Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Maximum Boost Control and Reduced Common-Mode Voltage Switching Patterns of Three-Level Z-Source Inverter

The maximum boost control (MBC) technique of voltage boosting offers the highest output voltage gain among other boost control techniques of Z-source inverter (ZSI). But, this technique suffers from the major drawback of sixth fundamental frequency (6thF1) ripple components of the impedance network inductor current. Due to this, the size/cost of the impedance network increases, which limits the practical applications of MBC. This article proposes an improved version of MBC via appropriate modification in the conventional space vector pulse width modulation of three-level ZSI (3L-ZSI). The improved MBC eliminates the problem of the 6thF1 impedance network inductor current ripple of 3L-ZSI without affecting its input/output gain and switching stress across power switches as compared to the existing MBC. Also, two new improved reduced common-mode voltage (RCMV) switching patterns have been proposed. As compared to the existing ones, the proposed RCMV switching patterns of 3L-ZSI offers reduced size of the impedance network while limiting the common-mode voltage magnitude to one-sixth of the available dc-link voltage. The above-mentioned findings have been successfully validated using theoretical analysis, simulation, and experimental results.
Recycling and recovery of PE‐PP‐PET‐based fiber polymeric wastes as aggregate replacement in lightweight mortar: Evaluation of environmental friendly application

Waste polymeric material, classified as secondary raw material, mainly consisting of selected polyolefins, PE and PP, and PET has brought great pressure on the environment, due to the large quantities produced by the urban lifestyles and economic activity. This research evaluated the possibility to reuse the plastic waste as aggregates in hydraulic lime based composite mortars.
Computational 19F NMR. 2. Organic compounds

Fluorine-19 NMR chemical shifts have been calculated for a wide variety of fluorinated organic molecules by relativistic density functional methods. The study includes, along with common fluorine-containing functional groups, several fluorinated biologically active molecules or models thereof. These calculations further showcase the predictive power of DFT-NMR, and illustrate how they can be used to assign 19F spectra for the structure determination of organofluorine compounds.
Gas sensors based on nanostructures of semiconductors ZnO and TiO2

The paper presents a resistance structures with sensor layers based on nanostructures elaborated on the base of TiO2 and ZnO. The structures were tested concerning their sensitivities to the effects of nitrogen dioxide in the atmosphere of synthetic air. The TiO2 and ZnO nanostructures played the role of sensor layers. Investigations have proved that the elaborated resistance structures with TiO2 and ZnO layers are sensitive to the presence of NO2 in the atmosphere of synthetic air. The resistance of the structure amounted to about 20Ω in the case of ZnO structures and to about 200Ω in the case of TiO2 structures. The investigations confirmed that resistance structures with ZnO and TiO2, exposed to the effect of nitrogen dioxide in the atmosphere of synthetic air changes their resistances relatively fast. This indicates that such structures might be practically applied in sensors of nitrogen dioxide ensuring a short time of response.
Combining stochastic density functional theory with deep potential molecular dynamics to study warm dense matter

In traditional finite-temperature Kohn–Sham density functional theory (KSDFT), the partial occupation of a large number of high-energy KS eigenstates restricts the use of first-principles molecular dynamics methods at extremely high temperatures. However, stochastic density functional theory (SDFT) can overcome this limitation. Recently, SDFT and the related mixed stochastic–deterministic density functional theory, based on a plane-wave basis set, have been implemented in the first-principles electronic structure software ABACUS [Q. Liu and M. Chen, Phys. Rev. B 106, 125132 (2022)]. In this study, we combine SDFT with the Born–Oppenheimer molecular dynamics method to investigate systems with temperatures ranging from a few tens of eV to 1000 eV. Importantly, we train machine-learning-based interatomic models using the SDFT data and employ these deep potential models to simulate large-scale systems with long trajectories. Subsequently, we compute and analyze the structural properties, dynamic properties, and transport coefficients of warm dense matter.
Potential of Lilium lancifolium in Alleviating Pain and Inflammation in a Rat Model of Monosodium Iodoacetate-Induced Osteoarthritis

