Miracle-dz/UniFAR-FTUs huggingface dataset:
The environmental impact of engineered nanomaterials

Nanoparticles are important in natural environments due to their size, tunable properties and accessible surfaces and our control over these properties can be exploited to create or add value to a variety of technologies.Many consumer products that incorporate nanoparticles, such as sunscreens and clothing, are already in the marketplace, and the industry is growing fast. This book highlights also the many valuable environmental technologies that can come from the applications of unique nanomaterial properties. As this nascent technology area matures, the debate about the whether the unknown risks of nanomaterial use balances its established benefits will only intensify.
Praziquantel-encapsulated niosomes against Schistosoma mansoni with reduced sensitivity to praziquantel

Abstract Introduction: Praziquantel (PZQ) is the only commercially available drug for schistosomiasis. The current shortage of alternative effective drugs and the lack of successful preventive measures enhance its value. The increase in the prevalence of PZQ resistance under sustained drug pressure is, therefore, an upcoming issue. Objective: To overcome the tolerance to PZQ using nanotechnology after laboratory induction of a Schistosoma mansoni isolate with reduced sensitivity to the drug during the intramolluscan phase. Materials and methods: Shedding snails were treated with PZQ doses of 200 mg/kg twice/ week followed by an interval of one week and then repeated twice in the same manner. The success of inducing reduced sensitivity was confirmed in vitro via the reduction of cercarial response to PZQ regarding their swimming activity and death percentage at different examination times. Results: Oral treatment with a single PZQ dose of 500 mg/kg in mice infected with cercariae with reduced sensitivity to PZQ revealed a non-significant reduction (35.1%) of total worm burden compared to non-treated control mice. Orally inoculated PZQ- encapsulated niosomes against S. mansoni with reduced sensitivity to PZQ successfully regained the pathogen’s sensitivity to PZQ as evidenced by measuring different parameters in comparison to the non-treated infected animals with parasites with reduced sensitivity to PZQ. The mean total worm load was 1.33 ± 0.52 with a statistically significant reduction of 94.09% and complete eradication of male worms. We obtained a remarkable increase in the percentage reduction of tissue egg counts in the liver and intestine (97.68% and 98.56%, respectively) associated with a massive increase in dead eggs and the complete absence of immature stages. Conclusion: PZQ-encapsulated niosomes restored the drug sensitivity against laboratory- induced S. mansoni adult worms with reduced sensitivity to PZQ.
Denoising Method and Fault Diagnosis of Rotating Machinery Vibrating Signal Based on Second Generation Wavelet Transform

There is different characteristics of signal in the fault vibrating signal of rotating machiner- y.In the denoising of traditional wavelet tansform,the result of wavelet decomposing is related with wave- let basis function.And the adopted wavelet which is ill-suihed for original signal can delute the local char- acteristic of vibrating signal ,and lost some useful detail information of original signal.In order to over- come mentioned limitation,a pre-processing method based on second generation wavelet transform for vi- brating signal is adopted.According to the local characteristics of signal and the selection criterion of minimizing the squared error ,an optimal predicting operator is selected for a transforming sample so that the used wavelet basis function can always fit the local characteristics of the signal.The simulation showed that the proposed method could overcome the denoising disadvantage of traditional wavelet transform.It not only can filter noise from original signal effectively,but also can hold local characteristics of original signal in the denoised signals.
Sentiment Analysis and Emotion Detection on Cryptocurrency Related Tweets using Ensemble LSTM-GRU Model

