Stroboscopic back-action evasion in a dense alkali-metal vapor

We explore experimentally quantum non-demolition (QND) measurements of atomic spin in a hot potassium vapor in the presence of spin-exchange relaxation. We demonstrate a new technique for back-action evasion by stroboscopic modulation of the probe light. With this technique we study spin noise as a function of polarization for atoms with spin greater than 1/2 and obtain good agreement with a simple theoretical model. We point that in a system with fast spin-exchange, where the spin relaxation rate is changing with time, it is possible to improve the long-term sensitivity of atomic magnetometry by using QND measurements

High Bandwidth Atomic Magnetometery with Continuous Quantum Non-demolition Measurements

We describe an experimental study of spin-projection noise in a high sensitivity alkali-metal magnetometer. We demonstrate a four-fold improvement in the measurement bandwidth of the magnetometer using continuous quantum non-demolition (QND) measurements. Operating in the scalar mode with a measurement volume of 2 cm^3 we achieve magnetic field sensitivity of 22 fT/Hz^(1/2) and a bandwidth of 1.9 kHz with a spin polarization of only 1%. Our experimental arrangement is naturally back-action evading and can be used to realize sub-fT sensitivity with a highly polarized spin-squeezed atomic vapor.Comment: 4 page

Spindle checkpoint silencing: ensuring rapid and concerted anaphase onset

The spindle checkpoint delays anaphase onset in the presence of defective kinetochore-microtubule attachments. Such delays can last for just a few minutes or several hours, but very shortly after all chromosomes achieve bi-orientation, a remarkably synchronous anaphase ensues. We are beginning to understand the pathways involved in silencing spindle checkpoint signals and subsequent activation of the anaphase-promoting complex. Here, we review recent advances made in our understanding of the molecular mechanisms regulating this critical cell cycle transition

Exploiting resource contention in highly mobile environments and its application to vehicular ad-hoc networks

As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. However, mobile environments also need to consider handover issues. Furthermore, in a highly mobile environment, traditional reactive approaches to handover are inadequate and thus proactive techniques have been investigated. Recent research in proactive handover techniques, defined two key parameters: Time Before Handover and Network Dwell Time for a mobile node in any given networking topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. This proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This paper therefore presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments

Optimized production of coal fly ash derived synthetic zeolites for mercury removal from wastewater

Coal fly ash (CFA) derived synthetic zeolites have become popular with recent advances and its ever-expanding range of applications, particularly as an adsorbent for water and gas purification and as a binder or additive in the construction industry and agriculture. Among these applications, perpetual interest has been in utilization of CFA derived synthetic zeolites for removal of heavy metals from wastewater. We herein focus on utilization of locally available CFA for efficient adsorption of mercury from wastewater. To this end, experimental conditions were investigated so that to produce synthetic zeolites from Kazakhstani CFAs with conversion into zeolite up to 78%, which has remarkably high magnetite content. In particular, the effect of synthesis reaction temperature, reaction time, and loading of adsorbent were systematically investigated and optimized. All produced synthetic zeolites and the respective CFAs were characterized using XRD, XRF, PSA and porosimetric instruments to obtain microstructural and mineralogical data. Furthermore, the synthesized zeolites were studied for the removal of mercury from aqueous solutions. A comparison of removal eficiency and its relationship to the physical and chemical properties of the synthetic zeolites were analyzed and interpreted

Cooperative Recombination of a Quantized High-Density Electron-Hole Plasma

We investigate photoluminescence from a high-density electron-hole plasma in semiconductor quantum wells created via intense femtosecond excitation in a strong perpendicular magnetic field, a fully-quantized and tunable system. At a critical magnetic field strength and excitation fluence, we observe a clear transition in the band-edge photoluminescence from omnidirectional output to a randomly directed but highly collimated beam. In addition, changes in the linewidth, carrier density, and magnetic field scaling of the PL spectral features correlate precisely with the onset of random directionality, indicative of cooperative recombination from a high density population of free carriers in a semiconductor environment

