bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improvementof small scale dolomite mine blast fragmentation efficiency using hybrid artificial intelligence and soft computing approaches-A case study
Authors: Taiwo Blessing Olamide 
Published: October 2022

Abstract
Blast fragmentation efficiency prediction can improve blast productivity, but it is capital intensive when done with available software. Soft computing models based on artificial intelligence approaches and multivariate regression techniques were proposed in this study to predict small diameter hole blast fragmentation efficiency at the Akoko Edo dolomite quarry. WipFrag software was used to analyze and evaluate blast fragmentation performance based on images of blast muck piles. The proposed model's performance was evaluated using five model performance indices, comprising the average bias error, root mean square error, correlation coefficient, and average absolute error. The obtained results indicate that the proposed model of the Adaptive Neuro-fuzzy inference system (ANFIS) is proficient of accurate prediction of blast fragmentation efficiency when compared to artificial neural networks and multivariate regression models.
N-space (NS)-Framework: a generalized solution for soft continuum robots via reinforcement learning
Authors: Wei Dehao , Zhou Jiaqi , Zhu YInheng , Ma Jiabin , Ma Shaohua 
Published: October 2022

Abstract
Soft continuum robots undergoes nonlinear spatial deformation. Deep reinforcement learning (DRL) suffers from large training dataset and high time consumption. This paper reports a generalized principle, N-space (NS) framework, that employs on value-based reinforcement learning algorithms (e.g. DQN and DDQN), to overcome the challenge of local minima associated with sample efficiency or limited time consumption in online training. The performance of NS-augmented DRL (NS-DRL) was examined on controlling a self-design rope-driven soft continuum robot with 5-degrees of freedom (DoF). In this framework, the action space of the robot was divided to 6 sub-action spaces. Subsequently, the target position was divided into six sub-target positions, determined by the volumetric vector projection in each sub-action space. The action sequence was determined by actions of vector projection of the target on each sub-action space. NS-DDQN increased the convergence speed by more than 100-fold, from over 100,000 steps to approximately a thousand steps, and reduced the positioning error by over 10-fold, from over 20 mm to less than 1 mm, compared with non-NS enabled DRL positioning. The performance augmentation was also tested in DQN, implying the generalization of NS strategy in controlling soft continuum robots.
Probabilistic assessment of cereal-rye impacts on regional crop yield and soil carbon
Authors: Rai Teerath Singh 
Published: October 2022

Abstract
Field research for exploring the impact of winter cover crops (WCCs) integration into cropping systems is resource intensive, time consuming and offers limited application beyond the study area. To bridge this gap, we used the APSIM model, to simulate corn (Zea mays L.) – rye – corn – rye and corn – rye – soybean (Glycine max L.) – rye rotations in comparison to corn – corn and corn – soybean rotations across the state of Illinois at a spatial resolution of 5 km × 5 km from 2000–2020 to study the impact of WCCs on soil organic carbon (SOC) dynamics and crop production. By propagating the uncertainty in model simulations associated with initial conditions, weather, soil, and management practices, we estimated the probability and the expected value of change in crop yield and SOC following WCC integration. Our results suggest that integrating cereal rye into the crop rotations did not incur any yield penalties, and on the contrary, imparted greater yield stability for corn across the state. It was found that the areas with low probability of increase in SOC (p < 0.75) respond equally well for soil carbon sequestration through long-term adoption of WCCs. Furthermore, the average simulated soil carbon sequestration rate was found to be higher than 0.4% as set by Lima Paris Action Agenda to meet sustainable development goals. This study presents the most complete uncertainty accounting of WCC benefits across broad region and provides greater insight into the spatiotemporal variability of WCCs benefits for increasing WCC adoption rate.
Application value of transcranial direct current Stimulation In stroke patients
Authors: Haq Usman , Aftab Alishba , Malik Mohammad Hamza Bin Abdul , Haq Ali , Malik Muhammad Awais Bin Abdul , Rashid Amna 
Published: October 2022

Abstract
Introduction: Poststroke consequences
including sensorimotor and cognitive impairments impose a stressful
situation and a great burden to the victims, their families, and
the society.

