Miracle-dz/UniFAR-FTUs huggingface dataset:
Sensorless Starting Control of the Brushless Synchronous Starter/Generator Based on Flux and Parameter Estimation of the Main Exciter

Using the main exciter (ME) as the quasi-resolver is an emerging advanced sensorless control technology. Since the ME becomes a dual-use machine, the structure of a brushless synchronous starter/generator (BSSG) is simplified and more compact. However, the existing rotor position estimation methods in this path are limited to the low-speed range. What is more, the acquisition of the stator parameters of ME is still tedious due to the special structure of BSSG. In this article, a sensorless starting control method of BSSG based on flux and parameter estimation of ME is proposed. First, the relationship between the rotor position and flux is strictly derived, and the low-speed limitation has been removed theoretically. According to this relationship, the rotor position estimation methods of ME and the main generator are then proposed. Besides, taking advantage of the nonlinear operating characteristics of the rotating rectifier, a simple parameter estimation method of ME is proposed. With this method, the stator parameters of ME are estimated with only stator voltages and currents by the recursive least squares algorithm, and rotation is not needed. Finally, the effectiveness of both the sensorless starting control method and the parameter estimation method is verified by experiments.
A Compact Dual-Band Dual-Polarized Omnidirectional Antenna for On-Body Applications

A compact dual-band dual-polarized wearable antenna for on-body communication in the 2.45 and 5.8 GHz ISM bands is presented. The antenna is linearly polarized (LP) at 2.45 GHz and circularly polarized (CP) with the conical pattern at 5.8 GHz, which is suitable for the multisensor link network. By using the characteristic modal analysis initially, the ground plane has been miniaturized and optimized to radiate an omnidirectional beam in the horizontal plane with the excitation of the <inline-formula> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula>/4 resonant mode. The higher order band at 5.8 GHz has been realized by the excitation of the <inline-formula> <tex-math notation="LaTeX">$3\lambda $ </tex-math></inline-formula>/4 resonant mode of the same L-shaped slot. These two odd-order modes radiate horizontally polarized omnidirectional patterns. The combination of the vertical polarization generated from the top-loaded patch antenna along with the <inline-formula> <tex-math notation="LaTeX">$3\lambda $ </tex-math></inline-formula>/4 mode from the L-shaped slot resulted into omnidirectional CP in the 5.8 GHz band. Furthermore, enhancement in axial ratio bandwidth is achieved with the addition of dielectric superstrate over the feed layer. Bending sensitivity study to emphasize for conformal applications, transmission loss along with specific absorption rate analysis has been performed for on-body characterization. The simulated and measured results are found to be in good agreement.
On the effects of task focus and processing level on the perception–production link in second-language speech learning

This study presents a reanalysis of existing data to investigate whether a relationship between perception and production abilities regarding a challenging second-language (L2) phonological contrast is observable (a) when both modalities must rely on accessing stored lexical representations and (b) when there is an asymmetry in task focus between perception and production. In the original studies, German learners of English were tested on their mastery of the English /ɛ/-/æ/ contrast in an auditory lexical decision task with phonological substitutions, a word-reading task, and a segmentally focused imitation task. Results showed that accurate nonword rejection in the lexical decision task was predicted by the Euclidean distance between the two vowels in word reading but not in imitation. These results extend previous findings to lexical perception and production, highlight the influence of task focus on the degree of coupling between the two modalities, and may have important implications for pronunciation training methods.
Editorial: Women in head and neck cancer, volume II: 2022

COPYRIGHT © 2023 Economopoulou, Kotsantis and Psyrri. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. TYPE Editorial PUBLISHED 12 September 2023 DOI 10.3389/fonc.2023. 1278798
Geochemistry of the Mesoarchean Fiskenaesset anorthosite complex and associated tonalite-trondhjemite-granodiorite (TTG) gneisses, southwestern Greenland

