Miracle-dz/UniFAR-FTUs huggingface dataset:
Minimum Backflow Power and ZVS Design for Dual-Active-Bridge DC–DC Converters

Significant improvement in the power efficiency of dual-active-bridge dc–dc converters can be achieved by implementing zero voltage switching (ZVS) which is facilitated by a negative switch current at the switching instant. Such negative current, however, causes undesirable backflow power that counteracts the efficiency gain. Thus, the conditions for achieving ZVS and maintaining minimum backflow power (MBP) are often conflicting. A design that implements ZVS and MBP simultaneously is, thus, desirable. While, existing research is short of exploring the accurate condition of MBP and ZVS. This work fully considers the influence of output capacitance of power switches on ZVS and tries to implement ZVS and MBP of a dual-active-bridge dc–dc converter by controlling the inductor current to a minimum value at the turn-off instant of a power switch. The expression of the minimum switching current for ZVS and MBP is first derived by considering the resonant transient process in dead time. The transmission power range with ZVS and MBP can be maximized by selecting appropriate voltage conversion ratio according to different values of minimum current. An optimal extended phase-shift control for enlarging the operating region for ZVS and MBP of a dual-active-bridge dc–dc converter is designed. The optimization method is experimentally verified.
PENERAPAN STRATEGI GREEN MARKETING DI TENGAH PANDEMI COVID-19

Perusahaan yang menerapkan green marketing sebagai strategi pemasarannya, dianggap lebih mudah dalam membangun citra positif perusahaan. Terlebih ketika perusahaan yang menerapkan green marketing adalah perusahaan dengan produk yang dipasarkan di pasar internasional. Tujuan penelitian ini adalah untuk mengetahui bagaimana penerapan green marketing pada UMKM di era pandemi covid-19 beserta dampaknya. Penelitian ini sekaligus bertujuan relevansinya penerapan green marketing sebagai alat pemasaran dalam situasi bisnis yang tidak pasti karena pandemi Covid-19. Jenis penelitian ini adalah penelitian deskriptif dengan pendekatan kualitatif. Implementasi strategi green marketing membutuhkan pendekatan fundamental, komprehensif dan terintegrasi dalam semua aspek fungsional pemasaran, termasuk bauran pemasaran secara keseluruhan, seperti desain produk, harga, lokasi dan promosi.
Far-Field Radiation Characteristics of Folded Monopole Antennas over a Conducting Ground Plane

Folded monopole structures have been used for many applications, including low-frequency electromagnetic wave transmission and reception. However, the literature on these antenna types is quite limited. Folded monopole antennas are mathematically complex compared to conventional monopole or dipole antennas since every fold introduces a new set of design parameters. This work studied the far-field radiation characteristics of multi-folded monopole antennas operating at 75 MHz in terms of their radiated power concerning the frequency, the far-field directivity of the electric field, and the effect of each design parameter on the far-field radiation power. According to the results, folding a monopole antenna multiple times increases its effective length, making this antenna a suitable candidate for applications where the antenna height is restricted. Additionally, the ground-to-wire separation has the biggest effect on radiated power. In both single-fold and two-fold cases, doubling the ground-to-wire separation increased the radiated power by 0.2 W compared to the other models with the same number of folds. As for the challenges, the impedance mismatch between the source and antenna causes a significant amount of power reflection; hence, suitable impedance matching is required to reduce reflected power.
Double-spiral terahertz tunable metasurface based on nano-printing technology

Electromagnetic devices made of artificially constructed metasurfaces can achieve filtering, modulation, sensing, and detection functions in the terahertz frequency band, which is essential for the application of terahertz waves in the fields of communication and imaging. We designed and prepared a flexible and transparent double helix metasurface based on nano-printing technology, and used the metasurface to construct a rotating tunable filter, which can achieve regular tuning of the terahertz wave transmittance by rotating the metasurface. After rotating by 90°, the transmittance at 0.52THz increased from 8% to 67%, and the transmittance at 0.92THz decreased from 68% to 3%, realizing active tuning with modulation depth greater than 88%. Moreover, the proposed Nano-printing metasurfaces have excellent properties of ultra-thinness, flexibility, and visible light transparency, which is conducive to the miniaturization, light-weight and large-area preparation of terahertz tunable devices.
Naturalizing Semantics? Beyond <i>Cognitive Neuro-Reductionism</i>: From Varela’s <i>Systemic Cognitive Neuroscience</i> to <i>Complex Realism Sociology</i>

