Miracle-dz/UniFAR-FTUs huggingface dataset:
PARAMETER EXTRACTION AND DEVICE PHYSICS PROJECTIONS ON LATERAL LOW VOLTAGE POWER MOSFET CONFIGURATIONS

The growing demand for battery-operated portable systems and power supply restrictions due to device scaling and reliability are major driving forces for development of low voltage/high current MOSFETs for VLSI technology. Reducing the power supply is a very effective way to reduce power consumption, hence increasing the device operating lifetime and relaxing the reliability constraints. The biggest challenge is to maintain high performance characteristics of the device, i.e. to prevent degradation of the device speed, by scaling down the device, thus lowering the threshold voltage and increasing the current-drive of the MOSFET. The contents of this document describe the major portion of experimental efforts and the subsequent results, of a project initiated by the Procter and Gamble Company with the intent of developing ultra low voltage power MOSFETs in collaboration with the University of Cincinnati. The specific objectives of the project are given below: • Full device characterization of existing state of the art power MOSFETs, verification and analysis and detailed understanding of the provided models and fitness comparison. • Parameter Extraction, model generation and comparison with obtained I-V characteristics. • Testing and full characterization of the lateral power MOSFET • Investigation of the semiconductor physics for short channel, high current, low voltage MOSFETs and impact of sub 1V design on power MOSFET performance. • Parameter extraction and modeling of the developed device.
Current-mode Single-Input Three-Output (SITO) Universal Filter Employing FTFNs and Reduced Number of Passive Components

In this paper, a new current-mode single-input three-output (SITO) universal filter employing FTFNs and reduced number of passive components is proposed. The circuit contains four FTFNs and five passive components, three of them are grounded. It provides simultaneous realisation of low-pass, band-pass and high-pass filter functions without changing the circuit topology and elements and does not require any parameter matching condition. The proposed circuit enjoys independent control of the parameters *, and <aJQ. Sensitivity analysis of the filter shows that it has tow passive sensitivities; *>, and (aJQ of the filter are insensitive to current tracking errors and tu, of the filter is also insensitive to voltage tracking errors of the FTFNs. High output impedances of the proposed universal filter enable the circuits to be cascaded without requiring any impedance matching device. The theoretical results are confirmed by PSPICE simulations. Übersicht Ein neues Universalfilter vom Stromquellentypus mit einem Eingang und drei Ausgängen (SITO) unter Verwendung von FTFN bei reduzierter Anzahl passiver Komponenten wird vorgeschlagen. Der Schaltkreis enthält vier FTFN sowie fünf passive Komponenten, von denen drei einseitig geerdet sind. Die Anordnung sieht gleichzeitige Realisierung von Tiefpaß-, Bandpaßund Hochpaß-Verhalten ohne Schaltungsänderung vor und stellt keine Nebenbedingungen bezüglich der Schaltungsparameter. Die Größen ob und <aJQ können unabhängig eingestellt werden. Eine niedrige passive Empfindlichkeit wird nachgewiesen, «b, Q und <aJQ des Riters sind unempfindlich gegenüber Stromänderungen, und ob ist außerdem unempfindlich gegenüber Spannungsänderungen der FTFN. Wegen der hohen Ausgangsimpedanzen können die vorgeschlagenen Schaltkreise ohne Anpaßmaßnahmen kaskadiert werden. PSPICE-Simulationen bestätigen die theoretischen Ergebnisse. Für die Dokumentation Signalverarbeitung mit Stromquellen / aktive Filter / FTFN
Integrating Risk Assessment in Planning for Sustainable Infrastructure Projects

Using risk assessment in planning for infrastructure project has significant impact on project life cycle performance, especially construction phase, which contributes to the 80% of project's total cost. Procurement of large infrastructure projects involves large amount of time and money spent to validate the appropriate risk assessment tools and techniques for successful project schedule and cost performance. This paper discuses and analyzes how qualitative and quantitative data, in highway construction projects, has been used in construction risk assessment and required action steps that should be considered for sustainable construction engineering and management practices. Further it also identifies the impact of transportation professional perception on the probability of project's cost growth and/or schedule growth in highway projects. Cost growth statistical dependency correlations have been tested against program and project related quantitative and qualitative data.
Cost and Latency Optimized Edge Computing Platform