This study presents new field, petrographic, and high precision geochemical data for the Mesoarchean Fiskenæsset Complex and spatially associated Mesoarchean to Neoarchean tonalite-trondhjemite-granodiorite (TTG) gneisses, in southwestern Greenland. On the basis of textural evidence, whole-rock geochemical data, and the trace element compositions of hornblende, plagioclase and clinopyroxene, it is suggested that hornblende has a magmatic origin. On the basis of whole-rock major and trace element characteristics and the trace element compositions of hornblende grains, two distinct geochemical suites (Suite A and Suite B) are recognized in the Fiskenæsset Complex. Field observations, whole-rock geochemistry, and hornblende, plagioclase and clinopyroxene trace element compositions indicate that the Fiskenæsset Complex originated through fractionation of olivine, pyroxene and hornblende, and late crystallization of plagioclase. Injection of new mafic magmas into variably solidified anorthositic magmas and crystal mushes resulted in the formation of leucogabbros via magma mixing. The rocks of the Fiskenæsset Complex are characterized arc signature, consistent with a subduction zone geodynamic setting. The occurrence of magmatic hornblende throughout the sequence is consistent with a hydrous mantle source. Orthogneisses in the Fiskenæsset region are composed of an older suite of metamorphosed TTGs, and a younger suite of high-K granites. The TTGs have high Al2O3, Na2O and Sr but low Y contents. They also have highly fractionated REE patterns, enrichment of Sr and Pb, and depletion of Nb and Ti. The geochemical characteristics of the TTGs can be explained by partial melting of hydrous basalts at the base of a thickened oceanic island arc, leaving a rutile-bearing eclogitic residue. Field observations and geochemical modelling suggest that the spatially and temporarily associated tholeiitic basalts (now amphibolites) in the Fiskenæsset region might have been the sources of TTG
Wilderness discount on livestock compensation costs for imperiled gray wolf Canis lupus

There is evidence that Wilderness reduces costs for livestock depredations caused by the endangered and threatened gray wolf (Canis lupus) in the northern Rockies and upper Midwest, U.S.A. From 1995 to 2004, direct costs for compensation in the northern Rockies came to only 47 to 78 percent of losses anticipated at wolf reintroduction and projected from non-wilderness habitat. Compensation was lowest in the wilderness-rich, central Idaho recovery area ($69/wolf/year), more than doubling in greater Yellowstone ($160/wolf/year) where private ranches commingle with extensive grazing leases on public land. Per capita compensation in northern Minnesota and Michigan was 5 percent to 14 percent of costs in wilderness-deficient northern Wisconsin ($163/wolf/ year). Globally, compensation for carnivore depredations tends to be higher where wild lands are scarce, but husbandry practices and grazing subsidies confound the discount in some regions. Nevertheless, a wilderness discount reduces some costs of (and may mitigate cultural resistance to) conservation programs aimed at restoring large predators.
Predicting the Impact of Customer Satisfaction as a Mediating Effect of Experiential Marketing on Repeat Purchases

Background –The emergence of the frozen food business has created fierce commercial competition. This is both a threat and a motivator for players in the refrigeration industry to remain competitive and retain the products they manufacture. To ensure competitiveness and viability, businesses need to understand consumer characteristics and how they influence purchasing decisions for customer satisfaction and loyalty. Customer buybacks are very important for businesses that want to maintain their business and grow their business in the form of long-term profits. Retaining existing customers is usually more profitable than acquiring new customers, so you can increase sales with existing customers. Objective –To analyze the predicted impact of Experiential Marketing on the repurchase of frozen food products through customer satisfaction as a mediating variable. Because experiential marketing is a marketing concept that provides information and opportunities for customers to gain experience for the benefits gained, generate emotions and feelings that have an impact on marketing. Design/methodology/approach – Based on the objectives to be achieved, this research is an explorative research because the aim is to find and predict the impact of Experiential marketing on Repurchase through consumer satisfaction as a mediating variable. This research is the development of problem solving (Malhotra, 2012) which aims to determine the predicted impact in the re-purchase
A Novel Drug-Drug Indicator Dataset and Ensemble Stacking Model for Detection and Classification of Drug-Drug Interaction Indicators