Lilium lancifolium (LL) is widely cultivated in East Asia and used to attenuate airway diseases. Our current study aimed to investigate the therapeutic effect of LL on pain level and inflammatory response in a rat model of monosodium iodoacetate (MIA)-induced osteoarthritis (OA). We first examined the effect of LL on inflammatory cytokines and inflammatory mediators in IL-1β-treated HTB-94 cells. The LL extract was found to significantly inhibit the levels of Interleukin-6 (IL-6), Interleukin-8 (IL-8), and prostaglandin-E2 (PGE-2) in Interleukin-1 β (IL-1β)-stimulated HTB-94 cells in a dose-dependent manner. Moreover, chronic oral administration of LL effectively restored the weight-bearing distribution in the rat model of MIA-induced OA. In addition, administration of LL inhibited inflammatory cytokines and inflammatory mediators, such as C-reactive protein (CRP), IL-6, leukotriene B4 (LTB-4), PGE-2, and matrix metalloproteinase-9 (MMP-9). Our findings collectively suggested LL as one of the potential therapeutic agents for OA, owing to its properties of reducing pain and inflammatory responses.
Hybrid Semi-Dense 3D Semantic-Topological Mapping From Stereo Visual-Inertial Odometry SLAM With Loop Closure Detection

Intelligent mobile vehicles asks for the ability to learn to comprehend immediate surroundings similar to human cognition and autonomously navigate in an unknown scene. Although simultaneous localization and mapping (SLAM) can construct a geometrically surrounding map, the map contains little semantic information. This paper presents a novel stereo visual-inertial system with loop closure detection based on a semantic-topological map framework. In our system, a hybrid 3D point cloud semantic-topological mapping framework is used to realize autonomous navigation simply by providing a map for path planning and meanwhile for storing semantic information under a dynamic environment. A stereo visual-inertial system can obtain more accurate visual-inertial odometry than a monocular system, and a visual-inertial system is capable of real-time map correction when the localization module detects a loop closure. This paper adopts state-of-the-art Mask R-CNN components to obtain 2D semantic information and project it to a semi-dense 3D semantic-topological map built by stereo visual-inertial SLAM. We perform experimental evaluation of our proposed system on the EuRoC MAV datasets and we also compare it with other competitive methods. Our results demonstrate that the proposed method is more effective than the other competitive methods.
Distributing drinking water without disinfectant: highest achievement or height of folly?

Preservation of the microbial quality of drinking water during distribution is a major objective in water supply. A disinfectant residual reduces regrowth but is not sufficiently effective against recontamination. It may cause taste and odour problems and result in the presence of compounds with toxic properties. Furthermore, the maintenance of an effective residual throughout the distribution system is hampered by the disinfectant decay caused by pipe materials and compounds present in the water. Prevention of microbial and chemical recontamination thus requires good engineering practices in the distribution system. Regrowth can be limited by distributing biostable drinking water and by applying biostable materials in contact with drinking water. Ensuring microbiological safety and controlling regrowth with these measures results in a better quality drinking water.
Estimation Method of Voltage Sag Frequency Considering Transformer Energization

The inrush current generated by power transformer energization (TE) causes voltage sag of the nearby bus, the typical residual voltage of the voltage sag caused by transformer energization (VSTE) is about 0.7 p.u. --0.9 p.u. and lasts for a longer duration, which may lead to the sensitive equipment trips. This paper proposes an estimation method of voltage sag frequency considering VSTE. Firstly, based on the maximum entropy method, the residual flux distribution is calculated by considering the relationship between the residual flux and closing angle at the moment of TE. The voltage sag waveform caused by TE is calculated based on the estimation of the probability distribution of residual flux, to evaluate VSTE objectively and comprehensively. Secondly, this paper proposes a non-rectangular voltage sag equivalent frequency statistical method based on multiple magnitude-duration (MMD) function, to avoid the overestimation of voltage sag frequency by the traditional methods. Furthermore, this paper proposes an assessment algorithm of voltage sag frequency. Finally, the simulation of IEEE-30 test system verifies the necessity and correctness of the proposed method.
Corporate Entrepreneurship: A Literature Review and Future Research Perspectives

