Miracle-dz/UniFAR-FTUs huggingface dataset:
Is Human Culture Locked by Evolution?

Human culture has evolved for thousands of years and thrived in the era of Internet. Due to the availability of big data, we could do research on human culture by analyzing its representation such as user item rating values on websites like MovieLens and Douban. Industrial workers have applied recommender systems in big data to predict user behavior and promote web traffic. In this paper, we analyze the social impact of an algorithm named ZeroMat to show that human culture is locked into a state where individual's cultural taste is predictable at high precision without historic data. We also provide solutions to this problem and interpretation of current Chinese government's regulations and policies.
Enhanced DFT-Based Controller for Selective Harmonic Compensation in Active Power Filters

Among the various selective harmonic current controllers, the traditional repetitive-based discrete Fourier transform controller (DFTRC) is increasingly favored thanks to its unique merits of excellent selectivity and simplicity. However, the traditional approach suffers from disadvantages like slow dynamic responses, defective control structure, and sensitivity to frequency fluctuation. In order to alleviate aforementioned shortcomings, an enhanced discrete Fourier transform-based controller is proposed. The proposed controller is based on the generalized discrete Fourier transform to improve the overall control performances of dynamic responses, structure flexibility, and control robustness. The proposed controller provides individual positive-feedback path and gain coefficient for each harmonic component. Therefore, it not only maintains the advantage of excellent selectivity but also realizes the individual control parameters tuning for each harmonic frequency, which is impossible in traditional DFTRC owing to the congenital defects of control structure. In addition, a correction function is embedded in the forward path to provide the overall phase compensation and correct the plant for better characteristic. The Lagrange interpolation method is adopted to realize the fractional-order delay and its adaption to frequency variations with fixed sampling frequency. Detailed mathematical model along with optimized design principle is given to make full use of the advantages of the enhanced control structure. Extensive experimental results validate the effectiveness of the theoretical analysis and the improvement achieved by the proposed controller.
Spray drift evaluation with point clouds data of 3D LiDAR as a potential alternative to the sampling method

Spray drift is an inescapable consequence of agricultural plant protection operation, which has always been one of the major concerns in the spray application industry. Spray drift evaluation is essential to provide a basis for the rational selection of spray technique and working surroundings. Nowadays, conventional sampling methods with passive collectors used in drift evaluation are complex, time-consuming, and labor-intensive. The aim of this paper is to present a method to evaluate spray drift based on 3D LiDAR sensor and to test the feasibility of alternatives to passive collectors. Firstly, a drift measurement algorithm was established based on point clouds data of 3D LiDAR. Wind tunnel tests included three types of agricultural nozzles, three pressure settings, and five wind speed settings were conducted. LiDAR sensor and passive collectors (polyethylene lines) were placed downwind from the nozzle to measure drift droplets in a vertical plane. Drift deposition volume on each line and the number of LiDAR droplet points in the corresponding height of the collecting line were calculated, and the influencing factors of this new method were analyzed. The results show that 3D LiDAR measurements provide a rich spatial information, such as the height and width of the drift droplet distribution, etc. High coefficients of determination (R2 > 0.75) were observed for drift points measured by 3D LiDAR compared to the deposition volume captured by passive collectors, and the anti-drift IDK12002 nozzle at 0.2 MPa spray pressure has the largest R2 value, which is 0.9583. Drift assessment with 3D LiDAR is sensitive to droplet density or drift mass in space and nozzle initial droplet spectrum; in general, larger droplet density or drift mass and smaller droplet size are not conducive to LiDAR detection, while the appropriate threshold range still needs further study. This study demonstrates that 3D LiDAR has the potential to be used as an alternative tool for rapid assessment of spray drift.
New Evidence on the Relative Scholarly Productivity of Male versus Female Political Scientists

ABSTRACT Considerable research finds that male political scientists publish more research on average than do female political scientists. Yet the reasons for this difference are not entirely clear. Those findings may also overestimate the relative productivity of men because they do not account for the longer time that more men have been in the profession and thus have been publishing longer than women. For a prominent survey dataset of political scientists, we demonstrate notable cohort differences in the research productivity of both men and women across time. Our results also indicate that the overall greater productivity of men results in part from senior women scholars not generally enjoying the same benefits of long tenure on their research output as men do.
The Role of Branched-Chain Amino Acids and Branched-Chain α-Keto Acid Dehydrogenase Kinase in Metabolic Disorders