Drug-drug interaction (DDI) is a significant public health issue that accounts for 30% of unanticipated clinically hazardous medication events. The past decade has seen an evolution in informatics-based research for DDI signal identification. This paper aims to create an ensemble stacking machine learning (ML) approach capable of accurately predicting novel DDI hazard indicators. The stacking ensemble machine learning architecture for predicting the signals of drug-drug interactions is supported by one of the most reliable sources of pharmacological data, DrugBank. We scrap a large dataset that contains drug-related information, including drug types, drug names, and other aspects of drug indicators, and make it publicly available to the research community. The proposed approach includes data preprocessing, balancing through a random oversampling, label encoding and one hot encoding technique used for categorical variables, and model prediction using an ensemble stacking technique. The proposed ensemble approach uses the Gradient Boosting (GB) classifier, Adaboost, and Gaussian Naive Bayes (GNB) to classify the drug indication types. The experimental results demonstrate that the suggested approach outperforms traditional machine learning approaches regarding accuracy and efficiency. The stacking model obtained the highest accuracy of 99.0%. The test indicates that the proposed model is more effective than traditional methods for detecting drug-drug interaction signals.
A Lightweight-Window-Portion-Based Multiple Imputation for Extreme Missing Gaps in IoT Systems

Intelligent techniques, including artificial intelligence and deep learning, normally perform on complete data without missing data. Multiple imputation is indispensable for addressing missing data resulting in unbiased estimates and dealing with uncertainty by providing more valid results. Most state-of-the-art techniques focus on high-missing rates (around 50%–60%) and short missing gaps, while imputation for extreme missing gaps and missing rates is an important challenge for multivariate time-series data generated through the Internet of Things (IoT). Hence, we propose an lightweight-window-portion-based multiple imputation (LWPMI) based on multivariate variables, correlation, data fusion, regression, and multiple imputations. We conduct extensive experiments by generating extreme missing gaps and high-missing rates ranging from 10% to 90% on data generated by sensors. We also investigate different sets of feature to examine how LWPMI works when features have high, weak, or a mixture of high and weak correlation. All the obtained results prove LWPMI outperforms baseline techniques in preserving pattern, structure, and trend in both 90% extreme missing gap and missing rates.
Effects of Physical Health Status, Social Support, and Depression on Quality of Life in the Korean Community-Dwelling Elderly

Background. This study was conducted to determine the effects of physical health status, social support, and depression on the quality of life in the elderly aged 65 and over who visit the senior employment center in G city, Republic of Korea. Methods. This study is a descriptive research targeting 466 elderly people aged 65 and over who lived in G city in Gyeongsangnam-do, Republic of Korea. Results. The subjects had one or more chronic diseases and slightly higher than normal depression, but had a slightly higher quality of life. A lower level of education, a higher number of chronic diseases, and a lower value of social networks was associated with lower quality of life. A higher subjective health status, a higher value of emotional network and a lower level of depression was associated with a higher quality of life. The explanatory power of this model for the quality of life was 31.3%. Conclusions. In order to improve the quality of life in the elderly, it is necessary to manage chronic diseases in old age, to increase the frequency of contact with family, relatives, and friends, to reduce negative emotions and depression and to enhance social support through various social activities. Therefore, it is necessary to develop a program and intervention strategies for individual and customized health care suitable for the characteristics of the elderly in the local community.
Current perspectives and trends in nanoparticle drug delivery systems in breast cancer: bibliometric analysis and review

