Road surface monitoring is a key factor to providing smooth and safe road infrastructure to road users. The key to road surface condition monitoring is to detect road surface anomalies, such as ...potholes, cracks, and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become increasingly popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road maintenance. However, current smartphone sensors operate at a low frequency, and undersampled sensor signals cause low detection accuracy. In this study, current approaches for using smartphones for road surface anomaly detection are reviewed and compared. In addition, further opportunities for research using smartphones in road surface anomaly detection are highlighted.
Conventional ice navigation in the sea is manually operated by well-trained navigators, whose experiences are heavily relied upon to guarantee the ship’s safety. Despite the increasingly available ...ice data and information, little has been done to develop an automatic ice navigation support system to better guide ships in the sea. In this study, using the vector-formatted ice data and navigation codes in northern regions, we calculate ice numeral and divide sea area into two parts: continuous navigable area and the counterpart numerous separate unnavigable area. We generate Voronoi Diagrams for the obstacle areas and build a road network-like graph for connections in the sea. Based on such a network, we design and develop a geographic information system (GIS) package to automatically compute the safest-and-shortest routes for different types of ships between origin and destination (OD) pairs. A visibility tool, Isovist, is also implemented to help automatically identify safe navigable areas in emergency situations. The developed GIS package is shared online as an open source project called NavSpace, available for validation and extension, e.g., indoor navigation service. This work would promote the development of ice navigation support system and potentially enhance the safety of ice navigation in the Arctic sea.
•Monitoring road surface roughness and detecting anomalies using smartphone sensors.•A vibration-based approach to detect road surface anomalies.•Crowdsourcing mobile app to collect road surface ...condition data.•Machin learning approach to classify discomfort level of road surface anomalies.
Road surface hazards affect the driving safety and comfort of road users. Recently, smartphones and mobile devices equipped with motion sensors such as accelerometers and gyroscope sensors have attracted researchers’ attention for the development of low-cost approaches for road surface monitoring. However, processing smartphone sensors to monitor road surface conditions is technically challenging due to dissimilar sensor properties, different smartphone placement, and also different vehicle mechanical properties. This study aimed to develop a hybrid method using threshold based and Machine Learning approaches for near real-time detection and classification of road surface anomalies using smartphone sensor data with higher-level accuracy. The proposed algorithm has self-adapting and self-updating capabilities to adapt itself to any type of smartphone and the dynamic behaviors of various vehicles and road surface conditions. A prototype is developed using MATLAB and ArcGIS to perform sensor data analysis, geocoding, geo-visualizing, and data querying for performance evaluation.
•We propose a novel smart parking mechanism which seeks to reduce the cruising time.•A non-myopic atomic game is formulated to control the price of anarchy.•A socially efficient price which accounts ...for the waiting times of customers is studied.•Using SF parking data, the average social welfare per vehicle is improved by up to 54%.
We propose a novel non-myopic smart parking mechanism which aims to decrease the cruising time spent in searching for parking, with the assumption of elastic demand for both on-street parking lots and parking garages. A non-myopic atomic game is formulated to address competition for parking through assignment of vehicles to candidate parking facilities that takes into account the differences in travel times for the vehicles from their point of origin to the parking facilities and the differences in walking times for the drivers from the parking facilities to their final destination, as well as dynamic pricing, cruising times, and occupancies of the parking facilities. This study integrates a socially efficient price that accounts for the waiting times of drivers in their search for parking. We incorporate a game model into the social optimum problem by considering the competition of drivers for parking spaces where the drivers’ preferences are reflected in a collective decision such as social welfare. Using actual parking data for the city of San Francisco, we found that under our proposed dynamic parking system the average social welfare per vehicle improved by up to 54% compared to other parking strategies.
