were detected in two other cases. In two patients, the coexistence of several heterozygous damaging rare variants associated with neurodegeneration was detected (1.7%). The APOE genotype had a high odds ratio for both the APOE ɛ4/3 and the ɛ4/4 genotype (OR = 2.7 (95%CI = 1.3-5.9) and OR = 6.5 (95%CI = 1.4-29.2), respectively). In TREM2, SORL1, and ABCA7 genes, 5 different rare damaging variants were detected as genetic risk factors. These alterations were not present in the control group. Conclusion: Based on our observations, a comprehensive, targeted panel of next-generation sequencing (NGS) testing investigating several neurodegeneration-associated genes may accelerate the path to achieve the proper genetic diagnosis since phenotypes are present on a spectrum. This can also reveal hidden correlations and overlaps in neurodegenerative diseases that would remain concealed in separated genetic testing

    Short-Term Therapies for Treatment of Acute and Advanced Heart Failure—Why so Few Drugs Available in Clinical Use, Why Even Fewer in the Pipeline?

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    Both acute and advanced heart failure are an increasing threat in term of survival, quality of life and socio-economical burdens. Paradoxically, the use of successful treatments for chronic heart failure can prolong life but—per definition—causes the rise in age of patients experiencing acute decompensations, since nothing at the moment helps avoiding an acute or final stage in the elderly population. To complicate the picture, acute heart failure syndromes are a collection of symptoms, signs and markers, with different aetiologies and different courses, also due to overlapping morbidities and to the plethora of chronic medications. The palette of cardio- and vasoactive drugs used in the hospitalization phase to stabilize the patient’s hemodynamic is scarce and even scarcer is the evidence for the agents commonly used in the practice (e.g., catecholamines). The pipeline in this field is poor and the clinical development chronically unsuccessful. Recent set backs in expected clinical trials for new agents in acute heart failure (AHF) (omecamtiv, serelaxine, ularitide) left a field desolately empty, where only few drugs have been approved for clinical use, for example, levosimendan and nesiritide. In this consensus opinion paper, experts from 26 European countries (Austria, Belgium, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, The Netherlands, Norway, Poland, Portugal, Russia, Slovenia, Spain, Sweden, Switzerland, Turkey, U.K. and Ukraine) analyse the situation in details also by help of artificial intelligence applied to bibliographic searches, try to distil some lesson-learned to avoid that future projects would make the same mistakes as in the past and recommend how to lead a successful development project in this field in dire need of new agents

    Short-Term Therapies for Treatment of Acute and Advanced Heart Failure—Why so Few Drugs Available in Clinical Use, Why Even Fewer in the Pipeline?

    Get PDF
    Both acute and advanced heart failure are an increasing threat in term of survival, quality of life and socio-economical burdens. Paradoxically, the use of successful treatments for chronic heart failure can prolong life but—per definition—causes the rise in age of patients experiencing acute decompensations, since nothing at the moment helps avoiding an acute or final stage in the elderly population. To complicate the picture, acute heart failure syndromes are a collection of symptoms, signs and markers, with different aetiologies and different courses, also due to overlapping morbidities and to the plethora of chronic medications. The palette of cardio- and vasoactive drugs used in the hospitalization phase to stabilize the patient’s hemodynamic is scarce and even scarcer is the evidence for the agents commonly used in the practice (e.g., catecholamines). The pipeline in this field is poor and the clinical development chronically unsuccessful. Recent set backs in expected clinical trials for new agents in acute heart failure (AHF) (omecamtiv, serelaxine, ularitide) left a field desolately empty, where only few drugs have been approved for clinical use, for example, levosimendan and nesiritide. In this consensus opinion paper, experts from 26 European countries (Austria, Belgium, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, The Netherlands, Norway, Poland, Portugal, Russia, Slovenia, Spain, Sweden, Switzerland, Turkey, U.K. and Ukraine) analyse the situation in details also by help of artificial intelligence applied to bibliographic searches, try to distil some lesson-learned to avoid that future projects would make the same mistakes as in the past and recommend how to lead a successful development project in this field in dire need of new agents
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