Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-temporal variations of lower tropospheric pollutants and their relation with meteorological factors in Karachi, Pakistan

Despite being one of the most populated cities globally, the air quality of Karachi is hardly ever comprehended. The present paper investigates the outdoor concentrations of 10 air pollutants, viz. NO, NO2, NOx, SO2, CO, O3, CH4, methane carbon, non-methane hydrocarbons, and total hydrocarbons at three different city sites, viz., Sohrab Goth, Defense Housing Authority, and North Nazimabad. The results demonstrate that these pollutants severely affected the city's air quality. The annual mean concentrations of both NO2 and SO2 exceeded the WHO guidelines at some study sites. The city experiences varied concentrations of major air pollutants because three types of fuel, viz. diesel, gasoline, and compressed natural gas, operate the motor vehicles in this conurbation. The study also correlates the various air pollutants with each other and with various meteorological factors. All the three oxides of nitrogen are statistically associated at all three sites with one another, with SO2 at Defense Housing Authority, with CO at North Nazimabad, and with meteorological factors at Sohrab Goth and Defense Housing Authority. Carbon monoxide is statistically associated with the meteorological factors only at North Nazimabad. The study suggests that higher air pollution in the city is due to the adoption of lenient vehicular emission standards because stringent emission standards cannot be adopted due to the non-availability of low or zero sulfur fuel. Moreover, ineffective regulation of exiting standards also contributes to higher vehicular emissions in the city.
Mesoporous Manganese Oxide/Lignin-Derived Carbon for High Performance of Supercapacitor Electrodes

This study explores the modification of lignin with surfactants, which can be used as a template to make mesoporous structures, and can also be used in combination with manganese oxide to produce manganese oxide/lignin-derived carbon. Organosolv extraction, using ethanol (70%) at 150 °C, was carried out to extract lignin from oil palm wood. Lignin was then mixed with Pluronic F-127, with and without Mn(NO3)2, and then crosslinked with acidic formaldehyde, resulting in a carbon precursor-based modified lignin. Carbonization was carried out at 900 °C to produce lignin-derived carbon and manganese oxide/lignin-derived carbon. The characterization materials included Fourier transform infrared (FTIR) spectroscopy, scanning electron microscope-energy dispersive X-ray (SEM-EDX) mapping, X-ray diffraction (XRD), and N2-sorption analysis. FTIR curves displayed the vibration bands of lignin and manganese oxide. SEM images exhibited the different morphological characteristics of carbon from LS120% (lignin with a Pluronic surfactant of 120%) and LS120%Mn20% (lignin with a Pluronic of 120% and Mn oxide of 20%). Carbon LS120% (C-LS120%) showed the highest specific surface area of 1425 m2/g with a mean pore size of 3.14 nm. The largest mean pore size of 5.23 nm with a specific surface area of 922 m2/g was exhibited by carbon LS120%-Mn20% (C-LS120%-Mn20%). C-LS120%Mn20% features two phases of Mn oxide crystals. The highest specific capacitance of 345 F/g was exhibited by C-LS120%-Mn20%.
How Chinese residents are aware of solar photovoltaic power generation

Under the global climate change and energy crisis, solar energy has become the focus of research, development, and utilization throughout the world. Therefore, an empirical study on the awareness of residents for solar photovoltaic power generation is of great significance. Based on the 330 questionnaire data, by adopting the single factor variance analysis (S-N-K test) methodology, this paper first analyzed the differences between various groups of residents from varied perspectives of Chinese residents, i.e., different ages, different education attainments, different income levels, different genders, and different industries. Then, it conducted a regression analysis of the demographic variables by using linear regression models. The results indicate that: (1) the awareness of different types of Chinese residents is significantly different; (2) education and income levels have significant impacts on their awareness. Finally, this paper proposed corresponding policy recommendations based on these findings.
A MODEL TO PREDICT THE IMPACT OF SPECIFICATION CHANGES ON CHLORIDE-INDUCED CORROSION SERVICE LIFE OF VIRGINIA BRIDGE DECKS

