Miracle-dz/UniFAR-FTUs huggingface dataset:
INS Error Estimation Based on an ANFIS and Its Application in Complex and Covert Surroundings

Inertial navigation is a crucial part of vehicle navigation systems in complex and covert surroundings. To address the low accuracy of vehicle inertial navigation in multifaced and covert surroundings, in this study, we proposed an inertial navigation error estimation based on an adaptive neuro fuzzy inference system (ANFIS) which can quickly and accurately output the position error of a vehicle end-to-end. The new system was tested using both single-sequence and multi-sequence data collected from a vehicle by the KITTI dataset. The results were compared with an inertial navigation system (INS) position solution method, artificial neural networks (ANNs) method, and a long short-term memory (LSTM) method. Test results indicated that the accumulative position errors in single sequence and multi-sequences experiments decreased from 9.83% and 4.14% to 0.45% and 0.61% by using ANFIS, respectively, which were significantly less than those of the other three approaches. This result suggests that the ANFIS can considerably improve the positioning accuracy of inertial navigation, which has significance for vehicle inertial navigation in complex and covert surroundings.
The effect of financialization on management earnings forecasts

ABSTRACT We examine the effect of financialization on management earnings forecasts. Using a sample of Chinese main board listed companies over 8 years, we find that financialization decreases the probability and frequency of issuing management earnings forecasts. The results imply that financialization impedes firms’ information disclosure and may negatively affect their long-term performance.
In-vivo Antiplasmodial Activity of Sulfadoxine/Pyrimethamine/Doxycycline on Plasmodium berghei Infected Mice

The search for newer antimalarial drug combinations is on the front burner due to rising Plasmodium resistance to some currently used antimalarial drugs. This study examined the antiplasmodial activity of sulfadoxine/pyrimethamine/doxycycline (S/P/D) on mice infected with Plasmodium berghei (P. berghei). Swiss albino mice (25-30 g) inoculated with P. bergei (1x10 7 ) were treated with D (2.2 mg/kg), S/P (21.4/10.7 mg/kg), and S/P/D for 4 days. The positive and negative controls were treated with normal saline (0.2 ml) and chloroquine (CQ) (10 mg/kg) for 4 days, respectively. After treatment, blood samples were collected and assessed for parasitemia levels and biochemical parameters. The mice were observed for mean survival time (MST). D, S/P, S/P/D and CQ significantly decreased parasitemia in the curative, prophylactic and suppressive tests at p<0.05; p<0.01, p<0.001 and p<0.001, respectively when compared to negative control. In the curative study, 55.9%, 65.1%, and 81.7% parasitemia inhibitions were produced by D, S/P and S/P/D, respectively whereas CQ produced 75.6 % parasitemia inhibition. D, S/P and S/P/D significantly prolonged MST at p<0.05, p<0.01 and p<0.001 respectively when compared to negative control. Original Research Article Georgewill and Adikwu; JABB, 24(5): 1-8, 2021; Article no.JABB. 67463 2 Altered serum biochemical markers in P. berghei infected mice were marked by significantly (p<0.001) decreased packed cell volume, red blood cells, hemoglobin, high density lipoprotein cholesterol levels with significantly (p<0.001) increased cholesterol, white blood cells, total cholesterol, low-density lipoprotein cholesterol and triglyceride levels when compared to control. However, D, S/P and S/P/D significantly restored the aforementioned markers at p<0.05, p<0.01 and p<0.001, respectively when compared to negative control. S/P/D may be used as an antimalarial drug.
Nonlinear responses of particulate nitrate to NOx emission controls in the megalopolises of China