Objectives: The main objective of the study is
to analyze the aapplication value of transcranial direct current
Stimulation (TDCS) In stroke patients. Material and
methods: This pilot study was conducted in Rawal Institute
of Health Sciences during June 2019 to June 2020. The components
required for TDCS include a Constant Current Stimulator and surface
electrodes soaked in normal saline. A Constant Current Stimulator
provides a steady flow of direct current (e.g., 0 – 4mA) while
constantly monitoring the resistance in the system.
Results: The study was completed by 136 patients.
Their mean age was 53.2 ± 8.4 years (range: 36-61 years). There
were more males than females (60% vs. 40%). Their demographic and
clinical characteristics are summarized in table 1.
Conclusion: It is concluded that TDCS combined
with VR can reduce motor impairment, improve function, increase ADL
in the affected upper limb in patients with subacute or chronic
ischemic stroke than VR alone.
Urbanization and CO2 emissions in Belt and Road Initiative Economies: Analysis of the mitigating effect of human capital in Asian countries
Authors: Gnangoin Thierry Y. , Kassi Diby Francois , Kongrong OuYang 
Published: October 2022

Abstract

Balanced and sustainable development is one of the main objectives of the Belt and Road Initiative (BRI). Therefore, considering the role of urbanization and human capital as critical elements for sustainable economic development, we analyze the moderating effect of human capital on the relationship between urbanization and CO2 emissions in Asian member countries of the Belt and Road Initiative. Using the STIRPAT framework and Environmental Kuznets Curve (EKC) hypothesis, we also analyze human capital's linear and nonlinear effects on CO2 emissions in multivariate models, including urbanization, gross domestic product per capita, energy use, and foreign direct investment. We employ the pooled OLS robust standard errors estimator Driscoll-Kraay, the Feasible Generalized Least Squares (FGLS), and the two-stage least square (2SLS) estimators in the case of 30 BRI countries for the period 1980–2019. The results show positive effects of energy and urbanization on CO2 emissions. Moreover, this study reveals that human capital annihilates the positive impact of urbanization on CO2 emissions. We also find that human capital has an inverted U-shaped effect on CO2 emissions. Accordingly, we provide policy implications on the conditional influence of human capital in the urbanization-CO2 emissions nexus for sustainable development in these countries.
JEL code: C21, Q01, Q56
Continued fractions and the Thomson Problem
Authors: Moscato Pablo , Haque Mohammad Nazmul , Moscato Anna 
Published: October 2022

Abstract
We introduce new analytical approximations of the minimum electrostatic energy configuration of n electrons, E(n), when they are constrained to be on the surface of a unit sphere. Using 454 putative optimal configurations we searched for approximations of the form E(n) = (n2/2) e g(n) where g(n) was obtained via a memetic algorithm that searched for truncated analytic continued fractions finally obtaining one with Mean Squared Error equal to 4.5744×10^(-8).
Using the Online Encyclopedia of Integer Sequences, we searched over 350,000 sequences and, for small values of n, we identified a strong correlation of the highest residual of our best approximations with the sequence of integers n defined by the condition that n2 +12 is a prime. We also observed an interesting correlation with the behaviour of the smallest angle α(n), measured in radians, subtended by the vectors associated with the nearest pair of electrons in the optimal configuration. When using both √n and α(n) as variables a very simple approximation formula for E(n) was obtained with MSE = 7.9963×10^(-8). When expanded as a power series in infinity, we observe that an unknown constant of an expansion as a function of n-1/2 of E(n) first proposed by Glasser and Every in 1992 as -1.1039, and later refined by Morris, Deaven and Ho as -1.104616 in 1996, may actually be very close to -1-π/30.
Lightweight convolutional neural network models for semantic segmentation of in-field cotton bolls
Authors: Singh Naseeb , Tewari V. K. , Biswas P. K. , Dhruw L. K. 
Published: October 2022