Latency-critical applications, e.g., automated and assisted driving services, can now be deployed in fog or edge computing environments, offloading energy-consuming tasks from end devices. Besides the proximity, though, the edge computing platform must provide the necessary operation techniques in order to avoid added delays by all means. In this paper, we propose an integrated edge platform that comprises orchestration methods with such objectives, in terms of handling the deployment of both functions and data. We show how the integration of the function orchestration solution with the adaptive data placement of a distributed key–value store can lead to decreased end-to-end latency even when the mobility of end devices creates a dynamic set of requirements. Along with the necessary monitoring features, the proposed edge platform is capable of serving the nomad users of novel applications with low latency requirements. We showcase this capability in several scenarios, in which we articulate the end-to-end latency performance of our platform by comparing delay measurements with the benchmark of a Redis-based setup lacking the adaptive nature of data orchestration. Our results prove that the stringent delay requisites necessitate the close integration that we present in this paper: functions and data must be orchestrated in sync in order to fully exploit the potential that the proximity of edge resources enables.
Tracking 3D Deformable Objects in Real Time

3D object tracking is a topic that has been widely studied for several years. Although there are already several robust solutions for tracking rigid objects, when it comes to deformable objects the problem increases in complexity. In recent years, there has been an increase in the use of Machine / Deep Learning techniques to solve problems in computer vision, including 3D object tracking. On the other hand, several low-cost devices (like Kinect) have appeared that allow obtaining RGB-D images, which, in addition to colour information, contain depth information. In this paper is proposed a 3D tracking approach for deformable objects that use Machine / Deep Learning techniques and have RGB-D images as input. Furthermore, our approach implements a tracking algorithm, increasing the object segmentation performance towards real time. Our tests were performed on a dataset acquired by ourselves and have obtained satisfactory results for the segmentation of the deformable object.
Differences between Arterial and Venous Umbilical Cord Plasma Metabolome and Association with Parity

Umbilical cord blood is frequently used in health monitoring of the neonate. Results may be affected by the proportion of arterial and venous cord blood, the venous blood coming from the mother to supply oxygen and nutrients to the infant, and the arterial carrying waste products from the fetus. Here, we sampled arterial and venous umbilical cords separately from 48 newly delivered infants and examined plasma metabolomes using GC-MS/MS metabolomics. We investigated differences in metabolomes between arterial and venous blood and their associations with gestational length, birth weight, sex, and whether the baby was the first born or not, as well as maternal age and BMI. Using multilevel random forest analysis, a classification rate of 79% was achieved for arteriovenous differences (p = 0.004). Several monosaccharides had higher concentrations in the arterial cord plasma while amino acids were higher in venous plasma, suggesting that the main differences in the measured arterial and venous plasma metabolomes are related to amino acid and energy metabolism. Venous cord plasma metabolites related to energy metabolism were positively associated with parity (77% classification rate, p = 0.004) while arterial cord plasma metabolites were not. This underlines the importance of defining cord blood type for metabolomic studies.
A Normative Anatomic Study of the Glenohumeral Joint and Rotator Cuff Tendons

Introduction: The purpose of this study is to determine normative values relating to the glenohumeral joint and rotator cuff tendons namely length, width, thickness and footprint of supraspinatus (SS), infraspinatus (IS), teres minor ™ and subscapularis (SC) from 19 specimens. Methods: Rotator cuff tendons and humerus dimensions were measured directly using a digital vernier calliper. In addition, moduli values of rotator cuff tendons were obtained from tensile tests on twelve cadaveric shoulders. The tendon footprints were delineated onto a tracing paper and their dimensions were calculated using digitiser software. The glenoid dimensions were obtained from marking its outline onto a tracing paper and the cavity dimensions from wax moulds. The results were tabulated and statistical analyses, including Student's t-test and ANOVA, were performed. Conclusion: The normative anatomic values obtained can be used in finite element modeling, computer simulation, design of implants and surgery.
Enhancing Performance of Mwasalat Misr Company in Greater Cairo-Egypt during COVID-19 Pandemic

