Miracle-dz/UniFAR-FTUs huggingface dataset:
On-Chip Quantum Communication Devices

We present here results of the Quantum Technology Flagship project UNIQORN in the area of integrated photonics for quantum communication applications. Three distinct integration platforms, namely indium phosphide based monolithic integration, polymer-based hybrid integration and the CMOS-compatible silicon platform, have been employed to manufacture components and sub-systems on chip for quantum communication devices. The choice of different platforms was made to exploit the best characteristics of each platform for the intended quantum communication device. The indium phosphide platform was employed to manufacture a transmitter chip for quantum key distribution featuring laser, modulators, and attenuators. The transmitter chip was evaluated in a QKD experiment achieving a secure rate of 1 kbit/s. The polymer platform was investigated for engineering non-classical light sources. Entangled and heralded single-photon sources, based on non-linear optics, were assembled on the polymer in a hybrid fashion together with waveguides and other passive micro-optical elements. A quantum random number generator, featuring a 70% randomness extraction efficiency, was also fabricated using the polymer integration technique. An array of 32 individual single-photon avalanche diodes, operating at room temperature and featuring an onboard coincidence logic, was coupled to the chip to demonstrate direct detection of photons on the polymer. Finally, a transimpedance amplifier based on gallium arsenide high electron mobility transistors was produced with an exceptional large electrical noise clearance of 28 dB at 100 MHz.
Investigation of Mechanical and Thermal Performance of Concrete with Scallop Shells as Partial Cement Replacement: Alternative Binder and Life Cycle Assessment

The adverse environmental impacts of building materials can be achieved by reducing the amount of cement in cementitious composites, specifically when incorporating wastes as partial replacement for Portland cement. In this work, we substitute cement with shell by-products while keeping useful specific properties. Scallop shells are good candidates to replace part of the Portland cement as they contain calcium and are available in abundance. We present an experimental and numerical study on the mechanics, hygrothermal behavior, and life cycle analysis of scallop shell concrete. In the fresh state, the replacement of cement by up to 10 wt. % of scallop shells does not significantly affect mortar properties. The results indicate that including 10% shells represents a decrease of up to 40% in the environmental impact, depending on the category of impact considered. Furthermore, the addition of Scallop shells makes the material more porous, leading to the facilitation of moisture transfer.
Precipitation Method for Determination of Carbon and Oxygen Isotopes to Detect Groundwater Contamination Near a Municipal Landfill

The paper emphasizes the importance of isotope studies as a unique tool for detecting groundwater contamination with the landfill leachate. The aim of the study was to present an additional and useful method for detecting groundwater contamination, based on stable isotope analysis. The proposed method relies on the interpretation of measured δ13CDIC and δ18O levels (in precipitated carbonates during preparation of a water sample). According to this method, two zones with different isotope composition of groundwater were identified: the first zone with natural groundwater and with low δ13CDIC levels (from −20.6 to −12.4‰) and high δ18O levels (from −13.6 to −8.0‰), and the second zone with leachate-contaminated groundwater rich in δ13CDIC (from −10.9 to + 3.6‰) and high level of δ18O (from −9.8 to −7.1‰). Measuring the isotopic composition of oxygen alone, is insufficient to delimit the contaminated zone due a partial overlap of natural levels with those of the contaminated with groundwater leachates. Determination of δ13CDIC and δ18O in the landfill leachate-contaminated water can provide an effective tool to detect groundwater contamination near municipal landfills, and it can help to minimize the number of samples collected for the analysis of conventional parameters. This proven method may offer an easy-to-use solution for detecting groundwater contamination.
Application of Mass Spectrometry for Determining the Geographic Production Area of Wagyu Beef

