Miracle-dz/UniFAR-FTUs huggingface dataset:
Gravity-Enhanced Magnetic (HGMS) Coal Cleaning

For economic and environmental reasons, precombustion magnetic coal cleaning must be performed on dry pulverized coal. Gravity-enhanced high-gradient magnetic separation has been successfully applied to the removal of mineral impurities from coal with a 4-T superconducting solenoid magnet. Under optimum separation conditions obtained in this study, this technique effectively cleans up to 72 wt % of the pyritic sulfur and 44 wt % of the ash content from a typical pulverized coal in a vertically upward airstream rig, and the heating value recovery is 95 wt %. Increasing applied magnetic fields and separator matrix lengths and decreasing superficial gas velocity each individually improve the cleaning performance. The results have indicated that the matrix made of 0.360-mm circular AISI 430 stainless steel wires is the best one for all the matrix grades used. These tests have paved the way for pilot plant trial runs at the power station site to be conducted.
Global Patterns and Climate Controls of Terrestrial Ecosystem Light Use Efficiency

Light use efficiency (LUE) is a critical parameter, on which we rely to quantify the vegetation's capability to harvest solar energy and thus the photosynthesis carbon uptake. However, our understanding on its magnitude, global pattern, and climatic drivers remains uncertain. In this study, we investigated global mean annual LUE during 1980–2013 based on state‐of‐the‐art estimates from scaled‐up eddy covariance measurements (data‐driven models) and 10 process‐based models used in Global Carbon Project. We found comparable global LUE estimates from data‐driven models (0.90 ± 0.25 g C MJ−1) and process‐based models (0.73 ± 0.22 g C MJ−1), with individual model estimates ranging from 0.49 to 0.98 g C MJ−1. While both types of models agreed on highest LUE over the tropical evergreen forests, discrepancies remained over middle and high latitudes of the Northern Hemisphere, which probably resulted from different response of LUE to climatic factors. Spatial analyses revealed that LUE variations were more driven by temperature and precipitation than by solar radiation. While the response of LUE to precipitation was almost always positive globally, the response of LUE to temperature was only positive in part of the nontropical regions. Process‐based models showed that precipitation strongly regulated the response of LUE to temperature, which shifted from negative to positive when mean annual precipitation was larger than 1,000 mm yr−1. Our results provide converging global LUE estimates and highlight the need to take fully account of interactive effects of climatic factors in regulating LUE and thus the response of photosynthesis to climate change.
Gas-Liquid Mass Transfer in Stirred Non-Newtonian Corn-Starch Dispersions

Oxygen transfer in colloidal dispersions of 1 to 4 wt% cornstarch in water was studied and the characteristic gas-liquid mass transfer coefficients in highly pseudoplastic conditions were obtained. The dispersions prepared were represented by flow behaviour indices between 0.64 and 0.90 and consistency indices between 0.002 and 0.2 Pa·sn. Mass transfer coefficients from 0.004 to 0.03 s–1 were obtained corresponding to apparent viscosities between 1 and 40 mPa·s. An equation was proposed to fit most of the data favourably. The presence of an antifoam agent was also considered.
A study on noise levels of machinery used in lumber industry enterprises.

The aim of this study is to help to create a healthier environment by measuring the noise levels in the furniture and lumber sectors of forest products industry. In this study, noise measurement for approximately 3 min has been conducted in 4 measurement spots in the side of the machinery, in the factory entrance and in full and empty state for each machinery; from 3 different chosen spots in enterprises producing lumber. Measurements have been recorded as 720, from each machine as 36 measurements, with the condition to be recorded every 5 sec for 3 min. For this purpose, noise measurements have been carried out in 17 workplaces producing lumber and results have been compared statistically. As a result of the obtained findings, it is understood that the noise levels of thickness machinery don’t exceed the value for the upper limit stated in the regulations. However, vertical wood band sawmill and band saw machines have been observed to go over this limit. Besides, some factors of planning and multi slitting machine don’t exceed this limit, some of them exceed. As a result, it has been conducted that when noise levels of machinery used in the lumber industry enterprises exceed the upper limit stated in the regulations, they can pose a serious threat to human health.
Polymer‐Clay Nanocomposite Solid‐State Electrolyte with Selective Cation Transport Boosting and Retarded Lithium Dendrite Formation

