Miracle-dz/UniFAR-FTUs huggingface dataset:
Biochanin A Mitigates Atherosclerosis by Inhibiting Lipid Accumulation and Inflammatory Response

Biochanin A (BCA), a dietary isoflavone extracted from red clover and cabbage, has been shown to antagonize hypertension and myocardial ischemia/reperfusion injury. However, very little is known about its role in atherogenesis. The aim of this study was to observe the effects of BCA on atherosclerosis and explore the underlying mechanisms. Our results showed that administration of BCA promoted reverse cholesterol transport (RCT), improved plasma lipid profile, and decreased serum proinflammatory cytokine levels and atherosclerotic lesion area in apoE−/− mice fed a Western diet. In THP-1 macrophage-derived foam cells, treatment with BCA upregulated ATP-binding cassette (ABC) transporter A1 (ABCA1) and ABCG1 expression and facilitated subsequent cholesterol efflux and diminished intracellular cholesterol contents by activating the peroxisome proliferator-activated receptor γ (PPARγ)/liver X receptor α (LXRα) and PPARγ/heme oxygenase 1 (HO-1) pathways. BCA also activated these two signaling pathways to inhibit the secretion of proinflammatory cytokines. Taken together, these findings suggest that BCA is protective against atherosclerosis by inhibiting lipid accumulation and inflammatory response through the PPARγ/LXRα and PPARγ/HO-1 pathways. BCA may be an attractive drug for the prevention and treatment of atherosclerotic cardiovascular disease.
Mapping cancer: the potential of cartograms and alternative map displays

Cancer atlases communicate cancer statistics over geographic domains, typically with a choropleth map. A choropleth map subdivides these domains into administrative regions such as countries, states, or suburbs. When communicating human-related statistics, the choropleth has a disadvantage in that it draws attention to sparsely populated rural areas to the neglect of small inner-city areas. The smaller geographic areas are important to consider if they are densely populated. Alternative map displays, such as a cartogram or a hexagon tile map, can shift the attention of map users from the large rural areas by decreasing their size on the map display. This means alternative displays can be more effective at accurately communicating spatial patterns across spatial areas. This study summarizes current practices for cancer atlases and investigates the alternative map displays that could be used to accurately represent the distribution of cancer statistics across a population, as many cancer atlases lack appropriate displays for population statistics. It is recommended that alternative displays are included in cancer atlases for a perceptually accurate display of the distribution of the burden of cancer over the population, in addition to the familiar choropleth map, if possible given time and budget constraints. With the ease of today’s technology, user interaction with the displays is also encouraged. Users should also be able to interactively display different statistics, such as incidence rate or relative incidence, or filter by demographic variables.
Integrated Yoga and Naturopathy Management (IYNM) of Obesity: A Case Report

A 45-year-old male patient with the nature of sedentary lifestyle, diagnosed with obesity (BMI33.2 kg/m2) since 2013, was visited for Integrated Yoga and Naturopathy Management (IYNM) for the weight reduction in our hospital on November 2019. He had mild pain over the both knees with sleeping disturbances. We advised him a tailor made individualized protocol for the weight management for the period of 6 months. The results showed reduction in weight (107.9kg to 90.6kg), Body Mass Index (BMI) (33.2kg/m2 to 29.32kg/m2), total cholesterol (209mg% to 185mg%), triglycerides (172mg% to 113mg%), Low Density Lipoprotein (LDL) (102mg% to 94mg%), and High Density Lipoprotein (HDL) (44mg% to 48mg%). His knee pain minimized on discharge as observed on a Visual Analog Scale (7 to 3 points). He had an improved feeling of wellness and overall functional health. This case report suggests that lifestyle change in the form of IYNM is useful in the management of Obesity. ABSTRACT *Corresponding author
QUALIDADE DO MOBILE BANKING NA PERSPECTIVA DOS USUÁRIOS