Abstract. Nitrate is an increasingly important component of fine particulate matter (PM2.5) in Chinese cities. The production of nitrate is not only related to the abundance of its precursor, but also supported by atmospheric photochemical oxidants. The control of nitrogen oxides (NOx) emissions may thereby lead to nonlinear changes of nitrate concentrations, raising a new challenge to the current emission control actions in China. This paper uses comprehensive measurements and a regional meteorology-chemistry model with optimized mechanisms to establish the nonlinear responses between particulate nitrate and NOx emission controls in the megalopolises of China. Nitrate is an essential component of PM2.5 in eastern China, accounting for 9.4–15.5 % and 11.5–32.1 % of the PM2.5 mass for the warm and cold seasons. The hypothetical NOx emission reduction scenarios (−10 %~−80 %) during summer-autumn result in almost linearly lower PM2.5 by −2.65 % in Beijing-Tianjin-Hebei (BTH) and −2.79 % in Yangtze River Delta (YRD) per 10 % cut of NOx emissions, whereas they increase the oxidant levels and lead to a rather complicated response of PM components in winter. Wintertime nitrate is found to increase by 4.28 % in BTH and 4.60 % in YRD, with higher dinitrogen pentoxide (N2O5) intermediate products produced from increased ozone introduced by lower NOx emissions. An inflexion point appears at 40–50 % NOx emission reduction, and a further cut in NOx emission is predicted to cause −8.74 % reduction of nitrate for BTH and −10.59 % for YRD per 10 % cut of NOx emissions. In addition, the 2012–2016 NOx control strategy actually leads to no change or even increase of nitrate in some areas (8.82 % in BTH and 14.41 % in YRD) during winter. This paper helps understand the nonlinear aerosol and photochemistry feedbacks, and defines the effectiveness of proposed mitigations for the increasingly serious nitrate pollution in China.
Arbuscular Mycorrhizal Fungi Symbiosis in Durum Wheat (Triticum durum Desf.) under No-tillage and Tillage Practices in a Semiarid Region

Background: Arbuscular mycorrhizal fungi (AMF) are root symbionts that improve host plant growth and resilience against biotic and abiotic stresses allowing a sustain plant production particularly under harsh conditions. Methods: The objective of this study is to compare the effect of conventional tillage and no-tillage practices on AMF symbiosis with durum wheat (Triticum durum Desf) through the evaluation of root colonization and AMF spore density in the soil of three different sites in a semi-arid region in Algeria. Two sites were conducted under rain-fed conditions and one was irrigated.Result: Mycorrhizal root colonization varied according to the site and the tillage practice, while spore density differed between sites. Spore density was higher in sites under rain-fed conditions suggesting that water deficit stimulate sporulation, while root colonization seems to be limited by drought. No-tillage improved root colonization rates by 54.3% compared to conventional tillage system and this improvement, particularly the arbuscular percentage, was higher under drought conditions. In addition, root colonization rates showed a positive correlation with the organic matter content and pH in the soil and a negative correlation with the available phosphorus in the soil. These results indicate that no-tillage enhance the establishment of AMF symbiosis with durum wheat under semi-arid conditions.
Evaluating experimentation in the public sector: learning from a Brazilian innovation lab

Abstract This paper presents an initial evaluation of the GNova lab, with the aim of contributing to the policy lab literature and debate on the value generated by public sector innovation labs. GNova is a Brazilian federal government innovation lab dedicated to developing creative solutions to public policy problems through design-led experiments that involve the active participation of members of partner teams. In the context of a political transition, GNova carried out an evaluation process to assess the results of its projects. By using working principles as evaluation criteria, the process was design-led and consisted of two phases. The first was a workshop with project partners, followed by a series of in-depth interviews with participants in six selected projects. The findings were grouped into three types of effects (effects of the process, effects of products and effects of the participation). The evaluation, even though with a limited scope, confirmed the assumption that, in addition to effects from specific products delivered, the lab contributes to the development of competencies in the civil servants who participate in the process, in resonance with a public administration paradigm based on public value.
Predicting the dynamics of establishing tree populations: A framework for statistical inference and lessons for data collection

