Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Miniaturized Frequency Selective Surfaces Using Minkowski Island Fractal

Abstract — This paper presents a simulation and experimental investigation of a frequency selective surface (FSS). The design is achieved by using the Minkowski island fractal. Two structures were designed with Minkowski island fractal level 1 and 2, which act as stop-band filters with resonant frequencies of 9 GHz and 10 GHz, respectively. Both simulation and experimental investigations were conducted. Simulation investigation was carried out using Ansoft Designer TM software, while experimental investigation used an Agilent Technologies vector network analyzer – model N5230A. Index Terms — Frequency Selective Surfaces, Stop-band filter, Minkowski fractal. I. INTRODUCTION Frequency Selective Surfaces are two-dimensional arrays of periodic metallic elements on a dielectric layer or two-dimensional arrays of apertures within a metallic screen. They are used for a variety of applications , such as bandpass radomes for missiles, sub-reflectors for dual frequency reflector systems, microwave, optical, and infrared filters etc. [1] – [3]. FSS with fractal elements has attracted the attention of microwave engineering researchers because of its attractive features. Several fractal iterations can be used to design an FSS with multiband frequency response associated to the geometry scales contained in the structure. The Sierpinski fractal was previously used to design a multiband FSS [4] – [5]. An experimental investigation was performed by Sarkar
Neural tracking to go: auditory attention decoding and saliency detection with mobile EEG

Objective. Neuro-steered assistive technologies have been suggested to offer a major advancement in future devices like neuro-steered hearing aids. Auditory attention decoding (AAD) methods would in that case allow for identification of an attended speaker within complex auditory environments, exclusively from neural data. Decoding the attended speaker using neural information has so far only been done in controlled laboratory settings. Yet, it is known that ever-present factors like distraction and movement are reflected in the neural signal parameters related to attention. Approach. Thus, in the current study we applied a two-competing speaker paradigm to investigate performance of a commonly applied electroencephalography-based AAD model outside of the laboratory during leisure walking and distraction. Unique environmental sounds were added to the auditory scene and served as distractor events. Main results. The current study shows, for the first time, that the attended speaker can be accurately decoded during natural movement. At a temporal resolution of as short as 5 s and without artifact attenuation, decoding was found to be significantly above chance level. Further, as hypothesized, we found a decrease in attention to the to-be-attended and the to-be-ignored speech stream after the occurrence of a salient event. Additionally, we demonstrate that it is possible to predict neural correlates of distraction with a computational model of auditory saliency based on acoustic features. Significance. Taken together, our study shows that auditory attention tracking outside of the laboratory in ecologically valid conditions is feasible and a step towards the development of future neural-steered hearing aids.
The Research on the Internet of Things Industry Chain for Barriers and Solutions

This paper takes the industry chain correlated theories as the instruction, and takes qualitative analysis primarily with quantitative analysis as auxiliary, and it mainly conducts the research from the following three aspects to the Internet of things industry: the composition of the industry chain of the Internet of things, obstacles existed in the industry chain of the Internet of things, and the method to remove barriers existed in the industry chain of the Internet of things. By the above analysis, this paper makes a more completely detailed study on the industry chain of the Internet of things and then makes some recommendations for the development of industry chain and the entire industry of the Internet of things.
Conductive Stimuli-Responsive Coordination Network Linked with Bismuth for Chemiresistive Gas Sensing

This paper describes the design, synthesis, characterization, and performance of a novel semiconductive crystalline coordination network, synthesized using 2,3,6,7,10,11-hexahydroxytriphenylene (HHTP) ligands interconnected with bismuth ions, toward chemiresistive gas sensing. Bi(HHTP) exhibits two distinct structures upon hydration and dehydration of the pores within the network, Bi(HHTP)-α and Bi(HHTP)-β, respectively, both with unprecedented network topology (2,3-c and 3,4,4,5-c nodal net stoichiometry, respectively) and unique corrugated coordination geometries of HHTP molecules held together by bismuth ions, as revealed by a crystal structure resolved via microelectron diffraction (MicroED) (1.00 Å resolution). Good electrical conductivity (5.3 × 10–3 S·cm–1) promotes the utility of this material in the chemical sensing of gases (NH3 and NO) and volatile organic compounds (VOCs: acetone, ethanol, methanol, and isopropanol). The chemiresistive sensing of NO and NH3 using Bi(HHTP) exhibits limits of detection 0.15 and 0.29 parts per million (ppm), respectively, at low driving voltages (0.1–1.0 V) and operation at room temperature. This material is also capable of exhibiting unique and distinct responses to VOCs at ppm concentrations. Spectroscopic assessment via X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopic methods (i.e., attenuated total reflectance-infrared spectroscopy (ATR-IR) and diffuse reflectance infrared Fourier transformed spectroscopy (DRIFTS)), suggests that the sensing mechanisms of Bi(HHTP) to VOCs, NO, and NH3 comprise a complex combination of steric, electronic, and protic properties of the targeted analytes.
External Knowledge Sourcing: Uncovering the Technology Scouting Process