Is it possible to naturalize semantics? Starting from Libet’s 1983 studies, current research developments in neuronal bases of behavior reduce the mind to the brain, with significant implications in reference to issues of free will, imputability and individual behavioral responsibility. However, many criticisms can be made at this approach. This paper shows the limits of Cognitive Neuro-reductionism, especially in the light of Varela’s Systemic Cognitive Neuroscience or Neurophenomenology and the current theoretical revision process of social systems as complex—dynamical, emergent and unpredictable—social systems, or Complex Realism Sociology. Here, there is an agreement point. The conception of living systems as complex system as well as that of social system as complex systems acknowledge the autonomy of human reflexivity capability and free will be able to initiate the chain of events that triggers the process of adaptation to environment and change and social emergence ones, and, in so doing, problematize a neuro-reductionist determinism of cognitive life and behavioral processes, with its dilemmatic consequences on individual social responsibility and, ultimately, on social order possibilities. This being stated, this paper reflects on dialogue possibilities between Varela’s neuroscientific revolution and Complex Realism Sociology. Going beyond the Parsonsian functionalism’s social homeostasis and maintaining the point firm of social emergence and relationship between reflexivity and social morphogenesis, Complex Realism Sociology can dialogue well with Varela’s Neurophenomenology. Lieb’s disciplined analysis shows to be a fruitful ground for interlocution about the understanding of that Organism which cannot be liquidated but must be reinterpreted in its function, about the understanding of neuronal circuits that mediate free will and intersubjectivity, conscious deHow to cite this paper: Condorelli, R. (2022). Naturalizing Semantics? Beyond Cognitive Neuro-Reductionism: From Varela’s Systemic Cognitive Neuroscience to Complex Realism Sociology. Sociology Mind, 12, 29-57. https://doi.org/10.4236/sm.2022. 122003 Received: January 14, 2022 Accepted: March 4, 2022 Published: March 7, 2022 Copyright © 2022 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/
Sliding Mode PWM-Direct Torque Controlled Induction Motor Drive with Kalman Filtration of Estimated Load

The paper presents an application of sliding mode controller and Kalman Filter (KFSMC) in speed control of pulse-width-modulation direct torque controlled induction motor drive. The performance of the direct torque control (DTC) is degraded by the uncertainty of stator resistance. In order to increase the robustness of the controlled system to the uncertainty, a sliding mode controller (SMC) is utilized to replace the proportional-integral (PI) speed controller in the conventional DTC drive structure. Computation of SMC requires estimation of load, and Kalman Filter is integrated to reduce noise in load estimation and chattering phenomenon in speed response. Simulations are carried out at different reference speeds in a wide range of noises of stator resistance. Indices including ITAE, settling time, overshoot, and undershoot are employed to compare the performance of drive structures. Results confirmed the desired characteristics of the proposed drive structure.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.
A Trust-Based Intrusion Detection System for RPL Networks: Detecting a Combination of Rank and Blackhole Attacks

Routing attacks are a major security issue for Internet of Things (IoT) networks utilising routing protocols, as malicious actors can overwhelm resource-constrained devices with denial-of-service (DoS) attacks, notably rank and blackhole attacks. In this work, we study the impact of the combination of rank and blackhole attacks in the IPv6 routing protocol for low-power and lossy (RPL) networks, and we propose a new security framework for RPL-based IoT networks (SRF-IoT). The framework includes a trust-based mechanism that detects and isolates malicious attackers with the help of an external intrusion detection system (IDS). Both SRF-IoT and IDS are implemented in the Contiki-NG operating system. Evaluation of the proposed framework is based on simulations using the Whitefield framework that combines both the Contiki-NG and the NS-3 simulator. Analysis of the simulations of the scenarios under active attacks showed the effectiveness of deploying SRF-IoT with 92.8% packet delivery ratio (PDR), a five-fold reduction in the number of packets dropped, and a three-fold decrease in the number of parent switches in comparison with the scenario without SRF-IoT. Moreover, the packet overhead introduced by SRF-IoT in attack scenarios is minimal at less than 2%. Obtained results suggest that the SRF-IoT framework is an efficient and promising solution that combines trust-based and IDS-based approaches to protect IoT networks against routing attacks. In addition, our solution works by deploying a watchdog mechanism on detector nodes only, leaving unaffected the operation of existing smart devices.
Ion Release and Surface Changes of Nickel–Titanium Archwires Induced by Changes in the pH Value of the Saliva—Significance for Human Health Risk Assessment

