Miracle-dz/UniFAR-FTUs huggingface dataset:
Water Treatment with Cation Selective Porous Graphene and Boron Nitride Membrane: A Molecular Dynamics Investigation

Almost any societies facing with achieving and developing the most efficient method of water treatment. The nanotechnology innovative achievement, provided a variety of nonporous membrane for water treatment application. High permeability of water and high rejection of salt are essential properties of these membranes and have been investigated as an efficient way for water desalination. All of these systems have been designed in a way that ions do not pass and water molecules permeate through the nanopores, so clean water is obtained through this process. But, in this research, we employed permeation of heavy metallic ions through the passivated nanopores under electric field to purify water from such contaminations. We employed molecular dynamics calculations to investigate the removal of heavy metallic ions from water using 2D boron nitride and graphene membrane. A nanopore of 6 Å diameter is located in the middle of graphene and 2D boron nitride membranes, the pores passivated by fluorine atoms which is shown to favor cations permeation. Potential mean force calculation, water density profile, number of ions permeation and required time for an ion to pass through nanopore both in graphene and 2D boron nitride membranes have been obtained and the results indicate, that 2D boron nitride has a better performance in cation permeability than graphene.
Beach Volume Measurement on Variation of UAV Altitude Mapping

Volume measurement is an important part of construction and mining work, including coastal volume to monitor changes occur along the beach. The volume measurement is usually done using conventional methods. The LiDAR method is the advanced mapping technology used for volume measurement purposes. However, it does involve high costs. Low-cost technology such as the UAV SfM-MVS (Unmanned Aerial Vehicle Structure from Motion Multi-View Stereo) found to be useful for the purpose of measuring the volume. The UAV photogrammetry technology make the mapping can be done all over area including the beach area. However, does the variation of UAV altitude beach mapping comes out with different volume measurement? This paper discovers the volume measurement for UAV photogrammetry mapping at 10m, 20m, 30m, 40m, and 50m altitudes along linear form of Desaru beach area in Johor, Malaysia. The research shows that, GSD of UAV mapping does not influence the UAV volume measurement, the uncertainty trend of UAV volume measurement happen when variation of UAV altitude mapping is done. Large error in UAV mapping effect the UAV volume measure. On the other hand, accurate mapping at certain UAV altitude is not a condition for quality UAV volume mapping as the UAV altitude mapping influence the result.
A Map Matching Algorithm for Noisy, Low Frequent Public Transportation GPS Data

Identifying the traveled road segments from raw GPS trajectories on a digital road network is known as the Map Matching. Map Matching becomes a challenging problem when the sparse geo-temporal data set is noisy (e.g., 10 meters away from the actual location) and has a low sampling rate (e.g., one data point per 3 minutes). The public transportation domain (e.g., buses) differs from the generic transportation (e.g., taxis) as it follows a predefined route, and that helps to build the ground truth trajectories. Ground truth trajectories are essential to validate the map-matching algorithms. There are many advanced map matching algorithms, but they are focused on the generic map matching problem. We propose an improvement to the existing Hidden Markov Model (HMM) map matching methodology to find the most likely road route considering the probability of the bus being on the predefined route. The proposed algorithm is validated using simulated GPS data in a dense road network with different noises and sample rates. Finally, the results are compared with the existing HMM solution using Route Mismatched Fraction (RMF).
Fusion of Amplitude and Complex Domains based on Deep Neural Networks for Speech Enhancement

Most of the recent works on speech enhancement has estimated the domain of clean spectrum and directly added noisy phase to the estimated domain without any processing. Nowadays, most of the phase-aware systems in speech processing are made up of using both real and imaginary parts of speech spectrum rather than the raw phase. In this paper, we propose a novel approach by the fusion of two deep methods for speech enhancement in the complex domain. This method combines the output of two deep neural networks (DNN) that estimate the complex ideal ratio mask (cIRM) and the amplitude of clean speech with a new logarithmic-based decision rule. This fusion rule which has been proposed according to psychoacoustics findings and spectrogram observations produces a complementary structure. Hence, it is capable of using the advantages of both amplitude and complex mask estimators in each time-frequency region. The above method, when evaluated on TIMIT corpus, outperforms the perceptual evaluation of speech quality (PESQ) compared to other approaches especially in unseen noise conditions showing the better generalization of the proposed architecture.
Condition Monitoring of Wound Rotor Resolvers

