Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparative Evaluation of Three-Phase AC-AC Voltage/Current-Source Converter Systems Employing Latest GaN Power Transistor Technology

The emergence of monolithic bidirectional GaN power transistors sparks renewed interest in AC-AC current-source converters (CSCs) as an alternative to AC-AC voltage-source converters (VSCs) for motor drive applications. This paper compares the two approaches with the CSC utilizing novel 600 V, 140 $\mathrm{m}\Omega$ monolithic bidirectional GaN transistors. Aiming for a comparison of next-generation plug-and-play motor drives, both systems must fulfill the same EMI limits that cover an extended frequency range from 9 kHz to 30 MHz at the grid and at the motor interface. Designing both systems with roughly the same total chip area for the same AC-AC efficiency of 97 % at a nominal power of 1.4 kW (200 V nominal line-to-line RMS voltage, 4 A nominal RMS current), we identify a suitable switching frequency of 72 kHz, and we discuss efficiency characteristics over the motor current (torque) and voltage (speed) ranges. A comparison of the total magnetic component volumes finds advantages for the VSC system, which disappear if motor-integration (voiding the need for a motor-side differential-mode EMI filter) is considered.
A N:1 Single-Channel TDMA Fault-Tolerant Technique for TSVs in 3D-ICs

As the number of 3D-IC stacks increases, defects of through silicon via (TSV) in manufacturing and bonding process seriously affect the yield and reliability of the chip. Comparing to discarding these defective ones, some faulttolerant architectures are proposed, however, these existing schemes have great hardware overhead. In the paper, an N:1 single-channel time division multiple access (TDMA) faulttolerant technique using redundant TSV to tolerate TSV defect is proposed. Data is grouped and transmitted through TSV by TDMA mechanism, which reduces the number of TSV. The number of groups depends on bandwidth and hardware. The N: 1 single-channel TDMA structure is designed to use a single TSV to accomplish the time-sharing transmission of a group of signals. Each signal TSV is equipped with an additional TSV to improve the fault-tolerant coverage. The functions are verified on 40 nm Xilinx virtex-6 FPGA. The simulation results of Design Compiler based on 45 nm PTM show that the fault coverage rate can be increased to 100%, and the area overhead is reduced by 60.8% compared with the existing methods.
Analysis and Conceptualization of a 800 V 100 kVA Full-GaN Three-Level Flying Capacitor Inverter for Next-Generation Electric Vehicle Drives

The rising pace of the transportation sector elec-trification is increasingly demanding for cheaper, lighter and more efficient powertrains. In particular, the inverter represents a crucial component of an electric vehicle (EV) drive train, being responsible for the DC/ AC power conversion between the battery and the electrical machine. Therefore, a great effort is currently being spent to develop a new generation of EV drive inverters, leveraging advanced converter topologies and modern wide bandgap (WBG) semiconductor devices. For instance, three-level inverters are particularly promising candidates for future 800 V powertrains, as they allow to exploit semiconductor devices with lower blocking voltage (i.e., 600/650 V) and higher switching performance, such as state-of-the-art GaN high electron mobility transistors (HEMTs). In this context, this paper proposes the analysis and the conceptualization of a full-GaN 100 kVA 800 V three-level flying capacitor inverter (3LFCI) for next-generation EV drives. A complete theoretical assessment of the system active and passive component stresses is carried out, providing the foun-dation for the converter sizing. Moreover, a 3LFCI design concept is developed, achieving an estimated 99.1 % peak semiconductor efficiency and 108kVA/dm3 volumetric power density.
Review on MPPT Techniques in Solar System

Maximum power point tracking (MPPT) algorithms are a practical solution to ensure the continuous operation of the photovoltaic systems, maximize the output of the PV system and overcome nonlinear characteristics under all circumstances. Different MPPT strategies were used to achieve the maximum output power of the photovoltaic system. There are conventional MPPT algorithms. Also, there are soft computing techniques to attract the maximum PowerPoint. In this paper, the MPPT approaches for solar systems are reviewed and compared in-depth with six different requirements, the comparison shows that the Incremental Conductance has an advantage over the conventional methods. Soft computing methods give high efficiency, but the effectiveness of soft computing techniques needs users for a good background on how it works, it's more complex than conventional MPPT methods, the essential variations among these approaches are digital versus analogy applications, design simplicity, sensor requirements, convergence time, effectiveness range, and hardware pricing. As a consequence, choosing the right algorithm is crucial for users since it impacts the electrical efficiency of the photovoltaic (PV) module and lowers expenses by lowering the number of solar panels required to produce the necessary electricity.
Four-switch Class-PN Power Amplifier for High Power Handling Capability in Wireless Power Transfer

