Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting Frauds In Credit Card Using KNN And Random Forest Machine Learning Approach

: Now-a-days online transactions and e-trade platforms are grown to be necessary factor of our lives. Additionally economic fraud is the most frequently occurring problem in financial enterprise, authorities and company businesses. Fraud may be described as wrongdoer deception with movie of acquiring financial advantage. Credit card frauds are without problems targets by fraudsters. As e-commerce and some different online sites have improved the online payment transactions, increases the risk for online frauds. Credit card fraud normally occurs when the card was stolen for any of the unauthorized objectives, or even when the fraudster uses the credit card information for his use. In the project, machine learning algorithms used such as Random Forest, K-Nearest Neighbor, Local Outlier Function, K-Means Clustering. Similar set of Algorithmic program are implemented and tested utilizing an online dataset. The performance based on the accuracy and low false positive rate. Results show that each algorithm can be used for credit card detection with higher accuracy. But as compare to other algorithms, K-Nearest Neighbor is considered as the best algorithm that is used to detect fraud.
An Investigation into the Perspectives of Elementary Pre-Service Teachers on Sustainable Development

Teachers in elementary schools play a crucial role in educating children about sustainable development. Therefore, the concept of sustainable development is essential for elementary pre-service teachers to be ready for their future careers. This study used the sequential mixed methods design to investigate the relationship between the sustainable development perspectives of elementary pre-service teachers in Southern Vietnam and the current teacher training curriculum. The EDINSOST sustainability questionnaire was distributed to 392 participants in order to measure four dimensions of sustainable development: critical contextualization of knowledge, sustainable use of resources, participation in community processes, and ethics. A set of six interview questions was conducted with eight participants, focused on their understandings of sustainable development and the evaluation of the curriculum on sustainable development. Quantitative findings revealed that elementary pre-service teachers rate moderately on all dimensions; however, the knowledge is slightly higher than the behavior. Moreover, there were variations in perspectives based on pre-service teachers’ grade level and gender. Qualitative findings suggested the lack of sustainable development perspectives amongst pre-service teachers and the gaps in the teacher training curriculums regarding sustainable development. Finally, detailed discussions regarding the implementation of sustainable development in the training curriculum were provided.
Characterization of a Virally Encoded Flavodoxin That Can Drive Bacterial Cytochrome P450 Monooxygenase Activity

Flavodoxins are small electron transport proteins that are involved in a myriad of photosynthetic and non-photosynthetic metabolic pathways in Bacteria (including cyanobacteria), Archaea and some algae. The sequenced genome of 0305φ8-36, a large bacteriophage that infects the soil bacterium Bacillus thuringiensis, was predicted to encode a putative flavodoxin redox protein. Here we confirm that 0305φ8-36 phage encodes a FMN-containing flavodoxin polypeptide and we report the expression, purification and enzymatic characterization of the recombinant protein. Purified 0305φ8-36 flavodoxin has near-identical spectral properties to control, purified Escherichia coli flavodoxin. Using in vitro assays we show that 0305φ8-36 flavodoxin can be reconstituted with E. coli flavodoxin reductase and support regio- and stereospecific cytochrome P450 CYP170A1 allyl-oxidation of epi-isozizaene to the sesquiterpene antibiotic product albaflavenone, found in the soil bacterium Streptomyces coelicolor. In vivo, 0305φ8-36 flavodoxin is predicted to mediate the 2-electron reduction of the β subunit of phage-encoded ribonucleotide reductase to catalyse the conversion of ribonucleotides to deoxyribonucleotides during viral replication. Our results demonstrate that this phage flavodoxin has the potential to manipulate and drive bacterial P450 cellular metabolism, which may affect both the host biological fitness and the communal microbiome. Such a scenario may also be applicable in other viral-host symbiotic/parasitic relationships.
Bicarbonate Effects on Antibacterial Immunity and Mucus Glycobiology in the Cystic Fibrosis Lung: A Review With Selected Experimental Observations

