Miracle-dz/UniFAR-FTUs huggingface dataset:
An Active Equalization Method for Lithium-ion Batteries Based on Flyback Transformer and Variable Step Size Generalized Predictive Control

The inconsistency in large-scale battery pack significantly degrades the performance of electric vehicles. In order to diminish the inconsistency, the study designs an active equalization method comprising of equalizer and equalization strategy for lithium-ion batteries. A bidirectional flyback transformer equalizer (BFTE) is designed and analyzed. The BFTE is controlled by a pulse width modulation (PWM) controller to output designated balancing currents. Under the purpose of shortening equalization time and reducing energy consumption during the equalization process, this paper proposes an equalization strategy based on variable step size generalized predictive control (VSSGPC). The VSSGPC is improved on the generalized predictive control (GPC) by introducing the Step Size Factor. The VSSGPC surmounts the local limitation of GPC by expanding the control and output horizons to the global equalization process without increasing computation owing to the Step Size Factor. The experiment results in static operating condition indicate that the equalization time and energy consumption are reduced by 8.3% and 16.5%, respectively. Further validation in CC-CV and EUDC operating conditions verifies the performance of the equalizer and rationality of the VSSGPC strategy.
Estimator Nadaraya-Watson dengan Pendekatan Cross Validation dan Generalized Cross Validation untuk Mengestimasi Produksi Jagung

Nadaraya-Watson Estimator with kernel approach depends on two-parameter, those are kernel function and bandwidth choice. However, between the two of them, bandwidth choice gave a huge impact on the result of the estimation. By minimizing the value of Mean Square Error (MSE), Cross-Validation (CV) and Generalized Cross-Validation (GCV) gave the optimal bandwidth value. In this research, corn production was considered as the dependent variable, while the planted area, harvested area, and the fertilizer as the independent variable. The result of this research showed that Nadaraya-Watson Estimator with Generalized Cross-Validation gives a better corn production estimation with optimal bandwidth value 742392,2, with and with MSE 202583,9. Keywords : kernel, estimator Nadaraya-Watson, cross validation, generalized cross validation.
Climate impact and adaptation to heat and drought stress of regional and global wheat production

Wheat (Triticum aestivum) is the most widely grown food crop in the world threatened by future climate change. In this study, we simulated climate change impacts and adaptation strategies for wheat globally using new crop genetic traits (CGT), including increased heat tolerance, early vigor to increase early crop water use, late flowering to reverse an earlier anthesis in warmer conditions, and the combined traits with additional nitrogen (N) fertilizer applications, as an option to maximize genetic gains. These simulations were completed using three wheat crop models and five Global Climate Models (GCM) for RCP 8.5 at mid-century. Crop simulations were compared with country, US state, and US county grain yield and production. Wheat yield and production from high-yielding and low-yielding countries were mostly captured by the model ensemble mean. However, US state and county yields and production were often poorly reproduced, with large variability in the models, which is likely due to poor soil and crop management input data at this scale. Climate change is projected to decrease global wheat production by −1.9% by mid-century. However, the most negative impacts are projected to affect developing countries in tropical regions. The model ensemble mean suggests large negative yield impacts for African and Southern Asian countries where food security is already a problem. Yields are predicted to decline by −15% in African countries and −16% in Southern Asian countries by 2050. Introducing CGT as an adaptation to climate change improved wheat yield in many regions, but due to poor nutrient management, many developing countries only benefited from adaptation from CGT when combined with additional N fertilizer. As growing conditions and the impact from climate change on wheat vary across the globe, region-specific adaptation strategies need to be explored to increase the possible benefits of adaptations to climate change in the future.
FAWA: Fast Adversarial Watermark Attack