Most power amplifiers (PA) for wireless power transfer (WPT) are based on single switch topologies (Class- $\mathbf{E},\ \mathbf{F},\ \Phi,)$. Single-switch topologies are easy to design and operate, but they are limited in power handling capability. Utilizing multi-switch topologies increases device utilization which improves power handling capability. In this paper a novel topology is introduced, which is referred as Class-PN. Class-PN is based on four switches, and is shown to have more than 6x higher power handling capability than Class-E. The topology consists of no resonating passive components, thus the same PA is operational at multiple switching frequencies. Series resonating load at output power of 135W and switching frequency of both 7MHz and 12MHz are shown at first to verify operation of Class-PN power amplifier. Finally, inductively coupled coils are used to transfer power wirelessly between the transmission and receiving coil. Wireless power delivered to the load at 6.15MHz of switching frequency is 400W, which was limited by the radio frequency (RF) load.
Path Loss Modeling and Channel Characterization at 28 GHz 5G Micro-Cell Outdoor Environment using 3D Ray-Tracing

Propagation models that are existing for the frequencies less than 6 GHz are not suitable for Millimeter wave (mmWave) bands. Path loss modeling (PLM) and channel characterization at 28 GHz 5G outdoor macro-cell environment is not possible with these models because of variation in propagation characteristics. This paper presents a PLM, channel modeling and coverage area analysis using 3D ray-tracing in outdoor environment. Analysis is performed with a distance of 130 mts from TX and RX in non-line-of-sight (NLOS) scenario. The measurements are taken at outdoor environment of shri vishnu engineering college women (SVECW), bhimavaram, India using site viewer 3D model. The path loss and received power measured by varying the receiver antenna height from 5 mts to 25 mts. The analysis is also performed with building material as glass and concrete. All the simulations are performed with MATLAB software.
Enabling Coverage-Based Verification in Chisel

Ever-increasing performance demands are pushing hardware designers towards designing domain-specific accelerators. This has created a demand for improving the overall efficiency of the hardware design and verification cycles. The design efficiency was improved with the introduction of Chisel. However, verification efficiency has yet to be tackled. One method that can increase verification efficiency is the use of various types of coverage measures. In this paper, we present our open-source, coverage-related verification tools targeting digital designs described in Chisel. Specifically, we have created a new method allowing for statement coverage at an intermediate representation of Chisel, and several methods for gathering functional coverage directly on a Chisel description.
The Calculation of Extreme Condition of Telescopic Boom of Drilling Jumbo Based on New Biogeography-Based Optimization Algorithm

As a key part of the boom structure of drilling jumbo, the structural stability of the telescopic boom plays a decisive role in the operational reliability of the drilling jumbo. However, the extreme condition of the telescopic boom in the existing optimization cases is determined according to the experience of designers, and there is a lack of research on the extreme condition of the telescopic boom. Given the above problem, the calculation model of the load at the top of the telescopic boom is constructed, and the Biogeography-Based Optimization (BBO) algorithm is used to optimize the pose parameters of the boom structure with the maximum optimization objective of the calculation results of the model. To solve the problem of insufficient adaptability of the linear migration model, 12 nonlinear migration models are proposed and combined with the original BBO algorithm. The performance tests of various migration models are carried out by calculating the limit value of the load at the top of the telescopic boom, the results show that the overall performance and stability of the BBO algorithm based on the exponential migration model is better than other classic optimization algorithms and BBO algorithms based on other migration models. The exponential migration model can better adapt to the nonlinear migration problem, and the corresponding BBO algorithm has better optimization ability.
Bidirectional Attention LSTM Networks for Non-instructive Load Monitoring

Non-instructive load monitoring (NILM) is a data processing method that decomposes the total energy consumption and estimates the power of individual electrical appliances. The application of NILM can provide additional information for optimal control strategy of smart grid, to achieve the purpose of saving energy by fine management. However, the accuracy of traditional NILM methods doesn’t have high accuracy of decomposed power value. In this work, we apply long short-term memory (LSTM) and achieve good accuracy by enhancing the LSTM model with bidirectional and attention mechanisms, as well as kernel density estimation. The model first normalizes the total energy consumption and converts the normalized data to time series of fixed length. LSTM extracts features from the time series, with the bidirectional mechanism to operate from both normal and reverse order and the attention mechanism to calculate the attention weights of different time steps. Besides, kernel density estimation is used to fit the training data and modify the output of the deep learning model, which upgrades the disaggregation accuracy. The proposed model is tested on UK-dale dataset.
Music Note Series Precipitation using Two Stacked Deep Long Short Term Memory Model