Japanese Black cattle (Japanese Wagyu) beef is attracting attention for its aroma and marbling, and its handling is increasing worldwide. Here, we focused on the origin discrimination of Wagyu beef and analyzed the nutritional components of Japanese Wagyu (produced in multiple prefectures of Japan), Hybrid Wagyu (a cross between Angus and Wagyu cattle born in Australia and transported to Japan), and Australian Wagyu beef using mass spectrometry (MS). Triple-quadrupole liquid chromatography–MS was used to clarify the molecular species of lipids in Wagyu beef. Fourteen classes of lipids were separated, and 128 different triacylglycerides (TGs) were detected. A simple comparative analysis of these TGs using high-performance liquid chromatography revealed significantly higher levels of triolein (C18:1/C18:1/C18:1; abbreviated OOO) and C18:1/C18:1/C16:1 (OOPo) in Japanese Wagyu. Wagyu elements beef were comprehensively analyzed using inductively coupled plasma (ICP)–MS and ICP–optical emission spectrometry. We found significant differences in the rubidium, cesium, and lithium levels of Japanese and Australian Wagyu beef. On comparing metabolites using gas chromatography–MS, we identified significant differences in the levels of amino acids and other components of the Japanese and Australian Wagyu beef. These results suggest the possibility of determining the origin of Wagyu cattle breeds using MS and genetic discrimination.
Effective Approaches to Study the Genetic Variability of SARS-CoV-2

Significant efforts are being made in many countries around the world to respond to the COVID-19 pandemic by developing diagnostic reagent kits, identifying infected people, determining treatment methods, and finally producing effective vaccines. However, novel coronavirus variants may potentially reduce the effectiveness of all these efforts, demonstrating increased transmissibility and abated response to therapy or vaccines, as well as the possibility of false negative results in diagnostic procedures based on nucleic acid amplification methods. Since the end of 2020, several variants of concern have been discovered around the world. When information about a new, potentially more dangerous strain of pathogen appears, it is crucial to determine the moment of its emergence in a region. Eventually, that permits taking timely measures and minimizing new risks associated with the spreading of the virus. Therefore, numerous nations have made tremendous efforts to identify and trace these virus variants, which necessitates serious technological processes to sequence a large number of viral genomes. Here, we report on our experience as one of the primary laboratories involved in monitoring SARS-CoV-2 variants in Russia. We discuss the various approaches used, describe effective protocols, and outline a potential technique combining several methods to increase the ability to trace genetic variants while minimizing financial and labor costs.
PeGraph: A System for Privacy-Preserving and Efficient Search Over Encrypted Social Graphs

With the widespread adoption of cloud computing, it is increasingly popular for online social network (OSN) service providers to leverage the public cloud as a back-end to manage their services for the cloud’s well-understood benefits. However, the cloud is also notoriously subject to a wide attack surface, making it an imperative need to embed security in the cloud-backed OSN service from the very beginning. In light of this, in this paper, we design, implement, and evaluate PeGraph, the first system simultaneously allowing private, efficient, and rich queries over encrypted social graphs. PeGraph is aimed at safeguarding the confidentiality of the social graph at the cloud, while preserving the functionality of social search, a key enabler for quality OSN services like friend discovery and user targeting. PeGraph is built from a delicate synergy of insights from social graph modelling and lightweight cryptography such as searchable encryption and additive secret sharing, supporting rich social search queries like exact queries, fuzzy queries, and mixed queries. PeGraph also allows the cloud to obliviously render the encrypted social search results in a ranked order according to their importance, as per users’ preferences. Extensive experiments demonstrate that PeGraph can securely process a wide range of practical social search queries within 1 second, over a real-world social graph consisting of millions of entities.
Angle Attitude Control for a 2-DOF Parallel Mechanism of PMAs Using Tracking Differentiators

This paper presents a Tornambe controller (TC) for a two-degree-of-freedom (DOF) parallel mechanism of pneumatic muscle actuators (PMAs) based on tracking differentiators (TDs). A dynamic nonlinear system is established for the 2-DOF parallel mechanism of PMAs. TC is designed for improving control performance of the dynamic nonlinear system. The TDs are utilized to obtain high order derivatives of tracking errors, which are required by TC. Moreover, stability analysis of the dynamic nonlinear system is shown by a Lyapunov approach. Finally, experimental results are shown to verify the effectiveness of the proposed control method in this paper.
Real-Time Application of Robust Offset-Free MPC in Maglev Planar Machine