O presente estudo buscou avaliar a qualidade dos servicos via Mobile Banking, na perspectiva dos usuarios, por meio da relacao entre importância e desempenho dos servicos bancarios. A metodologia da pesquisa segue uma abordagem quantitativa, com caracteristica descritiva, junto a uma amostra de 95 entrevistados. Os dados foram coletados de forma nao probabilistica e por conveniencia. O instrumento de pesquisa foi adaptado do modelo SERVQUAL, desenvolvido por Parasuraman, Zeithaml e Berry (1988). A analise dos dados foi realizada por meio de tecnicas estatisticas descritivas (frequencia e media), com o auxilio do software estatistico Statistical Package for the Social Sciences (SPSS), versao 20.0. Os resultados indicam que a importância na percepcao da qualidade atribuida pelos usuarios e maior do que o desempenho do servico prestado, em todas as dimensoes do modelo, com os maiores gaps nas dimensoes Empatia (-1,02), Confiabilidade (-1,01) e Responsividade (-1,00).
Multi-Compartment Vehicle Routing Problem to Find the Alternative Distribution Route of Petroleum Product Delivery

Distribution is an activity that the firm has to do to deliver their product to the customers. The product has to deliver to the customers on the right condition, at the right time, and with the minimal cost of delivery. This paper focuses to solve the planning distribution problem on petrol product delivery or Petrol Station Replenishment Problem. One of the ways to solve the planning distribution is VRP (Vehicle Routing Problem). VRP aims to find the minimal total cost delivery with some constraints depend on the factory. In this research, VRP is used by the distribution center to find the optimal route of distribution of petrol products. Using Multi-Compartment Vehicle Routing Problem (MC-VRP) that considers the demand for the petrol product, tank-truck capacity, distribution cost, and the number of the compartment. In this work, a mathematical formulation for MC-VRP is developed in the Mixed Integer Linear Programming (MILP) model. Using Ilog Cplex with branch and bound algorithm to solve this distribution problem with the minimum total distribution cost. There are 10 customers with different distances, different time deliveries and different travel costs in this research. The mathematic formulation produces the best alternative that is Rp 1.898. 584 to deliver products from depot to the customers.
An Efficient Denoising Architecture of MVD-RCA-SP-FIR filter for Real-time ECG signals

Electrocardiogram (ECG) is non-stationary, non-periodic real-time signal. It is provided to use full electrical information about heart functioning. It means by the analysis of ECG signal; we can identify any living person's hearts are working properly or not. In recent years there is a huge demand for the reduction of size and power of portable devices used for monitoring critical signals such as ECG. The technical advancements in VLSI have created a huge impact on biomedical signal processing. VLSI circuits working at high speed and these can be designed to consume less area and power. Especially for ECG signal denoising, digital filters such as FIR and IIR are used in most of the applications. Finite Impulse Filters (FIR) are used widely compared to IIR filters because of their good stability and high order. In this paper, FIR filter with modified Vedic multiplier-based architecture is introduced to carry out ECG signal denoising application. In this paper at first resource-efficient Vedic multiplier is introduced which is around 55% area-efficient for 8 bit, 15% efficient in terms of delay, and 45% efficient in terms of power in comparisons of the latest design proposed in 2020. Then with the help of a modified Vedic multiplier, FIR is developed which is also efficient in terms of resources. It has 40.5% better ADP and around 20% better APP. This latest design of the filter is much helpful for ECG signal denoising.
Motion Planning for Connected Automated Vehicles at Occluded Intersections With Infrastructure Sensors

Motion planning at urban intersections that accounts for the situation context, handles occlusions, and deals with measurement and prediction uncertainty is a major challenge on the way to urban automated driving. In this work, we address this challenge with a sampling-based optimization approach. For this, we formulate an optimal control problem that optimizes for low risk and high passenger comfort. The risk is calculated on the basis of the perception information and the respective uncertainty using a risk model. The risk model combines set-based methods and probabilistic approaches. Thus, the approach provides safety guarantees in a probabilistic sense, while for a vanishing risk, the formal safety guarantees of the set-based methods are inherited. By exploring all available behavior options, our approach solves decision making and longitudinal trajectory planning in one step. The available behavior options are provided by a formal representation of the situation context, which is also used to reduce calculation efforts. Occlusions are resolved using the external perception of infrastructure-mounted sensors. Yet, instead of merging external and ego perception with track-to-track fusion, the information is used in parallel. The motion planning scheme is validated through real-world experiments.
Effect of pesticides on cellulose degradation in soil under upland and flooded conditions

