Miracle-dz/UniFAR-FTUs huggingface dataset:
A High-Performance Multimem SHA-256 Accelerator for Society 5.0

The development of a low-cost high-performance secure hash algorithm (SHA)-256 accelerator has recently received extensive interest because SHA-256 is important in widespread applications, such as cryptocurrencies, data security, data integrity, and digital signatures. Unfortunately, most current researches have focused on the performance of the SHA-256 accelerator but not on a system level, in which the data transfer between the external memory and accelerator occupies a large time fraction. In this paper, we solve the state-of-art problem with a novel SHA-256 architecture named the multimem SHA-256 accelerator that achieves high performance at the system on chip (SoC) level. Notably, our accelerator employs three novel techniques, the pipelined arithmetic logic unit (ALU), multimem processing element (PE), and shift buffer in shift buffer out (SBi-SBo), to reduce the critical path delay and significantly increase the processing rate. Experiments on a field-programmable gate array (FPGA) and an application-specific integrated circuit (ASIC) show that the proposed accelerator achieves significantly better processing rate and hardware efficiency than previous works. The accelerator accuracy is verified on a real hardware platform (FPGA ZCU102). The accelerator is synthesized and laid out with 180 nm complementary metal oxide semiconductor (CMOS) technology with a chip sized $8.5\,mm \times 8.5\,mm$ , consumes 1.86 W, and provides a maximum processing rate of 40.96 Gbps at 80 MHz and 1.8 V. With FPGA Xilinx 16 nm FinFET technology, the accelerator processing rate is as high as 284 Gbps.
Characterization of Dielectric and Piezoelectric Properties of Ferroelectric AlScN Thin Films

The present work explores the dielectric and piezoelectric properties of ferroelectric scandium-doped aluminum nitride (AlScN) thin films. Films in a range from 20 to 500 nm are fabricated with scandium (Sc) percentages of 28%, 31%, and 36%. The rocking curves, piezoelectric coefficient d33, butterfly curves, capacitance and loss tangent versus voltage are characterized for different thicknesses and Sc percentage combinations. Additionally, the capacitance variation for different scandium concentrations is modeled to showcase the possibility of using AlScN thin films as varactors in a impedance matching network capable of canceling out inductance variations of up to 10%. Thus, the present work furthers the characterization efforts for AlScN ferroelectric films and steps towards transitioning them towards multi-functional platforms in for RF networks.
Track Prediction of Tropical Cyclones Using Long Short-Term Memory Network

Accurate track prediction of tropical cyclones is of utmost importance to minimize loss of lives and property. We propose a Long Short-Term Memory network based Recurrent Neural network that uses data of the first few hours of cyclones and predicts their track for the next several hours with high accuracy. The model uses variables like estimated central pressure, maximum sustained surface wind speed, latitude, and longitude, which are available at a regular time interval. The output of the model is a GridID, which has been obtained by a grid function applied on latitude and longitude ranges. The model has been applied to hurricanes in the Atlantic ocean, and tropical cyclones in the north Indian ocean. The model performance has been compared with existing state-of-the-art results. The proposed model outperforms the existing models in terms of mean absolute error, time-span of prediction, and training time.
Multiple Correlated Attributes Based Physical Layer Authentication in Wireless Networks

Physical (PHY) layer authentication has been a significant trend towards ensuring the identity security of terminals in wireless networks due to the high security and low complexity. However, the independence assumption of existing literature ignores the inherent correlation of the PHY-layer attributes, which limits its generality. In this paper, we propose a multi-attribute-based PHY-layer authentication scheme by taking the correlation into account. To cope with the exponential growth of computational complexity in correlated analysis, this paper studies the reconstruction and heuristic algorithm to find a suboptimal authentication solution with low complexity. Specific to the inherent volatility nature of the PHY-layer attributes, we propose an unsupervised machine learning (ML) based non-parametric clustering algorithm to enhance the reliability of PHY-layer authentication. Unlike existing PHY-layer authentication schemes based on ML, the proposed PHY-layer authentication scheme does not require any prior information or the training set, which has a more potent universality. Extensive simulations are performed under both synthetic and real data sets, and the figures verify that the proposed authentication scheme can achieve a reliable and robust performance with low complexity.
De-Biased Sparse PCA: Inference for Eigenstructure of Large Covariance Matrices