A model to determine the time to first repair and subsequent rehabilitation of concrete bridge decks exposed to chloride deicer salts that recognizes and incorporates the statistical nature of factors affecting the corrosion process is developed. The model expands on an existing deterministic model by using statistical computing techniques, including resampling techniques such as the parametric and simple bootstrap. Emphasis was placed on the diffusion portion of the diffusion-cracking model, but advances can be readily included for the time for corrosion deterioration after corrosion initiation. Data collected from ten bridge decks built in Virginia between 1981 and 1994 were used to model the surface chloride concentration, apparent diffusion coefficient, and clear cover depth. Several ranges of the chloride corrosion initiation concentration, as determined from the available literature, were investigated. The time to first repair and subsequent rehabilitation predicted by the stochastic model is shorter than the time to first repair and subsequent rehabilitation predicted by the deterministic model. The stochastic model is believed to more accurately reflect the true nature of bridge deck deterioration because it takes into account the fact that data for each of the parameters affecting chloride diffusion and corrosion initiation are not necessarily normally distributed. The model was validated by comparison of projected service lives of bridge decks built from 1981 to 1994 derived from the model to historical service life data for 129 bridge decks built in Virginia between 1968 and 1972. The time to rehabilitation predicted for the set of bridge decks built between 1981 and 1994 by the stochastic model was approximately 13 years longer than the normalized time to rehabilitation projected for the bridge decks built between 1968 and 1972 using historical data. The time to first repair and rehabilitation predicted by the probabilistic method more closely matches that of historical data than the time to first repair and rehabilitation predicted by the average value solution. The additional service life expected for the set of bridges built between 1981 and 1994 over those constructed from 1968 to 1972 can be attributed to the decrease in w/c ratio from 0.47 to 0.45 and slight increase in as-built cover depth from approximately 50 mm (2 in.) to 63.5 to 76 mm (2.5 to 3.0 in.).
GREY AND NEURAL NETWORK PREDICTION OF CONCRETE COMPRESSIVE STRENGTH USING PHYSICAL PROPERTIES OF ELECTRIC ARC FURNACE OXIDIZING SLAG

Various physical properties in electric arc furnace (EAF) slag will result in different concrete physical characteristics. If concrete compressive strength could be predicted using physical properties in EAF slag, both cost and time could be saved and better compressive strength could also be achieved. Since there was no previous study in which the compressive strength was predicted, the grey model (GM) and artificial neural network (ANN) were employed to predict concrete compressive strength of EAF slag in this study. When constructing the model, the minimum mean absolute percentage error (MAPE) of 1.2% and minimum mean square error (MSE) of 14 could be achieved using GMs. Using the optimum GM, it is predicted that the minimum MAPE of 0.9% and minimum MSE of 8 could be achieved. Although a goodness of fit could be obtained using ANN, it required a large quantity of data for model construction. In comparison, GM only required a small amount of data (at least 4 data) and the prediction results were far better than those of ANN. Therefore, GM could be applied successfully in predicting compressive strength when the information was not sufficient. The results also indicated that the compositions of slag could be applied on prediction of compressive strength well.
Involvement of the ACE2/Ang-(1–7)/MasR Axis in Pulmonary Fibrosis: Implications for COVID-19