The cryptocurrency market has been developed at an unprecedented speed over the past few years. Cryptocurrency works similar to standard currency, however, virtual payments are made for goods and services without the intervention of any central authority. Although cryptocurrency ensures legitimate and unique transactions by utilizing cryptographic methods, this industry is still in its inception and serious concerns have been raised about its use. Analysis of the sentiments about cryptocurrency is highly desirable to provide a holistic view of peoples’ perceptions. In this regard, this study performs both sentiment analysis and emotion detection using the tweets related to the cryptocurrency which are widely used for predicting the market prices of cryptocurrency. For increasing the efficacy of the analysis, a deep learning ensemble model LSTM-GRU is proposed that combines two recurrent neural networks applications including long short term memory (LSTM) and gated recurrent unit (GRU). LSTM and GRU are stacked where the GRU is trained on the features extracted by LSTM. Utilizing term frequency-inverse document frequency, word2vec, and bag of words (BoW) features, several machine learning and deep learning approaches and a proposed ensemble model are investigated. Furthermore, TextBlob and Text2Emotion are studied for emotion analysis with the selected models. Comparatively, a larger number of people feel happy with the use of cryptocurrency, followed by fear and surprise emotions. Results suggest that the performance of machine learning models is comparatively better when BoW features are used. The proposed LSTM-GRU ensemble shows an accuracy of 0.99 for sentiment analysis, and 0.92 for emotion prediction and outperforms both machine learning and state-of-the-art models.
Effect of probiotic Lactobacillus paracasei on tumor necrosis factor-alpha level in gingival crevicular fluid of patients undergoing impacted third molar removal.

PURPOSE This study was conducted to evaluate the effects of the probiotic Lactobacillus paracasei in patients undergoing removal of impacted mandibular third molars, focusing on tumor necrosis factor alpha (TNF-α) levels in gingival crevicular fluid, pain, swelling, trismus, and interincisal distance. METHODS Thirty patients were divided into two groups: (1) wound irrigation with the probiotic, and (2) irrigation with 0.9% normal saline. The data were collected at the baseline, and at 24 h and 7 days after the operation. The TNF-α level in gingival crevicular fluid was determined using the ELISA technique. RESULTS In the experimental group, the probiotic L. paracasei MSMC39 reduced the TNF-α level in gingival crevicular fluid to a significantly greater degree than in the control group (P < 0.05). Pain, swelling and trismus evaluated in terms of a visual analog scale (VAS) score were lower in the experimental group than in the control group, but not to a statistically significant degree (P > 0.05). The mean interincisal distance in the experimental group was higher than that in the control group (P = 0.014). CONCLUSION The probiotic L. paracasei is able to reduce the level of TNF-α in gingival crevicular fluid and can ameliorate postoperative complications after mandibular molar removal.
The Formation of the North Qilian Shan through Time: Clues from Detrital Zircon Fission-Track Data from Modern River Sediments

Understanding the formation of the North Qilian Shan in the NE Tibetan Plateau provides insights into the growth mechanisms of the northern region of the plateau across time. Detrital zircon fission-track (ZFT) analyses of river sediments can provide a comprehensive understanding of the exhumation history during prolonged orogenesis. Here, we applied the detrital thermochronology approach to the Qilian Shan orogenic belt. This work presents the first single-grain detrital ZFT data from river-bed sediments of the upper Hei River catchment in North Qilian Shan. The single ZFT ages are widely distributed between about 1200 Ma and about 40 Ma. These data record the protracted history of the Qilian Shan region from the Neoproterozoic evolution of Rodinia and late Paleozoic amalgamation of Central Asia to the accretion of the Gondwanian blocks during the Meso-Cenozoic era. Strong post-magmatic cooling events occurred in North Qilian Shan at 1200~1000 Ma, corresponding to the assembly of the Rodinia supercontinent. The age population at 800 Ma documents the oceanic spreading in the late Neoproterozoic dismantling of Rodinia. ZFT ages ranging from about 750 Ma to 550 Ma (with age peaks at 723 Ma and 588 Ma) are consistent with the timing of the opening and spreading of the Qilian Ocean. The age peaks at 523 Ma and 450 Ma mark the progressive closure of that ocean ending with the collision of the Qilian block with the Alxa block—North China craton in the Devonian. The Qilian Ocean finally closed in Late Devonian (age peak at 375 Ma). In the late Paleozoic (275 Ma), the subduction of the Paleotethys Ocean led to extensive magmatic activity in the North Qilian Shan. During the Lower Cretaceous (145 Ma), the accretion of the Lhasa block to the south (and potentially the closure of the Mongol-Okhotsk Ocean to the northeast) triggered a renewed tectonic activity in the Qilian Shan. Finally, a poorly defined early Eocene exhumation event (50 Ma) suggests that the NE Tibetan Plateau started to deform nearly synchronously with the onset of the India-Asia collision. This study demonstrates the usefulness of combining modern-river detrital thermo-/geochronological ages and bedrock geochronological ages to understand large-scale orogenic evolution processes.
Tray Based Millimeter-wave Quasi-Optical Amplifiers and Dual Polarized Phased Arrays

