Efficient separation of the orbital angular momentum eigenstates of light

Orbital angular momentum (OAM) of light is an attractive degree of freedom for funda- mentals studies in quantum mechanics. In addition, the discrete unbounded state-space of OAM has been used to enhance classical and quantum communications. Unambiguous mea- surement of OAM is a key part of all such experiments. However, state-of-the-art methods for separating single photons carrying a large number of different OAM values are limited to a theoretical separation efficiency of about 77 percent. Here we demonstrate a method which uses a series of unitary optical transformations to enable the measurement of lights OAM with an experimental separation efficiency of more than 92 percent. Further, we demonstrate the separation of modes in the angular position basis, which is mutually unbiased with respect to the OAM basis. The high degree of certainty achieved by our method makes it particu- larly attractive for enhancing the information capacity of multi-level quantum cryptography systems

Studying the Mechanisms of Developmental Vocal Learning and Adult Vocal Performance in Zebra Finches through Lentiviral Injection

Here we provide a detailed step-by-step protocol for using lentivirus to manipulate miRNA expression in Area X of juvenile zebra finches and for analyzing the consequences on song learning and song performance. This protocol has four parts: 1) making the lentiviral construct to overexpress miRNA miR-9; 2) packaging the lentiviral vector; 3) stereotaxic injection of the lentivirus into Area X of juvenile zebra finches; 4) analysis of song learning and song performance in juvenile and adult zebra finches. These methods complement the methods employed in recent works that showed changing FoxP2 gene expression in Area X with lentivirus or adeno-associated virus leads to impairments in song behavior

On-chip spectroscopy with thermally-tuned high-Q photonic crystal cavities

Spectroscopic methods are a sensitive way to determine the chemical composition of potentially hazardous materials. Here, we demonstrate that thermally-tuned high-Q photonic crystal cavities can be used as a compact high-resolution on-chip spectrometer. We have used such a chip-scale spectrometer to measure the absorption spectra of both acetylene and hydrogen cyanide in the 1550 nm spectral band, and show that we can discriminate between the two chemical species even though the two materials have spectral features in the same spectral region. Our results pave the way for the development of chip-size chemical sensors that can detect toxic substances

Towards Quantum Communication with more than 4 bits/photon: Near-Perfect Sorting of the Orbital Angular Momentum Modes of Light

We demonstrate a method that uses a series of optical transformations to sort the orbital angular momentum and the mutually-unbiased angular position modes of light with a separation efficiency of more than 92%

Preparation of Green Biosorbent using Rice Hull to Preconcentrate, Remove and Recover Heavy Metal and Other Metal Elements from Water

Sodium hydroxide treated rice hulls were investigated to preconcentrate, remove, and recover metal ions including Be2+, Al3+, Cr3+, CO2+, Ni2+, Cu2+, Zn2+, Sr2+, Ag+, Cd2+, Ba2+, and Pb2+ in both batch mode and column mode. Sodium hydroxide treatment significantly improved the removal efficiency for all metal ions of interest compared to the untreated rice hull. The removal kinetics were extremely fast for Co, Ni, Cu, Zn, Sr, Cd, and Ba, which made the treated rice hull a promising economic green adsorbent to preconcentrate, remove, and recover low-level metal ions in column mode at relatively high throughput. The principal removal mechanism is believed to be the electrostatic attraction between the negatively charged rice hulls and the positively charged metal ions. pH had a drastic impact on the removal for different metal ions and a pH of 5 worked best for most of the metal ions of interest. Processed rice hulls provide an economic alternative to costly resins that are currently commercially available products designed for metal ion preconcentration for trace metal analysis, and more importantly, for toxic heavy metal removal and recovery from the environment

Reshaping the Landscape of the Future: Software-Defined Manufacturing

We describe the concept of software-defined manufacturing, which divides the manufacturing ecosystem into software definition and physical manufacturing layers. Software-defined manufacturing allows better resource sharing and collaboration, and it has the potential to transform the existing manufacturing sector

Election with Bribed Voter Uncertainty: Hardness and Approximation Algorithm

Bribery in election (or computational social choice in general) is an important problem that has received a considerable amount of attention. In the classic bribery problem, the briber (or attacker) bribes some voters in attempting to make the briber's designated candidate win an election. In this paper, we introduce a novel variant of the bribery problem, "Election with Bribed Voter Uncertainty" or BVU for short, accommodating the uncertainty that the vote of a bribed voter may or may not be counted. This uncertainty occurs either because a bribed voter may not cast its vote in fear of being caught, or because a bribed voter is indeed caught and therefore its vote is discarded. As a first step towards ultimately understanding and addressing this important problem, we show that it does not admit any multiplicative $O(1)$-approximation algorithm modulo standard complexity assumptions. We further show that there is an approximation algorithm that returns a solution with an additive-$\epsilon$ error in FPT time for any fixed $\epsilon$.Comment: Accepted at AAAI 201

Prognostic value of routine laboratory variables in prediction of breast cancer recurrence.

The prognostic value of routine laboratory variables in breast cancer has been largely overlooked. Based on laboratory tests commonly performed in clinical practice, we aimed to develop a new model to predict disease free survival (DFS) after surgical removal of primary breast cancer. In a cohort of 1,596 breast cancer patients, we analyzed the associations of 33 laboratory variables with patient DFS. Based on 3 significant laboratory variables (hemoglobin, alkaline phosphatase, and international normalized ratio), together with important demographic and clinical variables, we developed a prognostic model, achieving the area under the curve of 0.79. We categorized patients into 3 risk groups according to the prognostic index developed from the final model. Compared with the patients in the low-risk group, those in the medium- and high-risk group had a significantly increased risk of recurrence with a hazard ratio (HR) of 1.75 (95% confidence interval [CI] 1.30-2.38) and 4.66 (95% CI 3.54-6.14), respectively. The results from the training set were validated in the testing set. Overall, our prognostic model incorporating readily available routine laboratory tests is powerful in identifying breast cancer patients who are at high risk of recurrence. Further study is warranted to validate its clinical application

A Game Theoretical Analysis of Non-Linear Blockchain System

Recent advances in the blockchain research have been made in two important directions. One is refined resilience analysis utilizing game theory to study the consequences of selfish behavior of users (miners), and the other is the extension from a linear (chain) structure to a non-linear (graphical) structure for performance improvements, such as IOTA and Graphcoin. The first question that comes to mind is what improvements that a blockchain system would see by leveraging these new advances. In this paper, we consider three major properties for a blockchain system: -partial verification, scalability, and finality-duration. We establish a formal framework and prove that no blockchain system can achieve -partial verification for any fixed constant , high scalability, and low finality-duration simultaneously. We observe that classical blockchain systems like Bitcoin achieves full verification ( = 1) and low finality-duration, Ethereum 2.0 Sharding achieves low finality-duration and high scalability. We are interested in whether it is possible to partially satisfy the three properties