Under global change, there is an urgent need to forecast the dynamics of establishing tree populations. However, tree population dynamics are slow and historical data on these dynamics are rare. This raises the question whether tree population dynamics can be reconstructed from data collected at a single time point. Doing so poses challenges for modelling, data collection and model‐data integration. We present a Bayesian framework that uses multiple data types to parametrize an individual‐based model (IBM) for the growth of establishing tree populations. The framework combines likelihood‐based Bayesian inference and approximate Bayesian computation (ABC). Using this framework, we assess the information content of three data types (recruitment data, dendrochronological data describing individual growth and molecular markers characterizing within‐population pedigrees) by comparing the bias and uncertainty of parameter estimates and model forecasts obtained under different simulated scenarios of data availability. The combination of all data types leads to accurate forecasts of the future state of tree populations, despite large uncertainties in some parameter estimates. Dendrochronological data were the most informative of the examined data types. Combining data types improved forecasts of population state. Nevertheless, for a given parameter related to a given process, combining data types did not improve estimates compared to using only the data type most closely related to the process. The presented Bayesian framework allows to infer the dynamics of establishing tree populations from data collected at a single time point. It helps to optimally allocate limited resources for data collection in order to rapidly improve the understanding and forecasting of tree population dynamics.
Simple Sequence Repeats Marker based Detection of Genetic Diversity of Indian Bean Dolichos lablab (L.) of Family Fabaceae

Background: Assessment and molecular characterization of genetic diversity among the Dolichos lablab (L.) have huge implication in scheming strategies for breeding. In India, there is less comprehensive information on the potential genetic diversity of lablab bean and this is a major challenge for systematic use of lablab bean in genetic breeding programs. To exploit the available trait of interest, the genetic diversity of the locally available genotypes must be known. The PCR-based SSR approach requires just nanogram amounts of template DNA, subjected to quick detection and less influenced by environment. In this manner SSR have been utilizing broadly to study hereditary assorted qualities of yields.Methods: In this study, genetic diversity on ten Indian Dolichos lablab (L.) genotypes were surveyed utilizing SSR markers at Department of Botany, Bundelkhand University, Jhansi during 2019-20 got from Indian gene bank. For SSR analysis, 5 primers were used for checking the diversity in Dolichos lablab (L.) and the performance of markers were measured by using 4 parameters (1) PIC, (2) Mean resolving Power, (3) Resolving Power and (4) MI. Result: SSR (05) markers produced a total of 51 bands, out of which 45 bands (88.23%) were polymorphic which varies from 6 (Primer-111) to 15 (Primer-AGB-9) with mean of 10.5 bands per primer. The polymorphic information content value ranges from 0.265 to 0.488 with a mean value of 0.390. The value of Matrix index is 3.2. The value of resolving power ranges from 2.2 to 12.60 with a mean value of 7.40. In the UPGMA dendogram, the 10 genotypes were separated into two main clusters with all the primers used. Our present examination uncovered that genetic markers might be effectively used for deciding hereditary variety and connections in Dolichos lablab (L.) genotypes and could be utilized as a part of breeding programs.
Year in Review 2020: Multisystemic impact of cystic fibrosis

Clinical care in cystic fibrosis (CF) has continued to advance over the last several years, particularly with the widespread eligibility and use of highly effective modulator therapy. Improved outcomes and longevity of persons with CF (PwCF) have increased recognition of the multisystem impact of the disease on the daily lives of PwCF. This review will cover a broad array of topics, from diagnosis to multisystem effects related to mental health, endocrine, palliative care, reproductive health, otolaryngology, and cardiac issues. Additionally, worldwide care delivery will be reviewed, demonstrating variation in outcomes based on resources and populations served. This review is part of the CF Year in Review 2020 series, focusing on the multi‐system effects of CF. This review focuses on articles from Pediatric Pulmonology but also includes articles published in 2020 from other journals that are of particular interest to clinicians.
A Multi-scale Residual Convolutional Neural Network for Sleep Staging Based on Single Channel Electroencephalography Signal