Opioid and glutamatergic receptors have a key role in depression following stress. In this study, we assessed opioid and glutamatergic receptors interaction with the depressant-like behavior of acute ...foot-shock stress in the mouse forced swimming test. Stress was induced by intermittent foot shock stimulation during 30min and swim periods were afterwards conducted by placing mice in separated glass cylinders filled with water for 6min. The immobility time during the last 4min of the test was considered. Acute foot-shock stress significantly increased the immobility time of mice compared to non-stressed control group (P≤0.01). Administration of non-selective opioid receptors antagonist, naltrexone (1 and 2mg/kg, i.p.), and the selective non-competitive NMDA receptor antagonist, MK-801 (0.05mg/kg, i.p.), and the selective serotonin reuptake inhibitor, fluoxetine (5mg/kg), significantly reduced the immobility time in stressed animals (P≤0.01). Lower doses of MK-801 (0.01mg/kg), naltrexone (0.3mg/kg), NMDA (75mg/kg) and morphine(5mg/kg) had no effect on foot-shock stressed mice. Combined treatment of sub-effective doses of naltrexone and MK-801 significantly showed an antidepressant-like effect (P≤0.001). On the other hand, co-administration of non-effective doses of NMDA and morphine with effective doses of naltrexone and MK-801 reversed the anti-immobility effect of these drugs. Taken together, we have for the first time demonstrated the possible role of opioid/NMDA receptors signaling in the depressant-like effect of foot-shock stress, and proposed the use of drugs that act like standard anti-depressants in stress-induced depression.
Freedom of association is one of the most important human rights of human beings, which also plays a serious role in the demand and realization of other human rights. In many cases, these rallies are ...held to protest participants against the government's policies. The peaceful holding of rallies and the important role played by the police and other security forces in securing them are among the important issues that need to be addressed. In some cases, some participants in peaceful rallies may resort to violence and the police may be forced to use force to maintain order and security. The fundamental question of this article is what are the powers and obligations of governments, especially in the use of force to control peaceful assembly? The research method of this research is analytical-descriptive and the method of collecting information is library. The results of this study show that Iran's domestic regulations are generally in line with human rights standards, but in some cases, there is a conflict between these regulations. In Law on the Use of Weapons by Armed Forces Officers, the police appear to use weapons to control illegal assemblies if other means are not effective, but in the human rights system, police can use force only in cases of legitimate self-defense.
Background: Approximately 90% of the fatty acids in sunflower oil are unsaturated. This study evaluated the antioxidant activity of leaf methanol extract of four Iranian olive cultivars on the ...oxidative stability of sunflower oil.Methods: Leaf methanolic extracts of four Iranian olive cultivars (Zard, Roghani, Shiraz, and Dezfool) were prepared by microwave extraction method. Total phenolic content, diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activity, and reducing power of the extracts were determined. Peroxide and anisidine values of sunflower oil treated with the extracts were measured during 30 days of storage at 60°C.Results: The concentration of methanolic extract of the Roghani cultivar (46.27±2.76 μg/mL) required to scavenge 50% of the initial DPPH radicals (IC50) showed a significant difference (p<0.05) with the IC50 of butylated hydroxytoluene (BHT) (112.90±14.81 μg/mL), meaning that the percent inhibition of the DPPH radical of the methanol extract of the Roghani cultivar was higher than that of BHT (p<0.05). During the 30 days storage period, sunflower oil samples without antioxidants showed significantly higher anisidine and peroxide values than samples treated with olive leaf extracts (p<0.05). In all treated samples, as the concentration of the extracts increased, peroxide and anisidine values significantly decreased (p<0.05).Conclusion: This study showed that the methanolic extracts of olive leaves had the ability to limit the oxidation of lipids and can be considered as a potential antioxidant source of natural origin. The methanolic extract of Roghani cultivar had the highest effect on the oxidative stability of sunflower oil.
Hexamethylenetetramine‐functionalized silica‐coated nano‐Fe3O4 particles (MNPs@Hexamethylenetetramine) were prepared as a reusable heterogeneous catalyst using a facile process. The catalyst was ...synthesized and characterized using infrared, X‐ray diffraction, scanning electron microscopy, thermogravimetric analysis, and vibrating sample magnetometer. This magnetic nanocatalyst was employed as an efficient, reusable, and environmentally benign heterogeneous catalyst for the synthesis of amidoalkylnaphthol derivatives from a one‐pot three‐component condensation reaction of beta‐naphthol, aldehydes, and amides in good to excellent yields, Moreover, this catalyst can be easily recovered by using a magnetic field and directly reused for at least seven runs without sign ificant loss of its activity.
Hexamethylenetetramine‐functionalized silica‐coated nano‐Fe3O4 particles were used for the synthesis of amidoalkylnaphthol derivatives using a solvent free, one‐pot, three‐component condensation reaction of beta‐naphthol, aldehydes, and amides in good to excellent yield.