Sparse principal component analysis has become one of the most widely used techniques for dimensionality reduction in high-dimensional datasets. While many methods are available for point estimation of eigenstructure in high-dimensional settings, in this paper we propose methodology for uncertainty quantification, such as construction of confidence intervals and tests for the principal eigenvector and the corresponding largest eigenvalue. We base our methodology on an M-estimator with Lasso penalty which achieves minimax optimal rates and is used to construct a de-biased sparse PCA estimator. The novel estimator has a Gaussian limiting distribution and can be used for hypothesis testing or support recovery of the first eigenvector. The empirical performance of the new estimator is demonstrated on synthetic data and we also show that the estimator compares favourably with the classical PCA in moderately high-dimensional regimes.
Enhancement of Frequency Stability in Injection Locked Bulk Mode MEMS Oscillators

This paper reports experimental results demonstrating significant gains in frequency stability for bulk acoustic wave (BAW) silicon disk resonator oscillators due to the locking of degenerate modes. The results show that when two degenerate modes are locked, the minimum Allan deviation is improved by a factor of more than two times in comparison with the minimum Allan deviation for oscillators locked to the individual degenerate modes. A shortterm stability of 48.3 μHz (51 ppt @ 0.27 s integration time) is recorded for a MEMS oscillator with an output of ~1 MHz which benchmarks favourably relative to the MEMS oscillator state-of-the-art and commercial crystal oscillators. The approach is applicable to the locking of oscillators based on degenerate modes generally and can be scaled to higher frequency axisymmetric resonators with the higher-order bulk modes also providing inherent immunity to shock and vibration.
Alveolar Tissue Fiber and Surfactant Effects on Lung Mechanics—Model Development and Validation on ARDS and IPF Patients

Goal: Alveolar compliance is a main determinant of lung airflow. The compliance of the alveoli is a function of their tissue fiber elasticity, fiber volume, and surface tension. The compliance varies during respiration because of the nonlinear nature of fiber elasticity and the time-varying surface tension coating the alveoli. Respiratory conditions, like acute respiratory distress syndrome (ARDS) and idiopathic pulmonary fibrosis (IPF) affect fiber elasticity, fiber volume and surface tension. In this paper, we study the alveolar tissue fibers and surface tension effects on lung mechanics. Methods: To better understand the lungs, we developed a physiology-based mathematical model to 1) describe the effect of tissue fiber elasticity, fiber volume and surface tension on alveolar compliance, and 2) the effect of time-varying alveolar compliance on lung mechanics for healthy, ARDS and IPF conditions. Results: We first present the model sensitivity analysis to show the effects of model parameters on the lung mechanics variables. Then, we perform model simulation and validate on healthy non-ventilated subjects and ventilated ARDS or IPF patients. Finally, we assess the robustness and stability of this dynamic system. Conclusions: We developed a mathematical model of the lung mechanics comprising alveolar tissue and surfactant properties that generates reasonable lung pressures and volumes compared to healthy, ARDS, and IPF patient data.
Design and Analysis of Solar PV Fed IMD Water - Pumping System

This paper presents a water-pumping system using solar photovoltaic Arrays. The system consists of PV array, DC-DC boost converter, voltage source inverter, 3$-\Phi$ induction motor drive (IMD) and centrifugal pump. The modified space vector pulse width modulation (MSVPWM) method for control of inrush current and drive’s commutation uses lower number of sensors. The main advantages of MSVPWM are its high efficiency, low cost due to reduced number of sensors and low harmonic current. The developed system model is simulated in the MATLAB/ Simulink software and its results are discussed in this paper. The system provides satisfactory performance in the dynamic, steady state conditions.
Piezoelectric Tantalum Aluminum Nitride Films for Vibrational Micro Energy Harvesters