The aim of this study was to explore whether changes in the salivary pH influence mechanical properties, surface roughness, and ion release from NiTi archwires with various surface coatings, and discuss the clinical significance of the findings. The uncoated, rhodium-coated, and nitrified NiTi wires were immersed into artificial saliva of different pH values (4.8, 5.1, 5.5, and 6.6). Released nickel and titanium ions were measured with inductively coupled plasma-optical emission spectroscopy at the end of 28 days. Atomic force microscopy was used to measure the arithmetic average surface roughness Ra, the root-mean-square roughness Rq, and the maximum height of the asperities RZ. The nanoindentation hardness (HIT) and Young’s modulus (EIT) measurements were performed. The change in the pH of artificial saliva is inversely proportional to the release of titanium from both coated and uncoated wires, and the release of nickel from uncoated wires. The surface roughness parameters of both coated and uncoated wires are unaffected by the change in the pH of artificial saliva. The change in the pH of saliva has minor influence on the hardness and Young’s modulus of elasticity of both coated and uncoated wires. The concentration of released metal ions measured was below the recommended upper limit for daily intake; nevertheless, hypersensitivity effects cannot be excluded, even at lower concentrations and at low pH.
Effects of swimming environment on bacterial motility

Swimming trajectories of bacteria can be altered by environmental conditions, such as background flow and physical barriers, that limit the free swimming of bacteria. We present a comprehensive model of a bacterium that consists of a rod-shaped cell body and a flagellum which is composed of a motor, a hook, and a filament. The elastic flagellum is modeled based on the Kirchhoff rod theory, the cell body is considered to be a rigid body, and the hydrodynamic interaction of a bacterium near a wall is described by regularized Stokeslet formulation combined with the image system. We consider three environmental conditions: (1) a rigid surface is placed horizontally and there is no shear flow, (2) a shear fluid flow is present and the bacterium is near the rigid surface, and (3) while the bacterium is near the rigid surface and is under shear flow, an additional sidewall which is perpendicular to the rigid surface is placed. Each environmental state modifies the swimming behavior. For the first condition, there are two modes of motility, trap and escape, whether the bacterium stays near the surface or moves away from the surface as we vary the physical and geometrical properties of the model bacterium. For the second condition, there exists a threshold of shear rate that classifies the motion into two types of paths in which the bacterium takes either a periodic coil trajectory or a linear trajectory. For the last condition, the bacterium takes upstream motility along the sidewall for lower shear rates and downstream motility for larger shear flow rates.
BACKGROUND RECONSTRUCTION AND OBJECT EXTRACTION BASED ON COLOR AND OBJECT TRACKING

In YCbCr colorspace, a method is proposed to reconstruct the background and extract moving objects based on the Gaussian model of chroma components. Background model is updated according to changes of chroma components. In order to eliminate the disturbance of shadow, a shadow detecting principle is proposed in YCbCr colorspace. A Kalman filter is introduced to estimate objects' positions in the image and then the pedestrian is tracked according to its information of shape. Experiments show that the background reconstruction and updating are successful, object extraction and shadow suppression are satisfactory, and real-time and reliable tracking is realized.
A Comparative Analysis of Rural versus Urban Preschool Children's Sugar-Sweetened Beverage Consumption, Body Mass Index and Parent's Weight Status