Abstract The primary defect in cystic fibrosis (CF) is abnormal chloride and bicarbonate transport in the CF transmembrane conductance regulator epithelial ion channel. The apical surface of the respiratory tract is lined by an airway surface liquid (ASL) layer composed of mucin comprising mainly MUC5A and MUC5B glycoproteins. ASL homeostasis depends on sodium bicarbonate secretion into the airways and secretion deficits alter mucus properties leading to airway obstruction, inflammation and infections. Downstream effects of abnormal ion transport in the lungs include altered intrinsic immune defenses. We observed that neutrophils killed Pseudomonas aeruginosa more efficiently when it had been exposed to sodium bicarbonate, and formation of neutrophil extracellular traps by neutrophils was augmented in the presence of increasing bicarbonate concentrations. Physiological levels of bicarbonate sensitized P. aeruginosa to the antimicrobial peptide cathelicidin LL-37, which is present in both lung ASL and neutrophil extracellular traps. Sodium bicarbonate has various uses in clinical medicine and in the care of CF patients and could be further explored as a therapeutic adjunct against Pseudomonas infections.
Estimation of Mean in Domain When Distribution of Variable is Skewed

The problem of estimation the expected value in the case when a random variable has skewed probability distribution was considered e.g. by Carroll and Ruppert (1988), Chandra and Chambers (2006), Chen and Chen (1996), Karlberg (2000). Their results are based on transformation of skewed data. In the paper another approach is presented. The proposed estimators are constructed on the rather well known following property. Kendall and Stuart (1967) showed that the covariance between sample variance and sample mean is proportional to the third central moment of a variable. This property is applied to construction of several estimators of mean in a domain. The estimators are useful in the case when the variable under study has asymmetrical distribution because under some additional assumption they are more accurate than the sample mean. The results of the paper can be applied in survey sampling of economic populations.
Postoperative day 1 serum cystatin C level predicts postoperative delayed graft function after kidney transplantation

Background Delayed graft function (DGF) commonly occurs after kidney transplantation, but no clinical predictors for guiding post-transplant management are available. Materials and methods Data including demographics, surgery, anesthesia, postoperative day 1 serum cystatin C (S-CysC) level, kidney functions, and postoperative complications in 603 kidney transplant recipients who met the enrollment criteria from January 2017 to December 2018 were collected and analyzed to form the Intention-To-Treat (ITT) set. All perioperative data were screened using the least absolute shrinkage and selection operator. The discrimination, calibration, and clinical effectiveness of the predictor were verified with area under curve (AUC), calibration plot, clinical decision curve, and impact curve. The predictor was trained in Per-Protocol set, validated in the ITT set, and its stability was further tested in the bootstrap resample data. Result Patients with DGF had significantly higher postoperative day 1 S-CysC level (4.2 ± 1.2 vs. 2.8 ± 0.9 mg/L; P < 0.001), serum creatinine level (821.1 ± 301.7 vs. 554.3 ± 223.2 μmol/L; P < 0.001) and dialysis postoperative (74 [82.2%] vs. 25 [5.9%]; P < 0.001) compared with patients without DGF. Among 41 potential predictors, S-CysC was the most effective in the parsimonious model, and its diagnostic cut-off value was 3.80 mg/L with the risk score (OR, 13.45; 95% CI, 8.02–22.57; P < 0.001). Its specificity and sensitivity indicated by AUC was 0.832 (95% CI, 0.779–0.884; P < 0.001) with well fit calibration. S-CysC yielded up to 50% of clinical benefit rate with 1:4 of cost/benefit ratio. Conclusion The postoperative day 1 S-CysC level predicts DGF and may be used as a predictor of DGF but warrants further study.
Green Facile Synthesis of Silver-Doped Zinc Oxide Nanoparticles and Evaluation of Their Effect on Drug Release

