Hot Spot

Studies on denudation rates can provide insight into the influence of climate change, tectonics, and human activities on landscape evolution. Research performed in Central Italy has shown considerable spatial variability of denudation rates in the major river basins. These studies have focused mainly on the Tyrrhenian side of the Italian peninsula, where Plio-Pleistocene marine deposits filling NW–SE elongated sedimentary basins have been uplifted during the Quaternary up to several hundreds of meters above present sea level. Small sub-catchments developed on clays are affected by sharp- and/or rounded-edged badlands (i.e. calanchi and biancane), representing denudation “hot spots” in the present-day morphoclimatic framework.In this paper, we analyze the relationships between indirectly estimated denudation rates at the catchment scale and field monitoring data at the hillslope scale. We attempt to better understand and quantify all hillslope processes that contribute to seasonal variability of denudation, to help with predicting the net input from “hot spots” to the overall estimated sediment yield at the basin outlets. At the hillslope scale, we discuss, in particular, the variability of denudation rates at calanchi and biancane badlands as a function of their different morphoevolution.

Abstract: Higher Education is increasingly relying on e-learning as a means of providing students with teaching and learning resources. Almost inevitably, this means that students interact with these learning resources through the medium of the computer screen. Although there have been significant advances in the design and implementation of online resources, exactly how students interact with these resources is a relatively new field of research. In this feasibility study students were asked to interact with a virtual learning environment, i.e. Blackboard, as well as Internet based resources, i.e. Ingenta and Wikipedia. Specifically, the students were asked to find the answer to a question provided, e.g. “what is classical conditioning?”orto locate a body of research related to a given topic, e.g. “theories of forgetting”. As they searched for the information the eye movements of the students were recorded using a Tobii X50 eye tracking system. The data gathered was analyseddynamic...

The winding hot-spot temperature is one of the most critical parameters that affect the useful life of the power transformers. The winding hot-spot temperature can be calculated as function of the top-oil temperature that can estimated by using the ambient temperature and transformer loading measured data. This paper proposes the estimation of the top-oil temperature by using a method based on Least Squares Support Vector Machines approach. The estimated top-oil temperature is compared with measured data of a power transformer in operation. The results are also compared with methods based on the IEEE Standard C57.91-1995/2000 and Artificial Neural Networks. It is shown that the Least Squares Support Vector Machines approach presents better performance than the methods based in the IEEE Standard C57.91-1995/2000 and artificial neural networks.

Power semiconductors can be modeled as a thermal network of resistors and capacitors. The thermal boundary condition of such a model is typically defined as the heat sink surface temperature, which is assumed to be constant. In reality, the heat sink surface temperature underneath the power module is not exactly known. In this paper we show how to set up a thermal model of the heat sink in form of a RC thermal equivalent network that can be directly embedded in any circuit simulator. The proposed thermal heat sink model takes into account convection cooling, thermal hotspots on the heat sink base plate, thermal time constants of the heat sink, and thermal coupling between different power modules mounted onto the heat sink. Experimental results are given and show high accuracy of the heat sink model with temperature errors below 10%.

Ascochyta blight (AB, Ascochyta rabiei (Pass.) Lab.) is one of the most important foliar disease of chickpea (Cicer arietinum L.), globally. Chickpea is attacked by AB at any growth stage in cool and humid weather depending on the inoculum availability. However, the disease epidemics are most prominent during the flowering and podding growth stages. The main objective of this study was to determine the effect of growth stages of chickpea on the genetic resistance of AB and use this information in a resistance breeding program. Two susceptible and two moderately resistant chickpea cultivars were spray inoculated at seedling (GS1), post-seedling (GS2), vegetative (GS3), flowering (GS4) and podding (GS5) growth stages with A. rabiei conidial suspension under controlled environment conditions. Irrespective of crop cultivars the incubation period (IP) was shorter in GS1, GS4 and GS5 and was significantly extended in GS2 and GS3. Symptom development was delayed significantly in moderately resistant cultivars. The AB severity 10 days after inoculation ranged between 7 and 9 on susceptible cultivars and 3 and 5 on moderately resistant cultivars. Further the correlation coefficient of disease severity between GS1, GS4 and GS5 was highly significant (r = 0.95) indicating that, evaluation for resistance to AB can be done at GS 1 (seedling stage), and or GS4 (flowering stage) to GS5 (podding stage) growth stages of chickpea. This supports the evaluation for AB resistance using 10-day-old-seedlings in controlled environment at ICRISAT and adult plant field screening at hot-spot locations in Dhaulakuan and Ludhiana in India.