The treatment of breast cancer (BC) is a serious challenge due to its heterogeneous nature, multidrug resistance (MDR), and limited therapeutic options. Nanoparticle-based drug delivery systems (NDDSs) represent a promising tool for overcoming toxicity and chemotherapy drug resistance in BC treatment. No bibliometric studies have yet been published on the research landscape of NDDS-based treatment of BC. In this review, we extracted data from 1,752 articles on NDDS-based treatment of BC published between 2012 and 2022 from the Web of Science Core Collection (WOSCC) database. VOSviewer, CiteSpace, and some online platforms were used for bibliometric analysis and visualization. Publication trends were initially observed: in terms of geographical distribution, China and the United States had the most papers on this subject. The highest contributing institution was Sichuan University. In terms of authorship and co-cited authorship, the most prolific author was Yu Zhang. Furthermore, Qiang Zhang and co-workers have made tremendous achievements in the field of NDDS-based BC treatment. The article titled “Nanomedicine in cancer therapy: challenges, opportunities, and clinical applications” had the most citations. The Journal of Controlled Release was one of the most active publishers in the field. “Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries” was the most cited reference. We also analysed “hot” and cutting-edge research for NDDSs in BC treatment. There were nine topic clusters: “tumour microenvironment,” “nanoparticles (drug delivery),” “breast cancer/triple-negative breast cancer,” “combination therapy,” “drug release (pathway),” “multidrug resistance,” “recent advance,” “targeted drug delivery”, and “cancer nanomedicine. ” We also reviewed the core themes of research. In summary, this article reviewed the application of NDDSs in the treatment of BC.
Generalized Optimal EEG Channels Selection for Motor Imagery Brain–Computer Interface

Brain–computer interfaces (BCI) enable people to communicate with external instruments through brain activity recorded by electroencephalography (EEG). BCI based on motor imagery (MI) can distinguish activation of specific brain regions by decoding EEG signals and then applying them to different situations. Because the activation regions of the brain are specific, using all EEG channels for classification is redundant and may lead to feature confusion and inconvenience for users when applying EEG. Current EEG channel selection methods focus primarily on a single subject and require the data from the subject to generate the chosen channel, which is inconvenient on the application side to determine suitable channels for new subjects. Therefore, this study introduces a novel method for generalized EEG channel selection. Two datasets are used: the BCI competition IV 2a dataset for generating generalized EEG channels and the OpenBMI dataset for validation by numerous subjects. First, the signals from each channel are fed into EEG-Net for classification and ranked by loss to generate optimal EEG channels. Then, the methods of ranking and non-dominated sorting genetic algorithm (NSGA)-II are used to find different combinations of optimal potential differences. Finally, the generalized EEG channels are generated and validated by EEG-Net again. The validation results show that 88.5% of the subjects can be well-classified in one session, including MI-illiteracy, defined by the dataset. The average accuracy is 77.7% and 79.26% in Sessions 1 and 2, using the average channel number around 5, instead of channels from the motor cortex region or all placed EEG channels.
Odorous volatile organic compounds in waste and wastewater management

Lehtinen, Jenni Odorous volatile organic compounds in waste and wastewater management Jyväskylä: University of Jyväskylä, 2012, 100 p. (Jyväskylä Studies in Biological and Environmental Science ISSN 1456-9701; 252) ISBN 978-951-39-4930-3 (nid.) ISBN 978-951-39-4931-0 (PDF) Yhteenveto: Hajua aiheuttavat haihtuvat orgaaniset yhdisteet jätteen ja jäteveden käsittelyssä Diss. The odour emission from waste and wastewater management is experienced as very unpleasant and life quality diminishing factor. The odorous compounds and their possible risks for employees health in three municipal wastewater plants, in pulp mill effluent plant and in two waste management plants were determined in this thesis. Correlation between odorous compounds and odour concentrations was determined. In wastewater treatment the odorous compounds were dimethyl sulphide (DMS), dimethyl disulphide (DMDS), dimethyl trisulphide (DMTS), hydrogen sulphide (H2S), limonene, toluene, heptanal and octanal. In some cases carboxylic acids were determined. In most cases the incoming wastewaters already had an important role in defining the character of wastewater odour. In pulp mill wastewater treatment the odorous compounds were alpha-pinene, DMS, DMDS, toluene and p-cymene. In composting plant the odorous compounds were acetic acid, butanoic acid, 2,3-butanedione, 3-hydroxy-2-butanone, ethyl acetate, 2butanol and limonene. The odorous compounds in the optic sorting of municipal waste were 2,3-butanedione, 3-hydroxy-2-butanone, ethyl acetate, ethyl benzene and p-cymene. As a difference from composting, aromatic and aliphatic hydrocarbons were abundantly present. Concentrations of VOCs in waste and wastewater treatment did not exceed the Finnish occupational exposure limits. Still some remarks were made from the results; 1,2-dichloroethane and styrene were determined in high concentrations being close to the WHO recommendation limits in one wastewater treatment plant. In waste management the concentrations of 2,3butanedione exceeded the limit proposals given by US NIOSH. TVOC concentrations were in the range of 232-2300 μg/m3 in waste management and in the range of 100-7719 μg/m3 in municipal wastewater management. Total sum of odorous compounds seemed to correlate with the measured odour concentration. When comparing the TVOC concentration with OU/m3 results, correlation between them was not determined.
Using Soil Testing Data to Monitor Changes in Maine Agricultural Soil Organic Carbon from 1995 to 2021