Silver doped zinc oxide nanoparticles (ZANPs) were synthesized by the gelatin mediated and polymerized sol-gel method, and a calcination temperature of 700 °C was applied for 2 h. X-ray diffraction (XRD), FESEM, TGA, DSC, and EDS were performed to study the structure of the prepared nano-powders. Both cubic silver and hexagonal ZnO diffraction peaks were detected in the XRD patterns. The XRD results, analyzed by the size strain plot (SSP) and Scherrer methods, showed that the crystalline sizes of these nanoparticles increased as the Ag concentration increased. The results were observed via transition electron microscopy (TEM), where the particle size of the prepared samples was increased in the presence of silver. Catechin was chosen as a drug model and was loaded into the hydrogels for release studies. The drug content percentage of catechin in the hydrogels showed a high loading of the drug, and the highest rate was 98.59 ± 2.11%, which was attributed to the Zn0.97Ag0. 03O hydrogels. The swelling of the samples and in vitro release studies were performed. The results showed that Zn0.91Ag0. 09O showed the highest swelling ratio (68 ± 3.40%) and, consequently, the highest release (84 ± 2.18%) within 300 min. The higher amount of silver ions in the hydrogel structure causes it to enhance the osmotic pressure of the inner structure and increases the relaxation of the structure chain.
A Distributed Power Management Strategy for Multi-Paralleled Bidirectional Interlinking Converters in Hybrid AC/DC Microgrids

For a hybrid ac/dc microgrid (MG), bidirectional interlinking converters (BICs) enable flexible power interactions between ac and dc subgrids. In each subgrid, power sharing among diversified sources has been effectively realized by droop controllers. These power sharing concepts can also be extended to BIC applications. This paper proposes a distributed power management strategy (DPMS) for multi-paralleled BICs in the hybrid MG to avoid the overstress of a single BIC. In this strategy, each BIC is assigned with a well-devised localized distributed controller (LDC) which generates the respective power reference for the BIC. By using the LDC, BICs are allowed to exchange information with one another in the distributed communication graph. The power interactions between ac and dc subgrids can be proportionally allocated to BICs based on their different power ratings in a full distributed manner. Then the system reliability and scalability are significantly improved. Meanwhile, accurate global power sharing among all ac and dc sources in the MG would be accordingly attained. Considering the communication time delay involved in BICs, a small signal model is derived to predict the maximum tolerable delay of the studied system. The validities of the proposed DPMS and delay stability analyses are verified by a controller hardware-in-loop experimental platform.
Harmol hydrochloride dihydrate induces autophagy in neuro cells and promotes the degradation of α‐Syn by Atg5/Atg12‐dependent pathway

Abstract Harmol hydrochloride dihydrate (HHD) is a novel alkaloid salt of the natural β‐carboline harmol, which is isolated from Peganum harmala L. Here, we studied whether HHD could induce autophagy in neuro cells and investigated the underlying molecular mechanism. After incubation with HHD, the number of GFP‐LC3 puncta in cells was measured using confocal microscopy. The distribution and colocalization of autophagosomes and autolysosomes in the cells were also detected. LC3 was gathered and cultured in a medium containing HHD. Compared with control cells and cells starved for 2 h, the number of GFP‐LC3 puncta and the LC3‐II expression level were significantly increased in HHD‐treated cells (p < .05). The number of autophagosome (red) was increased and most of them were colocalized with lysosomes (green). Moreover, HHD induced the formation of puncta with Lysotracker Red positive in the L3 fat bodies (p < .05). When treated HEK cells with HHD, the protein expression level of LC3‐II was markedly increased, and the protein expression level of α‐Syn was significantly decreased (p < .05). HHD could induce the increased autophagosome in neuro cells by induction of autophagy. Moreover, HHD may promote the degradation of α‐Syn protein to protect neuro cells by inducing autophagy.
High Resolution On-Road Air Pollution Using a Large Taxi-Based Mobile Sensor Network