This research study explores human resource management decisions, management roles, and how they can have a significant and unique impact on the performance of the Mwasalat Misr organization. The survey adopted a qualitative survey design using a sequential narrative approach using unstructured interviews and a stakeholder analysis approach using open-question questionnaires. The research focuses on how to advance the public transport industry by advancing the relationship between HRM and organizational performance. Some of the key unresolved issues that require further research and help industry management investigate these issues and build a more cumulative body of knowledge that has important implications for theory and practice. Suggestions. The study concludes that four factors influence performance: personnel decisions, management roles, employee satisfaction, and cultural and organizational behavior. The COVID 19 pandemic has been found to serve as a parameter between the completed variable and the company's performance.
A Macaque Brain Extraction Model Based on U-Net Combined with Residual Structure

Accurately extracting brain tissue is a critical and primary step in brain neuroimaging research. Due to the differences in brain size and structure between humans and nonhuman primates, the performance of the existing tools for brain tissue extraction, working on macaque brain MRI, is constrained. A new transfer learning training strategy was utilized to address the limitations, such as insufficient training data and unsatisfactory model generalization ability, when deep neural networks processing the limited samples of macaque magnetic resonance imaging(MRI). First, the project combines two human brain MRI data modes to pre-train the neural network, in order to achieve faster training and more accurate brain extraction. Then, a residual network structure in the U-Net model was added, in order to propose a ResTLU-Net model that aims to improve the generalization ability of multiple research sites data. The results demonstrated that the ResTLU-Net, combined with the proposed transfer learning strategy, achieved comparable accuracy for the macaque brain MRI extraction tasks on different macaque brain MRI volumes that were produced by various medical centers. The mean Dice of the ResTLU-Net was 95.81% (no need for denoise and recorrect), and the method required only approximately 30–60 s for one extraction task on an NVIDIA 1660S GPU.
A 25 W 70% Efficiency Doherty Power Amplifier at 6 dB Output Back-Off for 2.4

This paper shows the design and simula- tion results of a hybrid Doherty power amplifier. The amplifier has been designed at 2,4 GHz, obtaining pow - er-added efficiency above 70 % for 6 dB output power back-off, together with a small signal gain of 17 dB. Design and analysis equations are presented consid- ering class AB bias conditions for the main amplifier and class C for the peak one in back-off larger than 6 dB, and FET device assumption. An additional control on the bias point of the peak device has been carried out, in order to increase the gain on the Doherty re- gion and ease the design of the peak branch. A Cree's GaN-HEMT CGH40010F device has been used with a nonlinear model guarantied up to 6 GHz and with an expected output power of 10 W. The obtained output power is higher than 25-W. The simulation has been carried out using Agilent ADS CAD tools. The present design could present the state of the art in terms of continuous-wave (CW) characterization.
Photosensitive EGFR-Targeted Nanocarriers for Combined Photodynamic and Local Chemotherapy

The major limitation of any cancer therapy lies in the difficulty of precisely controlling the localization of the drug in the tumor cells. To improve this drawback, our study explores the use of actively-targeted chemo-photo-nanocarriers that recognize and bind to epidermal growth factor receptor-overexpressing cells and promote the local on-demand release of the chemotherapeutic agent doxorubicin triggered by light. Our results show that the attachment of high concentrations of doxorubicin to cetuximab-IRDye700DX-mesoporous silica nanoparticles yields efficient and selective photokilling of EGFR-expressing cells mainly through singlet oxygen-induced release of the doxorubicin from the nanocarrier and without any dark toxicity. Therefore, this novel triply functionalized nanosystem is an effective and safe nanodevice for light-triggered on-demand doxorubicin release.
Ethical Challenges in Nanometrology