Background. Nowadays, corporate entrepreneurship (CE) is perceived as an essential approach to boost the innovation and creativity within existing organizations for achieving higher opportunities in the market. This paper examines this concept, which has been largely discussed in the Anglo-Saxon world over the last thirty years. Like for many other phenomena, also in case of CE, this discussion has provided numerous conceptualizations, and consequently, there is not one unique definition of CE. In this respect, the search for an appropriate basis for understanding and describing the phenomenon of CE engenders a challenging issue for entrepreneurship researchers. Research aims. This paper aims at creating a large platform for understanding the concept of CE by means of a clarification effort through the review of the most important papers in this field and identification of the existing research gaps. Methodology. Systematic literature survey is the applied methodology. EBSCO and Taylor & Francis database were used as a source for the sampling process. Key findings. The analysis does acknowledge the need for more qualitative and rigorous research in this field and brings several recommendations for the future studies. The main conclusions also do urge for a more diversified research in terms of the sectors discussed, as the biggest gap identified is in the services sector. There is also a need for a more structured classification of the measures, depending on the real research focus: CE antecedents or outcomes.
Mahuang Decoction Antagonizes Acute Liver Failure via Modulating Tricarboxylic Acid Cycle and Amino Acids Metabolism

Acute liver failure (ALF) is a serious clinical disorder with high fatality rates. Mahuang decoction (MHD), a well-known traditional Chinese medicine, has multiple pharmacological effects, such as anti-inflammation, anti-allergy, anti-asthma, and anti-hyperglycemia. In this study, we investigated the protective effect of MHD against ALF. In the lipopolysaccharide and D-galactosamine (LPS/D-GalN)-induced ALF mouse model, the elevated activities of the serum alanine and aspartate transaminases as well as the liver pathological damage were markedly alleviated by MHD. Subsequently, a metabolomics study based on the ultrahigh performance liquid chromatograph coupled with Q Exactive Orbitrap mass spectrometry was carried to clarify the therapeutic mechanisms of MHD against ALF. A total of 36 metabolites contributing to LPS/D-GalN-induced ALF were identified in the serum samples, among which the abnormalities of 27 metabolites were ameliorated by MHD. The analysis of metabolic pathways revealed that the therapeutic effects of MHD are likely due to the modulation of the metabolic disorders of tricarboxylic acid (TCA) cycle, retinol metabolism, tryptophan metabolism, arginine and proline metabolism, nicotinate and nicotinamide metabolism, phenylalanine metabolism, phenylalanine, tyrosine and tryptophan synthesis, as well as cysteine and methionine metabolism. This study demonstrated for the first time that MHD exerted an obvious protective effect against ALF mainly through the regulation of TCA cycle and amino acid metabolism, highlighting the importance of metabolomics to investigate the drug-targeted metabolic pathways.
Recent Developments in the Cost of Bank Equity in Europe

This article assesses the cost of bank equity in Spain and the euro area since 2007, focusing particularly on the period of the COVID-19 pandemic. There was a marked rise in the cost of equity in March 2020, followed by a decline in the subsequent months. The article assesses the factors responsible for this movement, and compares it against the change in interest rates on alternative bank funding instruments.
HIV-1 and HIV-1-Tat Induce Mitochondrial DNA Damage in Human Neurons