Traffic-related air pollution (TRAP) was monitored using a mobile sensor network on 125 urban taxis in Shanghai (November 2019/December 2020), which provide real-time patterns of air pollution at high spatial resolution. Each device determined concentrations of carbon monoxide (CO), nitrogen dioxide (NO2), and PM2.5, which characterised spatial and temporal patterns of on-road pollutants. A total of 80% road coverage (motorways, trunk, primary, and secondary roads) required 80–100 taxis, but only 25 on trunk roads. Higher CO concentrations were observed in the urban centre, NO2 higher in motorway concentrations, and PM2.5 lower in the west away from the city centre. During the COVID-19 lockdown, concentrations of CO, NO2, and PM2.5 in Shanghai decreased by 32, 31 and 41%, compared with the previous period. Local contribution related to traffic emissions changed slightly before and after COVID-19 restrictions, while changing background contributions relate to seasonal variation. Mobile networks are a real-time tool for air quality monitoring, with high spatial resolution (~200 m) and robust against the loss of individual devices.
Multi-Class Support Vector Machine

Support vector machine (SVM) was initially designed for binary classiﬁcation. To extend SVM to the multi-class scenario, a number of classiﬁcation models were proposed such as the one by Crammer and Singer (J Mach Learn Res 2:265–292, 2001). However, the number of variables in Crammer and Singer’s dual problem is the product of the number of samples ( l ) by the number of classes ( k ), which produces a large computational complexity. This chapter sorts the existing classical techniques for multi-class SVM into the indirect and direct ones and further gives the comparison for them in terms of theory and experiments. Especially, this chapter exhibits a new Simpliﬁed Multi-class SVM (SimMSVM) that reduces the size of the resulting dual problem from l × k to l by introducing a relaxed classiﬁcation error bound. The experimental discussion demonstrates that the SimMSVM approach can greatly speed up the training process, while maintaining a competitive classiﬁcation accuracy.
Influence of continuous inspiratory resistive breathing trials on corticospinal excitability of lower limb muscles during isometric contraction

ABSTRACT BACKGROUND Increased work of breathing or fatigue of respiratory muscles has been suggested to reduce exercise performance. PURPOSE The present study investigated the effects of continuous inspiratory resistive breathing (IRB) on the responsiveness of corticospinal pathway innervating the vastus lateralis (VL) to determine whether respiratory muscle fatigue affects the central motor output to exercising limb muscles. METHODS Eight subjects underwent a 6-min IRB trial three times (IRB1–3) in two experiments. During each IRB trial, the subjects performed voluntary hyperventilation through a mask attached with an inspiratory resistive load (approximately 30% of maximal inspiratory pressure (PImax)). In Experiment 1, PImax was measured at baseline and after each IRB trial. In Experiment 2, VL responses to transcranial magnetic stimulation (motor evoked potentials (MEPs) and cortical silent periods were assessed during 5 s isometric knee extension at an intensity of 15% of the maximal voluntary contraction over the same time course as in Experiment 1. RESULTS PImax decreased from baseline after IRB2 and IRB3 (P < 0.05). MEPs increased from baseline after IRB1 and IRB2 (P < 0.05), whereas MEPs after IRB3 were not significantly different from baseline. Cortical silent periods did not change from baseline after IRB1 and IRB2, whereas cortical silent periods after IRB3 increased from baseline (P < 0.05). CONCLUSION These results suggest that as inspiratory muscle fatigue progresses, the corticospinal tract controlling the lower limb muscles can shift from excitatory dominance to inhibitory dominance as a whole, affecting the central motor output to working limb muscles.
Monitoring In Situ Microbial Growth and Decay in Soil Column Experiments by Induced Polarization

