Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative analysis of high frequency currents generated by pulsewidth modulation techniques

The paper investigates the influence of the modulation strategy on the generation of high frequency (HF) currents in modern electric drives. Firstly, HF current generation mechanisms are revised and related to key features of PWM modulation techniques. A comparative investigation on HF currents generated by three standard and three special modulation techniques is then experimentally performed on a 1.5 kW induction motor drive. Finally, useful guidelines to obtain the best compromise between HF currents amplitude and drive efficiency are carried out.
Quantum Confinement in Aligned Zigzag “Pseudo‐Ribbons” Embedded in Graphene on Ni(100)

Lateral quantum confinement is of great interest in tuning the electronic properties of graphene‐based nanostructures, making them suitable for technological applications. In principle, these properties might be controlled through the edge topology: for example, zigzag nanoribbons are predicted to have spin‐polarized edge states. The practical realization of these structures is of utmost importance in fully harnessing the electronic properties of graphene. Here, the formation of regular, 1.4 nm wide ribbon‐like graphene structures with zigzag edges are reported, showing 1D electronic states. It is found that these “pseudo‐ribbons” embedded in single‐layer graphene supported on Ni(100) can spontaneously form upon carbon segregation underneath 1D graphene moiré domains, extending hundreds of nanometers in length. On the basis of both microscopy/spectroscopy/diffraction experiments and theoretical simulations, it is shown that these structures, even though seamlessly incorporated in a matrix of strongly interacting graphene, exhibit electronic properties closely resembling those of zigzag nanoribbons.
Co-existence of GM and non-GM potato varieties on Finnish potato farms - po- tential costs and remedies

The aim of this study is to estimate by the seed potato inspecting data and farm model calculation that what the costs are caused by the segregation by potato varieties at farms. Furthermore this study assesses that, how contract production will be build up because of segregation. Co-existence is expensive to imple- ment if the inspections are systematic. When a farmer starts cultivating a GM variety, it is no longer profit- able for the farmer to return to cultivating non-GM potatoes. The deployments of gene technology and isola- tion requirements contribute to the networking of the supply chain
Organic acid, a virulence factor for pathogenic fungi, causing postharvest decay in fruits

Abstract Decay due to fungal infection is a major cause of postharvest losses in fruits. Acidic fungi may enhance their virulence by locally reducing the pH of the host. Several devastating postharvest fungi, such as Penicillium spp. , Botrytis cinerea, and Sclerotinia sclerotiorum, can secrete gluconic acid, oxalic acid, or citric acid. Emerging evidence suggests that organic acids secreted by acidic fungi are important virulence factors. In this review, we summarized the research progress on the biosynthesis of organic acids, the role of the pH signalling transcription factor PacC in regulating organic acid, and the action mechanism of the main organic acid secreted via postharvest pathogenic fungi during infection of host tissues. This paper systematically demonstrates the relationships between tissue acidification and postharvest fungal pathogenicity, which will motivate the study of host–pathogen interactions and provide a better understanding of virulence mechanisms of the pathogens so as to design new technical strategies to prevent postharvest diseases.
Communicating Like Nemo: "Scale-ability" from a Fish-Eye View

Recreational scuba diving is a highly social activity where divers are encouraged to work in groups of two or more people. Though collaborative, divers are unable to freely and naturally communicate. Additionally, the lack of instincts to help them keep track of critical information such as time, depth, and direction further impairs their ability to engage in this underwater world. We propose the development of a collaborative based system, the Nemo2020, to increase activityawareness, position-awareness, safety, and social integration for divers. Here we consider the design of this device, the ways in which current technology such as 802.11s Wi-Mesh and Android can be brought to bear on the problem, and how future systems may be able to rise to the challenge. 1 Design of the Nemo2020 The Nemo2020 is a collaborative dive computer system integrated with a messaging system, single and multiple divers’ status views, localization of divers’ position, and a safety alert enhancement. The device could be used standalone or in collaboration mode. In either mode, the system first leads the diver through a standard pre-dive procedure check (with the additional device pairing step), then enters the initial dive screen shown in Figure 1a. Divers click on an individual image to see details.
Automatic recognition of woven fabric pattern based on image processing and BP neural network