Al-Zayed, Ayman S. , Tray Based Millimeter-wave Quasi-Optical Amplifiers and Dual Polarized Phased Arrays. ( Under the direction of Amir Mortazawi.) At millimeter wavelengths, spatial power combining techniques offer a viable approach to realize compact, reliable, lightweight, robust, higher-power and economical systems This work focus on the tray based perpendicularly fed array systems, several design issues such as bandwidth improvement, power combining efficiency, dual polarity and beam steering were addressed in this thesis. A broadband tray based spatial power amplifier that employs dielectrically filled miniature horn arrays was investigated. Bandwidth improvement was achieved by replacing the patch arrays of an earlier design with the broadband dielectrically filled miniature horn arrays. This 5x5 spatial power amplifier with miniature horn arrays has a 3dB bandwidth of 1.32 GHz (13%), which is more than 4.5 times the 3 dB bandwidth of the perpendicularly fed patch array spatial power amplifier. This work presents experimental and numerical investigations on a 49-element Ka-band amplifier array. This study is aimed at determining the origin of various losses in the amplifier array. Passive simulation data confirms that the load seen by the active devices is well matched and that most of the power is coupled to the LSE10 mode. This means that coherent power combining should take place if there is no phase and amplitude variation due to the active devices and phase correcting dielectric lenses. This thesis presents a single aperture multibeam spatial power combining system that can support two separate polarizations. A Rotman lens is used as the power dividing network, which also has the ability to scan the beam over discrete angles. 1x9 dual polarized array was designed to demonstrate the beam steering in azimuth plane. The entire system is designed for the Ka band, with a center frequency of 32.6GHz. Through simulations and measurements, a ±30 degree scan range was achieved for the horizontal and vertical polarizations. The cross polarization for both the vertical and horizontal polarization ports was better than –16dB. Tray Based Millimeter-wave Quasi-Optical Amplifiers and Dual Polarized Phased Arrays
Metabolic engineering of Neurospora crassa for increasing carotenoids synthesis

Carotenoids are essential nutrient compounds with numerous biological functions. Neurospora crassa is a model filamentous fungus with orange pigmentation which is attributed to the accumulation of carotenoids containing neurosporaxanthin (NX) and neutral carotenoids (NC). To enhance carotenoids synthesis in N. crassa , isoprene diphosphate (IPP) and dimethylallyl diphosphate (DMAPP) were increased using the genes, xylulose-5-phosphate phosphoketolase ( XPK ), phosphotransacetylase ( PTA ), and NADH-specific-3-hydroxy-3-methyl glutaryl coenzyme A reductase ( HMGR ), as single, fused and three combined expressions to channel more carbon source into the mevalonate pathway (MVP). The single ( PTA , XPK , HMGR ), fused ( PTA:HMGR & XPK:HMGR ) and three combined gene ( PTA with fused XPK:HMGR ) expressions in engineered fungal resulted in carotenoid titers with contents of NX accumulated up to 4.5 mg/g DW and NC up to 1.7 mg/g DW as compared to the wild-type with NX up to 1.54 mg/g DW and NC up to 0.8 mg/g DW. The optimized MVP with metabolic engineering methods is a key method to increase the synthesis of carotenoid and other active terpenoids crassa .
NBER WORKING PAPER SERIES A UNIFIED WELFARE ANALYSIS OF GOVERNMENT POLICIES