This paper aims at contributing to the existing literatures on multinational management, technological search and open innovation by providing a detailed account of the process through which large multinational corporations (MNCs) use technology scouting units to systematically search for new technologies across geographic and organisational boundaries. Our data collection effort has extended over the period of two years; involved more than 50 semi-structured interviews with managers in three continents; numerous field observations and the use of both internal and publicly available archival data. Our findings seem to indicate that this process of search for knowledge across firm and geographic boundaries is filled with many nuances that a simple search-transfer model is not able to capture. Our data shows that this technology scouting process is comprised of six phases (internal
Characterization of Agarwood by Gas Chromatography–Mass Spectrometry and a Random Forest Model

Abstract Agarwood, resin produced by wounded Aquilaria plants, is widely used in perfume and medicine. In this study, artificial agarwood induced by physical injury, chemical stimulation, fungal infection, and comprehensive stimulation, which are the common induction methods, was collected. After gas chromatography–mass spectrometry (GC–MS) analysis, the total ion chromatogram/mass ion chromatogram (TIC/MIC) and qualitative peak data from artificial agarwood were used as training sets in discriminant analysis to examine the formation modes of natural agarwood by a random forest model which was shown to be superior to discriminate the formation of natural agarwood. The results implied that natural agarwood is likely formed through four formation modes. The discriminant result from random forest model showed that 17.1% of natural agarwood samples were formed by physical injury, 22.9% by chemical stimulation, 2.9% by fungal infection, and 57.1% by comprehensive stimulation. 2-Butanone-4-phenyl-, benzenepropanoic acid, guaiol, baimuxinal, and 2-(2-phenylethyl) chromone were the main chemical markers of the agarwood. The apparent abundance from the GC–MS fingerprints was used to distinguish agarwood formed by different formation processes.
Agile manufacturing framework and practice

This paper presents a framework for the implementation of agile manufacturing. The framework employs a bottom-up approach taking the company through three iterative implementation phases of robustness of operation, responsiveness to customers and proactive growth tactics. The framework incorporates a detailed assessment of the level of business environment turbulence and the impact of this turbulence on the enterprise. The results of this assessment are used to identify and customise an implantation plan as well as select the required tools and those measures of performance necessary to monitor the plans progress. This is carried while aligning any action to the company strategy.
Optical characterization of defects on patterned wafers: exploring light polarization

Polarization is an important and useful degree of freedom to explore defect SNR (Signal-to-Noise Ratio) improvement on repetitive memory devices. Sub-wavelength repetitive memory cell structures, especially in process layers of high-refractive-index dielectric and conducting materials, act as polarizer, resulting in a strong dependency of the optical response on polarization direction. In this study, STI layers of two typical memory products, Dynamic and Flash RAM, were selected to investigate defect detection capabilities with different polarization state of illumination light for different layouts. Several defect types, including void and scratch, are investigated. SNR improvement is observed primarily through linear polarization that is parallel to the pattern layout. Flash memory devices exhibit stronger birefringence than DRAM devices.
Membrane Domain Localization and Interaction of the Prion-Family Proteins, Prion and Shadoo with Calnexin

The cellular prion protein (PrPC) is renowned for its infectious conformational isoform PrPSc, capable of templating subsequent conversions of healthy PrPCs and thus triggering the group of incurable diseases known as transmissible spongiform encephalopathies. Besides this mechanism not being fully uncovered, the protein’s physiological role is also elusive. PrPC and its newest, less understood paralog Shadoo are glycosylphosphatidylinositol-anchored proteins highly expressed in the central nervous system. While they share some attributes and neuroprotective actions, opposing roles have also been reported for the two; however, the amount of data about their exact functions is lacking. Protein–protein interactions and membrane microdomain localizations are key determinants of protein function. Accurate identification of these functions for a membrane protein, however, can become biased due to interactions occurring during sample processing. To avoid such artifacts, we apply a non-detergent-based membrane-fractionation approach to study the prion protein and Shadoo. We show that the two proteins occupy similarly raft and non-raft membrane fractions when expressed in N2a cells and that both proteins pull down the chaperone calnexin in both rafts and non-rafts. These indicate their possible binding to calnexin in both types of membrane domains, which might be a necessary requisite to aid the inherently unstable native conformation during their lifetime.
Optimized Reactive Power Control of Module Power Imbalance of Cascaded Converter