Pulmonary fibrosis is a chronic, fibrotic lung disease affecting 3 million people worldwide. The ACE2/Ang-(1–7)/MasR axis is of interest in pulmonary fibrosis due to evidence of its anti-fibrotic action. Current scientific evidence supports that inhibition of ACE2 causes enhanced fibrosis. ACE2 is also the primary receptor that facilitates the entry of SARS-CoV-2, the virus responsible for the current COVID-19 pandemic. COVID-19 is associated with a myriad of symptoms ranging from asymptomatic to severe pneumonia and acute respiratory distress syndrome (ARDS) leading to respiratory failure, mechanical ventilation, and often death. One of the potential complications in people who recover from COVID-19 is pulmonary fibrosis. Cigarette smoking is a risk factor for fibrotic lung diseases, including the idiopathic form of this disease (idiopathic pulmonary fibrosis), which has a prevalence of 41% to 83%. Cigarette smoke increases the expression of pulmonary ACE2 and is thought to alter susceptibility to COVID-19. Cannabis is another popular combustible product that shares some similarities with cigarette smoke, however, cannabis contains cannabinoids that may reduce inflammation and/or ACE2 levels. The role of cannabis smoke in the pathogenesis of pulmonary fibrosis remains unknown. This review aimed to characterize the ACE2-Ang-(1–7)-MasR Axis in the context of pulmonary fibrosis with an emphasis on risk factors, including the SARS-CoV-2 virus and exposure to environmental toxicants. In the context of the pandemic, there is a dire need for an understanding of pulmonary fibrotic events. More research is needed to understand the interplay between ACE2, pulmonary fibrosis, and susceptibility to coronavirus infection.
ZTA Pipes with a Gradient Structure-Effect of the Rheological the Behavior of Ceramic Suspensions on the Gradient Structure and Characterized of the Obtained Products

This paper focuses on the verifying the possibility of producing Al2O3-ZrO2 composite pipes with a gradient structure using centrifugal slip casting method. The aim of the research is to define the correlation between the rheological properties of aqueous suspensions of ceramic powders with different solid loading and obtaining the ZrO2 phase gradient in the Al2O3 matrix. Such products, due to their unique properties, can be utilized in the transport of aggressive substances, even in extreme temperature or corrosive conditions. The suspensions and the sintered samples were characterized by: broad rheological analysis, scanning electron microscopy, X-ray diffraction, stereological analysis and Vickers hardness tests. The study reports on a series of samples produced of ceramic suspensions (70 vol.% Al2O3–30 vol.% ZrO2) differing in the total solid loading in the range of 30–55 vol.%. The results clearly indicate that obtaining the gradient structure of ceramic-ceramic composite pipes is closely related to the rheological properties of the suspensions from which the samples are cast. The phase gradient is obtainable from suspensions 30–40 vol.%, in which the possibility of moving ZrO2 particles relative to the Al2O3 is quite high—these suspensions are characterized by low viscosity and the dominance of viscous over elastic properties (G′ > G″).
Vitritis and retinal vasculitis caused by pseudorabies virus

Pseudorabies virus (PRV) is a herpesvirus of swine. PRV is also called suid herpesvirus 1 and is a member of the Alphaherpesvirinae subfamily within the family Herpesviridae. The number of PRV cases worldwide is small, but in susceptible individuals, infection with this virus has a poor prognosis. Therefore, it is urgent to improve our understanding of this disease in clinical practice to avoid misdiagnosis and to identify optimal treatments. We report a patient with PRV infection who was admitted to hospital with viral encephalitis and subsequently developed intraocular infection. Because to the lack of relevant clinical experience in the treatment of this disease, we carried out experimental treatment with good therapeutic effect. This case provides a basis for clinical diagnosis and treatment of patients with PRV.
A Adaptive Grey Fuzzy Prediction Controller Design based on the Improving Residual Error Model

1 Abstract—In this paper, based on improving residual error model, a novel adaptive grey fuzzy prediction control which combines the self-organizing fuzzy control (SOFC) with grey prediction control (GPC) is put forward. Depending on the precision of residual error model, the controller can self-adjust the combinational weights of SOFC and GPC model and prediction length by the fuzzy control equipment, so as to reach better adaptability and the dynamic characteristics. The result of the simulation shows that the controller has better dynamic characteristics and restrains interference more effectively than which of the traditional fuzzy control and the grey prediction control. Keywords—residual error model, SOFC, GPC
Automation of the CEI System for Security

This paper describes the functions to be performed by a new control system designed for the operation of the generation- transmission system of the Cleveland Electric Illuminating Company. The primary message of this paper is to show how this control system, scheduled to be in service in late 1972, is planned to improve the security of the power system through the implementation of several innovations in the areas of security analysis, trouble analysis, automatic circuit restoration, generalized operation load flow, interconnection modelling, exact economic dispatch, man-machine interfaces and display, and operator training.
A novel robust nomogram based on preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) for predicting lymph node metastasis of gastric cancer.