This paper reports the first attempt to apply highly piezoelectric Ta-doped AlN thin films for vibration-driven micro energy harvesters. Ta<inf>x</inf>Al<inf>1-x</inf>N (x = 0.068) films were grown on Pt/Ti/Si substrates and applied to microfabricate energy harvesters. The Ta-AlN films exhibit a highly c-axis crystal orientation and good electrical properties with low leakage current density of 0.2×10<sup>-6</sup> A/cm<sup>2</sup> and low loss tangent of 0.02. Our prototype of the Ta-AlN based micro energy harvesters shows the normalized power density (NPD) of 13.7 mW.g<sup>-2</sup>. cm<sup>-3</sup>. This result was an approximately 6-fold increase compared to the best of the published pure AlN harvesters and outperformed the PZT-based ones. Also, our first attempt is approaching to the best-published performance of the higher co-dopant concentration (MgHf)<inf>0.11</inf>Al<inf>0.89</inf>N and Sc<inf>0.43</inf>Al<inf>0.57</inf>N.
Factors affecting arsenic and uranium removal with zero-valent iron: laboratory tests with Kanchan-type iron nail filter columns with different groundwaters

Environmental context Tens of millions of people worldwide depend on groundwater with naturally high arsenic concentrations for drinking and cooking. We studied simple filters built with locally available and inexpensive iron nails, which can oxidise and bind arsenic in forming iron oxides and rust layers. Filters containing iron are being successfully applied in several regions, but efficiencies depend on the type of groundwater, and sufficiently large iron surfaces and contact times with water are needed for good arsenic removal. Abstract Zero-valent iron (ZVI)-based filters are able to remove arsenic and other pollutants from drinking water, but their performance depends on the form of ZVI, filter design, water composition and operating conditions. Kanchan filters use an upper bucket with ZVI in the form of commercial iron nails, followed by a sand filter, to remove arsenic and pathogens. We evaluated factors that influence the removal of arsenic and uranium with laboratory columns containing iron nails with six different synthetic groundwaters with 500μgL–1AsIII, 50μgL–1 U, 2mgL–1 B, and with 0 and 2mgL–1 P (added as o-phosphate), 0.25 and 2.5mM Ca, 3.2 and 8.3mM HCO3–, at pH 7.0 and 8.4 over 30 days. During the first 10 days, As removal was 65–95% and strongly depended on the water composition. As removal at pH 7.0 was better than at pH 8.4 and high P combined with low Ca decreased As removal. From 10–30 days, As removal decreased to 45–60% with all columns. Phosphate, in combination with low Ca concentrations lowered As removal, but had a slightly positive effect in combination with high Ca concentrations. U removal was only 10–70%, but showed similar trends. The drop in performance over time can be explained by decreasing release of iron to solution due to formation of layers of FeIII phases and calcite covering the iron surface. Mobile corrosion products contained ferrihydrite, Si-containing hydrous ferric oxides, and amorphous Fe–Si–P phases. Comparisons with another type of ZVI filter (SONO-filter) were used to evaluate filter design parameters. Higher ZVI surface areas and longer contact times should lead to satisfactory As removal with Kanchan-type filters.
Petri Nets Modelling of Assembly Robots Coordination