Display omitted
•Baclofen has an anti-depressant like effect in forced swimming test.•This effect increased by inhibition of nitric oxide production.•This effect increased by NMDA receptor ...antagonist.•This effect decreased by PDE5 inhibition.•The antidepressant-like action of baclofen mediated by NMDA receptors and NO-GMP pathway in forced swimming test
In the current study, the involvement of N-methyl-d-aspartate receptor (NMDAR) and nitric oxide (NO)/cyclic guanosine monophosphate (cGMP) system in the antidepressant-like effects of baclofen was evaluated by using animal model in forced swimming test. Followed by an open field test for the evaluation of locomotor activity, the immobility time for mice in force swimming test was recorded. Only the last four min was analyzed. Administration of Baclofen (0.5 and 1mg/kg, i.p.) reduced the immobility interval in the FST. Prior administration of l-arginine (750mg/kg, i.p.,) a nitric oxide synthase substrate or sildenafil (5mg/kg, i.p.) a phosphodiesterase 5 into mice suppressed the antidepressant-like activity of baclofen (1mg/kg, i.p.).Co-treatment of 7-nitroindazole (50mg/kg, i.p.,) an inhibitor of neuronal nitric oxide synthase, L-NAME (10mg/kg, i.p.,) a non-specific inhibitor of nitric oxide synthase or MK-801 (0.05mg/kg, i.p.) an NMDA receptor antagonist with subeffective dose of baclofen (0.1mg/kg, i.p.), reduced the immobility time in the FST as compared to the drugs when used alone. Co-administrated of lower doses of MK-801 (0.01mg/kg) or l-NAME (1mg/kg) failed to effect immobility time however, simultaneous administration of these two agents in same dose with subeffective dose of baclofen (0.1mg/kg, i.p.), minimized the immobility time in the FST. Thus, our results support the role of NMDA receptors and l-arginine-NO-GMP pathway in the antidepressant-like action of baclofen.
Incidences of disease, dieback, decline or mortality, some of which induced or enhanced by climate change, threaten the sustainability of forest stands in many ecosystems. Spatially explicit ...prediction of disease onset remains challenging, however, due to the involvement of several causative agents. In this paper, we developed a generic framework based on machine-learning algorithms and spatial analyses for landscape-level prediction of oak disease outbreaks caused by the charcoal fungus Biscogniauxia mediterranea in a mixed-oak forest of Mediterranean climate. For prediction, we used a set of fifteen causative factors as a cross-function of soil, site and stand-related predictors. A total of 80 sample plots, including 1134 affected trees, were surveyed and used for the modeling process at the 5600-ha landscape level of the southern Zagros, Iran, where the disease occurs in roughly 25% of forest lands. Ten machine learning algorithms were explored and the performance of each algorithm to predict oak disease outbreak was evaluated. The modeling framework used maximum entropy to remove the least influential variables and build the status-quo management scenario to which the results of the prediction models were compared. Results showed that the random forests algorithm (AUC = 0.96: Precision = 0.71: Accuracy = 0.90: F-Measure = 0.70) achieved significantly better results than the status-quo management (Precision = 0.13: Accuracy = 0.67: F-Measure = 0.12) and any other algorithm. Soil chemical properties (NPK, organic carbon and EC) and landform predictors (slope, distance to roads, and TWI) were major forecasters of oak disease outbreak identified by the random forest algorithm. Geostatistical analysis enabled the creation of a map that identified sites at higher risk of infestation, allowing epidemiologists and forest managers to find sites likely to be infested. Consequently, financial resources can be allocated and management practices such as sanitation felling treatments applied across large forest landscapes to minimize the risk of spread and severity to uninfested high-value trees on nearby or adjacent land zones that are in the early stage of epidemics.
•Soil and landform attributes explain short-term presence of oak charcoal disease.•Random forest (RF) algorithms outperform nine other machine learning algorithms.•RF predicts 41% of Brant's oak at moderate disease intensity in southern Zagros.•RF algorithm predicts oak dieback, decline or mortality with 96% accuracy.•Machine-learning algorithms predict spatial charcoal disease intensity in Brant's oak.
PDF