Background Accurate assessment of lymph node status in gastric cancer (GC) patients can help to select appropriate treatment strategies for GC, but the diagnostic accuracy of conventional methods needs to be improved. The aim of this study was to investigate the predictive value of preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) on lymph node status in GC patients and to construct a risk prediction model. Methods This study retrospectively analyzed the clinicopathological characteristics of 349 patients with GC who underwent radical gastrectomy, among which 250 patients were recruited in the training cohort and 99 patients in the independent validation cohort. Significant risk factors in univariate analysis were further identified as independent variables in multivariate logistic regression analysis, which were then incorporated and presented in a nomogram. Receiver operating characteristic (ROC) curves, Calibration curve and decision curve analysis (DCA) curves were used to evaluate the discrimination, prediction accuracy and clinical effectiveness of the model. Results Multifactorial logistic regression analysis showed that alcohol use (OR =2.203, P=0.036), Depth of invasion (OR =7.756, P<0.001), differentiation (OR =2.252, P=0.018), carcinoembryonic antigen (CEA) (OR =2.443, P=0.017), carbohydrate antigen 19-9 (CA199) (OR =2.715, P=0.008) and HALP (OR =2.276, P=0.032) were independent risk factors for lymph node metastasis (LNM) in GC. We used these factors to construct a nomogram for predicting LNM in GC patients, and the ROC curves showed good discrimination of the model with AUC values of 0.854 (training cohort) and 0.868 (validation cohort), respectively, and the calibration curves showed good predictive ability of the nomogram, in addition to the DCA curves results showed the clinical usefulness of the model. Conclusions In conclusion, we established a nomogram for predicting LNM in patients with GC.
Vision-Based Robotic Manipulation of Intelligent Wheelchair with Human-Computer Shared Control

Based on human-computer shared control, this paper introduces a novel robotic manipulation fashion combining computer vision and brain-computer interface (BCI). Designed for disabled groups, the intelligent wheelchair with our proposed method exhibits the precise robotic manipulation ability but also the human decision-making capabilities, which will bring better life quality for the disabled. The overall pipeline includes three parts: asynchronous brain-computer interface based on steady-state visual evoked potential (SSVEP), vision detection with deep network and robotic manipulation of UR5 robot. Particularly, first, the user receives the periodic visual stimulation with different frequencies and then electroencephalography (EEG) signals of the user are collected by EEG cap. Second, we preprocess the EEG signals and extract feature embedding. To judge the frequency of the stimulus signals received by the user, the canonical correlation analysis (CCA) algorithm is used to fit and compare it with the standard EEG signal. In our work, the signals with different frequencies corresponds to different types of objects item by item. Third, we apply the off-the-shelfvision detection algorithm, Mask-RCNN, to output the position of the object corresponding to the detected EEG in the image frame. UR5 robot arm plan manipulation path according to the position of objects transferred by robot operating system (ROS). Extensive experiments show that our method can achieves performance with more than 90% accuracy and the user can control the robot arm to grab the expected object accurately through BCI.
Direct comparisons of quantized Hall resistances

The quantized Hall resistances (QHRs) of three GaAs/Al/sub x/Ga/sub 1-x/As heterostructures were directly compared. Two of the three samples were grown by metalorganic chemical vapor deposition. and the third was produced by molecular beam epitaxy. A cryogenic current comparator bridge was used for the measurements. The provisional results show a residual difference lower than a few parts in 10/sup 9/ with an uncertainty of the same order. <<ETX>>
A Metaphor Recognition Model based on LSTM and Keyword Similarity Computation