As there are error judgments of float type in the traditional method based on image processing, it is hard to determine the woven fabric pattern from the recognition results. To solve this problem, fuzzy C‐means (FCM) algorithm was selected to classify the floats into two groups in the experiment, and BP neural network is chosen to recognize woven fabric pattern. White–black co‐occurrence matrix is used to extract its texture features. The texture and structure features of the normal fabrics extracted from the classification are input into the neural network to complete the learning process. During the recognition process, the texture features of the fabric are extracted from the classification results with white–black co‐occurrence matrix. The structure features are extracted simultaneously. These features are then input into BP neural network and woven fabric pattern would be output from the neural network. The experiment on actual fabrics proves that the method proposed in this study has fault tolerant ability, and it can recognize fabric patterns correctly.
Knowledge-guided artificial intelligence technologies for decoding complex multiomics interactions in cells

Cells survive and proliferate through complex interactions among diverse molecules across multiomics layers. Conventional experimental approaches for identifying these interactions have built a firm foundation for molecular biology, but their scalability is gradually becoming inadequate compared to the rapid accumulation of multiomics data measured by high-throughput technologies. Therefore, the need for data-driven computational modeling of interactions within cells has been highlighted in recent years. The complexity of multiomics interactions is primarily due to their nonlinearity. That is, their accurate modeling requires intricate conditional dependencies, synergies, or antagonisms between considered genes or proteins, which retard experimental validations. Artificial intelligence (AI) technologies, including deep learning models, are optimal choices for handling complex nonlinear relationships between features that are scalable and produce large amounts of data. Thus, they have great potential for modeling multiomics interactions. Although there exist many AI-driven models for computational biology applications, relatively few explicitly incorporate the prior knowledge within model architectures or training procedures. Such guidance of models by domain knowledge will greatly reduce the amount of data needed to train models and constrain their vast expressive powers to focus on the biologically relevant space. Therefore, it can enhance a model’s interpretability, reduce spurious interactions, and prove its validity and utility. Thus, to facilitate further development of knowledge-guided AI technologies for the modeling of multiomics interactions, here we review representative bioinformatics applications of deep learning models for multiomics interactions developed to date by categorizing them by guidance mode.
Regional-temporal Trends and Risk Assessment of Polychlorinated Biphenyls (PCBs) in Olive Lands in Bursa, Turkey

ABSTRACT In this study, it was aimed to determine the spatial and temporal variations of polychlorinated biphenyl (PCB) levels in olive lands (0–5 cm) and to identify dominant PCB homologous groups and cancer risk values. In this context, surface soil samples were taken from seven olive lands in Bursa-Turkey for 9 months. Sampling points were categorized as rural, semi-rural, residential, and industrial areas. Regional-temporal trends of 43 PCB compounds were reported. The total average (∑43) PCB concentrations ranged between 8.3 ± 3.31 ng/g DM and 15.4 ± 3.3 ng/g DM. The lowest ∑43 PCB concentration was measured at the rural area (Mudanya Yörükali-MY) and the highest value was measured at Orhangazi Asilzade (OA), which is an industrial area. The dominant homologous group in all seasons was found to be 5-CBs (31%) followed by 4-CBs (16%) and 6-CBs (15%). Cancer risks were calculated and risk trend was determined as ingestion > dermal > inhalation. The values ranged between 5.26 × 10−6 and 1.28x10−5, 2.62 × 10−5 and 1.08x10−5, 1.68 × 10−1 and 6.9 × 10−12 for dermal, ingestion and inhalation, respectively. Also, the correlation between the levels of certain soil characteristics (dry matter, pH, and temperature) was also investigated. Statistical results showed that for PCB#89/101, PCB#135/144, PCB#126, PCB#156/171/202, PCB#172 PCB#170/190 it was determined that there was a significant relationship.
Enhancement of Learning Objectives in Construction Engineering Education: A Step toward Simulation Assessment

