260 research outputs found
Knowledge, Attitude, and the Real Practice of General Dental Practitioners in Shiraz, Iran Towards Accepting HIV-Positive Patients
Chiral dynamics in QED and QCD in a magnetic background and nonlocal noncommutative field theories
We study the connection of the chiral dynamics in QED and QCD in a strong
magnetic field with noncommutative field theories (NCFT). It is shown that
these dynamics determine complicated nonlocal NCFT. In particular, although the
interaction vertices for electrically neutral composites in these gauge models
can be represented in the space with noncommutative spatial coordinates, there
is no field transformation that could put the vertices in the conventional form
considered in the literature. It is unlike the Nambu-Jona-Lasinio (NJL) model
in a magnetic field where such a field transformation can be found, with a cost
of introducing an exponentially damping form factor in field propagators. The
crucial distinction between these two types of models is in the characters of
their interactions, being short-range in the NJL-like models and long-range in
gauge theories. The relevance of the NCFT connected with the gauge models for
the description of the quantum Hall effect in condensed matter systems with
long-range interactions is briefly discussed.Comment: 19 pages, REVTeX4, v2: clarifications added, v3: to match PRD versio
FLOOD SUSCEPTIBILITY MODELLING USING GEOSPATIAL-BASED MULTI-CRITERIA DECISION MAKING IN LARGE SCALE AREAS
Flood is one of the most hazardous natural disasters that cause damages and poses a major threat to human lives and infrastructures worldwide, and its prevention is almost unfeasible. Thus, the detection of flood susceptible areas can be a key to lessen the amount of destruction and mortality. This study aims to implement a framework to identify flood potential zones in an ungauged large-scale area with frequent flood events in recent years. We used two Multi-Criteria Decision Making (MCDM) approaches combined with geospatial analysis, and remote sensing observations for this susceptibility analysis. Nine geomorphological and environmental factors that have an impact on flood behaviour were selected and used for susceptibility modelling. At first, the criteria’s weights were estimated using two MCDM approaches and based on experts’ knowledge. The resultant weights revealed that Flow Accumulation, Topographic wetness index, and Distance to River were the most influential flood susceptibility criteria. After calculating these weights, the criteria’s layers were aggregated through geospatial analysis, which resulted in generating flood susceptibility map. The area under the curve (AUC) and statistical measures such as the Kappa index were used to evaluate the proposed method's efficiency. The validation results illustrate that hybrid FAHP, with AUC= 96.68 and Kappa = 81.36 performed more efficiently than standard AHP, with AUC= 94.53 and Kappa=76.35. Overlaying these maps with the historical flood inventory dataset revealed that 86.43% of flooded areas were categorized as “high” and “very high”. Therefore, the flood susceptibility maps generated through the proposed approach can help the decision-makers and managers allocate the mitigation equipment and facility in data-scarce and ungauged large-scale areas
Tensor Self Energy in a Vector-Tensor Model
The tensor self energy is computed at one loop order in a model in which a
vector and tensor interact in a way that eliminates all tensor degrees of
freedom. Divergencies arise which cannot be eliminated without introducing a
kinetic term for the tensor field which does not appear in the classical
action. We comment on a possible resolution of this puzzle.Comment: 7 pages, LaTeX, additional analysis and comment
IDENTIFYING SUITABLE LOCATIONS FOR MANGROVE PLANTATION USING GEOSPATIAL INFORMATION SYSTEM AND REMOTE SENSING
Mangroves provide numerous environmental benefits, such as carbon sequestration, water purification, climate change mitigation, and flood and Tsunami impact reduction. Despite these unique advantages, mangroves are threatened by the combined adverse impacts of human activities and climate change. Therefore, it is essential to implement reasonable practices to avoid further degradation of mangroves and provide efficient workflows to increase their extent. Accordingly, better plantation policies are principally required for their conservation and rehabilitation. In this study, we desired to detect suitable locations for mangrove plantation in coastal areas of Hormozgan Province, Iran. We considered a relatively new Multi Criteria Decision Making (MCDM) technique to combine ten criteria derived from remote sensing in a GIS environment. The Best Worst Method (BWM), as an MDCM technique, was implemented to determine the relative importance of each criterion. Afterward, all criteria were aggregated using the Weighted Linear Combination (WLC) method to produce a mangrove plantation suitability map. Statistical measures, including Overall Accuracy (OA = 95%), Kappa Coefficient (KC = 87.9%), and Area Under Curve (AUC = 98.79%), indicated the high applicability of the implemented method for mangrove plantation site allocation. The produced map could give managers a profound insight into finding optimal spots to plant mangroves
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