This article improves the transient response of a magnetically levitated (maglev) planar machine through the model predictive control (MPC) benefiting from explicitly incorporating the tightened constraints of the input vector. The maglev system is characterized as a second-order linear model via the inverse model method to facilitate the fast online receding horizon optimization. The estimated lumped disturbance compensates for the deviations of the prediction caused by the unmodeled errors, so the obtained control signals eventually eliminate the steady-state errors. The robust stability of the motion control system is guaranteed by a reasonable horizon length without requiring the state constraints, which reduces the computational burden for the real-time implementation. Experimental results demonstrate that the proposed controller outperforms the antiwindup PID controller, switching linear quadratic regulator, baseline MPC, and nonlinear MPC in terms of the trajectory tracking.
Rigor and reproducibility: status and challenges for single vesicle analysis

This report summarises the presentations and activities of the SELECTBIO Workshop on Rigor and Reproducibility in EV Research and Single EV Analysis held in San Diego, USA, in December 2021. The motivation for the session was the recognition that progress in the extracellular vesicle (EV) field is limited by the availability of rigorous and reproducible EV measurement tools. These tools are absolutely required for EVs to evolve from a research lab curiosity to something that will improve our ability to understand, diagnose, treat, and prevent disease. The program focused on guidelines for EV measurement and characterization as laid out in the recent MISEV2018 and MIFlowCyt-EV publications, their implementation in routine practice, and their continued evolution as new EV measurement technologies are introduced. The conclusion of the workshop was that more effort focused on pre-analytical issues and benchmarking of isolation methods is needed to strengthen collaborations and advance more effective biomarkers.
Partial Differential Equations with Complex Analysis

Part 1 Elliptic and related equations: class "P" operators, the minimal surface equation and the Weierstrass representation, E. Kreyszig Differentialtransformationen bei quasilinearen Gleichungen zweiter Ordnung, J. Pungel and H. Florian on associated operators in the theory of Cauchy-Kovalevskaya problems, R. Heersink on the representation of solutions to linear partial differential equations of mixed tupe, H-J. Fischer and E. Lanckau reproducing kernels and uniqueness classes for the Cauchy problem in classes of generalized analytic functions, E.I. Obolashvili and M. Reissig a simplified construction of generalized analytic functions in several complex variable, W. Tutschke application of quaternionic analysis on generalized non-linear Stokes eigenvalue problem, W. Sprossig and K. Gurlebeck residues in Clifford analysis, R. Delanghe, et al. Part 2 Complex analysis: parallel accessible domains and domains that are convex in some direction, W. Koepf semi-dual functions and nonvanishing entire functions, K-J. Wirths radial growth of subharmonic functions, D.J. Hallenbeck polynomial expansions of analytic functions by function theoretic methods, P.A. McCoy. Part 3 Riemann-Hilbert boundary value problems: on the theory of the nonlinear Hilbert problem for holomorphic functions, L. von Wolfersdorf on the Riemann-Hilbert boundary value problem for nonlinear elliptic equations in the plane, D-Q Dai numerical method for the Riemann-Hilbert problem of nonlinear elliptic complex equations of first order, G.C. Wen and P-Q Li the Riemann-Hilbert boundary value problems associated with linear and semilinear pseudoparabolic systems of two space variables, W. Lin and D-Q Dai on nonlinear boundary value problems for a class of first order overdetermined elliptic system in a bicylinder, M.Z. Li on the Moisil-Theodorescu system, A. Dzhuravev Helmholtz equations and boundary value problems, Z. Xu.
Sensor fault detection and isolation via networked estimation: rank-deficient dynamical systems