In the medium voltage cascaded converter, the power imbalance problem among the converter modules will result in certain converter modules over-modulated. Reactive power control (RPC) scheme is an effective way to balance the cascaded converters. Many efforts, such as reactive power sharing control and apparent power sharing control have been used to solve the overmodulation issue. This paper investigates an optimization RPC scheme to solve the overmodulation problem by minimizing the total required reactive power. An improved minimum reactive power (IMRP) RPC scheme is presented, the feasible area for the active power imbalance is evaluated and compared with the reactive power sharing control scheme and the apparent power sharing control scheme. Finally, the control scheme is verified on a three-module scaled-down cascaded inverter.
Softsensor for estimation of steam quality in riser tubes of boilers

Steam fraction in riser tubes of boilers is a critical process variable which impacts the life of the tubes and could lead to tube rupture, long boiler down time, and expensive repairs. Unfortunately this parameter is difficult to measure by hardware sensors. This article presents a new neural network softsensor for estimation and monitoring steam mass and volume fractions in riser tubes. First, conventional data were collected from a target industrial boiler. The data are then used to develop a detailed nonlinear simulation model for the two phase flow in the riser tubes and risers and downcomers water circulation. The model output is verified against the collected field data. Next, the boiler nonlinear model is used to generate data covering a wide rage of operating conditions for training and testing the neural network. The input of the neural network includes the heating power, the steam flow rate, the water feed rate, the drum level, and the drum pressure. The neural networks predict the mass steam quality and the steam volume fractions. The softsensor achieves a root mean square error on the test data less than 1.5%. The predicted steam quality is then compared with the critical limits to guide the operators for safe and healthy operation of the boilers. The developed softsensor for estimation of the steam quality has simple structure and can be implemented easily at the operator stations or the application servers.
Loneliness Progression Among Older Adults During the Early Phase of the COVID-19 Pandemic in the United States and Canada

Abstract Objectives Older adults are at high risk for complications from coronavirus disease 2019 (COVID-19). Health guidelines recommend limiting physical contact during the pandemic, drastically reducing opportunities for in-person social exchange. Older adults are also susceptible to negative consequences from loneliness, and the COVID-19 pandemic has likely exacerbated this age-related vulnerability. Methods In 107 community-dwelling older individuals (65–90 years, 70.5% female) from Florida, the United States, and Ontario, Canada, we examined change in loneliness over the course of the pandemic after implementation of COVID-19-related physical distancing guidelines (March–September 2020; T1–T5; biweekly concurrent self-report) using multilevel modeling. We also explored gender differences in loneliness during the early phase of the COVID-19 pandemic at both data collection sites. Results Consistent across the 2 sites, levels of loneliness remained stable over time for the full sample (T1–T5). However, our exploratory moderation analysis suggested gender differences in the trajectory of loneliness between the United States and Canada, in that older men in Florida and older women in Ontario reported an increase in loneliness over time. Discussion Leveraging a longitudinal, binational data set collected during the early phase of the COVID-19 pandemic, this study advances understanding of stability and change in loneliness among a North American sample of individuals aged 65 and older faced with the unique challenges of social isolation. These results can inform public health policy in anticipation of future pandemics and highlight the need for targeted intervention to address acute loneliness among older populations.
Reduce Leakage Current and Average Power CMOS Current Comparator

The paper has been included the strategy about the current comparator. Therefore it has been contained or designed a different number of parameters after fabricating the circuit of the device. Here in designing of current comparator circuitry are using a current mirror circuitry designing, that type of circuit should be worked on boosting the higher speed of the system. After boosting the device it have been pulse range calculated from milli-ampere to pico-ampere. The device is using for contrasting the signal called comparator. Mainly parameters are calculated delay of the system for speed and also finding the signal to noise ratio with leakage (current or power). In this chapter the analytical comparison of various type of comparator designed, are given. The designing parameters of proposed comparator are calculated with previous year designed comparator parameters and after formulating the results of parameter the leakage (current has been calculated 6.868μA and the power has been measured 2.866μW) . The power dissipation has been measured 13. 94μW with reduction of delay 7%. Keywords: Power dissipation, propagation delay, speed, current comparator, cadence tool.
BIM-SPEED Inhabitant’s App: A BIM-Based Application for Crowdsourcing of Inhabitants’ Input in Renovation Projects

This report summarizes the conceptual framework and the technical implementation of a BIM-based user-friendly application to gather inhabitant’s input in the context of renovation projects developed in the European funded project BIM-SPEED. It starts with the underlying objectives and the role of data acquisition in the project. Then, it explains and outlines the conceptual framework and the methodology used in relation to the identified use cases, where inhabitants’ input is required. Furthermore, it describes the implementation and the development of the proposed methods as a user-friendly app and, finally, it ends with ethical and privacy considerations, specifically the measures taken for safe handling of privacy-sensitive data.
Modeling Synaptic Effects of Anesthesia and its Cortical Cholinergic Reversal