People need to get relieve from their stress and thoughts by engaging themselves with entertainment. Music plays a vital role in changing the people environment to overcome their personal problems. As technology is involved in all the fields, deep learning is extensively contributing its performance in the music industry towards generation of music note sequence. Music confirms to be a tough dynamic than image data as it is temporal with hierarchical structure and cross-temporal dependencies. As music is composed of multiple instruments by being interdependent and being evolved over time, it remains a challenging issue for the researchers to work. Since music is distributed into chords, arpeggios, melodies and each time-step generating multiple outputs, the generation of music note sequences through deep learning network extend higher issue for the researchers in programming. By interpreting the above scenario, a new two-stacked Deep Long Short Term Memory (TSD-LSTM) model is designed for music note sequence generation using audio framework of piano with 16000 frame length. The dataset is extracted from Maestro database repository. The audio framework data is converted into MIDI format using pretty_midi package. The MIDI digital data is parsed with 30513 number of notes resulting with sequence length of 25 frames and vocabulary size of 128 pitch length. The total digital data is ended up with 1282 MIDI information frames. The parsed audio digital data is splitted into training data with 967 MIDI data, validation data with 137 MIDI data and testing data with 178 MIDI data. Model fitting is done with TSD-LSTM. The proposed model design is refined with parameter optimization. The project is implemented with Python under NVidia Tesla V100 GPU server with 215938 trainable parameters, training epochs of 300, batch size of 64 along with training rate of 0.001. The music note sequence generation is done with TSD-LSTM and fitted with single stack LSTM, 3 stack LSTM and 4 stack LSTM and the performance is analyzed and compared with metrics like train loss, duration loss, pitch loss and step loss. Implementation results shows that TSD- LSTM model have minimum value for test loss of 0.0567, duration loss of 0.0086, pitch loss of 0.8150 and step loss of 0.0073 compared to other models.
Depletion of Petroleum Reserves and Oil Price trends

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Depletion of Petroleum Reserves and Oil Price trends Denis Babusiaux, Pierre-René Bauquis
Anti-Candidae¡ect of bacillomycin D-like lipopeptides from BacillussubtilisB38

Bacillus subtilis B38, isolated from soil, showed antimicrobial activity against human pathogenic Candida albicans species. Speciﬁc PCR primers revealed the presence of the bamC gene, which is involved in the biosynthesis of bacillomycin D. Three anti- Candida compounds designated a 1 , a 2 and a 3 were puriﬁed from culture supernatant and identiﬁed using matrix-assisted laser desorption/ioniza-tion time-of-ﬂight MS as analogues of bacillomycin D-like lipopeptides of 14, 15 and 16 carbon fatty acid long chains, respectively. The compound a 3 displayed the strongest fungicidal activity against pathogenic C. albicans strains. It was even more active than amphotericin B with a lethal concentration of 59.07 vs. 135.26 m M of the antimycotic drug against the pathogenic strain C. albicans sp. 311 isolated from ﬁnger nail. Only moderate or weak anti- Candida activity was recorded for a 1 and a 2 compounds. Furthermore, a 3 showed the highest hemolytic activity, reaching 50% hemolysis at 22.14 m M, whereas a 1 and a 2 displayed a limited hemolysis at 68.26 and 37.41 m M, respectively. These ﬁndings suggest that the acyl chain length of bacillomycin D-like lipopeptides plays a major role in hemolytic and antifungal activities.
THE EFFECT OF GELLING AGENT ON THE MICROPROPAGATION OF COMMON LILAC ( SYRINGA VULGARIS L.)

In order to assess the effect of gelling agents upon lilac in vitro proliferation rate, eight types of gelling agents were tested, at concentrations considered to be optimal, based on preliminary tests as follow: 3 g/L Fibrous Agar, 6g/L Daishin Agar, 4 g/L Gelcarin, 2 g/L Gelrite, 15 g/L Isubgol, 4 g/L Micro Agar, 6 g/L Phyto Agar and 4 g/L Plant Agar. The culture media was Murashige & Skoog (MS) supplemented with 4 mg/L 6-benzylaminopurine (BAP). The plant material consisted of shoots picked from in vitro cultures on MS+0.5 mg/L BAP gelled with Plant Agar. The highest multiplication rate was 3.76, obtained in the experimental treatment with the media gelled with 15 g/L Isubgol, while the lowest proliferation rate was 1.4, on the media gelled with Daishin Agar. The shoots obtained in these eight experimental treatments were rooted ex vitro and acclimatized using the floating perlite method, in two experimental treatments: one with hormone-free floating perlite and one supplemented with 1mg/L indole-3-butyric acid (IBA). The highest rooting and acclimatization percentage (90%) was obtained in the hormone-free floating perlite experimental treatment, from shoots obtained in the media gelled with 6 g/L Daishin Agar.
Mathematical modelling of whole chromosome replication. Nucleic Acids Research, 38 (17). pp. 5623-5633.