Resolver is an electromagnetic sensor for calculating position and speed in motion control drive of electrical machines. Due to electromechanical structure of the machine, occurrence of the mechanical faults includes static and dynamic eccentricities (SE, DE) is inevitable. Even an inherent level of SE exists in newly manufactured machines. Furthermore, due to thin wires of the stator and rotor windings short circuit fault has also high probability. Since the accuracy of the resolver is significantly affected by electrical and mechanical faults, it is required to diagnose them at the very beginning of their development. In this paper, some indices are proposed for condition monitoring of wound rotor resolvers under mechanical and electrical fault. It is shown that the proposed index of each fault is unique and is not excited by other fault. The discussions are done using time stepping finite element method and the results are verified by experimental tests on prototype resolver.
A Two Stage Approach for AMR Parsing Using the Concept Inference Order

In this paper we introduce a simple, pipeline graph-based approach for AMR parsing. Transition-based parsers have been researched intensively for the task of AMR parsing since the introduction of AMR and its associated sembank in 2013, but more recently there’s been a shift towards graph based approaches, which seem to do better on the task. However, these graph-based approaches often employ large models, trained end-to-end. We intend to see the limitations of a small, pipeline architecture. We use an attention-based sequence-to-sequence model for predicting an ordered list of nodes, then predict the heads for each node in a subsequent step.
Mitigation of Voltage Fluctuations in Grid-Connected Microgrids

Distributed renewable energy resources have variable active power output caused by changes in the environmental conditions, such as wind speed or solar irradiance, which affect the voltage magnitude in microgrids. Moreover, the load variations have an impact on the voltage magnitude. Such fluctuations have devastating effects, particularly on sensitive loads. Also, these fluctuations can cause flickering. In this paper, by using sensitivity analysis, the optimal reactive power of solar inverters is calculated and used to reduce the voltage fluctuations in solar photovoltaic-based microgrids. The proposed method leads to injecting or absorbing the reactive power to prevent the voltage fluctuations by solar inverters. This is done by sending data of changes of active and reactive power via a communication link. Therefore, the voltage magnitude of all buses is controlled without using any additional compensator. The proposed method is tested on the IEEE 33-bus distribution network. The results validate the efficiency of the proposed method.
AIS Link Budget Design and Probability of Detection Analysis in Multi User System

The Automatic Identification System (AIS) was introduced By International Maritime Organization (IMO) in 2000 for the first time to increase the maritime safety. In the past several decades, Satellite Automatic Identification System (S-AIS) has played an important role in maritime communications. Due to this subject, this paper mainly focused on AIS link budget calculation, channel load and throughput system for the vessels near IRAN maritime boundaries. The aim of our work is to examine the effects of distance and angle between satellites to ship for computing the probability of detection. An experimental model for the S-AIS system has been evaluated based on Systems (Satellite) Tool Kit (STK) software. Also, the probability of detection versus number of interference with different signal to interference power ratio in satellite has been extracted, numerically.
A novel Off-Board Interleaved Charger for EVs with G2H/G2VH/V2H Functions and Capable of Controlling Reactive Power

This paper proposes a novel off-board interleaved charger for electric vehicles (EVs) that can be used in smart homes and buildings as a rectifier converter. Working as rectifier to provide appropriate DC voltage for DC residential loads (G2H), providing DC output voltage and charging EV battery, simultaneously (G2VH), and returning stored energy in EV battery to DC load (V2H) are the operation modes of proposed charger. It has the ability to provide wide range of output voltage because of its exclusive DC-DC stage structure. It has sinusoidal AC input current with low total harmonic distortion (THD). A suitable control method is introduced, which can control the reactive power depending on smart grid commands or consumer requirements. One notable feature of proposed topology is the battery bases grounded which causes noise conduction and protect the circuit. In order to validate the converter's features, it is simulated in MATLAB/SIMULINK software and results confirm charger capabilities.
Logic Encryption to Prevent Trojan Insertion with Dual-Function Gates

The outsourcing of integrated circuits (IC) makes some of the vulnerabilities and enable the adversary to reverse engineering attack, IP piracy, overproduction, counterfeiting or hardware Trojan (HT) insertion throughout the supply chain of the IC. The attacker by inserting the hardware Trojan can destroy normal operation in IC, or steal sensitive information from the design. Nowadays the prevention of IP piracy and HT insertion is an important issue in hardware security. Logic encryption as part of Design for Hardware Trust (DFHT) techniques, applies key-gates in order to encrypt the logic of the chip. Therefore if the key inputs are correct the chip has normal function otherwise function is wrong, this work prevention of IP piracy. Furthermore, in some cases of logic encryption techniques, the rare signals that are a good place for insert an HT can be reduced. Therefore, if the HT is inserted in the chip by functional tests can be detected. In this article, a new key-gate that has a double-function is designed to prevent HT insertion as well as preventing from IP piracy. In this paper, by reducing the rare signals and reducing the signals with low observability, prevent HT insertion also, this type of key-gates is resistant to reverse engineering more than the previously designed key-gates. This key-gates has overhead less than insertion based method with XOR and XNOR key-gates.
Direct Power Control of PWM Three-Phase Rectifier Using the Predictive Method: Aims to Reduce THD