Real‐time monitoring of the microbial activity in porous media faces considerable challenges because conventional analytical procedures are intrusive. Induced polarization has shown promises as a non‐intrusive monitoring approach for such processes. However, quantitative analysis of soil column experiments to show how IP‐based parameters can be related to the density of bacteria is still lacking. The evolution of bacterial density and the induced polarization was performed in soil‐packed column experiments using Pseudomonas aeruginosa O1. A quantitative relationship between the quadrature conductivity and the bacterial density was established and further applied to assess the bacterial growth and decay, and infer the Monod kinetic parameters. The Monod kinetic parameters inferred from the column experiments mimicking field conditions were different to those obtained from the batch experiments.
Deep Convolutional Neural Networks for Link Adaptations in MIMO-OFDM Wireless Systems

This letter proposes a deep convolutional neural network (DCNN) approach for adaptive modulation and coding in practical multiple-input, multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems. Our target is to maximize the throughput and fulfill a packet error rate constraint. We consider practical impairments of MIMO-OFDM receiver, such as imperfect timing synchronization, carrier frequency offset correction, and channel estimation. We treat the estimated channel state information and the noise standard deviation as input features to the DCNN. The main advantages of the proposed approach are: 1) it learns the characteristics of the MIMO-OFDM channel properly and predicts the suitable modulation and coding scheme and 2) it does not need complex features selection.
Backyard Hydroclimatology: Citizen Scientists Contribute to Drought Detection and Monitoring

The Community Collaborative Rain, Hail and Snow (CoCoRaHS) network is a well-regarded, trusted source of precipitation data. The network’s volunteers also provide weather and climate observations through daily comments, significant weather reports, and condition monitoring reports. Designed to meet a need for local information about drought events and their impacts, “condition monitoring” was initiated as a pilot project in North Carolina and South Carolina in 2013 and launched nationally in October 2016. Volunteers regularly report on how precipitation, or a lack thereof, affects their local environment and community by ranking current conditions on a 7-point scale ranging from severely dry to severely wet and sharing observations through written narratives. This study assesses the usefulness of these reports for drought monitoring and decision making, drawing from the >7,100 reports submitted in the Carolinas between October 2016 and June 2020. This period encompasses the Carolinas’ climate patterns and extreme events such as droughts, wildfires, and hurricanes (“drought-busters”). Three aspects of usefulness were evaluated in the reports: the extent to which volunteers’ assessments of dry-to-wet conditions correspond to objective drought indicators (EDDI, SPI, SPEI) typically employed for monitoring drought; how volunteers’ qualitative observations depict changing conditions, focusing on two flash droughts in 2019; and actual use of the reports by National Weather Service offices, State Climate Offices, U.S. Drought Monitor authors, and drought response committees. Although report content can vary widely, findings show that volunteers’ assessments reflect meteorological conditions and provide on-the-ground details that are being incorporated into existing drought monitoring processes.
The effect of aging on identification of Mandarin consonants in normal and whisper registers

Consonant perception in older adults has been widely explored in recent years. However, how aging affects the identification of Mandarin consonants, especially in whispered condition, are under studied. Mandarin consonants and whispering speech have unique features, which may result in different identification difficulties for older adults. The current study investigated older adults' identification of Mandarin consonants in phonated and whispered conditions in comparison with the performance of younger adults. It was found that in phonated condition, older adults showed the lowest accuracy for affricatives and fricatives owing to their insensitivity to high-frequency information. The lower accuracy of affricatives and plosives was largely attributed to the difficulty in recognizing articulatory places. Identifying aspirated plosives was much more difficult than unaspirated counterparts for older adults. In whispered condition, the recognition of voiced consonants and aspirated-unaspirated distinction became challenging, especially for older adults. Contrary to the expectation, some consonants became easier to be recognized in the whispered condition, i.e., /ph, tɕh, x/. These findings enrich our understanding of how aging affects consonant identification in different languages and less ideal conditions. It also suggests that the listener's ability, language uniqueness, and characteristics of distorted speech should be all taken into consideration when investigating speech perception in adverse conditions.