Introduction: Mitochondrial dysregulation is a key event in HIV-1 infection. Recent studies have suggested that age-related neurodegenerative disorders are associated with increased mitochondrial DNA (mtDNA) damage. As accelerated ageing was found in HIV-1 patients, we hypothesized that HIV-1 infection or HIV-1 proteins can lead to mtDNA damage. Unrepaired mtDNA impairs mitochondrial function, which can lead to oxidative stress and cell death. Investigations of mechanisms of mtDNA damage are limited by the lack of available human models. Methods: We compared mtDNA or nDNA (nuclear DNA) damage in human cortical neurons and PBMC cells. Primary neuronal cultures were incubated with conditioned media from HIV-1 infected PBMC, or HIV-1 viral proteins Tat or Vpr. Total genomic DNA (nuclear and mtDNA) was isolated using the QIAamp Kit. Nuclear and mtDNA were amplified using the long q-PCR/Gene Amp XL Kit. Real-Time RT-PCR using mitochondrial energy metabolism array was performed to assess mitochondrial energy metabolism markers. Superoxide dismutase (SOD) activity in neuronal cells was measured by the OxiSelect SOD Activity Assay. Reactive oxygen species (ROS) were determined by the confocal microscopy. ATP levels were analyzed using ATP determination biochemical assay. Mitochondrial, cytoplasmic and nuclear proteins were studied by quantitative western-blot assay. Results: We show that both treatment of neuronal cells with HIV-1 conditioned media, or infection of PBMC with HIV-1 increase mtDNA damage in cells. mtDNA damage was also seen in neuronal cells, incubated with HIV-1 proteins, Tat and Vpr. Next, we confirmed that mtDNA damage was also increased in neuronal cells transfected by Tat expressing plasmids. We showed that mtDNA was not damaged in neuronal cells following treatment with heat inactivated HIV-1 or Tat protein. Further, we demonstrated that HIV-1 or Tat caused more mtDNA damage compared to nuclear DNA damage in neuronal cells. Finally, we showed that Tat dysregulates RNA expression of several genes regulating mitochondrial energy metabolism, suggesting involvement of Tat in mitochondrial bioenergetics in human neurons. Finally, our hypothesis was confirmed by qWestern analysis of mitochondrial and apoptotic proteins demonstrating the accumulation of apoptotic Bax and Bad proteins in mitochondrial fraction of Tat-treated neuronal cells, suggesting toxic effects of Tat on mitochondrial survival. Conclusion: We showed an increase of mtDNA damage in primary neurons, treated with HIV-1 proteins and in PBMC, infected with HIV-1. Increased mtDNA damage can lead to neurodegeneration, and cause neuronal apoptosis. Our system presents a suitable model to study mtDNA changes during HIV-1 infection.
Evaluation of Aydughmush River water quality using the National Sanitation Foundation Water Quality Index (NSFWQI), River Pollution Index (RPI), and Forestry Water Quality Index (FWQI)

AbstractIn rivers, water flowing results in dilution and decomposition of pollutants faster than standing water. Water quality index (WQI) is a tool to reflect the composite influence of different water quality parameters. WQI is a fast and simple manner to show water quality from the point of view of a special consumption such as human consumption etc. Therefore, in this study, the water quality of the Aydughmush River evaluated by the National Sanitation Foundation Water Quality Index (NSFWQI), Forestry Water Quality Index (FWQI), and River Pollution Index (RPI). This study surveyed the parameters of the NSFWQI and RPI including dissolved oxygen percentage, temperature difference, biochemical oxygen demand (BOD), fecal coliform bacteria, turbidity, total suspended solids, pH, and phosphate. In addition, 22 parameters were measured for FWQI calculating. These parameters were measured at eight stations for one year (2010–2011). The results showed that water quality of Aydughmush River is within the “Mediu.
Halogen bonding enhances nonlinear optical response in poled supramolecular polymers

We demonstrate that halogen bonding strongly enhances the nonlinear optical response of poled supramolecular polymer systems. We compare three nonlinear optical chromophores with similar electronic structures but different bond-donating units, and show that both the type and the strength of the noncovalent interaction between the chromophores and the polymer matrix play their own distinctive roles in the optical nonlinearity of the systems.
IMPROVING MDF FIBRE DRYING OPERATION BY APPLICATION OF A MATHEMATICAL MODEL