This paper is focusing on the Petri net as a modelling tool to deal with the assembly robot's coordination. The deadlock controls in flexible assembly systems (FAS), where deadlocks are caused by unmarked siphons in their Petri nets (PNs) model. An efficient siphons PN plays an important role in preventing the deadlock of robots trajectory specifications. The model is considered to encompass all possible realizations of the assembly process execution. Efficient siphon-based methods obtained procedure is highly permissive solutions using as few control places as possible. This work utilizes in particular, systems designed for assembly robot coordination that is modelled of the PN for the control flow of in assembly robots on S3PR-net. The analyses of S3PR lead us to characterize the deadlock situation in terms of insufficiently marked siphons. Moreover, the simulation PNs are helping us to allow the high-level description of complex interactions for the automatic control modelling of assembly robots tasks based on siphon control. Siphons based the controller exhibits to be the optimal performance of the sequence assembly robots without blocking. Finally, an example is given to illustrate the effectiveness of the siphon.
An Applayed Survey with ESP8266 Lolin + Shield Base with Nextion Touchscreen Display

This manuscript presents the results of an applied survey on the Internet of Things (IoT), considering the use of the Lolin ES P8266 devices with Shield base and Nextion touchscreen display. Considering the scarcity of scientific research materials that involve the subject of Internet of Things, considering as main objective: to demonstrate the results of technical applications, in which it is necessary to create solutions for automation, contributing to the development of solutions that can as a basis for future studies, with content that can support more sophisticated scientific research projects. The results of this study made possible the technical understanding for the creation of projects that can serve different areas, such as automation, monitoring, security, remote operations, facilitating the remote control of devices or Internet, equipment with portability in different environments, such as smart phones, computers and tablets.
Extraction of D31 Piezoelectric Coefficient of AlN Thin Film

Piezoelectric materials have the property of electromechanical coupling, which is very useful in Micro Electro Mechanical Systems (MEMS). Aluminium Nitride (AlN) thin film is an ideal candidate for resonators in on-chip front end circuit. The piezoelectric coupling coefficient d31 is responsible for the excitation in longitudinal mode resonators. Direct measurement of the value of d31 is still an area of research. We propose a method to extract the piezoelectric coefficient d31 from the transmission characteristics of a resonator. The average extracted value of d31 is -0.943 pC/N with standard deviation 0.21 pC/N, which is comparable with reported values.
Ordered Transmissions Schemes for Detection in Spatially Correlated Wireless Sensor Networks

The ordered transmissions scheme requires fewer sensor nodes to transmit their measurements than the conventional unordered transmissions scheme (UTS) in which all nodes transmit. Yet, it achieves the same error probability as UTS. For the practically relevant scenario in which the measurements of the sensor nodes are spatially correlated, we present a novel correlation-aware ordered transmissions scheme (CA-OTS) for the binary hypothesis testing problem with Gaussian statistics. It uses the timer scheme to make the nodes transmit their measurements in the decreasing order of the absolute values of the measurements without any node knowing the measurements of other nodes. CA-OTS applies to the general case where the hypotheses differ in the mean vector and covariance matrix, and markedly reduces the number of transmissions. It differs from the literature that assumes that the measurements of the nodes, when conditioned on the hypotheses, are statistically independent or the covariance matrix has a special structure. When the mean vector or covariance matrix is the same for the two hypotheses, we propose novel refinements that require even fewer transmissions. We also derive insightful upper bounds for them that apply to a general product-correlation model.
Integrating Edge Computing into Low Earth Orbit Satellite Networks: Architecture and Prototype

Low Earth Orbit (LEO) satellite network is a cost-efficient way to achieve global covering for wide-area Internet of Things (IoT). As more and more IoT applications require large amounts of computing resources, cloud computing paradigm becomes one of the IoT’s main enablers. Abundant resources can be used to execute computation-intensive IoT applications in the cloud. Moreover, edge computing has emerged to alleviate the high latency and low bandwidth problem of cloud computing. The integration of edge computing into LEO networks (which is called LEC in this paper) can improve satellite IoT network’s performance. In addition, it is an effective way to support delay-sensitive and resource-hungry wide-area IoT applications. However, there are many technical challenges for LEC, which is different from edge computing in terrestrial networks. Therefore, we study LEC in depth and a novel system architecture is proposed. A LEC prototype system is implemented which verifies our design. The simulation result demonstrates that LEC can improve system performance compared with cloud computing in LEO networks.
Microbial Degradation of Phenol- A Review