Background Childhood overweight and obesity continues to be a major public health concern, especially in minority, low-income, and rural populations. In order to develop health promotion interventions aimed at reducing obesity rates, there is a need to identify which populations have the highest rates of obesity and the risk factors associated with these high rates. Methods Data collected from low-income, preschool children and their parents in an urban community and a rural community in Alabama were analyzed and compared. Body Mass Index (BMI) was collected during school based health screenings, and information regarding parent's BMI and child's consumption of sugar-sweetened beverages (SSBs) were collected by parent report. Results Of the 363 children screened, 12.8% (15.2% rural and 11.9% urban) were considered overweight, and 15.8% (20.2% rural and 14.2% urban) of the sample was classified as obese. Rates of overweight and obesity for mothers were 27.6% (25.3% rural and 28.4% urban) and 48% (56.3% rural and 44.8% urban) respectively and 39.6% (53.3% rural and 34.4% urban) and 34.6% (28.3% rural and 36.9% urban) for fathers. Parents reported their child consumed 3.82 SSBs per day. Overall, mother's BMI, father's BMI and sugar-sweetened beverage consumption was positively associated with child's BMI. However, there were no significant interactions between the rural and urban groups. Conclusion Rates of overweight and obesity remain high in low-income, predominantly minority preschool children and their parents in two communities in Alabama. Consumption of SSBs, mother's BMI, and father's BMI are three factors impacting the weight status of low-income preschool children. These factors are significant in both rural and urban children.
Acceleration Enhanced Unscented Kalman Filter Algorithm and Its Applications on Unmanned Surface Vehicles

High-performance control of unmanned surface vehicle(USV) trajectory tracking requires the systems to obtain motion state and uncertainty with high precision.However,the lack of direct highly precise measuring methods and the strong nonlinearity and coupling make it difficult to obtain the information needed.As to solve this problem,a kind of novel estimation algorithm is proposed,which combines singular value decomposition unscented Kalman filter(SVDUKF) with acceleration measurement together.SVDUKF is an improved algorithm of unscented Kalman filter(UKF) with wider application conditions.In addition,its main advantage lies in binding the ability of UKF to deal the strong nonlinearity with the feather of acceleration with much disturbance information to simplify the system estimation model so that it becomes an online estimation algorithm with higher precision and lower calculation complexity.The nonlinear model of USV is derived,and the model simplification idea of acceleration and the basic steps of SVDUKF are introduced.The advantages in estimation accuracy and computation efficiency of the proposed algorithm are verified.
Plant functional diversity influences water and carbon fluxes and their use efficiencies in native and disturbed dryland ecosystems

Vegetation is changing rapidly in dryland ecosystems, but critical gaps remain in understanding the long‐term fluxes of carbon (C) and water. We used 6 years of data from two adjacent eddy covariance sites in the Sonoran Desert, a species‐rich woody C3 native shrubland and a species‐poor C4 shrubland converted to buffelgrass savanna. Although emphasis has been given to the physical determinants of productivity in dryland ecosystems, we assessed how PFTs changes influenced (1) water and C fluxes and (2) water‐use (WUEe) and intrinsic C‐use efficiencies (CUEei) in the two sites under the same climatological conditions. We hypothesized that changes in PFTs would alter accessibility, rate and use efficiencies of water and carbon, with poorly known effects on the long‐term fluxes and efficiencies. Annual net ecosystem productivity (NEP) in the shrubland was a C‐source in drier years and a sink in others. However, longer C uptake, greater WUEe and lower CUEei were the crucial drivers for higher and positive NEP (C sink) in the savanna. Annual and seasonal WUEe and CUEei discrepancies indicated the importance of dominant PFTs after disturbance and ecohydrological feedbacks. As the world becomes drier and vegetation disturbance more common, the role of PFT changes should contribute to gaining a clearer understanding of their role in the C and water fluxes of dryland ecosystems.
Serum gamma-glutamyl transpeptidase-to-platelet ratio (GPR) can predict the prognosis of hepatocellular carcinoma: a meta-analysis and systematic review