Commercialized lithium‐ion batteries (LIBs) with a liquid electrolyte have a high potential for combustion or explosion. The use of solid electrolytes in LIBs is a promising way to overcome the drawbacks of conventional liquid electrolyte‐based systems, but they generally have a lower ionic conductivity and lithium ion mobility. Here, a UV‐crosslinked composite polymer‐clay electrolyte (U‐CPCE) that is composed of a durable semi‐interpenetrating polymer network (semi‐IPN) ion transportive matrix (ETPTA/PVdF‐HFP) and 2D ultrathin clay nanosheets that are fabricated by a one‐step in situ UV curing method, are reported. The U‐CPCE exhibits robust and flexible properties with an ionic conductivity of more than 10−3 S cm−1 at room temperature with the help of exfoliated clay nanosheets. As a result, the U‐CPCE‐based LIBs show an initial discharge capacity of 152 mAh g−1 (at 0.2 C for a LiCoO2 half‐cell), which is comparable to that of conventional liquid electrolyte‐based cells. In addition, they show excellent cycling performance (96% capacity retention after 200 cycles at 0.5 C) due to a significantly enhanced Li+ transference number (tLi+ = 0.78) and inhibition of lithium dendrite formation on the lithium metal surface. Furthermore, a molecular dynamics (MD) study is conducted to elucidate the mechanism of improving ionic conductivity. The U‐CPCE design can offer opportunities for future all‐solid‐state Li‐ion batteries.
Clinical Benefit of Rehabilitation Training in Spinal Cord Injury: A Systematic Review and Meta-Analysis.

STUDY DESIGN A systematic review and meta-analysis. OBJECTIVE This study was performed to evaluate the effects of different rehabilitation interventions in spinal cord injury. SUMMARY OF BACKGROUND DATA Several activity-based interventions have been widely applied in spinal cord injury in the past, but the effects of these rehabilitation exercises are controversial. METHODS Publications were searched from databases (PubMed, Embase, Cochrane, the database of the U.S. National Institutes of Health and World Health Organization International Clinical Trials Registry Platform) using the searching terms like spinal cord injury, transcranial magnetic stimulation, functional electrical stimulation, activity-based therapy, and robotic-assisted locomotor training. Randomized controlled trials and controlled trials were included. The primary outcomes included functional upper/lower extremity independence, walking capacity, spasticity, and life quality of individuals with spinal cord injury. Meta-analysis was performed using Revman 5.0 software. RESULTS Thirty-one articles were included. Meta-analysis showed that transcranial magnetic stimulation improved walking speed (95% confidence interval [CI] 0.01, 0.16) and lower extremity function (95% CI 1.55, 7.27); functional electrical stimulation significantly increased upper extremity independence (95% CI 0.37, 5.48). Robotic-assisted treadmill training improved lower extremity function (95% CI 3.44, 6.56) compared with related controls. CONCLUSION Activity-based intervention like transcranial magnetic stimulation, functional electrical stimulation, and robotic-assisted treadmill training are effective in improving function in individuals with spinal cord injury.Level of Evidence: 1.
Mechanistic Study of Shape Evolution of Silver Nanoprisms in The Presence of KSCN