Aromatic compounds are widely distributed in nature and free phenols are frequently liberated as metabolic intermediates during the degradation of plant materials. In recent years the natural supply of phenolic substances has been greatly increased due to the release of industrial byproducts into the environment. Effluents from petrochemical, textile and coal industries contain phenolic compounds in very high concentration; therefore there is a necessity to remove phenolic compounds from the environment. Among various techniques available for removal of phenols, biodegradation is an environment friendly and cost effective method. The efficiency of biodegradation of organic compounds is influenced by the type of the organic pollutant, the nature of the organism, the enzyme involved, the mechanism of degradation and the nature of the influencing factors. This also depends on aerobic and anaerobic conditions. Under aerobic conditions, degradation of phenol was shown to be initiated by oxygenation into catechols as intermediates followed by a ring cleavage at either the ortho or meta position, depending on the type of strain. Aerobically, phenol is first converted to catechol, and subsequently, the catechol is degraded via ortho or meta fission to intermediates of central metabolism. This paper describes about the various sources of phenol, various microorganisms involved in the biodegradation including aerobe and anaerobe, effect of environmental parameters on phenol degradation and kinetic analysis of biodegradation.
Rebel Regimes and Military Powersharing: Consequences of Conflict for Authoritarian Durability

Dictators face a powersharing tradeoff: sharing power more credibly delivers spoils to elites, but also lowers organizational hurdles to staging a coup against the ruler. We argue that origins in violent rebellion create favorable conditions for achieving peaceful powersharing with military elites. Fighting enables rulers of rebel regimes to transform the military and to place members of their rebel group into top positions. Although these military elites possess the means to overthrow the ruler, sharing power with allies will alleviate coup risk. Using data on African regimes from 1960–2017, we establish that rebel regimes are significantly less likely to fall than others. We then show evidence for powersharing using originally collected data. Rulers in rebel regimes frequently transform the state military upon taking power. Compared to other regimes, they are more likely to appoint a Minister of Defense (who were usually guerrilla leaders) and less likely to face coups. *Assistant Professor of Political Science, University of Virginia, Email: ameng@virginia.edu Assistant Professor of Political Science, University of Rochester, Email: jackpaine@rochester.edu
Numerical Simulations of Capillary Aerosol Generation: CFD Model Development and Comparisons with Experimental Data

For a capillary aerosol generation system, the mechanisms governing droplet transport from the capillary tip through deposition in an enclosed geometry have not been previously explored. The objective of this study was to develop and validate a CFD model of transport and deposition for capillary-generated albuterol in water aerosols in a standard USP induction port used for pharmaceutical aerosol testing. Within this system, comparisons have been made between experimental measurements and numerical predictions of the jet angle, aerosol deposition in a sectioned induction port model, and size distributions of exiting particles. The CFD model employed accounts for multiscale and multicomponent flow initialized at the 57 μ m capillary tip and extending through the USP induction port with 30 L/min of co-flow air. A discrete Lagrangian particle tracking algorithm with corrections for near-wall anisotropic turbulence has been implemented to model the polydisperse particle phase including the effects of turbulent dispersion and evaporation. Results indicated good agreement between predictions of the numerical model and experimental in vitro measurements. The experimental mean (SD) total mass fraction of drug deposited in the sectioned induction port was 14.6 (1.1)%. Numerical predictions of deposited mass fraction for non-evaporating particles and evaporating droplets were 13.1% and 13.3%, respectively, resulting in relative differences of 10.3% and 8.9%. Comparisons between in vitro measurements and predictions within individual sections of the induction port resulted in relative differences as low at 0.75%. The predicted mass median diameters exiting the induction port for the particle and evaporating droplet models were 3.07 and 3.45 μ m, respectively, in comparison to an experimental value of 3.06 μ m. The numerical model developed in this study can be applied to optimize the capillary aerosol generation process and improve its delivery of aerosols to the lung.