Sleep disorder is a serious public health problem. Non hospital sleep monitoring system for monitoring sleep quality can effectively support the screening of sleep disorder related diseases. A new algorithm of multi-scale residual convolutional neural network (MS-RESCNN) was proposed to discover the feature of electroencephalography (EEG) signals detected with wearable system and staging the sleep stage. EEG signals were analyzed by this algorithm every 30 seconds, and then sleep staging results of wake-up (W), rapid eye movement sleep (REM) and non-rapid eye movement sleep (NREM) were outputed. NREM can also be subdivided into N1, N2 and N3 stages. 5-fold cross validation and independent subject cross validation were performed on the dataset with Kappa cofficients 0.7360 and 0.7001, respectively. The accuracy rates of those methods were 92.06% and 91.13%, respectively. Compared with the other methods, our proposed method can obtain the information of sleep stages from single channel EEG signals without special feature extraction. It has a good performance and can provide support for clinical application based on automatic sleep staging.
Factors Affecting Customer Satisfaction with The lastmile Delivery Service of The Food and Beverage Industry E-Commerce in Hanoi City

THAO VY NGUYEN, BAO CHAU NGUYEN, THU HANG CAO, THI NGA NGUYEN, HOANG MINH HOAI NGUYEN, LE HAI HA DINH, XUAN HUNG NGUYEN 1 School of Advanced Education Programs, National Economics University, Vietnam. School of Advanced Education Programs, National Economics University, Vietnam. School of Advanced Education Programs, National Economics University, Vietnam. School of Advanced Education Programs, National Economics University, Vietnam. School of Advanced Education Programs, National Economics University, Vietnam. Doctor, School of Trade and International Economics, National Economics University, Vietnam. 7 Associate professor, School of Trade and International Economics, National Economics University, Vietnam. *Corresponding Author Email: thaovy1882k@gmail.com, bchauuunn@gmail.com , thuhang19320@gmail.com, ngandu162000@gmail.com, minhhhoaii@gmail.com,dinhlehaiha@neu.edu. vn, hungnx@neu.edu. vn Abstract:The purpose of this article is to analyze the factors affecting customer satisfaction with the use of last-mile delivery service in the food and beverage industry in e-commerce in Hanoi.The authors examine the impact of factors on customer satisfaction from 2015 to 2021 using the SERVQUAL service quality model combined with the SERVPERF perceived level model, and the American customer satisfaction index model ACSI. The results show a relatively significant impact of several factors such as reliability, assurance, empathy and perceived value. In addition, income and gender factors also affect customer satisfaction.
Boys’ gaming identities and opportunities for learning

ABSTRACT This article addresses a gap in research about primary school boys’ identification as ‘gamers. ’ Drawing on a survey of 318 Year 3 (7–8 years old) students, the research identified boys’ self-reported enjoyment for gaming, their frequency using digital devices, and their self-rated digital skills. Interviews with four boys from the survey also explored the lifeworlds of self-professed ‘gamers. ’ Findings point to the salience of games for many boys’ emerging identities and the inter-related nature of their experiences. We argue that teachers can capitalise on the strength of video games to create ‘in-group’ cultures and communities of practice in their classrooms to support learning.
Indentation behavior of metal matrix composites reinforced with arbitrary shape particle using a coupled FE-EFG approach

Abstract The effect of particle volume fraction, size, and shape on the indentation behavior of particulate composites is investigated using coupled FE-EFG approach. A systematic approach is presented where the particles are modeled only in a small region under the indenter and the homogenized properties are assigned to the remaining region. Equivalent properties are determined using RVE analysis. Von-Mises criterion along-with updated Lagrangian approach is employed to capture elastoplastic large deformation behavior. Node-to-segment contact algorithm is adopted to model the contact behavior between indenter and matrix. Results in-terms of residual von-Mises stress, equivalent plastic strain, and deformed surface profile are presented.
Climate Impact of China’s Promotion of the Filling Mining Method: Bottom-Up Estimation of Greenhouse Gas Emissions in Underground Metal Mines