Abstract
Robotic harvesting of cotton bolls will incorporate the
benefits of manual picking as well as mechanical harvesting. For
robotic harvesting, in-field cotton segmentation with minimal
errors is desirable which is a challenging task. In the present
study, three lightweight fully convolutional neural network models
were developed for the semantic segmentation of in-field cotton
bolls. Model 1 does not include any residual or skip connections,
while model 2 consists of residual connections to tackle the
vanishing gradient problem and skip connections for feature
concatenation. Model 3 along with residual and skip connections,
consists of filters of multiple sizes. The effects of filter size
and the dropout rate were studied. All proposed models segment the
cotton bolls successfully with the cotton-IoU
(intersection-over-union) value of above 88%. The highest
cotton-IoU of 91.03% was achieved by model 2. The proposed models
achieved F1-score and pixel accuracy values greater than 95% and
98%, respectively. The developed models were compared with existing
state-of-the-art networks namely VGG19, ResNet18, EfficientNet-B1,
and InceptionV3. Despite having a limited number of trainable
parameters, the proposed models achieved mean-IoU (mean
intersection-over-union) of 93.84%, 94.15%, and 94.65% against the
mean-IoU values of 95.39%, 96.54%, 96.40%, and 96.37% obtained
using state-of-the-art networks. The segmentation time for the
developed models was reduced up to 52% compared to state-of-the-art
networks. The developed lightweight models segmented the in-field
cotton bolls comparatively faster and with greater accuracy. Hence,
developed models can be deployed to cotton harvesting robots for
real-time recognition of in-field cotton bolls for harvesting.
iPSC-derived cells lack immune tolerance to autologous NK-cells due to imbalance in ligands for activating and inhibitory NK-cell receptors
Authors: Bogomiakova Margarita E. , Sekretova Elizaveta K. , Anufrieva Ksenia S. , Khabarova Polina O. , Kazakova Anastasia N. , Bobrovsky Pavel A. , Grigoryeva Tatiana V. , Eremeev Artem V. , Lebedeva Olga S. , Bogomazova Alexandra N. , Lagarkova Maria A. 
Published: October 2022

Abstract
Background: Dozens of transplants generated from pluripotent stem cells are currently in clinical trials. The creation of patient-specific iPSCs makes personalized therapy possible due to their main advantage of immunotolerance. However, some reports have claimed recently that aberrant gene expression followed by proteome alterations and neoantigen formation can result in iPSCs recognition by autologous T-cells. Meanwhile, the possibility of NK-cell activation has not been previously considered. This study focused on the comparison of autologous and allogeneic immune response to iPSC-derived cells and isogeneic parental somatic cells used for reprogramming.
Methods: We established an isogeneic cell model consisting of parental dermal fibroblasts, fibroblast-like iPSC-derivatives (iPS-fibro) and iPS-fibro lacking beta-2-microglobulin (B2M). Using the cells obtained from two patients, we analyzed the activation of autologous and allogeneic T-lymphocytes and NK-cells cocultured with target cells.
Results: Here we report that cells differentiated from iPSCs can be recognized by NK-cells rather than by autologous T-cells. We observed that iPS-fibro elicited a high level of NK-cell degranulation and cytotoxicity, while isogeneic parental skin fibroblasts used to obtain iPSCs barely triggered an NK-cell response. iPSC-derivatives with B2M knockout did not cause an additional increase in NK-cell activation, although they were devoid of HLA-I, the major inhibitory molecules for NK-cells. Transcriptome analysis revealed a significant imbalance of ligands for activating and inhibitory NK-cell receptors in iPS-fibro. Compared to parental fibroblasts, iPSC-derivatives had a reduced expression of HLA-I simultaneously with an increased gene expression of major activating ligands, such as MICA, NECTIN2, and PVR. The lack of inhibitory signals might be due to insufficient maturity of cells differentiated from iPSCs. In addition, we showed that the ligand imbalance could be reversed to normal. Longer cultivation and passaging of iPS-fibro or pretreatment with proinflammatory cytokines boosted HLA class I expression, which reduced the degranulation and cytotoxicity of NK-cells.
Conclusion: In summary, we showed that iPSC-derived cells can be sensitive to the cytotoxic potential of autologous NK-cells regardless of HLA-I status. Thus, the balance of ligands for NK-cell receptors should be considered prior to iPSC-based cell therapies.
Trial registration: Not applicable.
Responses of burial characteristics of n-alkanes and polycyclic aromatic hydrocarbons in Poyang Lake, China to changes in organic matter inputs from 1886 to 2019
Authors: Tian Jiaming , Chen Yan , Zhao Zihan , Zhu Wangyue , Wu Hanzhi , Zhang Mingli , Wang Yanhua 
Published: October 2022