The growing use of digital technology in design and construction has brought a change in teaching dynamics. For example, serious games have shown great potential in enhancing the learning of dynamic construction concepts traditionally acquired through practical experience. One such example is the Virtual Construction Simulator 3 (VCS3) game, developed and implemented to engage students in an active learning environment by simulating the planning and managing of a construction project. Initial assessment of the VCS3 game has demonstrated benefits for both students' motivation and basic understanding of construction concepts. However, further assessment is required to demonstrate the benefits on higher order cognitive skills. This paper introduces the first step, the formulation of learning objectives for higher order cognitive skills in construction simulation gaming. Learning objectives from third- and fourth-year construction engineering courses, together with the previous VCS3 learning objectives, are analyzed and categorized. The learning objectives guiding the next phase of the VCS4 simulation game development are then presented from lower to higher level thinking skills. This initial step opens the next phase in the development and assessment of the VCS4.
Fundamentals and working mechanisms of artificial muscles with textile application in the loop

Natural muscles, that convert chemical energy derived from glucose into mechanical and thermal energy, are capable of performing complex movements. This natural muscle power was the only way to perform mechanical work in a targeted manner for millions of years. In the course of thousands of years of technical development, mankind has succeeded in harnessing various physical and chemical phenomena to drive specific mechanical processes. Wind and water power, steam and combustion engines or electric motors are just a few examples. However, in order to make the diversity and flexibility of natural motion patterns usable for machines, attempts have been made for many years to develop artificial muscles. These man-made smart materials or structures are able to react to environmental conditions by significantly changing their shape or size. For the design of effective artificial muscles that closely resemble the natural original, the usage of textile technology offers great advantages. By means of weaving, individual actuators can be parallelized, which enables the transmission of greater forces. By knitting the maximum stretching performance can be enhanced by combining the intrinsic stretching capacity of the actuators with the structural-geometric stretching capacity of the fabric. Furthermore textile production techniques are well suited for the requirement-specific, individual placement of actuators in order to achieve the optimal geometry for the respective needs in every load case. Ongoing technical development has created fiber based and non-fibrous artificial muscles that are capable of mimicking and even out-performing their biological prodigy. Meanwhile, a large number of partly similar, but also very different functional principles and configurations were developed, each with its own specific characteristics. This paper provides an overview of the relevant and most promising technical approaches for realizing artificial muscles, classifies them to specific material types and explains the mechanisms used as well as the possible textile applications.
Improved recursive Newton-type algorithm for power system relaying and measurement

A new recursive Newton-type algorithm suitable for measurement applications in power systems is presented. In an improved form it is used for power system frequency, phasors and spectra estimation. The key algorithm improvement is provided through a new forgetting factor tuning procedure, by which the speed of convergence and accuracy are improved. The results of computer simulation, laboratory testing and offline full-scale real-life data processing are given to show the main algorithm properties.
Social Commerce: A Bibliometric Analysis and Future Research Directions

The present study performs the bibliometric analysis of the social commerce (s-commerce) literature, highlights the major research themes, and suggests future research directions. The HistCite software has been used for bibliometric analysis on a sample of 660 s-commerce papers obtained from the ISI Web of Science database. This study analyses these papers to present the details about the influential journals, authors, and universities regarding s-commerce research. Following research themes have been identified based on the content analysis as well as citation mapping of the top-cited 53 s-commerce papers: 1) S-commerce – Purchase Intention, 2) S-commerce – Sharing Intention, 3) Social Media – Marketing and Consumer Engagement, 4) S-commerce – User Preferences and Concerns. Subsequently, a multi-dimensional conceptual model has been developed to highlight the coupling and flow between s-commerce growth drivers, practice indicators, and performance metrics. Finally, future research directions have been recommended.
Correlated microwave-ultrasonic multi-sensor for reliable measurements of velocity and range