Background The relationship between serum gamma-glutamyl transpeptidase-to-platelet ratio (GPR) before treatment and the prognosis of patients with hepatocellular carcinoma (HCC) is unclear. Here, we review and summarize existing data and try to determine the predictive value of GPR in the treatment of HCC. Methods We searched Web of Science, PubMed, Embase and China national knowledge infrastructure (CNKI) for clinical trials investigating GPR and HCC in participants with and without HCC. We developed the inclusion criteria based on the principle of population-intervention-result-control-study design. Studies that do not meet the standards were excluded. Studies were subjected to quality assessments using the Cochrane Risk of Bias Tool for cluster-randomized control trials. Sensitivity, statistical, heterogeneity, and publication bias analyses on STATA version 16.1 (STATA 2020). Results The pooled data from 7 studies of 1,952 patients showed that the specificity of GPR for predicting the prognosis of HCC was 0.67 (95% CI: 0.61–0.73), and the sensitivity was 0.62 (95% CI: 0.57–0.67). The Fagan chart prediction shows that the patient’s GPR indicates the prognostic effect of HCC. The positive predictive value is 32%, which is significantly higher than before. The ROC curve is used to analyze the effectiveness of GPR in predicting the prognosis of HCC, and the area under the curve (AUC) is 0.69 (0.65–0.73). There is no publication bias in this study (The Deek funnel chart, P=0.48). Discussion Our results are similar to those of most previous studies, and meta-analysis showed that GPR has well sensitivity, accuracy, and prognostic value in HCC.
An ECOSVS-based support vector machine for network anomaly detection

: In this paper, the support vector machine (SVM) classification technique to classify normal and attack traffic in the Spark distributed environment has been introduced and evaluated. In terms of classification speed, SVM suffers from the important shortcomings of high time and memory training complexities, which depend on the training set size. The authors have proposed an effective correlation-based support vector selection (ECOSVS) algorithm for SVM speed optimisation. ECOSVS-based SVM performed better when compared with the other three supervised classifiers, namely, logistic regression (LR), decision tree (DT), and random forest (RF) in terms of accuracy and training time. Apache Spark’s RDD structure has been used for the detection of network-based anomalies. The analysis of the said algorithm was performed on two publicly available network datasets, namely, Network Security Laboratory-Knowledge Discovery in Databases (NSL-KDD) dataset and Coburg Intrusion Detection Datasets (CIDDS-2017). The results showed that our proposed algorithm reduced the training set size of NSL-KDD and CIDDS-2017 datasets to 99.3% and 85%, respectively. Accuracies of 80% and 87% for the ECOSVS-based SVM classifier were achieved.
Modular Single-Stage Three-Phase Flyback Differential Inverter for Medium/High-Power Grid Integrated Applications

This paper proposes a single-stage three-phase modular flyback differential inverter (MFBDI) for medium/high power solar PV grid-integrated applications. The proposed inverter structure consists of parallel modules of flyback DC-DC converters based on the required power level. The MFBDI offers many features for renewable energy applications, such as reduced components, single-stage power processing, high-power density, voltage-boosting property, improved footprint, flexibility with modular extension capability, and galvanic isolation. The proposed inverter has been modelled, designed, and scaled up to the required application rating. A new mathematical model of the proposed MFBDI is presented and analyzed with a time-varying duty-cycle, wide-range of frequency variation, and power balancing in order to display its grid current harmonic orders for grid-tied applications. In addition, an LPF-based harmonic compensation strategy is used for second-order harmonic component (SOHC) compensation. With the help of the compensation technique, the grid current THD is reduced from 36% to 4.6% by diminishing the SOHC from 51% to 0.8%. Moreover, the SOHC compensation technique eliminates third-order harmonic components from the DC input current. In addition, a 15% parameters mismatch has been applied between the flyback parallel modules to confirm the modular operation of the proposed MFBDI under modules divergence. In addition, SiC MOSFETs are used for inverter switches implementation, which decrease the inverter switching losses at high-switching frequency. The proposed MFBDI is verified by using three flyback parallel modules/phase using PSIM/Simulink software, with a rating of 5 kW, 200 V, and 50 kHz switching frequency, as well as experimental environments.