Branched-chain amino acids (BCAAs), composed of leucine, isoleucine, and valine, are important essential amino acids in human physiology. Decades of studies have revealed their roles in protein synthesis, regulating neurotransmitter synthesis, and the mechanistic target of rapamycin (mTOR). BCAAs are found to be related to many metabolic disorders, such as insulin resistance, obesity, and heart failure. Also, many diseases are related to the alteration of the BCAA catabolism enzyme branched-chain α-keto acid dehydrogenase kinase (BCKDK), including maple syrup urine disease, human autism with epilepsy, and so on. In this review, diseases and the corresponding therapies are discussed after the introduction of the catabolism and detection methods of BCAAs and BCKDK. Also, the interaction between microbiota and BCAAs is highlighted.
Posttraumatic Stress Disorder Mediates the Association between Traumatic World Trade Center Dust Cloud Exposure and Ongoing Systemic Inflammation in Community Members

Exposure to World Trade Center (WTC) dust/fumes and traumas on 11 September 2001 has been reported as a risk factor for post-traumatic stress disorder (PTSD) and other mental/physical health symptoms in WTC-affected populations. Increased systemic inflammation and oxidative stress from the exposure and subsequent illnesses have been proposed as contributors to the underlying biological processes. Many blood-based biomarkers of systemic inflammation, including C-reactive protein (CRP), are useful for non-invasive diagnostic and monitoring of disease process, and also potential targets for therapeutic interventions. Twenty years after 9/11, however, the relationships between WTC exposure, chronic PTSD, and systemic inflammation are only beginning to be systematically investigated in the WTC-affected civilian population despite the fact that symptoms of PTSD and systemic inflammation are still common and persistent. This paper aims to address this knowledge gap, using enrollees of the WTC Environmental Health Center (EHC), a federally designated treatment and surveillance program for community members (WTC Survivors) exposed to the 9/11 terrorist attack. We conducted a mediation analysis to investigate the association between acute WTC dust cloud traumatic exposure (WDCTE) on 9/11, chronic PTSD symptoms, and levels of systemic inflammation. The data indicate that the chronic PTSD symptoms and some specific symptom clusters of PTSD significantly mediate the WDCTE on systemic inflammation, as reflected by the CRP levels. As both chronic PTSD and systemic inflammation are long-term risk factors for neurodegeneration and cognitive decline, further research on the implications of this finding is warranted.
Hopf-Galois extensions for monoidal Hom-Hopf algebras

We investigate the theory of Hopf-Galois extensions for monoidal Hom-Hopf algebras. As the main result of this paper, we prove the Schneider's affineness theorems in the case of monoidal Hom-Hopf algebras in terms of the theory of the total integral and Hom-Hopf Galois extensions. In addition, we obtain the affineness criterion for relative Hom-Hopf module associated with faithfully flat Hom-Hopf Galois extensions.
Injury, alcohol, and drug use in an emergency department in Mexico City

ABSTRACT Background There is no prior study in Mexico reporting on the 6-h prevalence and risk of drug use among injured patients attending an Emergency Department (ED). Methods We report here on a sample of 705 adult patients, admitted to the ED of a public hospital in Mexico City (January and February 2002). Patients reported on alcohol and drug use (amphetamines, tranquilizers, marihuana, cocaine, cocaine–crack, hallucinogens, inhalants, heroin, and others) during the last 12 months, within the 6 h prior to the injury and for the day prior to the injury, the same day the week prior and the same day the last month. Results Drug use was not just infrequently reported immediately before the injury but was less frequently reported in that period than in any other control period. Co-occurrence of drug use and alcohol was not common and did not increase the risk of an injury. Sole use of alcohol was a strong risk factor, while sole use of drugs decreased the risk of injury. Conclusions It is not apparent why drug use alone reduces the risk of an injury. Studies focusing on a single cause of injuries with larger samples to study the differential effects of specific drugs are needed.
Single Shot Dual Wavelength Polarised Interferometer

In this paper we present a single-shot Dualwavelength Polarised Interferometer (DPI) for measuring micro/nano-scale structured surfaces. The two wavelength interferometer is combined with a polarisation phase shift method to extend the 2π ambiguity range without any mechanical movement, enabling a single-shot approach to freeze any unwanted environmental disturbances. The measurement results of using cross grating of 200 nm, 500 nm, and 1200 nm depth is presented. A measurement of 40 nm step height also is presented. The system has the potential to be used for measuring moving surfaces with the measuring range being limited by synthetic wavelength. Keywords— polarised interferometry, two-wavelength, singleshot
High-Gain Luneburg Lens on COC Substrate for 300-GHz Applications

A Luneburg lens quasi-optical beam-former is used to excite a leaky-wave antenna at 275 GHz. Both the lens and the antenna are fabricated on a Cyclic Olefin Copolymer (COC) substrate. The full system is etched on the polymer by photolithography. Numerical results show a reflection coefficient lower than −24 dB and a gain higher than 21 dBi over a 40% fractional bandwidth, spanning from 220 GHz to 330 GHz. The efficiency of the antenna is estimated to be 28% at the center frequency (275 GHz).
A strategy for intentional islanding of distribution networks based on node electrical relevance and artificial bee colony algorithm