Silver nanoprisms can be etched and transformed into silver nanodiscs in the presence of SCN– ions. However, the blue-shifts of SPR bands of silver colloids abnormally depend on the concentrations of SCN– ions; for example, the values of blue-shifts in this study were 40, 250, and 100 nm in the presence of 10–4, 3 × 10–4, and 3 × 10–3 M SCN–, respectively. Blue-shifts of SPR bands reached the maxima, and two isosbestic points were found in the time-course spectra in the presence of KSCN within the so-called critical concentration range, at approximately 3 × 10–4 to 5 × 10–4 M. These two isosbestic points indicate that silver nanoprisms were not etched gradually in the presence of a critical concentration range of KSCN, but transformed into nanodiscs directly and immediately without forming blunt intermediates. Time-course TEM images of silver nanostructures, which were protected by the modification of a thin layer of HS(CH2)15CO2H (MHA) on the surface of the nanoparticles, were recorded to verify the mech.
Paracrystal model of the high-temperature lamellar phase of a ternary microemulsion system

Small-angle neutron scattering was used to investigate the microstructure of the high-temperature Lα phase in the AOT/water/decane system [AOT = sodium bis(2-ethylhexyl) sulfosuccinate]. The system was modeled as randomly oriented lamellar stacks with a one-dimensional paracrystalline distortion. For samples injected into cells at high temperature, the two-dimensional Q maps show anisotropic scattering consistent with partial alignment of the phase, while samples injected near room temperature do not exhibit this feature. From the latter samples, it was found that a stack typically contains about 15 lamellae, about 80 A apart. Each layer is coated by a diffuse surfactant interface with a characteristic thickness of approximately 9 A. The fact that the scattering spectra do not exhibit maxima beyond the first order is explained by the observation that the Hosemann g factor gives about a 20% variation in the interlamellar spacing. The mean spacing is inversely proportional to the surfactant concentration, as expected for a lamellar phase. Over-estimation of the zero-order scattering predicted by the paracrystal model is attributed primarily to improper treatment of the contrast between each layer and the space-filling lamellar matrix.
Investigation of a Method for EEG Signal De-Noising Based on the DIVA Model

The DIVA (Directions Into Velocities of Articulators) model is an adaptive neural network model that is used to control the movement of the analog vocal tract to generate words, syllables, or phonemes. The input signal to the DIVA model is the EEG (electroencephalogram) signal acquired from the human brain. However, due to the influence of power frequency interference and other forms of noise, the input signal can be non-stationary and can also contain a variety of multi-form waveforms in its instantaneous structure. Input of such a signal into the DIVA model affects normal speech processing. Therefore, based on the concept of sparse decomposition, this paper applies and improves an adaptive sparse decomposition model for feature extraction of the general EEG signal structure and then uses the Matching Pursuit algorithm to compute the optimal atom. The original EEG signal can then be represented by atoms in a complete atomic library. This model removes noise from the EEG signal resulting in a better signal than the wavelet transform method. Finally, applies the EEG signal de-noised by this model to DIAV model. Simulation results show that the method improves phonetic pronunciation greatly.
Characterization with hybrid imaging of cystic pheochromocytomas: correlation with pathology.

Pheochromocytomas are rare neuroendocrine tumors derived from chromaffin cells arising from adrenal medulla, that may precipitate life-threatening hypertension or cardiac arrhythmias because of excessive catecholamine secretion (1). These tumors usually appear as solid hypervascular masses on imaging studies. Rarely, these lesions may undergo varying degrees of lesion degeneration such as cystic or intracellular lipid changes, or may be associated to the presence of necrosis, calcification and fibrosis, thus having unusual clinical as well as imaging appearances and thus mimicking other adrenal lesions (2). Of note, cystic lesions of the adrenal gland are uncommon, often asymptomatic and may also show malignant nature (3). Although cases of cystic pheochromocytoma have been previously reported (4), the diagnosis of these atypical pheochromocytomas is very challenging. We describe two cases of cystic pheochromocytomas with different clinical and morphologic features in which hybrid imaging using FDG PET/MRI or PET/CT reflected tumor characteristics; in particular, we highlighted the diagnostic pitfalls that can be encountered in imaging interpretation.
An Experimental Study on the Hindered Settling Properties of Backfill Tailings Particles