We first and foremost thank the several hundred researchers whose empirical results form the foundation of our estimates. We are also deeply indebted to a wonderful team of research assistants: Caroline Dockes, Harris Eppsteiner, Adriano Fernandez, Jack Hoyle, Omeed Maghzian, Kate Musen, and the rest of the exceptional team of Pre-Doctoral Fellows at Opportunity Insights. We are also grateful to Raj Chetty, David Deming, Winnie van Dijk, Amy Finkelstein, John Friedman, Andrew Goodman-Bacon, Hilary Hoynes, John Eric Humphries, Larry Katz, Sarah Miller, Evan Soltas, Larry Summers, Michael Stepner, and Laura Wherry for helpful comments and suggestions, along with seminar participants at Georgetown, LSE, IFS, the University of Kentucky, the University of Minnesota, and Texas A&M. This research was funded by the National Science Foundation (#CAREER1653686 (Hendren) and #DGE1745303 (SprungKeyser)), the Sloan Foundation (Hendren), the Bill and Melinda Gates Foundation (Hendren), and the Chan Zuckerberg Initiative (Hendren). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Building a QA system through local convolution with global self-attention (IID SQuAD track)

Recurrent Neural Networks (RNN) were historically successful architecture for Machine Reading comprehension. QANet was the first architecture to achieve higher performance with only convolutions and self-attention. In this paper, we discuss our implementation of this architecture with an emphasis made on the encoder block and the choice of the optimization algorithm. We tested our implementation on Stanford Question Answering Dataset 2.0 [1]
Study of friction extrusion and consolidation

Friction extrusion and consolidation was invented by The Welding Institute (Cambridge, UK) in the early 1990’s. It is related to simple extrusion processes with the primary difference being that the extrusion die rotates about the extrusion axis and the die is required to impart substantial deformation to the initially, finely divided charge (like metal waste or chips) in order to consolidate it prior to extrusion. It can produce high quality wire and fully consolidated bulk material from low cost precursors like metal chips or powders. The advantages lie in that it is a direct method to recycle metal chips or scraps and considered as more convenient, economical and “green” process when compared with conventional recycle processes involving melting and casting. This is a novel process believed to have huge potential for producing high quality wire products with customized chemical composition for fusion welding and additive manufacturing with relatively simpler devices and less time/labor/energy requirements. This dissertation work aims to develop insight understanding of the underlying physics of friction extrusion and consolidation processes and enable its use for a wide range of high value added manufacturing applications, like additive manufacturing. The specific works are listed as follow: The thermal-mechanical progression of friction extrusion and consolidation process was studied experimentally and numerically. The deformation and material flow were revealed via a marker insert technique, thus strain in friction extrusion wire is deduced. Relationship between control parameters (like extrusion/consolidation force and die rotational speed) and responses (like torque, extrusion rate, grain size and features of marker pattern etc.) were analyzed. Electron backscatter diffraction result showed that there is no strong texture preference in friction extruded aluminum wire. Using friction extruded aluminum alloy wire, wall samples were built via wire and arc additive manufacturing. Finite element simulation helped predict heat transfer and temperature field during the additive manufacturing process. Post-analysis indicates that good mechanical properties can be achieved if favorable thermal management was provided.
MEASURING THE OVERLAP WITH OTHER CUSTOMERS IN THE SINGLE SERVER QUEUE

The single server queue is one of the most basic queueing systems to model stochastic waiting dynamics. Most work involving the single server queue only analyzes the customer or agent behavior. However, in this work, we are inspired by COVID-19 applications and are interested in the interaction between customers and more speciﬁcally, the time that adjacent customers overlap in the queue. To this end, we derive a new recursion for this overlap time and study the steady state behavior of the overlap time via simulation and probabilistic analysis. We ﬁnd that the overlap time between adjacent customers in the M/M/1 queue has a conditional distribution that is given by an exponential distribution, however, as the distance between customers grows, the probability of a non-negative overlap time decreases geometrically. We also ﬁnd via simulation that the exponential distribution still holds when the distribution is non-exponential, hinting at a more general result.
ANALYSIS OF MEDICAL IMAGE CLASSIFICATION BASED ON CONVOLUTION NEURAL NETWORK