This paper considers model-based fault detection of large-scale (possibly rank-deficient) dynamic systems. Assuming only global (and not local) observability over a sensor network, we introduce a single time-scale networked estimator/observer. Sensors take local outputs/measurements of system states with partial observability and share their information (including estimation and/or output) over a communication network, and gain distributed observability. We define the conditions on the network structure ensuring distributed observability and stabilising the error dynamics. However, system outputs are prone to faults and uncertainties, which affect the state estimation of all sensors as a consequence of communicating (possibly) faulty data. From the cyber-physical-systems (CPS) perspective, such faults add bias to the data transferred from the physical layer (dynamic system) to the cyber layer (sensor network). In this work, we propose a localised fault detection and isolation (FDI) mechanism at sensors to secure distributed estimation. This protocol enables every sensor to locally identify the possible fault at the sensor measurement, and, via local detection and isolation, to prevent the spread of biased/faulty information over the network. This distributed isolation and localisation of fault follows from our partial observability assumption instead of full observability at every sensor. Then, other sensors can estimate/track the system by using observationally-equivalent output information to recover for possible loss of observability. In particular, we study rank-deficient systems as they are known to demand more information-sharing, and thus, are more vulnerable to the spread of possible faults over the network. One challenge is the detection of faults in the presence of system/output noise without making (simplifying and unrealistic) upper-bound assumptions on the noise support. We resolve this by adopting probabilistic threshold designs on the residuals. Further, we show that additive faults at rank-deficiency-related outputs affect the residuals at all sensors, a consequence that mandates more constraints on the (distributed) FDI strategy. We address this problem by constrained LMI design of the feedback gain matrix. Finally, we design q-redundant distributed estimators, resilient to isolation/removal of up to q number of faulty sensors, and further, we consider thresholding residual history over a sliding time-window, known as the stateful FDI.
Vitamin K1 and progression of cardiovascular calcifications in hemodialysis patients: the VitaVasK randomized controlled trial

Abstract Background Cardiovascular calcifications are prevented by matrix Gla protein (MGP), a vitamin K–dependent protein. Haemodialysis patients exhibit marked vitamin K deficiency. The randomized, prospective, open-label, multicentre VitaVasK trial analysed whether vitamin K1 supplementation reduces progression of coronary artery calcifications (CACs) and thoracic aortic calcifications (TACs). Methods Patients with pre-existing CACs were randomized to continue on standard care or to additionally receive 5 mg of vitamin K1 orally thrice weekly. Hierarchically ordered primary endpoints were progression of TAC and CAC in computed tomography scans at 18 months. Linear mixed effects models with repeated measures at baseline and 12 and 18 months assessed treatment effects after adjusting for study site. Results Of 60 randomized patients, 20 dropped out for reasons unrelated to vitamin K1, resulting in 23 control and 17 vitamin K1 patients. The trial was stopped early due to slow recruitment. At 18 months, the average TAC progression was 56% lower in the vitamin K1 compared with the control group (p = .039). CAC significantly progressed within the control group, but not within the vitamin K1 group. Average progression at 18 months was 68% lower in the vitamin K1 compared to the control group (P = .072). Vitamin K1 reduced plasma levels of pro-calcific uncarboxylated MGP by 69% at 18 months. No treatment-related adverse events were noted. Conclusion Vitamin K1 intervention is a potent, safe and cost-effective approach to correct vitamin K deficiency and to potentially reduce cardiovascular calcification in this high-risk population.
Adiabatic/MTJ-Based Physically Unclonable Function for Consumer Electronics Security

Consumer electronics require secure operation in the face of the many emerging threat vectors. One hardware security primitive is the Physically Unclonable Function (PUF). PUFs utilize process variations to give a device a digital fingerprint and are an important resource in secure hardware. One drawback of the addition of secure hardware is the increased energy consumption. In this paper, we look to design a secure, low-energy PUF using both adiabatic logic and Magnetic Tunnel Junctions (MTJ). Adiabatic logic reduces the dynamic energy consumption of the PUF while the MTJs offer a near zero-leakage power, non-volatile memory option. MTJs have two stable states depending on the magnetization direction of the free layer with respect to that of the fixed layer. Hence, the proposed adiabatic/MTJ PUF offers two modes of operation depending on the orientation of the MTJ. Our proposed adiabatic/MTJ PUF has average reliability of 97.07% and 96.97% between the two modes of operation while taking into account temperature, supply voltage, and TMR variations. The two modes of our proposed PUF consume 5.2 fJ and 5.1 fJ per bit.
Ergodic theory, symbolic dynamics, and hyperbolic spaces