﻿Mining using backfill methods has been utilized by many mines around the world. Tailings thickening, one of the ways to prepare backfill materials, has been studied worldwide and components of the process such as the thickening mechanism of the tailings tank and principles of selecting flocculants have already been worked out. The studies of hindered settling properties of tailings during this process have lagged which can restrict the precise control of tailings thickening and affect the backfill result. Using in-situ tailings from a mine, hindered and polydisperse settling experiments of tailing slurries with different concentrations and different particle size distributions have been launched to study and analyze the hindered settling features of tailing particles. The experimental results show that the R-square figure of the hindered settling rates of classified tailings between calculated values based on Richardson-Zaki model and experimental ones is over 0.87 proving the Richardson-Zaki model can be used to calculate and predict the hindered settling rates of classified tailings. Moreover, Selim’s theory can capture the main properties of the polydisperse settling process of the mix of sieved and silica tailings. The self-flocculation of fine particles in silica tailings has increased the “hindering effect” among particles, the experimental settling rates of silica tailings are less than those theoretical values calculated by Selim theory.
Effect of Feijoa Sellowiana Acetonic Extract on Proliferation Inhibition and Apoptosis Induction in Human Gastric Cancer Cells

Gastric cancer (GC) still represents a relevant health problem in the world for both incidence and mortality rates. Many studies underlined that natural products consumption could reduce GC risk, indicating flavonoids as responsible for the beneficial effects through the modulation of several biological processes, such as the inhibition of cancer antioxidant defense and induction of apoptosis. Since Feijoa sellowiana fruit is known to contain high amounts of flavonoids, among which is flavone, we evaluated the antiproliferative and proapoptotic effects of F. sellowiana acetonic extract on GC cell lines through MTS and Annexin-V FITC assays. Among three GC cell lines tested, SNU-1 results being sensitive to both the F. sellowiana acetonic extract and synthetic flavone, which was used as the reference treatment. Moreover, we evaluated their antioxidant effects, assessing the activity of the antioxidant enzymes supeoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx) in polymorphonuclear cells. We found a significant increase of their activity after exposure to both F. sellowiana acetonic extract and flavone, supporting the idea that a diet that includes flavone-rich fruits could be of benefit for health. In addition to this antioxidant effect on normal cells, this study indicates, for the first time, an anticancer effect of F. sellowiana acetonic extract in GC cells.
Do Not Neglect the Power of Symbols on Employee Performance: An Empirical Evidence From Turkey

Symbols, which are considered as a reflection of an organization’s culture, also provide clues about an organization’s character and value system. The positioning of symbols in the business world and academic studies thus remains an important issue. This study, which measures the effects of organizational symbolism on organizational commitment and firm performance, carries out a scale development study to evaluate the concept of symbolism. For this analysis, a questionnaire was provided to 727 family-owned business employees. In the scale development section, the organizational symbolism was divided into three dimensions, where it was observed that structural and administrative symbolism, along with outward symbolism, affect organizational commitment and firm performance, although narrative and discursive symbolism do not affect organizational commitment and firm performance. The findings are partially consistent with the current literature. In the “Discussion” section, suggestions are given to academicians and administrators.
Perturbation approach to combined QM/MM simulation of solute-solvent interactions in solution

A perturbation approach based on the generalized molecular interaction potential with polarization (GMIPp) has been developed for combined quantum mechanical and molecular mechanical (QM/MM) simulations of solutions. A unique feature of the method is to avoid repeated self-consistent field calculations for each new solvent configuration during the fluid simulation. The results show that the GMIPp potential coupled to Monte Carlo simulations yields similar energetic and structural results for a series of 14 organic compounds in aqueous solution in comparison with the results obtained from full ab initio QM/MM simulations at the HF/6-31G(d) level. Importantly, the solute electronic polarization energy is reasonably estimated by the GMIPp method. The implementation of the GMIPp within the Monte Carlo simulation framework appears to be a promising computational strategy for carrying out QM/MM calculations for large molecules, which otherwise would be difficult by using standard QM/MM techniques.
Machine Learning Assisted Petrophysical Logs Quality Control, Editing and Reconstruction