Abstract
The potential influences of the increased anthropogenic stress during the Anthropocene have led to a focus on the sedimentary record in lake and estuary environments. In this study, the spatio-temporal occurrence of 16 polycyclic aromatic hydrocarbons (PAHs) and the n-alkanes from nC12–nC37 associated with organic groups (i.e., organic nitrogen (ON), organic carbon (OC), organic hydrogen (OH), and organic sulfur (OS)) in the 210Pb-dated estuary sediments of Poyang Lake were investigated and their sources and impacts were traced. The ON, OC, OS, and OH contents in the sediment cores ranged between 0.12 − 0.65%, 1 − 7.95%, 0.01 − 0.82%, and 0.03 − 1%, respectively. The age of estuarine sediment cores in Poyang Lake was measured to be 1885–2019 by the 210Pb-dating method. The 133-year sediment deposition occurred over different stages, each with its own characteristics. The PAH fluxes were in the range of 787.65–11269.18 ng cm− 2 a− 1. The high-ring PAHs were dominant, accounting for 74.02% of the total, and the main sources were biomass combustion and automobile exhaust emissions from 1885–2019 without marked change. On a centennial scale, the main n-alkane peaks were nC15, nC31, and nC33, which had an obvious odd-even predominance. The deposition flux of Σn-alkanes varied within the range of 10.33 − 213.86 µg cm− 2 a− 1. The long-chain monomers were dominant, and were found to originate from herbs. The environmental indicator analysis revealed that the restoration of forests and eutrophication of water bodies caused by human activities and a climate change from wet to drought conditions contributed to the relative contribution of autochthonous organisms and vascular plants during 1886–2019.
Long-term effects of meteorological factors and extreme weather on daily outpatient visits for conjunctivitis from 2013 to 2020: a time-series study in Urumqi, China
Authors: Gui Si-Yu , Qiao Jian-Chao , Wang Xin-Chen , Yang Fan , Hu Cheng-Yang , Tao Fang-Biao , Yi Xiang-Long , jiang zhengxuan 
Published: October 2022

Abstract
Background
Conjunctivitis is a common multifactorial inflammatory ocular surface disease characterized by symptoms such as congestion, edema, and increased secretion of conjunctival tissue, and the potential effects of meteorological factors as well as extreme meteorological factors on conjunctivitis and their lagging effects have not been fully evaluated.
Materials and Methods
We obtained the electronic case information of 59,731 outpatients with conjunctivitis from the Ophthalmology Department of the First Affiliated Hospital of Xinjiang Medical University (Urumqi, Xinjiang, China) for the period from January 1, 2013, to December 31, 2020. Meteorological data for daily mean temperature (°C), daily relative humidity (%), daily average wind speed (m/s), and atmospheric pressure (hPa) were obtained from the China Meteorological Data Sharing Service. The air pollutant data were obtained from 11 standard urban background fixed air quality monitors. A time-series analysis design and a quasi-Poisson generalized linear regression model combined with a distributed lagged nonlinear model (DLNM) were used to fit the effects of exposure to different meteorological factors and extreme weather on conjunctivitis outpatient visits. Subgroup analyses were performed on gender, age and season, and type of conjunctivitis.
Results
Univariate and multifactorial model results indicated that each 10-unit increase in mean temperature and relative humidity was associated with an increased risk of conjunctivitis outpatient visits, while each 10-unit increase in atmospheric pressure was associated with a decreased risk. The results of the extreme weather analysis suggested that extremely low levels of atmospheric pressure and relative humidity as well as extreme levels of temperature were associated with an increased risk of outpatient conjunctivitis visits, and extreme wind speeds were associated with a decreased risk. The results of the subgroup analysis suggested gender, age, and seasonal differences.
Conclusions
We conducted the first large sample size time series analysis in the large city furthest from the ocean in the world and confirmed for the first time that elevated mean temperature and extreme low levels of relative humidity in Urumqi were risk factors for local conjunctivitis outpatient visits, while elevated atmospheric pressure and extreme low levels of wind speed were protective factors, and there were lagged effects of temperature and atmospheric pressure. Multicenter studies with larger sample sizes are needed.
Deposition of ultra-thin coatings by a nature-inspired Spray-on-Screen technology
Authors: kumar Rachith nithyananda , Rameirez Andrea , verding Pieter , Nivelle Philippe , Renner Frank , D'Haen Jan , Deferme Wim 
Published: October 2022