Intentional islanding is an effective approach to avoid large‐area blackouts and minimize outage losses through making full use of renewable energy sources. This paper proposes a novel strategy based on node electrical relevance and artificial bee colony algorithm. The node electrical relevance is defined with equivalent electrical distance and traditional line weight, which can reflect the electrical characteristics of power systems, differentiating the proposed strategy from most existing strategies which are based on graph theory. The artificial bee colony (ABC) algorithm employed has fewer control parameters, strong robustness, and high accuracy; therefore, more loads can be incorporated into islands and restored. The constraints of load priority, load controllability, line capacity, and stable operation requirements of power systems are considered to tally with the actual distribution networks. The strategy is tested using the IEEE 69‐bus distribution system and compared with other strategies from the literature. The simulation results demonstrate that the proposed strategy is more feasible and efficient. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Shielding the magnetic field of wireless power transfer system using zero‐permeability metamaterial

The wireless power transfer (WPT) has attracted considerable attention due to its convenience and reliability. However, the electromagnetic leakage of WPT can be harmful to humans and environment. In order to meet safety requirements, electromagnetic leakage to the nearby transmission channel should be controlled below a certain level. Beyond ferrite and metallic shields, several researchers have proposed mu-near-zero metamaterial (MNZ MM). However, little work researches the application of MNZ MM in four-coil WPT systems. Here, the authors propose an optimised MNZ MM for shielding leaked electromagnetic field. Next, the authors setup a miniaturised WPT system loaded with MNZ slab at 13.56 MHz. It can serve as a frequency selector that reflected a specified frequency of 13.56 MHz, while allowing all other frequencies to pass undisturbed. As a result, the transmission efficiency is dramatically reduced at a 30 cm distance. The magnetic field magnitude of the receiver has been decreased. Obviously, the proposed MNZ MM has good performance in magnetic field shielding for WPT systems.
Effect of genotype and NPK fertilizer on seedlings of Arabica coffee and its genetic variability

Genetic make-up and maintenance of seedlings are influencing factors for cultivation of arabica coffee. The goal of this experiment was to study the effect of genotypes of arabica coffee and NPK fertilizer on seedlings performance and genetic variability of seedlings. A factorial experiment with randomized complete block design with three replications was conducted at experimental garden of Agriculture Faculty of Universitas HKBP Nommensen in Medan. Thirtytwo genotypes of arabica coffee and four levels of NPK fertilizer was tested. The result revealed that genotype differences were highly significant in plant height, the age at which the cotyledons open, and phenotype ratios. Genotype G3 from District Dairi performed the earliest age at the cotyledon opening (13.67 days). NPK fertilizer differences were significant to highly significant. Variance component of genotypes (VG) contributed 17.76% to total variance (VT) in ratio of plant height to age at the opening of cotyledon. Genotype showed greater variance than NPK fertilizer. Genotypic (GCV) and phenotypic coefficient of variation (PCV) varied from 1.13% to 8.17% and from 10.75% to 18.37%, respectively. It can be concluded that the role of genotype is more decisive than the role of NPK fertilizer, and genotypes showed genotypic and phenotypic variability.
Investigating the determinants of ecological and carbon footprints. Evidence from high-income countries

High-income countries have experienced rapid economic growth, urbanization, consumption of renewable and non-renewable energy, increased trade dependency, and the attainment and maintenance of higher living standards over the last four decades, while also experiencing an increasing trend in environmental degradation. These experiences have fueled our desire to learn more about the factors that influence the ecological footprint and carbon footprint of high-income countries. The purpose of the present study is to investigate the effects of natural resources, urbanization, GDP per capita, population, and fossil fuels on ecological and carbon footprint for 34 high-income countries over the period 2003–2015. Using the STIRPAT model, the results confirm the environmental Kuznets curve hypothesis in the case of total ecological footprint while the link between economic growth and carbon footprint is in U-shape. In terms of total ecological footprint determinants, population reduction as well as efficient urban design, are viable solutions. The findings support the positive and statistically significant influence of population, urbanization, and fossil fuels on total ecological footprint, as well as the negative impact of ecological efficiency. The findings of the carbon footprint suggest that reduction in coal and oil consumption, as well as increasing the use of gas as a source of energy, are all viable choices to mitigate carbon footprint. Furthermore, increasing ecological efficiency could be a viable policy option for reducing high-income countries' footprints.
Wide Area Detection and Distribution Characteristics of Landslides along Sichuan Expressways

