Multiphoton Bloch-Siegert shifts and level-splittings in spin-one systems

We consider a spin-boson model in which a spin 1 system is coupled to an oscillator. A unitary transformation is applied which allows a separation of terms responsible for the Bloch-Siegert shift, and terms responsible for the level splittings at anticrossings associated with Bloch-Siegert resonances. When the oscillator is highly excited, the system can maintain resonance for sequential multiphoton transitions. At lower levels of excitation, resonance cannot be maintained because energy exchange with the oscillator changes the level shift. An estimate for the critical excitation level of the oscillator is developed.Comment: 14 pages, 3 figure

An Overview of Treatment of Steel-Making Slag for Recovery of Lime Phosphorus Values

The steelmaking slag containing high phosphorus (1-3 % P2O5) can not be used in blast furnace, as it increases the refining load. Removal of phosphorus is essential for the recycling of slag which consists of major phases like dicalcium silicate, dicalcium ferrite and wustite. The majority of phosphorus is present in the dicalcium silicate. The objective of this study is to remove this phase selectively to the extent of 90% by different methods. The paper reviews these methods and suggests a methodology for removal of phosphorus

Unsteady Viscous Flow Down an Inclined Open Channel with Naturally Permeable Bed

The exact velocity distribution for the flow of viscous incompressible fluid in an inclined channel with naturally permeable bed has been obtained by using the Laplace transform and the Finite Fourier Sine transform technique. It has been assumed that (i) the fluid flows in the steady state for t < 0, (ii) unsteady state occurs at t > 0, and (iii) unsteady state motion is influenced by time dependent pressure gradient

Water level prediction from social media images with a multi-task ranking approach

Floods are among the most frequent and catastrophic natural disasters and affect millions of people worldwide. It is important to create accurate flood maps to plan (offline) and conduct (real-time) flood mitigation and flood rescue operations. Arguably, images collected from social media can provide useful information for that task, which would otherwise be unavailable. We introduce a computer vision system that estimates water depth from social media images taken during flooding events, in order to build flood maps in (near) real-time. We propose a multi-task (deep) learning approach, where a model is trained using both a regression and a pairwise ranking loss. Our approach is motivated by the observation that a main bottleneck for image-based flood level estimation is training data: it is diffcult and requires a lot of effort to annotate uncontrolled images with the correct water depth. We demonstrate how to effciently learn a predictor from a small set of annotated water levels and a larger set of weaker annotations that only indicate in which of two images the water level is higher, and are much easier to obtain. Moreover, we provide a new dataset, named DeepFlood, with 8145 annotated ground-level images, and show that the proposed multi-task approach can predict the water level from a single, crowd-sourced image with ~11 cm root mean square error.Comment: Accepted in ISPRS Journal 202

Interesting thermomagnetic history effects in the antiferromagnetic state of SmMn_2Ge_2

We present results of magnetization measurements showing that the magnetic response of the antiferromagnetic state of SmMn_2Ge_2 depends on the path used in the field(H)-temperature(T) phase space to reach this state. Distinct signature of metastablity is observed in this antiferromagnetic state when obtained via field-cooling/field-warming paths. The isothermal M-H loops show lack of end-point memory, reminiscent of that seen in metastable vortex states near the field-induced first order phase transition in various type-II superconductors.Comment: 11 pages of text and 3 figure

Deterministic Sampling and Range Counting in Geometric Data Streams

We present memory-efficient deterministic algorithms for constructing epsilon-nets and epsilon-approximations of streams of geometric data. Unlike probabilistic approaches, these deterministic samples provide guaranteed bounds on their approximation factors. We show how our deterministic samples can be used to answer approximate online iceberg geometric queries on data streams. We use these techniques to approximate several robust statistics of geometric data streams, including Tukey depth, simplicial depth, regression depth, the Thiel-Sen estimator, and the least median of squares. Our algorithms use only a polylogarithmic amount of memory, provided the desired approximation factors are inverse-polylogarithmic. We also include a lower bound for non-iceberg geometric queries.Comment: 12 pages, 1 figur

Peak effect in the vortex state of V<SUB>3</SUB>Si: a study of history dependence

We present results of transport properties measurement on a single crystal of V3Si showing distinct signature of peak-effect (PE) in its vortex state. The field variation of the electrical resistance in the flux-line lattice prepared by different experimental path, namely zero field cooling and field cooling, shows a distinct path dependence in the vicinity of the PE regime. In the field cooled state, small cycling of magnetic field modifies the resistance drastically around the PE regime, highlighting the metastable nature of that state in the concerned regime

Study of feto-maternal outcome in patients with hepatitis E infection during pregnancy

Background: Hepatitis E is considered as a common cause of high maternal morbidity and mortality particularly in third trimester and also high perinatal morbidity and mortality. Thus, this study is conducted to evaluate the feto-maternal outcome in patients infected with hepatitis E during pregnancy.Methods: It is a retrospective observational study conducted in department of obstetrics and gynecology at L. G. hospital. Fifty pregnant women with clinical hepatitis in third trimester of pregnancy were included in this study and thorough investigation were carried out. Patients were monitored till postpartum period and fetal monitoring data were collected from neonatal ICU.Results: In this study, majority of pregnant patients with hepatitis B were admitted during monsoon season suggests that HEV outbreaks are more common during monsoon months. Majority of the patients (70%) were emergency cases. Majority of these patients (82%) were belonged to lower socio-economic class. Co-infection with HAV was in 2% and with HBV in 4%. S. bilirubin >15 mg/dl in 16% of patients. PT and APTT were raised in 28% of patients. FDP was raised in 70% of patients. 76% were delivered vaginally and 22% were delivered by LSCS. Most common complication in HEV infected pregnant women was disseminated intravascular coagulation (DIC) (26%). Maternal mortality rate is 14%. Out of 50 patients, 88% delivered live baby, out of which 72% needed NICU admission. Perinatal mortality rate was as high as 28%.Conclusions: Hepatitis E infection and pregnancy is a deadly and fatal combination. Specifically, in 3rd trimester of pregnancy, acute hepatitis E has a grave prognosis with high maternal morbidity and mortality. Prevention is the mainstay of controlling HEV especially in developing countries