China recently implemented a “Green Mine” policy focused on promoting the filling method, aiming to mitigate the environmental impacts of underground mining; nevertheless, quantitative inventories have rarely been provided to support or negate such promotion, especially from a life-cycle perspective. Accordingly, this paper proposes a bottom-up model for estimating life-cycle greenhouse gas (GHG) emissions from underground metal mines using either filling or caving methods. Two filling-based (Luohe and Longtangyan) and two caving-based (Maogong and Xiaowanggou) iron mines were studied; their direct GHG emissions were 0.576, 0.278, 2.130, and 1.425 tons of carbon dioxide equivalent per kiloton-extracted ore (t CO2 eq/kt), respectively. When indirect GHG emissions were considered, the results increased to 17.386, 15.211, 5.554, and 5.602 t CO2 eq/kt, respectively. In contrast to popular belief, such results demonstrate that promoting the filling method can potentially raise the overall GHG emissions. Although filling-based projects generate less direct GHG emissions, the emissions are transferred to upstream sectors, especially the cement and power sectors. The additional electricity consumption in the haulage and backfilling stages is primarily responsible for the greater GHG emissions occurring in filling-based projects. Some mitigation approaches are suggested, such as backfilling the subsidence pit, using industrial waste as cementing materials, employing energy-efficient pumps, and further developing hauling systems.
Fungal and mycotoxin occurrence, affecting factors, and prevention in herbal medicines: a review

Abstract Herbal medicines have been applied in clinical treatment worldwide, whose significant curative effect attracts considerable global research attention. However, as the herbal medicine industry develops continuously in recent years, new challenges including monitoring the quality and safety of herbal medicines appear in this industry. Numerous cases of fungal and mycotoxin contamination have been reported that affected the quality and safety of herbal medicines. The main mycotoxins found in herbal medicines include aflatoxin, ochratoxin A, and fumonisin B, which cause substantial harm to human health. They are mainly produced by species from Aspergillus, Penicillium, and Fusarium. Various reports have focused on studying the conditions for fungal growth and mycotoxin synthesis to provide references for prevention. The chemical compounds and antagonism microorganisms were also explored to inhibit fungal growth, and decrease mycotoxin accumulation. This review discusses natural occurrence of three main fungal genera (Aspergillus, Penicillium, and Fusarium) and three main mycotoxins (aflatoxin, ochratoxin A, and fumonisin B) in herbal medicines, analyzing the endogenous and exogenous factors that affect fungal growth and mycotoxin production. Moreover, the prevention methods of fungal contamination are included.
Structural Analysis of Unimer Nanoparticles Composed of Hydrophobized Poly(amino acid)s

Amphiphilic random copolymers of poly(γ-glutamic acid)-graft-l-phenylalanine (γ-PGA-Phe), with various lengths of γ-PGA main chains (molecular weight of 70, 140, and 220 kDa) plus hydrophobic moieties of Phe groups (grafting degree 12–60%), self-assembled in aqueous media to form nanoparticles (NPs). The aggregation number (Nagg) could be adjusted according to their molecular structures as well as the preparative methods/conditions. The γ-PGA-Phe NPs were further characterized by means of dynamic and static light scattering, small-angle neutron scattering, as well as steady-state fluorescence measurements/quenching techniques. The single chain state had hydrophobic domains, and formed spherical structures, herein called unimer NPs, and were obtained using molecular weights of γ-PGA higher than 140 kDa conjugated with Phe at 27–42% due to the balance of hydrophobicity/hydrophilicity along the single polymer chain. The number of hydrophobic domains in one NP (Ndomain), estimated by means of fluorescence que.
Half a Century of NVSQ: Thematic Stability Across Years and Editors

The aim of this article is to understand how the scholarship of the nonprofit sector shifted after almost half a century (1972–2019) of publication in the field’s premier journal, Nonprofit and Voluntary Sector Quarterly. Unlike previous attempts to understand the field’s scholarly evolution, we did not rely on expert opinion and analysis of themes but applied an automated content analytic method, more specifically structural topic modeling (STM). Using this method, we identified 37 key thematic topics that most optimally represent the 1,516 articles that were published in the studied period. After reporting these 37 thematic topics, we analyzed fluctuations based on three key periods of the journal and the editors’ disciplinary fields. While overall there was a trend of continuity (29 out of 37 topics) and little if any impact of the editors’ disciplines, a few thematic topics showed decline and fewer showed increase over time.