Abstract The effect of pesticides on cellulose degradation in a soil was estimated by incubation experiments under upland conditions, transitional flooded conditions from aerobic to anaerobic, and fully anaerobic flooded conditions. Pesticides examined were trichlamide [(RS)-N-(1-butoxy-2,2,2-trichIoroethyl)salicyl-amide], chlorothalonil (TPN, 2,4,5,6-tetrachloro-1,3-isophthalonitrile), quin-tozene (PCNB, pentachloronitrobenzene), and hymexazol (3-hydroxy-5-meth-ylisoxazol) as fungicides, paraquat (1,1′-dimethyl-4,4′-bipyridium dichloride), thiobencarb (benthiocarb, S-p-chlorobenzyldiethyl thiocarbamate), propanil (DCPA, 3′,4′-dichloropropionanilide), and butachlor [2-chloro-2′,6′-diethyI-N-(butoxymethyl)acetoanilide] as herbicides, and diazinon (2-isopropyl-4-niethyl-pyrimidyl-6-diethylthiophosphate) as insecticide. Trichlamide inhibited completely the cellulose degradation under the two flooded conditions, while the inhibition under upland conditions was weak. The inhibition by chlorothalonil was strong.
Fabrication of Magnetic Tunnel Junctions with Amorphous CoFeSiB Ferromagnetic Electrode for Magnetic Field Sensor Devices

The magnetic tunnel junctions (MTJs) with a soft magnetic CoFeSiB amorphous electrode and a MgO barrier layer were fabricated. A double annealing process was carried out to obtain the linear resistance response to the external magnetic field. The effect of the annealing temperature on the sensitivity of magnetic sensors was systematically investigated. We achieved a high sensitivity of 40%/Oe, where the sensitivity is defined as TMR/(2Hk), where TMR is the tunnel magnetoresistance ratio and Hk is the magnetic anisotropy field of the free layer of MTJs.
A software‐defined networks‐based measurement method of network traffic for 6G technologies

In software‐defined networks (SDN) for 6G technologies, the controller should accurately and efficiently measure the flow traffic in switches for traffic engineering. Fine‐grained flow measurement can more accurately describe the traffic in the network, but it also consumes much more resources. To reduce the overhead incurred in the measurement process and obtain the approximate fine‐grained measurements, we propose a novel lightweight measurement scheme that runs in the controller. The novel lightweight measurement architecture consists of two parts: coarse‐grained measurement and interpolation‐optimization. In the first part, based on the SDN architecture, we use the pull‐based random sampling method to quickly obtain the coarse‐grained measurement of flow traffic through OpenFlow protocol. In the second part, we insert some discrete values into the coarse‐grained measurement with the interpolation theory, then we optimize interpolation results until finding the optimal fine‐grained flow traffic measurement by utilizing the multiconstraint method. We verified the feasibility of the proposed measurement method, and simulation results show that the measurement error of the proposed method is under 25%, but the flow measurement overhead of this method occupies only 3.3% compared with that of the fine‐grained method.
Likelihood‐based inference for spatiotemporal data with censored and missing responses

This paper proposes an alternative method to deal with spatiotemporal data with censored and missing responses using the SAEM algorithm. This algorithm is a stochastic approximation of the widely used EM algorithm and is an important tool for models in which the E‐step does not have an analytic form. Besides the algorithm developed to estimate the model parameters from a likelihood‐based perspective, we present analytical expressions to compute the observed information matrix. Global influence measures are also developed and presented. Several simulation studies are conducted to examine the asymptotic properties of the SAEM estimates. The proposed method is illustrated by environmental data analysis. The computing codes are implemented in the new R package StempCens.
Household food insecurity and associated socio-economic factors among recent Syrian refugees in two Canadian cities