Recently, adversarial attacks have shown to lead the state-of-the-art deep neural networks (DNNs) to misclassification. However, most adversarial attacks are generated according to whether they are perceptual to human visual system, measured by geometric metrics such as the <inline-formula><tex-math notation="LaTeX">$\ell _2$</tex-math><alternatives><mml:math><mml:msub><mml:mi>ℓ</mml:mi><mml:mn>2</mml:mn></mml:msub></mml:math><inline-graphic xlink:href="jiang-ieq1-3065172.gif"/></alternatives></inline-formula>-norm, which ignores the common watermarks in cyber-physical systems. In this article, we propose a fast adversarial watermark attack (FAWA) method based on fast differential evolution technique, which optimally superimposes a watermark on an image to fool DNNs. We also attempt to explain the reason why the attack is successful and propose two hypotheses on the vulnerability of DNN classifiers and the influence of the watermark attack on higher-layer features extraction respectively. In addition, we propose two countermeasure methods against FAWA based on random rotation and median filtering respectively. Experimental results show that our method achieves 41.3 percent success rate in fooling VGG-16 and have good transferability. Our approach is also shown to be effective in deceiving deep learning as a service (DLaaS) systems as well as the physical world. The proposed FAWA, hypotheses, and the countermeasure methods, provide a timely help for DNN designers to gain some knowledge of model vulnerability while designing DNN classifiers and related DLaaS applications.
A macroecological perspective on the fluctuations of exploited fish populations

The natural variability of fish populations is increased by exploitation, but the specific mechanisms driving this variability are still debated. We propose a macroscopic approach combining the size-density relationship and Taylor’s law to predict the temporal variance of exploited and unexploited fish populations. Using information from 11 years of fishery-independent abundance surveys, we showed that the body-size dependence of the variance of exploited (targeted) and unexploited (non-targeted or bycatch) fish populations can be accurately predicted. Targeted fish populations showed a variability that was 2 orders of magnitude greater than that of non-targeted fish populations. Such variability was explained solely by the higher relative abundance of the former, regardless of their specific trophic position, while aggregated community fluctuation was lower in a high trophic position group. This study showed the usefulness of the macroscopic approach to predict fish variability and fishing effect in the whole community. This approach is complementary to other modeling strategies and seems to be useful in tackling the problem of variability in population fluctuations of exploited fish, particularly in cases where specific details of the interacting species are lacking.
DETAILED VIEW ON REPURPOSED DRUGS, TRACKING OF VACCINES,AND BRIEF VIEW ON PROPHYLACTIC NANOMEDICINES AS AN ALTERNATIVE APPROACH AND PATIENT CARE FOR COVID-19

In December 2019, a rare case of pneumonia was reported in Wuhan, China. This was later analyzed and known to have similar characteristics as viral pneumonia caused by a novel coronavirus. Later, on 11 February 2020, the World Health Organization (WHO) officially named the disease as COVID19. The Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) ought to taint both the upper respiratory tract and the lower respiratory tract. This COVID-19 is spreading quickly with an immense rise in cases around the world. This infection's mechanism stays obscure, and the medications explicit for the infection were not grown at this point. Infection is highly contagious. Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2) is one of seven kinds of crown infection, including the one which causes severe maladies like Middle East respiratory disorder (MERS) and abrupt, intense respiratory syndrome(SARS). Since its revelation, the infection has spread and has caused anxiety and fear among people. Recent vaccines are tracked, and clinical trials can bring an immediate protocol on a medication approach. By including different therapeutic approaches, it is easier to combat the disease quickly. With very low mortality and high transmission rate, new approaches to vaccines and nanomedicines bring down the spread. Controlled patient care is also crucial. On 11 March, the World Health Organization (WHO) declared the disease as 'global pandemic’. COVID-19, therefore, poses a significant threat to global public health. This article reviews the epidemiology, pathogenesis, and diagnostic methods. The review also focuses on repurposed drugs, traced vaccines, and a quick view of prophylactic nanomedicines as an alternative for COVID 19. For this review, the complete database has been collected from various search engines such as PubMed, ScienceDirect, Scopus, Elsevier, etc., from the year 2001-2020 using the following keywords.
Collision risk assessment in Jiangsu section of the Yangtze River based on evidential reasoning

