Exposure to GSM 900-MHz mobile radiation impaired inhibitory avoidance memory consolidation in rat: Involvements of opioidergic and nitrergic systems

Abstract The use of mobile phones is increasing, and the main health concern is the possible deleterious effects of radiation on brain functioning. The present study aimed to examine the effects of exposure to a global system for mobile communication (GSM) with mobile phones on inhibitory avoidance (IA) memory performance as well as the involvement of endogenous opioids and nitric oxide (NO) in this task. Male Wistar rats, 10–12 weeks old, were used. The results showed that four weeks of mobile phone exposure impaired IA memory performance in rats. The results also revealed that post-training, but not pre-training, as well as pre-test intracerebroventricular (i.c.v.) injections of naloxone (0.4, 4 and 40 ng/rat), dose-dependently recovered the impairment of IA memory performance induced by GSM radiation. Additionally, the impairment of IA memory performance was completely recovered in the exposed animals with post-training treatment of naloxone (40 ng/rat) plus pre-test i.c.v. injections of L-arginine (100 and 200 nmol/rat). However, pre-test i.c.v. injections of L-NAME (10 and 20 nmol/rat), impaired IA memory performance in the animals receiving post-training naloxone (40 ng/rat). In the animals receiving post-training naloxone treatment, the impairment of IA memory performance due to pre-test i.c.v. injections of L-NAME was recovered by the pre-test co-administration of L-arginine. It was concluded that the recovery from impairment of IA memory in GSM-exposed animals with post-training naloxone treatment was the result of blockade of the opioidergic system in early memory consolidation as well as activation of the nitrergic system in the retrieval phase of memory. Keywords: GSM 900-MHz Endogenous opioids Memory performance Consolidation Nitric oxid

OPTIMAL BAND RATIO ANALYSIS OF WORLDVIEW-3 IMAGERY FOR BATHYMETRY OF SHALLOW RIVERS (CASE STUDY: SARCA RIVER, ITALY)

The Optimal Band Ratio Analysis (OBRA) could be considered as an efficient technique for bathymetry from optical imagery due to its robustness on substrate variability. This point receives more attention for very shallow rivers where different substrate types can contribute remarkably into total at-sensor radiance. The OBRA examines the total possible pairs of spectral bands in order to identify the optimal two-band ratio that its log transformation yields a strong linear relation with field measured water depths. This paper aims at investigating the effectiveness of additional spectral bands of newly launched WorldView-3 (WV-3) imagery in the visible and NIR spectrum through OBRA for retrieving water depths in shallow rivers. In this regard, the OBRA is performed on a WV-3 image as well as a GeoEye image of a small Alpine river in Italy. In-situ depths are gathered in two river reaches using a precise GPS device. In each testing scenario, 50% of the field data is used for calibration of the model and the remained as independent check points for accuracy assessment. In general, the effect of changes in water depth is highly pronounced in longer wavelengths (i.e. NIR) due to high and rapid absorption of light in this spectrum as long as it is not saturated. As the studied river is shallow, NIR portion of the spectrum has not been reduced so much not to reach the riverbed; making use of the observed radiance over this spectral range as denominator has shown a strong correlation through OBRA. More specifically, tightly focused channels of red-edge, NIR-1 and NIR-2 provide a wealth of choices for OBRA rather than a single NIR band of conventional 4-band images (e.g. GeoEye). This advantage of WV-3 images is outstanding as well for choosing the optimal numerator of the ratio model. Coastal-blue and yellow bands of WV-3 are identified as proper numerators while only green band of the GeoEye image contributed to a reliable correlation of image derived values and field measured depths. According to the results, the additional and narrow spectral bands of WV-3 image lead to an average determination coefficient of 67% in two river segments, which is 10% higher than that of obtained from the 4-band GeoEye image. In addition, RMSEs of depth estimations are calculated as 4 cm and 6 cm respectively for WV-3 and GeoEye images, considering the optimal band ratio.</jats:p