In Canada, the prevalence of food insecurity is high among low-income households, particularly recent refugees. We evaluated the prevalence of food security among recent Syrian refugees and the associated factors in two Canadian cities, Toronto and Saskatoon. We collected data using the Household Food ‎Security Model, sociodemographic and socioeconomic questionnaires from 151 families. 84% of the Syrian households were food insecure, with no significant difference in prevalence between Saskatoon and Toronto. The risk of food insecurity was four ‎times higher for households with the annual income below $40,000. Households with educated woman (high school or higher) had four times higher risk of household food insecurity compared to families with less-educated women. ‎Our findings indicate the high prevalence of food insecurity among recently resettled Syrian refugees in Canada. Higher-income directly associated with food security. The inverse association between education and food security in households with highly educated women warrants further investigation.
The Impact of a Twelve-Month Comprehensive Program of Cognitive Training for Alzheimer Patients: A Pilot Study

Research has shown that non-pharmacological therapies can be useful in the treatment of Alzheimer’s disease (AD), significantly delaying cognitive decay. However, most AD interventions did not last beyond six months. Hence, little is known about the effect of these programs in the AD patients after six months of treatment. The purpose of this study was to evaluate the efficacy of the twelve-month Comprehensive Program of Cognitive Training (CPCT) for a sample of AD patients and to compare the results with the average annual rate of change. Thirty-nine AD patients participated in the study. The CPCT consists of a set of cognitive stimulations, intervention in activities of daily life (ADL), and motor training for 12 months. All patients were evaluated at baseline and in three-month intervals via the Mini Mental State Examination (MMSE), the Cambridge Cognitive Examination (CAMCOG), the Lawton Instrumental Activities of Daily Living Scale (IADL), and the Global Deterioration Scale (GDS). After CPCT implementation, there were no significant differences in the MMSE, IADL, and GDS evaluations between baseline and twelve months. Concerning the CAMCOG evaluation, there was no significant difference between the baseline and sixth-month assessments. Overall, the participants’ cognitive functioning did not decline when compared to the average annual rate of change. The CPCT extends the benefit of non-pharmacological interventions for AD patients to twelve months. Its implementation might provide the patients’ relatives with some guarantee concerning the delay of the disease. Future research may investigate the efficacy of the CPCT in comparison with a control group and over a more extended period.
Automated Well Correlation using Machine Learning and Facial Recognition Techniques

This paper outlines the study results of machine learning application to automate well correlation. Algorithms are designed to address challenges such as geological field complexity, number of wells and geological horizons, and quality of log data, that are usually associated with well correlation The Kansas state oil and gas fields, USA has more than 350000 wells and produced over 5 billion barrels of oil, with an estimated 11 billion barrels of oil still remaining underground. Nearly 100 wells from Thomas, Scott, Logan, Barton, Stafford and Wichita Counties are selected for this study. Petrophysical data such as Gama Ray, Neutron, and Density logs, considered most sensitive for lithology and Geological Cores descriptions are used as input. Sedimentary facies variation from limestone, shale, sandstone and coal were used as indicators to separate stratigraphic sequences. The approach followed is a 1D adaptation of panoramic stitching using feature vectors generated from a 1D Convolution Autoencoder. Convolutional autoencoders learn a compressed representation of input by first compressing the input using encoder and decompressing it back using decoder to match the original output This autoencoder is a neural network trained to reproduce input image in output layer, similar to facial recognition techniques. It identifies a series of matching points between a pair of well logs and trained to pick and match geological well tops. In order to demonstrate the performance of algorithms in term of accuracy, speed and to address the range of uncertainties, more than 30 wells were used for training. The study results have demonstrated high level of constancy in automatically subdividing the reservoir units of different wells consistent with stratigraphy and consistent across wells even though distance separating for each individual well is considerably more than one kilometer.
A comparative XPS surface study of Li2FeSiO4/C cycled with LiTFSI- and LiPF6-based electrolytes