In this paper, direct control of predictive power for three-phase rectifier using pulse width modulation is presented. For this purpose, direct power control is based on strategy of predictive control to achieve simultaneous control of active & reactive power of converter. To achieve this goal at the beginning of each period the switching average voltage vector of the rectifier which makes possible to zero the error of active& reactive power tracking. Also, at the end of the switching period voltage vectors are calculated by the predictive control algorithm based on the deadbeat control method. As a result, with usage of PWM, the pulses which are required for the rectifier switches are produced.
A 0.6-V High-Speed Digitally Controlled Low-Dropout Regulator with 99.8% Current Efficiency at 50-mA Load

A digital fast transient response low-dropout regulator which can work in both coarse and fine modes is presented. If the difference between reference voltage and output voltage is high, both coarse and fine circuits work simultaneously to provide higher speed for following the reference voltage, and when the difference between reference voltage and output is in the defined range, only the fine part of the proposed circuit is activated with lower operating frequency to both increase the output voltage accuracy and reduce the circuit power consumption. Designed in a standard 0.18-μm CMOS technology, the circuit occupies 195×255μm2 of silicon area. Post-layout simulation results show that operating with 500MHz input clock signal, the maximum regulator delay is 250ns and the voltage ripple is less than 20mV in steady state condition with load and line regulation of 0.13mV/mA and 8.1mV/V, respectively. Furthermore, it reaches the current efficiency of 99.8% at a load current of 50mA. Operated with 0.78V supply voltage, the quiescent current is 90μA, with achieving of 0.072ps figure of merit.
System Identification and Damping Controller Design Based on Wide-Area Phasor Measurements

Ever growing changes in power systems have made modeling and control problems challenging and more complex. On the other hand, significant improvements have been done in wide-area monitoring and control systems. In the present paper a low-order model identification method based on phasor measurement unit data is used. This model properly represents dominant inter-area modes which are concerned in interconnected power systems. Then, a damping controller is designed using robust and adaptive approaches. The controller is selected as power system stabilizer. The proposed method is tested on four-machine two-area system by using phasor dynamic data obtained from simulation environment using MATLAB software, and the results demonstrate its effectiveness.
Characteristics and Outcomes Based on Perceived Illness Severity in SARS-CoV-2

Uncertainty surrounding the COVID-19 epidemic exists, partly driven by the difficulty in prognostication and understanding risk factors that portend worse outcomes. This study examines whether differences in clinical characteristics on admission result in the need for intensive care unit (ICU)–level care and demonstrates few differences among patients needing ICU care and those that did not. Furthermore, patients admitted to the ICU generally have poor outcomes. Abstract Objectives The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) epidemic is characterized by a global sense of uncertainty, partly driven by the paucity of real-life clinical data. This study assessed whether admission patient characteristics were associated with need for intensive care unit (ICU) care. Methods The observational study included consecutive patients admitted to a large community teaching hospital with a diagnosis of SARS-CoV-2 between March 6, 2020 and March 31, 2020. Comparisons were made based on the need for ICU admission. Results A total of 156 patients were admitted, 42 of whom (26.9%) required ICU admission and 114 (73.1%) did not. No difference in age (61.9 years vs 60.5 years, P = 0.67), race/ethnicity, or comorbidities were noted, except that patients requiring ICU care had lower serum albumin levels and lymphocyte counts and higher liver function tests, white blood cell count, and absolute neutrophil count on admission. The average time from admission to death was similar (10 days in an ICU subset vs 9.2 days in a non-ICU subset, P = 0.78), yet patients necessitating ICU care had longer hospital lengths of stay (10.2 vs 5.1 days, P = 0.0002). At the time of data extraction, 15 patients in the ICU had died, 7 were discharged from the hospital, and 20 were still admitted while 5 patients died in the non-ICU cohort with 97 discharged and 12 patients admitted. Conclusions This is the largest study assessing clinical differences based on the need for ICU admission in inpatients with SARS-CoV-2. It found few major differences in clinical variables between subsets. Among patients admitted to the ICU, outcomes were generally poor.
Specialized proresolving mediators in infection and lung injury