Collision between ships is one of the dominant types of accidents in the Jiangsu section of the Yangtze River, accounting for over 60% of the accidents. An evidential reasoning (ER) approach is introduced to perform a quantitative assessment of the safety of the whole waterway by dividing it into 17 sub-sections. The Risk Influencing Factors (RIFs) including channel condition, navigation environment and navigation aids conditions are considered and further decomposed into several sub-factors. The expert knowledge is used to quantify the relative importance of the RIFs to the collision risk. The historical data is used to make the Basic Probability Assignments (BPAs) of the belief structures. The hazard index (HI) is used as a measure of collision risk. The results indicate that Kouanzhi Waters and Jiaoshan Waters carry much higher collision risk than other waters, whereas Nanjing Waters and Fanjiafan Waters have the lowest collision risk. The results are useful for the maritime safety management in the Jiangsu section of the Yangtze River.
Vibrio vulnificus Hemolysin Induces TNF-α Independent ROS Production by Primary Murine Macrophages

BackgroundVibrio vulnificus (V. vulnificus) is a gram-negative opportunistic pathogen that causes lethal infections in humans. Vibrio vulnificus hemolysin (VVH) is a key virulence factor that exhibits strong hemolytic and cytolytic activities and contributes to the pathogen's invasion, vasodilatation, and septic shock. Most of the studies so far have focused on VVH's cytolytic activity against cell lines derived from host cells. However, the cytolytic activity of VVH on primary macrophages is still unclear. In addition, although it is known that VVH induces host cell apoptosis via triggering ROS production, the impact of VVH on host immune response has not been fully understood. This study aimed to investigate the role of VVH-induced TNF-α expression and ROS production in the absence of apoptosis of murine primary macrophages and related signaling pathways using FACS, DCFH-DA, real-time PCR, and western blotting. ResultsThe results showed that murine primary macrophages from different organs displayed differential sensitivities towards VVH-induced cell death. Liver Kupffer cells, splenic macrophages, and BMMfs were more sensitive to VVH-induced cytotoxicity, while alveolar macrophages, lung interstitial macrophages, and lung neutrophils were resistant to VVH-induced cell death. Besides, we found that a low dose of VVH, which did not induce apoptosis in murine primary macrophages, could induce apoptosis independent TNF-α expression and ROS generation. Such ROS production in macrophages could be further blocked by inhibiting p38-MAPKs or NFκB activation but was not affected by knockout of TNF-α. ConclusionsVVH produced cytotoxicity in macrophages, an apoptosis-independent TNF-α expression, and ROS production, which provides insight into the mechanism underlying the crosstalk between VVH-induced inflammation and oxidative stress.
Full Energy Management of EO-AAC: Toward a Dynamic Equivalence With MMC

Energy management in modular type converters constitutes a key aspect of their operational stability. This paper introduces a full energy management structure for the Extended Overlap-Alternate Arm Converter (EO-AAC) ensuring both equal energy distribution across all six stacks and the maintaining of ripple-free DC current during steady state. The performance of the control structure against active power step events is validated by detailed simulations using EMTP-RV software. Moreover, the full energy management allows the EO-AAC to have an equivalent controllability to Modular Multilevel Converter (MMC) through only two conducting stacks in overlap mode ensuring the power balance. From this observation, it is demonstrated that the use of control strategy like the virtual capacitor to support HVDC system, originally designed for MMC, is possible. Gathering all these controllers leads to a general conclusion which is the dynamic equivalence between EO-AAC and MMC.
The FIT-MoM Method for Analysis of Electromagnetic Scattering by Bodies-of-Revolution Embedded in Multilayered Media