A Cascade Neural Network Architecture investigating Surface Plasmon Polaritons propagation for thin metals in OpenMP

Surface plasmon polaritons (SPPs) confined along metal-dielectric interface have attracted a relevant interest in the area of ultracompact photonic circuits, photovoltaic devices and other applications due to their strong field confinement and enhancement. This paper investigates a novel cascade neural network (NN) architecture to find the dependance of metal thickness on the SPP propagation. Additionally, a novel training procedure for the proposed cascade NN has been developed using an OpenMP-based framework, thus greatly reducing training time. The performed experiments confirm the effectiveness of the proposed NN architecture for the problem at hand

Non-Invasive Biomarkers for Earlier Detection of Pancreatic Cancer-A Comprehensive Review

SIMPLE SUMMARY: Pancreatic ductal adenocarcinoma (PDAC), which represents approximately 90% of all pancreatic cancers, is an extremely aggressive and lethal disease. It is considered a silent killer due to a largely asymptomatic course and late clinical presentation. Earlier detection of the disease would likely have a great impact on changing the currently poor survival figures for this malignancy. In this comprehensive review, we assessed over 4000 reports on non-invasive PDAC biomarkers in the last decade. Applying the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool, we selected and reviewed in more detail 49 relevant studies reporting on the most promising candidate biomarkers. In addition, we also highlight the present challenges and complexities of translating novel biomarkers into clinical use. ABSTRACT: Pancreatic ductal adenocarcinoma (PDAC) carries a deadly diagnosis, due in large part to delayed presentation when the disease is already at an advanced stage. CA19-9 is currently the most commonly utilized biomarker for PDAC; however, it lacks the necessary accuracy to detect precursor lesions or stage I PDAC. Novel biomarkers that could detect this malignancy with improved sensitivity (SN) and specificity (SP) would likely result in more curative resections and more effective therapeutic interventions, changing thus the present dismal survival figures. The aim of this study was to systematically and comprehensively review the scientific literature on non-invasive biomarkers in biofluids such as blood, urine and saliva that were attempting earlier PDAC detection. The search performed covered a period of 10 years (January 2010—August 2020). Data were extracted using keywords search in the three databases: MEDLINE, Web of Science and Embase. The Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool was applied for study selection based on establishing the risk of bias and applicability concerns in Patient Selection, Index test (biomarker assay) and Reference Standard (standard-of-care diagnostic test). Out of initially over 4000 published reports, 49 relevant studies were selected and reviewed in more detail. In addition, we discuss the present challenges and complexities in the path of translating the discovered biomarkers into the clinical setting. Our systematic review highlighted several promising biomarkers that could, either alone or in combination with CA19-9, potentially improve earlier detection of PDAC. Overall, reviewed biomarker studies should aim to improve methodological and reporting quality, and novel candidate biomarkers should be investigated further in order to demonstrate their clinical usefulness. However, challenges and complexities in the path of translating the discovered biomarkers from the research laboratory to the clinical setting remain and would have to be addressed before a more realistic breakthrough in earlier detection of PDAC is achieved

ARPES in the normal state of the cuprates: comparing the marginal Fermi liquid and spin fluctuation scenarios

We address the issue whether ARPES measurements of the spectral function $A_k (\omega)$ near the Fermi surface in the normal state of near optimally doped cuprates can distinguish between the marginal Fermi liquid scenario and the spin-fluctuation scenario. We argue that the data for momenta near the Fermi surface are equally well described by both theories, but this agreement is nearly meaningless as in both cases one has to add to $\Sigma^{\prime \prime} (\omega)$ a large constant of yet unknown origin. We show that the data can be well fitted by keeping only this constant term in the self-energy. To distinguish between the two scenarios, one has to analyze the data away from the Fermi surface, when the intrinsic piece in $\Sigma (\omega)$ becomes dominant.Comment: Accepted for publication in Europhysics Letters, Incorrect interpretation of reference 10 correcte