Nanoscience and nanotechnology (N&N) introduced a way of building molecular structures by the bottom-up approach. It provides opportunities in the fields of information technology, medicine, and new materials. The main aims of this branch are design, preparation, manipulation, and application of materials and structures having at least one dimension within the interval from 1 to 100 nm [1], [2]. (For comparison the size of Si atom is 0.22 nm). The mentioned interval originally determined by a simple convention is now widened at its lower boundary due to the appearance of graphene monolayer with the thickness of 0.34 nm, being the most progressive structure of the present material research. Basic nano-objects are molecules, atomic clusters, nanoparticles (NPs), nanowires, nanolayers, etc., which represent the building blocks of devices and structures. Characterized by a well-known statement by R. Smalley (2000) nanotechnology is the art of building devices at the ultimate level of finesse. The high scientific relevance of N&N may be documented by the fact that its discoveries and inventions were awarded by three Nobel prizes in physics (E. Ruska, G. Binning and H. Rohrer; A. Fert and P. Grünberg; A. Geim and K. Novoselov) and four Nobel prizes in chemistry (R. F. Curl, H. Kroto and R. E. Smalley; W. Kohn; E. Betzig, S. W. Hell and W. E. Moerner; J. P. Sauvage, J. F. Stoddart and B. L. Feringa) [2]. In the field of nanometrology, attention is paid to all seven basic physical quantities time, length, mass, electrical current, temperature, light intensity, amount of substance. Most important are, however, structure, morphology, composition, surface area, etc., of nanostructures. They are studied by almost 30 methods, divided into two basic groups [3], [4]: a) ensemble-averaging approach (EAA) where the techniques analyse larger samples providing statistically averaged output. Examples are spectroscopies, X-ray diffraction, calorimetric methods, light scattering, etc., and b) individual particle approach (IPA), that gives information about small samples and even individual atoms and molecules. Examples are electron and probe microscopies. The operational space of N&N is largely interdisciplinary, as it lies in the overlapping area of: • two-dimensional, one-dimensional and zero-dimensional (2D, 1D, 0D) nanostructures with a large surface area and excellent catalytic properties, biocompatibility and low size dispersion; • multipurpose materials with high thermal stability and controlled electrical and magnetic properties; • complex characterization and movement for high reproducibility. Our research is focused on spherical magnetic and biocompatible NPs belonging to iron oxide family with the good ability of self-assembly.
A modular RANS approach for modeling hypersonic flow transition on an air-breathing configuration

In this study, the laminar-turbulent flow transition scenario on a blunted double ramp, and further on a 20%-scale X-51A forebody configuration, has been simulated with a recently proposed RANS (Reynolds-Averaged Navier-Stokes) transition/turbulence model, which takes into account of the rational effects of compressibility, crossflow and flowseparation characteristics on different instability modes in 3-D boundary-layer flows. The model is based on the K-ω-γ three-equation eddy-viscosity concept with K representing the fluctuating kinetic energy, ω the specific dissipation rate and γ the intermittency factor. This model performs pretty well in the blunted double ramp case, where the hypersonic flow transition is caused by flow separation at the compression corner. For the X-51A forebody configuration, computed results are in good agreement with experimental data under both quiet and noisy conditions.
Analysis and Design of Three-Phase LLC Resonant Converter with Matrix Transformers

This study presents the topology of a three-phase LLC resonant converter with matrix transformers. The three-phase LLC resonant converter has the advantages of conventional LLC resonant converters, including zero-voltage switching at the primary side, zero-current switching at the secondary side, high-frequency feasibility, and high efficiency. Moreover, it has additional advantages that differ from conventional LLC, including low output capacitor current ripple, natural current sharing in three resonant currents, and a high power level. As a result of the above mentioned characteristics, LLC topology has been used in many electric vehicle charging systems, server power systems, and other high-power applications. However, as the power level becomes higher and higher, the input voltage is usually too high to reduce conduction loss, and the output current also increases. This situation makes transformer design more difficult. The increasing current means more core and copper loss, and the heat dissipation of the transformer becomes more difficult. Matrix transformer technology can improve this problem directly and simply. By utilizing matrix transformers, which are primary series connected and secondary parallel connected, the primary voltage stress and secondary current stress of the transformers can be reduced, and the output current can be distributed. The analysis of the proposed converter in this study includes a circuit operation introduction, a time-domain analysis, calculation of the transfer ratio curve in the frequency domain, and a loss analysis. The theoretical analysis and performance of the proposed converter are verified. A three-phase LLC resonant converter with matrix transformers prototype is built with a high input voltage of 800-VDC and high output current of 200-A. The output voltage is 100-VDC. The waveform and efficiency data will be shown in the experimental results.
Internal Combustion Engine Starting and Torque Boosting Control System Design with Vibration Active Damping Features for a P0 Mild Hybrid Vehicle Configuration