General anesthetics work through a variety of molecular mechanisms while resulting in the common end point of sedation and loss of consciousness. Generally, the administration of common inhalation anesthetics induces decreases in synaptic excitation while promoting synaptic inhibition. Animal studies have shown that, during anesthesia, exogenously induced increases in acetylcholine-mediated effects in the brain can elicit wakeful-like behavior despite the continued presence of the anesthetic. Less investigated, however, is the question of whether the brain’s electrophysiological activity is also restored to pre-anesthetic levels and quality by such interventions. Here we apply a computational model of a network composed of excitatory and inhibitory neurons to simulate the network effects of changes in synaptic inhibition and excitation due to anesthesia and its reversal by muscarinic receptor-mediated cholinergic effects. We use a differential evolution algorithm to fit model parameters to match measures of spiking activity, neuronal connectivity, and network dynamics recorded in the visual cortex of rodents during anesthesia with desflurane in vivo. We find that facilitating muscarinic receptor effects of acetylcholine on top of anesthetic-induced synaptic changes predicts reversal of the neurons’ spiking activity, functional connectivity, as well as pairwise and population interactions. Thus, our model results predict a possible neuronal mechanism for the induced reversal of the effects of anesthesia on post synaptic potentials, consistent with experimental behavioral observations. Author Summary Here, we apply a computational model of a network composed of excitatory and inhibitory neurons to simulate the network effects of changes in synaptic inhibition and excitation due to anesthesia and we investigate the possibility of its reversal by muscarinic receptor-mediated cholinergic effects. Specifically, we use a differential evolution algorithm to fit model parameters to match dynamics recorded in the visual cortex of rodents during anesthesia with desflurane in vivo. We find that changes of the fitted synaptic parameters in response to the increasing desflurane concentration matched those established by neurophysiology. Further, our results demonstrate that the cellular effects induced by anesthesia can be mitigated by the changes in cellular excitability due to acetylcholine.
Synthesis, Optimization, and Characterization of Ecofriendly Production of Gold Nanoparticles Using Lemon Peel Extract

This study examines the importance of utilizing green synthesis using lemon peel for gold nanoparticles over other chemicals since it is environmentally friendly, available, and cheap. Several parameters were optimized to ensure the extraction of the GNPs concentration of lemon peels using HAuCl4 and lemon peel extract having a ratio of 2 : 1. For the optimum result, the ratio used was 2 : 1. The gold nanoparticles fabrication happened in 10 minutes. The initial observation was the color change of the solution. The UV-visibility spectroscopic studies are performed to confirm the result. The experiments are done concurrently to ensure the solution is mixed on the proper ratio. The GNP is also characterized by the different techniques in their sizes and electronic transmission microscopy, essential in extracting gold nanoparticles. Other elements of the composition are removed by the EDAX methods, the FTIR method, and the TEM methods, all of which reveal the real reason behind the required extraction capacity. Most gold nanoparticles show a maximum absorption rate at the peak of 535 to 579 nm. The result obtained from the TEM and the SEM analysis revealed that the grain size is analogized to the average size of 6.67 nm. With a simple synthesis of the price, some processes show that the medically available nanoparticles are necessary. The used method in this paper to fabricate GNPs is cheap, easy, fast, and sustainable and it can be done with ease in any laboratory.
Special Issue: Recent Advances in Transition‐Metal Catalysis

This special issue "Recent Advances in Transition-Metal Catalysis" containing forty-two personal accounts and seven record reviews, discusses the ascendancy of transition metals in modern organic synthesis. The included articles portray the manifold application of transition metals in various processes such as addition/cyclization reactions, asymmetric synthesis, olefin metathesis reactions, coupling reactions, C-H bond activation/functionalization reactions. Additionally, reports describing novel organic transformations based on the employment of transition-metal catalysis in the fields of radical chemistry and materials science are also presented in this collection.
SECURITY ISSUES OF FEDERATED LEARNING IN REAL-LIFE APPLICATIONS

Machine Learning (ML) is becoming one of the most popular and widely used IT technologies in the past 10 years. The sharing and analysing of large volumes of data promises to revolutionalise many sectors, such as transport, healthcare and defence. This data's value and the consequent competitive advantages from its processing have attracted significant adversarial efforts against its security, privacy and availability. Recent advancements in federated learning (FL) show promising results in protecting data security and privacy and equally create additional opportunities for organised cyber criminals to capitalise from its use. This paper presents the existing and emerging security threats against FL using real-life scenarios and applications.