Specialized proresolving mediators (SPMs) are endogenous lipid metabolites of long‐chain polyunsaturated fatty acids that are involved in promoting the resolution of inflammation. Many disease conditions characterized by excessive inflammation have impaired or altered SPM biosynthesis, which may lead to chronic, unresolved inflammation. Exogenous administration of SPMs in infectious conditions has been shown to be effective at improving infection clearance and survival in preclinical models. SPMs have also shown tremendous promise in the context of inflammatory lung conditions, such as acute respiratory distress syndrome and chronic obstructive pulmonary disease, mostly in preclinical settings. To date, SPMs have not been studied in the context of the novel Coronavirus, severe acute respiratory syndrome Coronavirus‐2 (SARS‐CoV‐2), however their preclinical efficacy in combatting infections and improving acute respiratory distress suggest they may be a valuable resource in the fight against Coronavirus disease‐19 (COVID‐19). Overall, while the research on SPMs is still evolving, they may offer a novel therapeutic option for inflammatory conditions.
Recirculating Aquaculture Is Possible without Major Energy Tradeoff: Life Cycle Assessment of Warmwater Fish Farming in Sweden

Seafood is seen as promising for more sustainable diets. The increasing production in land-based closed Recirculating Aquaculture Systems (RASs) has overcome many local environmental challenges with traditional open net-pen systems such as eutrophication. The energy needed to maintain suitable water quality, with associated emissions, has however been seen as challenging from a global perspective. This study uses Life Cycle Assessment (LCA) to investigate the environmental performance and improvement potentials of a commercial RAS farm of tilapia and Clarias in Sweden. The environmental impact categories and indicators considered were freshwater eutrophication, climate change, energy demand, land use, and dependency on animal-source feed inputs per kg of fillet. We found that feed production contributed most to all environmental impacts (between 67 and 98%) except for energy demand for tilapia, contradicting previous findings that farm-level energy use is a driver of environmental pressures. The main improvement potentials include improved by-product utilization and use of a larger proportion of plant-based feed ingredients. Together with further smaller improvement potential identified, this suggests that RASs may play a more important role in a future, environmentally sustainable food system.
Closure Strategies for Turbulent and Transitional Flows: Reacting Flows and Probability Density Function Methods

In this chapter the statistical description of turbulent reacting flow is considered. In particular second moment closure for variable density flows and the one-point probability density function (PDF) approach are introduced. In turbulence modelling a subset of statistical properties is obtained by calculating a selected set of moments (e.g. mean and variances of quantities at one point in space) from modelled transport equations. For reacting flow it is advantageous to enlarge the subset to involve the complete probability density function of variables defined at one point in space and time. This approach leads to an incomplete description of turbulence properties and closure assumptions have to be made. The structure of the presentation in this chapter is as follows: instantaneous conservation equations are considered first because they provide the basis for the averaged equations and also for the transport equation satisfied by the probability density function. Next some basic concepts from statistics are considered. Finally the mean conservation equations are introduced and a discussion of the main closure problems and their possible solution in terms of second moment equations and/or PDFs are given. A more detailed description of models and results is given in [20] and [21]. Further information on the PDF approach can be found in Pope (1985), Dopazo (1994), Fox (1996), Pope (2000).
Sex steroid hormone receptors of telocytes - potential key role in leiomyoma development.

BACKGROUND Uterine leiomyoma is the most widespread benign tumor affecting women of childbearing age. There are still gaps in the understanding of its pathogenesis. Telocytes are unique cells found in more than 50 different locations inside the human body. The functional relationship between cells could clarify the pathogenesis of leiomyomata. Examination of membrane receptors on telocytes could explain their role in fibrosis, oxidative stress, and myometrial contractility. AIM This research was conducted to assess the density of telocytes in terms of their putative role in leiomyoma formation by focusing on their correlation with the expression of estrogen and progesterone receptors. METHODS For gross evaluation of uterine tissue samples from leiomyoma, routine histology of adjacent and unaffected myometrium was performed. Immunohistochemical analysis of c-kit, tryptase, CD34, PDGFRα (telocyte-specific), and ER and PRs (estrogen and progesterone receptors) was performed to examine uterine telocytes and the expression of sex steroid receptors. RESULTS The decline in telocyte density in leiomyoma foci was correlated with high progesterone expression and low estrogen receptor expression. The unchanged myometrium showed the opposite correlation and balance between both steroid hormone receptors. The difference in sex steroid receptor expression is correlated with the density of uterine telocytes, which emphasizes their conductor function. CONCLUSIONS A reduction in telocyte density and the changes in examined marker expression demonstrate the involvement of telocytes in local homeostasis. The expression of membrane receptors explicitly indicates their functional potential in the human myometrium, focusing attention on contractility and local homeostasis.