The potential of the combination of ultrasound and microwaves to improve existing sensors in terms of sensitivity and reliability is demonstrated. While noise and disturbances affect both waves differently, signal returns form target reflectors will be coherent. With data fusion performed on the signal level, the applicability is significantly improved compared with multisensors based on complementary sensor outputs. A compact low-cost sensor for the robust measurement of presence, velocity and distance of objects, using 24 GHz microwaves and 40 kHz ultrasound, has been designed. Key issues for a smart sensor design, inherently exploited by the multisensor approach, are the adaptation to the environment, self calibration and function monitoring. The design and operating parameters of the multisensor system are discussed and evidence for the satisfactory performance is given.
An ensemble feature method for food classification

In the last years, several works on automatic image-based food recognition have been proposed, often based on texture feature extraction and classification. However, there is still a lack of proper comparisons to evaluate which approaches are better suited for this specific task. In this work, we adopt a Random Forest classifier to measure the performances of different texture filter banks and feature encoding techniques on three different food image datasets. Comparative results are given to show the performance of each considered approach, as well as to compare the proposed Random Forest classifiers with other feature-based state-of-the-art solutions.
A Horseshoe Crab Inspired Surf Zone Robot With Righting Capabilities

In this paper, we present the design of RoboCrab, an amphibious robot capable of traversing moderate surf zone environments. By taking inspiration from the morphology, locomotion, and righting behaviors of a horseshoe crab, the robot is designed for traversal and righting on granular terrain, open water, and turbulent surf zones. We present the details of the crab’s morphology that informed the design of our robot. Next, we present the mechanical design, material selection, and manufacturing of the various parts of the robot. We report the results from the computational fluid dynamics simulations used to characterize the robot shell performance. Finally, we present demonstrations of the physical robot walking and righting in a granular environment.Copyright © 2014 by ASME
A novel control scheme of a parallel current-controlled PWM inverter

A parallel technique for current-controlled pulse-width-modulated (PWM) inverters is described. Two voltage source inverters, the output terminals of which are connected in parallel through current balancers, are used as a main circuit. In this scheme, excellent characteristics both in steady states and in transient states are obtained, keeping the average values of the cross current and zero sequence current at zero level. This current control scheme is applicable to large-capacity GTO inverters because good performance is attained even if the switching frequency is only a few hundred hertz, as is shown in the experimental results. >
Effect of dead time on harmonic distortion in class-D audio power amplifiers

A model is described for predicting the harmonic levels introduced by the use of dead time in class-D, PWM-driven audio power output stages. The model demonstrates that the harmonic levels are a function of load impedance, modulation depth, dead time and switching frequency. In addition, measurements show that, for audio applications, dead time is the dominant cause of power stage nonlinearity.
Understand spiral heat exchangers

Shell-and-tube heat exchangers are standard in most chemical process industries (CPI) applications. However, they do have limitations related to thermal efficiency, mechanical design, and maintenance requirements that will not allow the standard straight-tube fixed-tubesheet shell-and-tube (S and T) heat exchanger to work properly in certain applications. It is in these problem areas that spiral heat exchangers (SHEs) have been used successfully worldwide for over 60 years. The SHE can be a viable alternative to the complex and often expensive shell-and-tube heat exchanger. The SHEs' unique spiral countercurrent monochannel design gives them exceptionally high heat-transfer rates and low fouling tendencies. The mechanical configuration of the SHE also allows full access to all heat-transfer surfaces for simplified inspection, maintenance, and cleaning. This article describes how SHEs operate, discusses their advantages in terms of thermal efficiency, fouling, mechanical design, and maintenance characteristics, and provides guidance on choosing between spiral and tubular exchangers.
A tunable all-pass MMIC active phase shifter