All chromosomes must be completely replicated prior to cell division, a requirement that demands the activation of a sufficient number of appropriately distributed DNA replication origins. Here we investigate how the activity of multiple origins on each chromosome is coordinated to ensure successful replication. We present a stochastic model for whole chromosome replication where the dynamics are based upon the parameters of individual origins. Using this model we demonstrate that mean replication time at any given chromosome position is determined collectively by the parameters of all origins. Combining parameter estimation with extensive simulations we show that there is a range of model parameters consistent with mean replication data, emphasising the need for caution in interpreting such data. In contrast, the replicated-fraction at time points through S phase contains more information than mean replication time data and allowed us to use our model to uniquely estimate many origin parameters. These estimated parameters enable us to make a number of predictions that showed agreement with independent experimental data, confirming that our model has predictive power. In summary, we demonstrate that a stochastic model can recapitulate experimental observations, including those that might be interpreted as deterministic such as ordered origin activation times.
DDDT_A_255607 2841..2851

Department of Pharmacology and Toxicology, College of Pharmacy, University of Sulaimani, Sulaimani, Kurdistan Region, Iraq Objective: The present study was designed to evaluate the anti-inflammatory effects of different doses of aliskiren in two animal models of inflammation. Methodology: Sixty-six Wistar rats were allocated into five groups: the first group (six rats) was treated with the vehicle only, without induction of paw edema and granulomatous inflammation, and served as a negative control; the second group (12 rats) was allocated into two subgroups and treated with the vehicle only, with induction of paw edema and granulomatous inflammation, and served as a positive control; the third group (36 rats) was allocated into six subgroups and treated with different doses of aliskiren (15, 30, and 60mg/kg) in both models; the fourth group (12 rats) was treated with dexamethasone (1 mg/kg) in both models of inflammation. Serum concentrations of tumor necrosis factor-α (TNF-α), interleukin-10 (IL-10), vascular cell adhesion molecule-1 (VCAM-1), and high sensitivity C-reactive protein (hs-CRP) were measured. Skin samples were also sent for histopathological examination. Results: Aliskiren, in a dose-dependent pattern, significantly decreased inflammation in rat models of inflammation, by attenuating the percentage of exudate, granuloma, and paw edema. Furthermore, it significantly reduced serum concentrations of TNF-α, VCAM-1, and hs-CRP and restored the serum concentration of IL-10. Additionally, significant improvement was seen in the histopathological findings. Conclusion: In the current study, aliskiren was successful in decreasing inflammation in both models. These findings suggest that aliskiren is a good candidate for the treatment of inflammatory diseases.
Blowfish Hybridized Weighted Attribute-Based Encryption for Secure and Efficient Data Collaboration in Cloud Computing

: Cloud computing plays a major role in sharing data and resources to other devices through data outsourcing. During sharing resources, it is a challenging task to provide access control and secure write operations. The main issue is to provide secure read and write operations collaboratively and to reduce computational overload by effective key management. In this paper, a secure and an efﬁcient data collaboration scheme blowﬁsh hybridized weighted attribute-based Encryption (BH-WABE ) for secure data writing and proﬁcient access control has been proposed. Here, weight is assigned to each attribute based on its importance and data are encrypted using access control policies. The cloud service provider stores the outsourced data and an attribute authority revokes or updates the attributes by assigning different attributes based on the weight. The receiver can access the data ﬁle corresponding to its weight in order to reduce the computational overload. The proposed BH-WABE provides collusion resistance, multiauthority security and ﬁne-grained access control in terms of security, reliability, and efﬁciency. The performance is compared with the conventional hybrid attribute-based encryption (HABE) scheme in terms data
CPU-friendly Tracking in Wireless Sensor Networks

—The problem of tracking multiple targets using Sequential Monte Carlo technique under the framework of Bayesian techniques for wireless sensor networks is discussed. Distributed filtering in wireless sensor networks is an active area of research owing to the high communication costs of centralized tracking. However, distributed filtering must carefully address the conflict between high correlation among signals picked up by neighboring sensors and detached sensing by far away nodes due to limited sensing radii. Further challenges relate to the processing and communication of large number of particles in resource-constrained sensor nodes. This paper proposes a novel integrated approach to network management and target tracking by which distributed tracking is achieved in a lightweight manner. Important contributions are ‘Consensus Tracking’ as a low-cost distributed solution for sensor tasking and ‘Multitiling’ as computationally efficient solution for managing and propagating particles.