ABSTRACT Estimates of soil organic matter (SOM) are commonly part of soil testing, and typically use the loss-on-ignition (LOI) method. To explore the utility of existing soil testing databases as a resource for estimating soil organic carbon (SOC) concentrations over time, we determined the relationship between SOM estimated by LOI and SOC measured using IR detection of CO2 for Maine soils. We then examined trends in SOC concentrations in Maine agricultural soils over the past 27 years using data from 97,713 standard soil samples received by the Maine Soil Testing Service. For 91 agricultural soil samples representative of Maine cropping systems, we found that the standard LOI temperature used by the Maine Soil Testing Service, 375°C, produced LOI values that correlated more strongly with SOC measured by IR detection of CO2 than the three higher temperatures we studied, although all temperatures produced data that was well correlated (R2 values from 0.95 to 0.98). Soil texture did not influence the correlation. Our analysis of soil testing data from 1995 to 2021 suggested increases in SOC concentrations in soils planted to grain and hay, and possibly corn, broadly corresponding with changing agricultural practices occurring over this time frame. Of our four focal crop categories, only potato soils decreased in SOC concentration from 1995 to 2021, underscoring the unique challenges associated with potato soil management relative to other cropping systems in Maine. Our study confirms the potential utility of soil testing databases in assessing changes in SOC concentrations in agricultural soils over decades.
Zα domain proteins mediate the immune response

The Zα domain has a compact α/β architecture containing a three-helix bundle flanked on one side by a twisted antiparallel β sheet. This domain displays a specific affinity for double-stranded nucleic acids that adopt a left-handed helical conformation. Currently, only three Zα-domain proteins have been identified in eukaryotes, specifically ADAR1, ZBP1, and PKZ. ADAR1 is a double-stranded RNA (dsRNA) binding protein that catalyzes the conversion of adenosine residues to inosine, resulting in changes in RNA structure, function, and expression. In addition to its editing function, ADAR1 has been shown to play a role in antiviral defense, gene regulation, and cellular differentiation. Dysregulation of ADAR1 expression and activity has been associated with various disease states, including cancer, autoimmune disorders, and neurological disorders. As a sensing molecule, ZBP1 exhibits the ability to recognize nucleic acids with a left-handed conformation. ZBP1 harbors a RIP homotypic interaction motif (RHIM), composed of a highly charged surface region and a leucine-rich hydrophobic core, enabling the formation of homotypic interactions between proteins with similar structure. Upon activation, ZBP1 initiates a downstream signaling cascade leading to programmed cell death, a process mediated by RIPK3 via the RHIM motif. PKZ was identified in fish, and contains two Zα domains at the N-terminus. PKZ is essential for normal growth and development and may contribute to the regulation of immune system function in fish. Interestingly, some pathogenic microorganisms also encode Zα domain proteins, such as, Vaccinia virus and Cyprinid Herpesvirus. Zα domain proteins derived from pathogenic microorganisms have been demonstrated to be pivotal contributors in impeding the host immune response and promoting virus replication and spread. This review focuses on the mammalian Zα domain proteins: ADAR1 and ZBP1, and thoroughly elucidates their functions in the immune response.