Alan F. Beardon: An introduction to hyperbolic geometry Michael Keane: Ergodic theory and subshifts of finite type Anthony Manning: Dynamics of geodesic and horocycle flows on surfaces of constant negative curvature Roy L. Adler: Geodesic flows, interval maps, and symbolic dynamics Caroline Series: Geometrical methods of symbolic coding Mark Pollicott: Closed geodesics and zeta functions Dieter H. Mayer: Continued fractions and related transformations Steven P. Lalley: Probabilistic methods in certain counting problems of ergodic theory Peter J. Nicholls: A measure on the limit set of a discrete group Etienne Ghys & Pierre de la Harpe: Infinite groups as geometric objects (after Gromov) James W. Cannon: The theory of negatively curved spaces and groups
Autonomous MEMS Gyroscope and Accelerometer for North Finding System

The precision in detecting the north direction and estimate orientation is highly important. Excellent standard of gyroscopes, such as ring laser gyros, are capable of maintaining measurement at a high level. However, the device and technology required for it are bulky and high in cost. The accuracy of common instruments in detecting direction such as compass and electronics magnetometer can be easily reduced due to electromagnetic interference. Therefore, a continuous rotation method of the Micro-Electro-Mechanical System gyroscope and accelerometer is proposed, in order to seek true north angle. With this method, the issues regarding gyroscope will be solved. Moreover, the autonomous system consists of gyroscope and accelerometer which function in mounting the horizontal shape of the rotating laser controlled by the microcontroller. Moreover, it has been proven that the developed prototype provides an accuracy with complementary filter factor, a = 0.97. In addition, besides the fact that the rotator displays a successful rotation at ±0.02° for a rotation angle ranging from 0° to 360°, an autocollimator has also calibrated the rotator. Apart from that, it has been proven from the field test results that an accuracy of ±1°, is acquired by the developed system, regarding the true north angle that is verified by the Department of Survey and Mapping Malaysia.
Radiological versus laparoscopic insertion of peritoneal dialysis catheter: a study comparing outcomes at a single centre

Although peritoneal dialysis (PD) is a well‐established and effective form of renal replacement therapy in end‐stage renal failure (ESRF) patients, there is no consensus as to the optimal insertion technique. This study compares the outcomes of PD catheters inserted radiologically versus laparoscopically at a single centre.
High-Temperature-Sensing Smart Bolt Based on Indium Tin Oxide/In2O3 Thin-Film Thermocouples with Nickel-Based Single-Crystal Superalloy via Screen Printing

In this study, thin-film thermocouples (TFTCs) were combined with a smart bolt to design a smart bolt that can directly test high temperature in service monitoring and parameter calculation for gas turbine structure design. The first-principles calculation was used to analyze the design of the surface properties of nickel-based alloys and insulating layers, and finite element analysis was used to optimize dimension parameters by controlling the thermal stress matching of insulating layers and sensitive layers. The effect of the glass powder with different particle sizes on the microstructure of the ITO and In2O3 films was studied via SEM. The preferred particle size of the additive glass powder is 400 nm. The XRD pattern shows the (222) peak has the highest intensity. The intensities of the (222) and (622) peaks increase after the heat treatment. The calibration results show that the average Seebeck coefficient of the TFTCs can reach 64.9 μV/°C at 1100 °C with a maximum voltage of 71.4 mV. The repeatability error of the cycles of the sensor after heat treatment is ±1.05%. The repeatability of the sensor is up to 98.95%. The smart bolts were tested for application in small aero engines. It can be seen that under the impact of 1000 °C, the thermal response of the prepared smart bolt is better than that of the K-type armored thermocouple, and the thermal balance is achieved faster. The intelligent bolt sensor proposed in this work has better engineering application prospects owing to its convenience of installation in harsh environments.