A Radio-Inertial Localization and Tracking System with BLE Beacons Prior Maps

© 2018 IEEE. In this paper, we develop a system for the low-cost indoor localization and tracking problem using radio signal strength indicator, Inertial Measurement Unit (IMU), and magnetometer sensors. We develop a novel and simplified probabilistic IMU motion model as the proposal distribution of the sequential Monte-Carlo technique to track the robot trajectory. Our algorithm can globally localize and track a robot with a priori unknown location, given an informative prior map of the Bluetooth Low Energy (BLE) beacons. Also, we formulate the problem as an optimization problem that serves as the Backend of the algorithm mentioned above (Front-end). Thus, by simultaneously solving for the robot trajectory and the map of BLE beacons, we recover a continuous and smooth trajectory of the robot, corrected locations of the BLE beacons, and the time-varying IMU bias. The evaluations achieved using hardware show that through the proposed closed-loop system the localization performance can be improved; furthermore, the system becomes robust to the error in the map of beacons by feeding back the optimized map to the Front-end

Information-based view initialization in visual SLAM with a single omnidirectional camera

© 2015 Elsevier B.V. All rights reserved. This paper presents a novel mechanism to initiate new views within the map building process for an EKF-based visual SLAM (Simultaneous Localization and Mapping) approach using omnidirectional images. In presence of non-linearities, the EKF is very likely to compromise the final estimation. Particularly, the omnidirectional observation model induces non-linear errors, thus it becomes a potential source of uncertainty. To deal with this issue we propose a novel mechanism for view initialization which accounts for information gain and losses more efficiently. The main outcome of this contribution is the reduction of the map uncertainty and thus the higher consistency of the final estimation. Its basis relies on a Gaussian Process to infer an information distribution model from sensor data. This model represents feature points existence probabilities and their information content analysis leads to the proposed view initialization scheme. To demonstrate the suitability and effectiveness of the approach we present a series of real data experiments conducted with a robot equipped with a camera sensor and map model solely based on omnidirectional views. The results reveal a beneficial reduction on the uncertainty but also on the error in the pose and the map estimate

Classification-driven search for effective sm partitioning in multitasking GPUs

Graphics processing units (GPUs) feature an increasing number of streaming multiprocessors (SMs) with each successive generation. At the same time, GPUs are increasingly widely adopted in cloud services and data centers to accelerate general-purpose workloads. Running multiple applications on a GPU in such environments requires effective multitasking support. Spatial multitasking in which independent applications co-execute on different sets of SMs is a promising solution to share GPU resources. Unfortunately, how to effectively partition SMs is an open problem. In this paper, we observe that compared to widely-used even partitioning, dynamic SM partitioning based on the characteristics of the co-executing applications can significantly improve performance and power efficiency. Unfortunately, finding an effective SM partition is challenging because the number of possible combinations increases exponentially with the number of SMs and co-executing applications. Through offline analysis, we find that first classifying workloads, and then searching an effective SM partition based on the workload characteristics can significantly reduce the search space, making dynamic SM partitioning tractable. Based on these insights, we propose Classification-Driven search (CD-search) for low-overhead dynamic SM partitioning in multitasking GPUs. CD-search first classifies workloads using a novel off-SM bandwidth model, after which it enters the performance mode or power mode depending on the workload's characteristics. Both modes follow a specific search strategy to quickly determine the optimum SM partition. Our evaluation shows that CD-search improves system throughput by 10.4% on average (and up to 62.9%) over even partitioning for workloads that are classified for the performance mode. For workloads classified for the power mode, CD-search reduces power consumption by 25% on average (and up to 41.2%). CD-search incurs limited runtime overhead