In modern data centers, energy consumption accounts for a considerably large slice of operational expenses. The state of the art in data center energy optimization is focusing only on job distribution between computing servers based on workload or thermal profiles. This paper underlines the role of communication fabric in data center energy consumption and presents a scheduling approach that combines energy efficiency and network awareness, termed DENS. The DENS methodology balances the energy consumption of a data center, individual job performance, and traffic demands. The proposed approach optimizes the tradeoff between job consolidation (to minimize the amount of computing servers) and distribution of traffic patterns (to avoid hotspots in the data center network).

Weisburd (2015) has proposed the law of crime concentration at places, which states that urban crimes
concentrate in micro geospatial units, hot spots, within a narrow band of high percentages. For example,
in large cities around 50% of crime occurs in only 5% of a city’s block‐long street segments. Should hot
spot programs for crime prevention by police be constant for a year or more over the range from 0% to
5% of a city’s street network, or should they be dynamic? Of course, in the trivial case of a hot spot
being permanently eliminated, police would no longer allocate special prevention. This chapter is
concerned with non‐trivial cases.
While the Koper curve (Koper 1995) addresses optimal duration of directed patrols on a daily basis in
crime hot spots, the literature has been largely silent on longer time‐scales of weeks, months, or years
for optimal duration of hot spot programs. For example, the Telep, Mitchel, and Weisburd (2014) hot
spot field trials in Sacramento called for 15 minute patrols (following the Koper curve) every two hours
from 9:00 AM until 1:00 AM, for a total of 8 patrols per hot spot and day. For implementation by the
Sacramento police, however, should some hot spots have treatment for a year or longer but others for
shorter durations of time—weeks or months? If so, for how long?
To address these questions, this chapter further decomposes hot spots into two primary types by
duration, chronic and temporary. Chronic hot spots are fixed with durations of at least a year, but often
last much longer, even for decades. Temporary hot spots are dynamic with an on‐and‐off behavior for
weeks or months at a time. As such, chronic hot spots merit constant crime prevention programs by
police while temporary hot spots should have dynamic allocations of police resources. Needed for
dynamic allocations are accurate models for predicting temporary hot spots, or early detection with
accurate predictions of persistence. Criminological theories suggest crime patterns that are the basis for
accurate‐enough crime prediction models.
Notable in our paper (Gorr and Lee 2015) and in this chapter is the introduction of distributional equity
of police crime prevention services as an important performance criterion for hot spot program design,
in addition to the commonly‐used effectiveness criterion. This chapter makes the case that a
combination chronic and temporary hot spot program is the most effective and equitable program. In
doing so the chapter reviews related criminological theories, prediction models, police interventions for
crime prevention, performance measures, and police policy.

All electric equipment in a power system has to be designed to withstand the mechanical and thermal stresses of potential short-circuit currents. Any reduction of these currents can lead to significant cost savings. Among all current limiting devices, superconducting fault current ...

The objective of the 13th edition of Ph Doctoral Students in Object-Oriented Systems workshop (PHDOOS) was to offer an oppor- tunity for PhD students to meet and share their research experiences, and to discover commonalities in research and student ship. In this way, the participants may receive insightful comment about their research, learn about related work and initiate future research

Machining and processing activities (and mining activities for U) produce particulate U and Pu, which can be transported in air as fine material, and physically in soil and water through various physical and biological transport processes. Dissolved U and Pu can be produced by chemical processing, leaching, or weathering of particulates, especially for U. Uranium is transported in groundwater primarily as dissolved U(VI). The dissolved species depends strongly upon the solution pH and dissolved carbonate concentration, as well as other aspects of water chemistry and substrate properties along the transport - pathways. In general, UO2 2+ dominates in waters less than pH 6, UO2OH + and (UO2)2CO3(OH)3 in waters in equilibrium with atmospheric CO2 between pH 6 and 7, and UO2(CO3)2 2- and UO2(CO3)3 4- in most waters above pH 7, and in carbonate-rich waters above pH 6. Pu chemistry is more complex. Depending upon redox and pH conditions, Pu is able to exist in 3 or 4 oxidation states in n...