Mature field operators collect log data for tens of years. Collection of log dataset include various generation and multiple vintages of logging tool from multiple vendors. Standard approach is to correct the logs for various artefacts and normalize the logs over a field scale. Manually conducting this routine is time consuming and subjective. The objective of the study was to create a machine learning (ML) assisted tool for logs in a giant Lower Cretaceous Carbonate Onshore field in Abu Dhabi, UAE to automatically perform data QC, bad data identification and log reconstruction (correcting for borehole effects, filling gaps, cleaning spikes, etc.) of Quad Combo well logs. The study targets Quad Combo logs acquired since mid-60's. Machine learning algorithm was trained on 50 vertical wells, spread throughout the structure of the field. The workflow solution consists of several advanced algorithms guided by domain knowledge and physics based well logs correlation, all embedded in an ML-data-driven environment. The methodology consists of the following steps: oOutliers detection and complete data clustering.oSupervised ML to map outliers to clusters.oRandom Forest based ML training by clusters, by logs combination on complete data.oSaved models are applied back to the whole data including outliers and sections with one or several logs missing.oValidation and Blind test of results.oModels can be stored and re-used for prediction on new data. The ML tool demonstrated its effectiveness while correcting logs for outliers’ like Depth Offsets between logs, identifying Erroneous readings, logs prediction for absent data and Synthetic logs corrections. The tool has a tendency to harmonize logs. First test demonstrated robustness of the selected algorithm for outliers’ detection. It cleaned data from most of contamination, while keeping good but statistically underrepresented logs readings. Clustering algorithm was enhanced to supplement cluster assignment by extraction of the corresponding probabilities that were used as a cut-off value and utilized for a mixture of different ML models results. This application made results more realistic in the intervals where clustering was problematic and at the transition between different clusters. Several intervals of bad and depth shifted logs corrections were noticed. Outliers’ corrections for these logs was performed the way that at Neutron-Density or Neutron-Sonic cross-plots points were moved towards expected lithology lines. Algorithm could pick-up hidden outliers (such as synthetic logs) and edited the logs to make it look intuitively natural to a human analyst. The work successfully demonstrated effectiveness of ML tool for log editing in a complex environment working on a big dataset that was subject of manual editing and has number of hidden outliers. This strong log quality assurance further assisted in building Rock Typing based Static Model in complex and diagenetically altered Carbonates.
Molecular detection and phylogenetic analysis of pigeon circovirus in China during 2016-2019

The Pigeon circovirus (PiCV) which contains a circular single stranded DNA (approximately 2 kb) belongs to the genus Circovirus and the family Circoviridae. PiCV infections in pigeons (Columba livia) have been reported worldwide. Nowadays, pigeon racing is becoming increasingly popular and considered to be a national sport in China, and even, the greatest competitions of racing pigeons are stake place in China. However, there is no epidemiologic data on PiCV infections among racing pigeons in China. To trace the prevalence, genetic variation and evolution of PiCV in sick and healthy racing pigeons, 622 samples were collected from 11 provinces or municipalities of China from 2016 to 2019. Samples were tested by polymerase chain reaction. The results showed that the positive rate of PiCV was 19.3% (120/622) at the sample level; 59.0% (23/39) at the club level, suggesting that the virus was prevalent in Chinese racing pigeons. A sequence analysis revealed that the cap genes of the PiCV strains identified in our study display high genetic diversity and shared nucleotide homologies of 71.9%–100% and amino acid homologies of 71.7%–100%. 28 and 37 unique amino acid substitutions were observed among the cap proteins and rep proteins of our PiCV strains, respectively. Furthermore, two initiation codons (GTG and ATT) of cap gene were newly found. A cap-gene-based phylogenetic analysis showed that the strains in this study could be further divided into six groups (A, B, C, E, G, H and I) and some of our strains are closely related to worldwide strains from different types of pigeons. A large number of recombination events (31 events) were also detected in the PiCV genomes from Chinese racing pigeons. These findings suggest that PiCV strains circulating in China exhibits higher genetic diversity.