BIM-GIS ORIENTED INTELLIGENT KNOWLEDGE DISCOVERY

Urban and population growth results in increasing pressure on the public utilities like transport, energy, healthcare services, crime management and emergency services in the realm of smart city management. Smart management of these services increases the necessity of dealing with big data which is come from different sources with various types and formats like 3D city information, GPS, traffic, mobile, Building Information Model (BIM), environmental, social activities and IoT stream data. Therefore, an approach to mine/analysis/interpret these data and extract useful knowledge from this diverse big data sources emerges in order to extract the hidden pattern of data using computational algorithms from statistics, machine learning and information theory. However, inconsistency, duplication and repetition and misconducting with the different type of discrete and continuous data can cause erroneous decision-making. This paper focuses on providing a rules extraction and supervised-decision making methods for facilitating the fusion of BIM and 2D and 3D GIS-based information coupling with IoT stream data residing in a spatial database and 3D BIM data. The proposed methods can be used in those applications like Emergency Response, Evacuation Planning, Occupancy Mapping, and Urban Monitoring to Smart Multi-Buildings so that their input data mostly come from 2D and 3D GIS, BIM and IoT stream. This research focus on proposing the unified rules extraction and decision engine to help smart citizens and managers using BIM and GIS data to make smart decision rather than focus on applications in certain field of BIM and GIS

Herbal-based drugs for dry eye; treatment and adverse reaction

33-40Dry eye syndrome is one of the most common types of eye diseases. Due to the significant prevalence of the disease, there is an important need for treatment of dry eye in a simple but efficient way. Artificial tears are the most common agents used for treating dry eye but are not very useful. In recent years, the use of herbal remedies has attracted much attention, because the process of producing most herbal remedies is simple, inexpensive and has fewer side effects. In many clinical studies, the potential interactions between medicines and herbs have been demonstrated. According to reports, some herbal products have the potential to be used for the treatment of dry eye while the use of certain products can lead to this syndrome. In this review, we have listed some of the herbal drugs and components which can prevent or treat the dry eye or cause it

Recognition and identification analysis of the features of the epistemology of the MOOC (Massive and Courses)

Background and Objectives: One of the forms of knowledge acquisition in the current era is the distance education system, which has changed the traditional teaching methods, made it possible for everyone to learn everywhere and at any time, and has established social justice in the distribution of resources and facilities. It has created the necessary conditions for standardized education and in accordance with the needs of individuals and society, as well as the significant help that this system can easily and timely modernize education, save time, money and energy consumption, create opportunities for continuing education for employed people, strengthen specializations and creates calmness and reduces anxiety. And given that in addition to classroom teaching at the university, distance learning is now a valid method worldwide and UNESCO and other educational organizations around the world emphasize the expansion of distance learning, it is necessary to seriously develop it and the foundations of epistemology; and make it known to policymakers, planners and learners.The present study was conducted with the aim of identification and assessing the epistemological characteristics of MOOC (massive and courses). Methods: For this purpose, two methods of exploratory search (qualitative) and a questionnaire (quantitative) method were used. In the qualitative part of the research environment, the relevant electronic sources related to the subject matter of the research including 20 related articles were selected. In the quantitative section from the statistical population of 60 specialists in planning distance education in 2018 in the country a sample of 36 people was selected through voluntary sampling. To analyze the qualitative data, content analysis method and content validity index were used for analyzing quantitative data from mean weight and Friedman test. Findings: The results of content analysis indicated that four episodes of the learner, the content, teaching organization and educational environment can be investigated in MOOC epistemology (massive and courses). A total of 35 criteria were identified and confirmed. Quantitative results show that improving the level of information and digital literacy of professors, and knowledge with previous cognitive structures are the most important criterions of the epistemological characteristics of the courses of MOOC; and the criteria of ease of usedigital content, the recruitment of information technology professionals, for knowledge courses and the provision of Internet-based learning group environment, are the most important criterion for epistemology of massive MOOC. Conclusion: The results showed that in the epistemology of massive courses the dim   ===================================================================================== COPYRIGHTS  ©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================