Fibre drying is an important process in production of medium density fibreboard (MDF) which consumes a large amount of energy, affects product quality and, without appropriate control, causes environmental concerns. Based on fundamental knowledge of wood fibre-water relationships and heat/mass transfer, a mathematical model has been developed to simulate the MDF fibre drying processes. The model is able to predict fibre moisture content, air temperature and air humidity along the dryer length. After validation against the measured air temperature and humidity, the model has been extended to include both fibre drying and fibre conditioning, the latter occurring in the dry fibre conveyers. Due to potential benefits in reducing emissions of volatile organic compounds (VOCs) and in improving panel quality, lower drying temperatures are more desirable than higher temperatures. However, in order to achieve the target moisture content after drying, a higher air velocity is needed or a second-stage dryer is added. The model was employed to determine the air velocity required and to assist in designing a second dryer for further drying and recovery of moist vapour and heat. A further study was undertaken to investigate fibre drying or fibre conditioning in the fibre conveyers and, once again, the fibre drying model was used to determine the air conditions.
State of the Nation: A 50-State COVID-19 Survey: Report #9: Will Americans Vaccinate Themselves and Their Children Against COVID-19?

From the Document: "We surveyed 19,058 individuals across all 50 states plus the District of Columbia The survey was conducted on 10-26 July 2020 by PureSpectrum via an online, nonprobability sample, with state-level representative quotas for race/ethnicity, age, and gender (for methodological details on the other waves, see covidstates org) In addition to balancing on these dimensions, we reweighted our data using demographic characteristics to match the U S population with respect to race/ethnicity, age, gender, education, and living in urban, suburban, or rural areas This was the seventh in a series of surveys we have been conducting since April 2020, examining attitudes and behaviors regarding COVID-19 [coronavirus disease 2019] in the United States "
The effect of the state of the banking system on national economic resilience

Economic resilience is directly related to the level of development of the banking system within a single economic space. This article identifies the degree of influence of the main indicators of the state of the banking system on the values of the resilience of the national economy of Russia. A review of the main research results in this area is carried out and the similarity of the positions of various authors on the issue of direct influence between the dynamics of banks’ development and economic growth trends is revealed. The dynamic and structural analysis reflecting the degree of integration of the banking system and the Russian economy is carried out. The main determinants of the banking system, which have a direct impact on the dynamics of the national economy, are identified and systematized. An econometric analysis is carried out in the form of a regression model describing the degree of connection and influence of the main banking indicators on the stability of the Russian economy in terms of GDP per capita. The results obtained reflect a high degree of connection between the dynamics of indicators of the state of the banking system and the level the national economic resilience.
Research-Policy Linkages: Empirical Evidence From Agroeconomic Research in India

Policy-making processes in developing countries often continue to operate devoid of evidence. In this study, we explore the research-policy linkages between the agroeconomic research system (AERS) and the agricultural policy system (APS) in India. Specifically, we examine questions directed to the Ministry of Agriculture and Farmersâ€™ Welfare in the two houses of the national parliamentâ€”the House of the People (Lok Sabha) and the Council of States (Rajya Sabha)â€”and filter them for key issues that confront the APS. In addition, using the list of research articles published in two major national agricultural economics journals, we examine the alignment of the AERS toward addressing pressing policy issues. We use 6,465 questions raised by elected representatives in the parliamentary houses and 377 research articles, both during the period 2014â€“2018. We use machine learning techniques for information retrieval because the required information is hidden as non-numerical text. Using tag clouds (lists of words by frequency), we identify key divergences between the concerns of the APS and the research focus of the AERS, and explore their linkages. To broaden our understanding, we employ latent Dirichlet allocation, a natural language processing technique that identifies crucial issues and automates their classification under appropriate clusters, to examine synergies between the research and policy systems. Results show remarkable alignment between the AERS and the APS, invalidating the two-communities hypothesis. We identify persistent issues in the policy domain that require the support of the research system, as well as potential areas for research system realignment.
Current Research Trends and Growing Importance of Nanomedicine

Copyright: ©2020 Ostafin A. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The science behind the design and development of nano-scale materials has expanded tremendously over the past few decades owing to the improvement and sophistication of nanoscale level physicochemical characterization tools and techniques and has consequently enabled evolution and advancement of technological applications in diverse fields of practical utility. The applications of nanoscience and nanotechnology in the fields of medicine (both diagnostic and therapeutic) and in agriculture has had a great impact in the recent years.