X-Ray photoelectron spectroscopy (XPS) has been used to characterise the surfaces of carbon-coated Li2FeSiO4 cathodes extracted from Li-ion batteries in both a charged and discharged state. 1 M lithium bis(trifluoromethylsulfonyl)imide (LiTFSI) and lithium hexafluorophosphate (LiPF6) based electrolytes were used with ethylene carbonate (EC) and diethyl carbonate (DEC) as organic solvents. The LiTFSI-based electrolyte exhibited high salt stability and no significant formation of LiF. However, solvent reaction products from EC were found together with lithium carbonate. A LiPF6-based electrolyte, on the other hand, showed inferior salt stability with LixPFy, LixPOyFz and LiF species formed on the surface. Solvent reaction products together with lithium carbonate were also found. There are also indications that Li2FeSiO4 is degraded by the HF formed in the electrolyte by the hydrolysis of LiPF6. A better understanding of the surface chemistry of carbon-coated Li2FeSiO4 after the first cycles in a Li-ion battery has thus been achieved, thereby facilitating the optimisation of Li-ion batteries based on this potentially cheap and electrochemically most promising cathode material giving excellent capacity retention: <3% drop over 120 cycles.
Fuzzy Integration to Standard Calculation of K-Nearest Neighbour Attributes

The development of information and data in the era of the industrial revolution 4.0 is very fast. Researchers, institutions and even industry are competing to find and utilize methods in data processing that are more effective and efficient. In data mining classification, there are several best methods and are widely used by researchers. One of them is K-Nearest Neighbor (KNN). The calculation process in the KNN algorithm is carried out by comparing the testing data to all existing training data. This comparison is generally symbolized by the value of closeness or similarity between attribute records. The KNN method is proven to be good for handling large datasets and datasets with many attributes. One of the drawbacks in calculating the similarity of the KNN is that if there are attributes with a large range value, the similarity value will also be large. Conversely, if the range in an attribute is small, the similarity is also small. This condition is clearly unfair considering the types of attributes in the current data vary widely. One solution to this problem is to use standardization for all existing data attributes. Fuzzy is a model introduced by Prof. Zadeh which allows a faint value to be a value between 1 and 0. In this study the fuzzy model will be integrated in the KNN similarity calculation to obtain standardization of all data attributes. The results show that the use of the KNN algorithm in the classification of credit approval has an accuracy rate of 91.83%.
Oxidation behavior of aluminum nitride

The evaluation of the thermal stability of three different fully dense AlN materials in the temperature range of 600 °C to 1400 °C in air indicates the strong effect of the starting composition on the oxidation process. The oxidation resistance of pure AlN and Y_2O_3-doped AlN was found to be good up to ≍1350 °C. The kinetics are linear (1100 ≤ T ≤ 1400 °C) and the process is governed by a surface reaction that gives rise to the formation of a porous, nonprotective oxide scale, where Al_2O_3 and Y-aluminates (i.e., AlN–Y_2O_3) have been found as crystalline reaction products. For AlN-CaC_2, higher oxidation rates indicate that the outward migration of Ca modifies the reaction mechanisms. Linear kinetics in the range 1100 ≤ T ≤ 1200 °C are followed by parabolic kinetics at higher temperatures ( T > 1250 °C); with regard to the latter behavior, an activation energy of 160 kJ/mole could indicate the diffusion of oxygen through the oxidation scale as the rate-controlling mechanism.
Increased colluvial hollow discharge and subsequent recovery after a low intensity wildfire in the Blue Ridge Mountains, USA

Wildfires in mountainous regions have been documented to enhance water repellent soils which can increase runoff, erosion, and sedimentation during subsequent rain events. However, the extent of soil hydrophobicity and water repellency varies significantly with burn severity and between ecosystems, and the southern Appalachians remain an understudied region. Here we examine the impact of the low severity Chestnut Knob Fire, which occurred in the fall 2016, on soil properties and runoff in South Mountains State Park. To examine these impacts, we installed crest‐stage gauges in burned (n = 10) and unburned (n = 8) colluvial hollows to compare peak runoff. Results from the 2017 field season indicated that burned locations produced significantly higher peak discharges than unburned sites. From July 2019 to January 2020, we repeated the experiment and found that burned areas produced runoff comparable to unburned areas. Examination of soil profiles during the summer of 2017 found high variability in hydrophobicity in both the burned (n = 10) and unburned (n = 2) soils. Further, we found that burned soils had significantly deflated organic surface horizons compared with unburned soils. We interpret the differences in runoff in 2017 to be the result of a combination of increased hydrophobicity and decreased soil moisture storage capacity in organic rich surface soils. While the recovery we observed here was relatively fast, it is important to understand that increased runoff immediately after a fire likely increases the chances of sediment mobilization and debris flow occurrence.