In order to meet the increasingly stricter emissions’ regulations, road vehicles require additional technologies aimed at the reduction of emissions from the internal combustion engine (ICE). A favorable solution from the standpoint of costs and simplicity of integration is a 48-V electrical architecture utilizing a low-voltage/high-power induction machine, which operates as the so-called engine belt starter generator (BSG) coupled via a timing belt with the ICE crankshaft within a P0 mild hybrid power train and used for starting up and boosting of the ICE power output, as well as for recuperating kinetic energy during vehicle deceleration. The aim of this work was to design a vibration damping system for the belt transmission within the so-called front end accessory drive (FEAD), which couples the BSG with the ICE crankshaft and to test the control system by means of simulations for realistic operating regimes of the P0 mild hybrid power train in order to show the functionality of the proposed approach in terms of mild hybrid vehicle performance improvement. Simulation results have pointed out effective attenuation of belt compliance-related vibrations using the proposed active damping control, with vibration magnitude reduced between three and five times compared to the default case during engine start-up phase. They have indicated the realistic belt slippage effects during engine start-up phase and have illustrated the effectiveness of the FEAD torque boosting capability with 30% gain in acceleration during vehicle launch.
Untargeted 1H-NMR Urine Metabolomic Analysis of Preterm Infants with Neonatal Sepsis

One of the most critical medical conditions occurring after preterm birth is neonatal sepsis, a systemic infection with high rates of morbidity and mortality, chiefly amongst neonates hospitalized in Neonatal Intensive Care Units (NICU). Neonatal sepsis is categorized as early-onset sepsis (EOS) and late-onset sepsis (LOS) regarding the time of the disease onset. The accurate early diagnosis or prognosis have hurdles to overcome, since there are not specific clinical signs or laboratory tests. Herein, a need for biomarkers presents, with the goals of aiding accurate medical treatment, reducing the clinical severity of symptoms and the hospitalization time. Through nuclear magnetic resonance (NMR) based metabolomics, we aim to investigate the urine metabolomic profile of septic neonates and reveal those metabolites which could be indicative for an initial discrimination between the diseased and the healthy ones. Multivariate and univariate statistical analysis between NMR spectroscopic data of urine samples from neonates that developed EOS, LOS, and a healthy control group revealed a discriminate metabolic profile of septic newborns. Gluconate, myo-inositol, betaine, taurine, lactose, glucose, creatinine and hippurate were the metabolites highlighted as significant in most comparisons.
Crystal Chemistry and Electronic Properties of the Al-Rich Compounds, Al2Cu, ω-Al7Cu2Fe and θ-Al13Fe4 with Cu Solution

In this work, we investigate Cu solution in θ-Al13Fe4 and related Al-rich ω-Al7Cu2Fe and Al2Cu phases in the Al-Cu-Fe system using the first-principles density functional theory (DFT) with on-site Coulomb interaction correction. The results show preference of Cu at Al7, forming a ternary θ-Al76Cu2Fe24 at ambient conditions, and both Al7 and Al9 sites (in Grin’s note), forming θ-(Al76−xCu2+x)Fe24 at a high temperature. The relative stability of the Al-rich compounds and their crystal and electronic properties are investigated. We show the importance of the Hubbard U correction to the standard DFT functionals for Cu-containing metallic materials. This study helps characterize the intermetallic compounds in Cu-containing Al alloys, and helps further control Fe-containing intermetallic compounds in the solidification of Al-based alloys.