: Image classification has long been a popular study topic across the world, and the advent of deep learning has aided in the advancement of this discipline. convolution neural networks (CNNs) have gradually become the dominant algorithm for image classification, and the CNN architecture used for other visual recognition tasks is generally derived from the network architecture used for image classification. The application of information and communication technologies in medical imaging to improve healthcare services is known as medical imaging informatics. The purpose of medical imaging analytics is to improve the accuracy and reliability of medical services, particularly medical image use and interchange across complicated healthcare systems. Deep learning techniques, particularly convolution networks, have swiftly emerged as the primary method for analyzing medical images. This paper is analysis medical image classification which exploits a large image dataset based on Convolution Neural Network models.
QANet and Performance on SQuAD v2.0

Question answering, and more generally machine reading comprehension, has always been a staple in NLP benchmark testing because of its representation of machine’s ability to understand linguistic elements. Modern question answering systems, ranging from the RNN-based systems to the large-scale transformer-based models, have become remarkably complex within the last few years. The goal of this project is to build upon the BiDAF method [1] by adding character-embeddings, and build from scratch the transformer-based QANet model adapted from Yu et al. [2] Additionally, we tuned the three parameters, learning rate, dropout probability, and number of stacked encoder blocks in relationship with batch size. We achieved an F1 score of 69.11 and an EM score of 65.85 on the hidden test set.
Valproic Acid Leads to an Increase in ROS Generation by Inhibiting the Deacetylation of Mitochondrial SOD

Valproic Acid Leads to an Increase in ROS Generation by Inhibiting the Deacetylation of Mitochondrial SOD2 Stephen Marc Lucas Department of Physiology and Developmental Biology, BYU Master of Science Valproic Acid Promotes Acetylation of Superoxide Dismutase-2 During Neurogenesis. Valproic acid (VPA) is a known developmental toxicant associated with a high prevalence of neural tube defects (NTD). The mechanism of VPA-induced NTD is unclear, but oxidative stress may be implicated. To understand how embryotoxic oxidative stress may occur, we measured superoxide dismutase (SOD) activity following VPA treatment in the embryonic pluripotent P19 mouse carcinoma cell line. In undifferentiated P19 cultures treated with VPA (5 mM), dichlorofluorescein fluorescence increased 15% compared to untreated controls over 20 min, indicating a modest, yet statistically significant increase in ROS generation. Undifferentiated P19 cells were treated with VPA for 6 h, after which total SOD and mitochondrial SOD (SOD2) activities were measured. VPA treatment decreased total SOD activity by approximately 20% but SOD2 activity was undetectable; but this was not a consequence of changes to SOD (SOD1 or SOD2) protein concentrations. Interestingly, glutathione redox state increased from -262 mV to -245 mV after a 6 h treatment with VPA, indicating significant oxidation of the cellular redox environment. Measurement of mitochondrial superoxide levels showed an increase following VPA treatments. While it is unlikely that VPA works directly as an oxidant, these data suggest that VPA may promote oxidative stress through an alternative means, such as via the inhibition of SOD activity and thus, allow for an increase in ROS. Importantly, VPA is a known deacetylase inhibitor, and SOD2 function is regulated by acetylation. As such, we evaluated the acetylation state of SOD2 to determine potential disruption via acetylation. Treated undifferentiated P19 cells showed a significant increase in SOD2 acetylation. However, in fully differentiated P19-derived neurons, cells showed no such SOD2 acetylation. Additionally, pretreatment with dithiole-3-thione (D3T), a Nrf2 activator of the antioxidant response, attenuated VPA-induced mitochondrial ROS production and SOD2 acetylation and improved SOD2 activity, suggesting Nrf2 as a potential means to reduce VPA-mediated oxidative stress. To evaluate the effects in the embryo proper, gestational day 8 mouse embryos were treated with VPA in culture for 6 h. Similar to P19 cells, VPA-treated neurulating embryos showed significant SOD2 acetylation and a concomitant decrease in total SOD activity. These data support a similar consequence of VPA-induced oxidative stress in embryos as is demonstrated in our cellular model. Since no SOD2 acetylation is observed in differentiated neurons and VPAinduced SOD2 acetylation occurs more prevalently in undifferentiated/differentiating cells, these data purport means by which VPA preferentially induces oxidative stress in developing systems.