Wide area landslide detection is a major international research hotspot in the field of geological hazards, and the integration of multi-temporal optical satellite images and spaceborne interferometric synthetic aperture radar (InSAR) appears to be an effective way to realize this. In this paper, a technical framework is presented for wide area landslide detection: (i) multi-temporal satellite optical images are used to detect landslides with distinguishable geomorphological features; (ii) Generic Atmospheric Correction Online Service (GACOS) assisted InSAR stacking is employed to generate annual surface displacement rate maps in radar line of sight using satellite SAR images from both ascending and descending tracks, which are in turn utilized to automatically detect active landslides from ground motion using hotspot analysis, and (iii) the distribution characteristics of the detected landslides are investigated by examining their relationships with topographic and hydrological factors. Three expressways in Sichuan Province, China—namely the Yakang (Ya’an-Kangding), Yaxi (Ya’an-Xichang), and Lushi (Luding-Shimian) expressways—and their surrounding regions (a total area of approximately 20,000 square kilometers) were chosen as the study area. A total of 413 landslides were detected, among which 320 were detected using multi-temporal satellite optical images, and 109 were detected using GACOS-assisted InSAR stacking. It should be noted that only 16 landslides were detected by both approaches; these landslides all exhibited not only obvious geomorphological features but also ground motion. A statistical analysis of the topographic and hydrological factors shows that of the detected landslides: 81% are distributed at elevations of 1000–2500 m, over 60% lie within the elevation range of 100~400 m, and 90% present with medium and steep slopes (20°~45°), and 80% are located within areas seeing an annual rainfall of 950~1050 mm. Nine landslides were found to pose potential safety hazards to the expressways. The research findings in this paper have directly benefitted the Sichuan expressways; equally important, it is believed that the technical framework presented in this paper will provide guidance for hazard mitigation and the prevention of transportation hazards in the future.
Short-Term Tax Cuts, Long-Term Stimulus

We study the persistent effects of temporary changes in U.S. federal corporate and personal income tax rates using a narrative identification approach. A corporate income tax cut leads to a sustained increase in GDP and productivity, with peak effects between five and eight years. R&D spending and capital investment display hump-shaped responses while hours worked and employment are much less affected. In contrast, personal income tax cuts trigger a short-lived boost to GDP, productivity and hours worked but have no long-term effects. We develop and estimate an endogenous growth model with variable factor utilization and show that these features generate a pro-cyclical response of productivity which is key to account for our empirical findings. JEL classification: E23, E62, H24, H25, H31, H32, O32
Plant Leaf Disease Detection using Deep Learning: A Review

To maintain the ecosystem of the environment major role is played by the plants. India largely depends on agriculture which is one of the major sectors in Indian economy. Majority of people are dependent on it to sustain themselves. Due to lack of technical knowledge and resources farmers recognize the plant disease by observing certain unusual patterns, colors, physical appearance etc. Sometimes expertise is required to detect plant infection and abnormalities which is a tedious process. Due to certain disease when the leaves of the plants are infected, production is reduced and also the quality of the food is also affected. The aim is to study different types of plants diseases and how these diseases can be detected by using modern advanced machines and techniques. Automation can help in early-stage disease detection stage which in turn helps to avert any further damage to the plant. Over the past few years, many promising technology and techniques have been launched that provides state-of-art solutions to modernize the agriculture sector and improve the quality and yield of the crops. Modern concept of smart farming provides agriculture sector with more efficient and effective planting system with the help of high precision algorithm. Efficient techniques lead to greater yields which keeps the population happy and healthy.
Using computational fluid dynamic and artificial neural networks to predict the performance and cavitation volume of a propeller under different geometrical and physical characteristics

ABSTRACT In the current study, simulations of hydrodynamic characteristics of a propeller under different geometrical and physical characteristics are conducted by the computational fluid dynamic (CFD). Then, by designing appropriate artificial neural networks (ANNs), the hydrodynamic performance and cavitation volume of propellers are predicted under intended conditions. For this accomplishment, finite volume-based Navier–Stokes equations associated with incompressible large eddy simulation turbulence model are used. In order to verify the computational procedure, mesh sensitivity analysis and validation study are conducted and appropriate accuracy is observed. In the CFD simulations, propeller thrust, torque and cavitation volume are computed under different pitch ratio (P/D), rake angle (RA) and skew angle (SA), advance velocity ratio (J) and cavitation number (σ). By the CFD results, a significant increase in propeller thrust and torque is observable by enhancement of P/D and positive value of RA. Moreover, maximum mean square errors of ANNs output in the prediction of propeller thrust, torque and cavitation volume achieved are 0.000111, 7.4206E−5 and 0.000667, respectively. Also, related to ANNs’ weights and bias, four set of equations are proposed to predict the performance and cavitation volume of propellers.