In this article, the previously introduced finite-integration technique/method-of-moments (FIT-MoM) hybrid method, which is suited for the analysis of electromagnetic scattering by inhomogeneous bodies of revolution (BoRs), is generalized to problems involving multilayered environment. Due to the fact that BoR-typical azimuthal mode decomposition is used, appropriate modal Green’s functions for multilayered media are given. They are responsible for source-field interactions within the region that is external with regard to the FIT part. Formulas for modal decomposition of incident plane wave fields as well as the approximation enabling computing fields produced by sources associated with individual modes in the far-zone are also provided.
Performance of Liver Stiffness Measurement from FibroScan was Affected by Glucose Metabolism in Patients with Nonalcoholic Fatty Liver Disease

Background: The performance of liver stiffness measurement (LSM) obtained using FibroScan can be affected by several factors and cut-off values were different for fibrosis caused by various etiologies. The aim of this study was to evaluate the diagnostic performance of LSM in nonalcoholic fatty liver disease (NAFLD) patients with abnormal glucose metabolism and investigate whether LSM value would be affected by metabolic indicators. Methods: The study involved 91 NAFLD patients with abnormal glucose metabolism who underwent liver biopsy. The receiver operator characteristic (ROC) curves were used to evaluate the diagnostic accuracy, with the biopsy results taken as the gold standard. Multivariate linear regression and subgroup analysis were used to determine the correlated indicators.Results: The areas under ROC curves (AUROCs) of LSM values in diagnosing fibrosis stage≥1, 2, 3 and 4 were 0.793 (95% confidence interval [CI]: 0.695-0.871), 0.764 (95% CI: 0.663-0.846), 0.837 (95% CI: 0.744-0.906) and 0.902 (95% CI: 0.822-0.955), with cut-off values of 6.3, 7.6, 8.3 and 13.8 kPa, respectively. Multivariate linear regression demonstrated that HbA1c (β=0.200, p=0.038) and AST (β=0.200, p=0.044) were independently associated with LSM value after adjustment for fibrosis stage from liver biopsy. Subgroup analysis revealed that LSM values were slightly higher in patients with HbA1c ≥7% than those HbA1c <7%, and in patients with BMI ≥30kg/m2 than those BMI <30kg/m2.Conclusions: FibroScan was valuable for the evaluation of liver fibrosis in NAFLD patients with abnormal glucose metabolism. It was recommended for evaluating severe fibrosis, especially for excluding advanced fibrosis. Glucose metabolism state may affect LSM value.
Construction of Time Invariant Spatially Coupled LDPC Codes Free of Small Trapping Sets

In this paper, we propose a design technique for the construction of variable-regular time-invariant spatially-coupled low-density parity-check (SC-LDPC) codes with small constraint length and low error floor. The proposed technique reduces the error floor by imposing simple constraints on the short cycles in the code’s Tanner graph, which in turn, result in the elimination of the most dominant trapping sets of the code. In some cases, we also derive lower bounds on the syndrome former memory for satisfying such constraints. The designed codes are superior to the state-of-the-art in terms of error floor performance and/or decoding complexity and latency.
A hybrid silicon evanescent quantum dot laser

We report the first demonstration of a hybrid silicon quantum dot (QD) laser, evanescently coupled to a silicon waveguide. InAs/GaAs QD laser structures with thin AlGaAs lower cladding layers were transferred by direct wafer bonding onto silicon waveguides defining cavities with adiabatic taper structures and distributed Bragg reflectors. The laser operates at temperatures up to 115 °C under pulsed current conditions, with a characteristic temperature T0 of 303 K near room temperature. Furthermore, by reducing the width of the GaAs/AlGaAs mesa down to 8 µm, continuous-wave operation is realized at 25 °C.
Factors affecting farmers’ behavior in using nitrogen fertilizers: society vs. farmers’ valuation in southwest Iran