Metaphor, as a common figure of speech, can reflect literary grace and profoundness to a certain extent, and is an important indicator in article appreciation. However, at present, there is no perfect application model in automatic recognition. According to the three structures and basic principles of metaphorical sentences, this paper designs a metaphorical sentence recognition model based on LSTM and keyword similarity from the perspective of the sentence itself and its syntactic structure. It solves the problems that LSTM model cannot quickly extract the feature structure of metaphorical sentences and keyword similarity computation ignores the context semantics. The word vector and part of speech tagging are input into the multi-input cyclic neural network, and a recognition method based on LSTM model is designed. On the basis of the metaphorical comparison theory, by using the extracted metaphor tenor and vehicle, this paper improves the computation method of word similarity in CNKI, and designs a recognition method based on keyword similarity. The two, LSTM and keyword similarity, are integrated, with the comprehensive consideration of metaphorical sentences in structure, semantics and context. Finally, the model is verified in the collected corpus files, thus achieving high accuracy.
Effects of Laccaria bicolor on Gene Expression of Populus trichocarpa Root under Poplar Canker Stress

Poplars can be harmed by poplar canker. Inoculation with mycorrhizal fungi can improve the resistance of poplars to canker, but the molecular mechanism is still unclear. In this study, an aseptic inoculation system of L. bicolor–P. trichocarpa–B. dothidea was constructed, and transcriptome analysis was performed to investigate regulation by L. bicolor of the expression of genes in the roots of P. trichocarpa during the onset of B. dothidea infection, and a total of 3022 differentially expressed genes (DEGs) were identified. Weighted correlation network analysis (WGCNA) was performed on these DEGs, and 661 genes’ expressions were considered to be affected by inoculation with L. bicolor and B. dothidea. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses showed that these 661 DEGs were involved in multiple pathways such as signal transduction, reactive oxygen metabolism, and plant-pathogen interaction. Inoculation with L. bicolor changed the gene expression pattern of the roots, evidencing its involvement in the disease resistance response of P. trichocarpa. This research reveals the mechanism of L. bicolor in inducing resistance to canker of P. trichocarpa at the molecular level and provides a theoretical basis for the practical application of mycorrhizal fungi to improve plant disease resistance.
CO2 Surface Variability, from the Stratosphere or Not?

Abstract. Fluctuations in atmospheric CO2 can be measured with great precision and are used to identify human-driven sources as well as natural cycles of ocean and land carbon. One source of variability is the stratosphere, where the influx of aged CO2-depleted air can produce fluctuations at the surface. This process has been speculated a potential source of interannual variability (IAV) in CO2 that might obscure the quantification of other sources of IAV. Given the recent success in demonstrating that the stratospheric influx of N2O- and chlorofluorocarbon-depleted air is a dominant source of their surface IAV in the southern hemisphere, we here apply the same model and measurement analysis to CO2. Using chemistry-transport modeling or scaling of the observed N2O variability, we find that the stratosphere-driven surface variability in CO2 is at most 10 % of the observed IAV and is not an important source. The southern hemisphere stations with multi-decadal CO2 records can provide clues to sources through the phase shifts of the IAV relative to the northern hemisphere.
Passively Adaptive Compliant Gripper

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shapes and surfaces is a very challenging task. Passively compliant underactuated mechanisms are one way to obtain the gripper which could accommodate to any irregular and sensitive grasping objects. The purpose of the underactuation is to use the power of one actuator to drive the open and close motion of the gripper. The underactuation can morph shapes of the gripper to accommodate to different objects. As a result, they require less complex control algorithms. The fully compliant mechanism has multiple degrees of freedom and can be considered as an underactuated mechanism. This paper presents a new design of the adaptive underactuated compliant gripper with distributed compliance and embedded sensors in the gripper structure. The adaptive gripper surfaces will have the sensing capability by these embedded sensors. The gripper will be made of a silicone rubber and conductive silicone rubber will be used for the embedded sensors. The main points of this paper are in explanation of the construction and production of the gripper structure and showing the methodology of a new sensing capability of the gripper.