This paper describes a novel structure for a monolithic-microwave integrated-circuit active phase shifter based on a bridge all-pass network. The design procedure has been developed, leading to a fixed-frequency circuit with large tunable phase variation, associated to a low-gain ripple, and requiring nearly no design optimization. Simulated results predicted an analog tunable 180/spl deg/ phase variation, at 5-GHz operation frequency. The circuit was implemented using GEC-Marconi pseudomorphic high electron-mobility transistor H40 technology, and measured results validated the proposed design method and circuit structure.
Reoccurring Bovine Anthrax in Germany on the Same Pasture after 12 Years

The zoonotic disease anthrax, caused by the endospore-forming bacterium Bacillus anthracis, is very rare in Germany. In the state of Bavaria, the last case occurred in July of 2009, resulting in four dead cows. ABSTRACT The zoonotic disease anthrax, caused by the endospore-forming bacterium Bacillus anthracis, is very rare in Germany. In the state of Bavaria, the last case occurred in July of 2009, resulting in four dead cows. In August of 2021, the disease reemerged after heavy rains, killing one gestating cow. Notably, both outbreaks affected the same pasture, suggesting a close epidemiological connection. B. anthracis could be grown from blood culture, and the presence of both virulence plasmids (pXO1 and pXO2) was confirmed by PCR. Also, recently developed diagnostic tools enabled rapid detection of B. anthracis cells and nucleic acids directly in clinical samples. The complete genome of the strain isolated from blood, designated BF-5, was DNA sequenced and phylogenetically grouped within the B.Br. CNEVA clade, which is typical for European B. anthracis strains. The genome was almost identical to BF-1, the isolate from 2009, separated only by three single nucleotide polymorphisms (SNPs) on the chromosome, one on plasmid pXO2 and three indel regions. Further, B. anthracis DNA was detected by PCR from soil samples taken from spots in the pasture where the cow had fallen. New tools based on phage receptor-binding proteins enabled the microscopic detection and isolation of B. anthracis directly from soil samples. These environmental isolates were genotyped and found to be identical to BF-5 in terms of SNPs. Therefore, it seems that the BF-5 genotype is currently the prevalent one at the affected premises. The area contaminated by the cadaver was subsequently disinfected with formaldehyde.
Smart, In Situ, Wide Range Pressure Sensor for Advanced Engine Controls

Air Force Research Laboratory (AFRL) is pursuing development of advanced, distributed, intelligent, adaptive engine controls and engine health monitoring systems. The goals this pursuit are enhancing engine performance, safety, affordability, operability, and reliability while reducing obsolescence risk. The development of smart, high-bandwidth, high-temperature-operable, wide-range, pressure/temperature multi-sensors, which addresses these goals, is discussed. The resulting sensors and packaging can be manufactured at low cost and operate in corrosive environments, while measuring temperatures up to 2,552 °F (1,400 °C) with simultaneous pressure measurements up to 1,000 psi (68 atm). Such a sensor suite provides unprecedented monitoring of propulsion, energy generation, and industrial systems. The multi-sensor approach reduces control system weight and wiring complexity, design time, and cost, while increasing accuracy and fault tolerance. In situ pressure sensors reduce size and weight while eliminating failures associated with hypo-tube fouling. High-bandwidth sensors support advanced compressor and combustor control schemes that facilitate higher thrust, reduced fuel consumption and reduced emissions. Smart sensors are a key enabling technology for distributed engine control which is an important architectural paradigm shift to achieve increased flexibility, scalability, fault tolerance and performance while reducing weight, lifecycle costs and obsolescence risk. Current efforts include combining the sensor technology with other high-temperature electronics to produce smart sensors for distributed engine controls, capacitive transducer elements with increased dynamic bandwidth, and advanced high-temperature sensor packaging technologies. Test results demonstrating technology readiness level (TRL) 6 are reported herein.