Overapplication of nitrogen (N) has direct and indirect environmental and social impacts, both now and in the future. Therefore, applying N more efficiently is an important goal in many developing countries. The purpose of this study is to understand the factors affecting the intention of nitrogen consumption behavior by farmers in Ramshir county in Khuzestan province (located in southwestern Iran). To this end, we used the extensive normative activation model enriched with the planned behavior model to understand farmers’ behavior. The statistical population for the study included 200 farmers in Ramshir county in Khuzestan province in southwestern Iran. Structural equation modeling revealed that the proposed model predicted 32% and 45% of the variance in intention and behavior, respectively. Personal norms were stronger predictors of intention, whereas attitude and subjective norms had no impact on intention. As fertilizer use continues to increase, imbalanced and unsustainable use of fertilizers and their environmental effects will become a major concern according to the findings. Factors that affect farmers’ decision-making on fertilizer usage need to be studied and better understood in order to establish correct policies on costs, incentives, and future program goals. It is therefore important for policymakers to communicate information to producers through demonstration projects, technical assistance, and educational programs, in order to formulate successful emission control policies. Under a changed political environment, some integration of education and economic benefits could be lower cost and more effective tools to achieve desired conservative environmental goals.
Minimal Expected Time in Drawdown through Investment for an Insurance Diffusion Model

Consider an insurance company whose surplus is modelled by an arithmetic Brownian motion of not necessarily positive drift. Additionally, the insurer has the possibility to invest in a stock modelled by a geometric Brownian motion independent of the surplus. Our key variable is the (absolute) drawdown Δ of the surplus X, defined as the distance to its running maximum X¯. Large, long-lasting drawdowns are unfavourable for the insurance company. We consider the stochastic optimisation problem of minimising the expected time that the drawdown is larger than a positive critical value (weighted by a discounting factor) under investment. A fixed-point argument is used to show that the value function is the unique solution to the Hamilton–Jacobi–Bellman equation related to the problem. It turns out that the optimal investment strategy is given by a piecewise monotone and continuously differentiable function of the current drawdown. Several numerical examples illustrate our findings.
Dynamics of the Universe and the Growth of Structures: Dark side of Special Relativity, Curvature and Space-Time

The special relativity explains how the matter transforms into energy. According to that matter can be generated with negative energy and matter can destroy with negative energy. The negative energy can be identified as dark energy. According to this matter generation, which is the process of black holes, emitting radiation from the quasar is the evidence. Matter generation as radiation matter. Matter destroying is the process of stars. The energy and dark energy get negated in the supernova and nova explosions. Stars emit the light by the speed of light is the evidence of the matter destroying process. The matter creation process makes the universe grow and the matter destroying process makes the universe to shrink, combining this process makes the universe to curvature. Also, matter generation makes the universe expansion power of -ρc 2 and matter destroying make the universe to compression power of ρc 2 . This makes state equation same as the curvature. Therefore k 0 and compression universe results. A black hole formed from anti-matter, which created with the positive matter, and created positive matter(the process of m = E/c 2 ) attract to the black hole make a galaxy. Inflation is the period of the first step of matter generation. Then dark energy got inflationary expansion and positive energy get compression by the speed of light(E/c 2 +(-E)). Created matter makes neutral atoms make the HI region. The matter makes a connection with dark energy make ionized matter and make the HII region. Then nebulas created in the HII region by dark energy and positive matter. Sufficient density of matter and dark energy formed a star and make the process of E= mc 2 and negated in a supernova and nova explosions. The remaining matter creates dwarfs or neutron stars. Remaining dark energy creates pulsars. Therefore special relativity theory of matter generation and matter destroying explain the universe how to origin and evaluation as well as why it is happening. It explains the dynamics of the universe especially expansion and compression and how it is happening. How the power for the universe created by matter generation and matter destroying. It also explains the inflation and collapse of the universe. It explains the universe's constitution of matter, anti-matter, energy, and dark energy. As well as it explains how the universe structures of galaxies and stellar and how those are evolved. Therefor ultimate fate describes by matter generation and matter destroying is nothing, expanding, flat, compression, nothing, and yet another universe to begin again. Also, universe dynamics consist of complex scale factors. If the scale factor is real, then expansion related to the positive matter. If the scale factor is complex, then expansion related to the negative matter.