Abstract
Nanometer-thick, ultrathin coatings applied over a large area are of paramount importance for various application fields such as biomedicine, space and automotive, organic electronics, memory devices, or energy storage devices. So far wet chemical deposition as a cost-effective, scalable, and versatile method can only be used for thicker deposits. Here the formation of uniform ultra-thin coatings with thicknesses below 15nm using a nature-inspired, roll-to-roll compatible Spray-on-Screen (SoS) technology is reported. For this, the finite micro-droplet generation of Ultrasonic Spray Coating (USSC) is combined with the coating formation from a screen printing mesh. Hydrophobic micro-threads of the mesh, resembling the micro-hair on the legs of water striders, produce millidroplets from microdroplets, and when applying external pressure to the mesh, dynamic wetting is enforced. The proposed technology is applicable for a wide variety of substrates and applications. It is shown by theory and experiment that ultra-thin coatings below 5nm homogeneous over a large area can be deposited without the use of extended ink formulation or high substrate temperatures during or after deposition. This simple yet effective technique enables the deposition of ultra-thin films on any substrates, and is very promising to fabricate the organic, inorganic electronics devices and batteries cost effectively.
Evaluation the potential of recovering various valuable elements from a vanadiferous titanomagnetite tailing based on chemical and process mineralogical characterization
Authors: Liu Jinsheng , Xing Zhenxing , Liu Jianxing , Ding Xueyong , Xue Xiangxin 
Published: October 2022

Abstract
In order to evaluate the potential of recovering various valuable elements from vanadiferous titanomagnetite tailing (VTMT), the chemical and process mineralogical characterization of VTMT were investigated in this study by various analytical techniques such as XRF, XRD, optical microscope, SEM, EDS and AMICS et al. It was found that VTMT is coarser powder in general, about 50% of the particle size is greater than 54.30 µm. The total iron content of the VTMT was 22.40 wt.%, and its TiO2 grade is 14.45 wt.%, even higher than those found in natural ilmenite ores. The majority of iron and titanium were located in ilmenite and hematite, 62.84% of hematite and 90.27% of ilmenite were present in monomeric form. However, there is still a portion of ilmenite and hematite embedded in gangue such as anorthite, diopside, and serpentite et al. For the recovery of valuable fractions such as Fe and TiO2 from VTMT, a treatment process including ball milling – high-intensity magnetic separation – one roughing and three refining flotation was proposed. Finally, a concentrate with TiO2 grade of 47.31% and TFe grade of 35.44% was produced, TiO2 and TFe had recovery rates of 57.71% and 28.23%, respectively. The recovered product is absolutely adequate as a raw material for the production of rutile. This study provides a reference and a new research direction for the recycling and comprehensive utilization of VTMT.
Study on spatiotemporal evolution of farmland abandonment and its influencing factors in the developed county of China
Authors: Wang Cheng , Su Yue , He Shan , Xie Yan , Xia Panpan , Cui Yanglin 
Published: October 2022

Abstract
The protection of farmland resources is related to world food security, as well as the smooth realization of the goals of UN 2030 Agenda for Sustainable Development and China's Rural Revitalization Plan. As the most active region in the global economic development and one of the main grain producing areas, the problem of farmland abandonment in the Yangtze River Delta gradually appears with the rapid development of urbanization. Therefore, Based on the interpretation data of remote sensing images and field survey data of three periods in 2000, 2010 and 2018, this study used Moran’s I and Geographical barycenter model to reveal the spatiotemporal evolution law of farmland abandonment in Pingyang County of the Yangtze River Delta. And then, this study selected 10 indicators covering four categories: geography, proximity, distance and policy, and used random forest model to reveal the main influencing factors of farmland abandonment in the study area. The results showed that the abandoned farmland increased from 441.58 hm2 in 2000 to 5797.40 hm2 in 2018. The hot spot and barycenter of land abandonment gradually shifted from the western mountainous areas to the eastern plain areas. Altitude and slope were the main factors affecting the farmland abandonment. The high the altitude and the great the slope, the farmland abandonment in mountainous areas were serious. The proximity factors had a greater impact on the expansion of farmland abandonment from 2000 to 2010, and then the impact weakened. In view of the above analysis, the countermeasures and suggestions for maintaining food security were finally put forward.