An Iterative Method of Sentiment Analysis for Reliable User Evaluation

Indiana University-Purdue University Indianapolis (IUPUI)Benefited from the booming social network, reading posts from other users over the internet is becoming one of commonest ways for people to intake information. One may also have noticed that sometimes we tend to focus on users provide well-founded analysis, rather than those merely who vent their emotions. This thesis aims at finding a simple and efficient way to recognize reliable information sources among countless internet users by examining the sentiments from their past posts. To achieve this goal, the research utilized a dataset of tweets about Apple's stock price retrieved from Twitter. Key features we studied include post-date, user name, number of followers of that user, and the sentiment of that tweet. Prior to making further use of the dataset, tweets from users who do not have sufficient posts are filtered out. To compare user sentiments and the derivative of Apple's stock price, we use Pearson correlation between them to describe how well each user performs. Then we iteratively increase the weight of reliable users and lower the weight of untrustworthy users, the correlation between overall sentiment and the derivative of stock price will finally converge. The final correlations for individual users are their performance scores. Due to the chaos of real-world data, manual segmentation via data visualization is also proposed as a denoise method to improve performance. Besides our method, other metrics can also be considered as user trust index, such as numbers of followers of each user. Experiments are conducted to prove that our method outperforms others. With simple input, this method can be applied to a wide range of topics including election, economy, and the job market

Tunnelling effect of charged and magnetized particles from the Kerr–Newman–Kasuya black hole

AbstractIn this Letter, we extend the Parikh–Wilczek tunnelling framework to calculate the emission rate of a particle with electric and magnetic charges. We first reconstruct the electromagnetic field tensor and the Lagrangian of the field corresponding to the source with electric and magnetic charges. Then, in the background of Kerr–Newman–Kasuya black hole spacetime, we calculate the emission spectrum of the outgoing particles with electric and magnetic charges. For the sake of simplicity, we only consider the case that the rate of electric and magnetic charge of the emission particle is constant and equals that of the black hole. In this case, the emission spectrum deviates from the pure thermal spectrum, but it is consistent with an underlying unitary theory and takes the same functional form as that of uncharged massless particles. Finally, discussions about the result are presented

Modification Strategies of Titanium Dioxide

Titanium dioxide (TiO2) is a standard white pigment. However, when TiO2 is exposed to ultraviolet light, it will catalyze the degradation of the surrounding organic matrix. Surface coating of TiO2 is an effective method for reducing the catalytic effect of TiO2. It can also improve the dispersion of TiO2 in an organic matrix. This review critically introduces recent results on the surface coating of TiO2. First, the main features of TiO2, including processes, structure, and final properties, are described briefly. Second, this chapter reports and discusses different surface coating methods for TiO2 with inorganic oxides and organic matter. Inorganic oxides, such as Al2O3, SiO2, and ZrO2, would form a continuous dense film and block the defects of the TiO2 lattice. They can give TiO2 excellent weather resistance. The organic matter available for surface treatment includes the surfactant, the coupling agent, and the macromolecule. They can improve the affinity of TiO2 with various organic matrices. Surfactant treatment is relatively simple. Coupling agents can give TiO2 more novel properties, such as thermal stability. Macromolecules can increase the volume of TiO2 particles through steric hindrance and improve the dispersion of TiO2 in an organic matrix. However, coating TiO2 in a single matter is challenging to meet the increasing performance requirements. Therefore, it is necessary to study further the effect of co-coating with different inorganic oxides and organic matter on the structure and properties of TiO2

Recent advances in neural mechanism of general anesthesia induced unconsciousness: insights from optogenetics and chemogenetics

For over 170 years, general anesthesia has played a crucial role in clinical practice, yet a comprehensive understanding of the neural mechanisms underlying the induction of unconsciousness by general anesthetics remains elusive. Ongoing research into these mechanisms primarily centers around the brain nuclei and neural circuits associated with sleep-wake. In this context, two sophisticated methodologies, optogenetics and chemogenetics, have emerged as vital tools for recording and modulating the activity of specific neuronal populations or circuits within distinct brain regions. Recent advancements have successfully employed these techniques to investigate the impact of general anesthesia on various brain nuclei and neural pathways. This paper provides an in-depth examination of the use of optogenetic and chemogenetic methodologies in studying the effects of general anesthesia on specific brain nuclei and pathways. Additionally, it discusses in depth the advantages and limitations of these two methodologies, as well as the issues that must be considered for scientific research applications. By shedding light on these facets, this paper serves as a valuable reference for furthering the accurate exploration of the neural mechanisms underlying general anesthesia. It aids researchers and clinicians in effectively evaluating the applicability of these techniques in advancing scientific research and clinical practice

Drosophila TRPA1 isoforms detect UV light via photochemical production of H2O2

The transient receptor potential A1 (TRPA1) channel is an evolutionarily conserved detector of temperature and irritant chemicals. Here, we show that two specific isoforms of TRPA1 in Drosophila are H2O2 sensitive and that they can detect strong UV light via sensing light-induced production of H2O2. We found that ectopic expression of these H2O2-sensitive Drosophila TRPA1 (dTRPA1) isoforms conferred UV sensitivity to light-insensitive HEK293 cells and Drosophila neurons, whereas expressing the H2O2-insensitive isoform did not. Curiously, when expressed in one specific group of motor neurons in adult flies, the H2O2-sensitive dTRPA1 isoforms were as competent as the blue light-gated channelrhodopsin-2 in triggering motor output in response to light. We found that the corpus cardiacum (CC) cells, a group of neuroendocrine cells that produce the adipokinetic hormone (AKH) in the larval ring gland endogenously express these H2O2-sensitive dTRPA1 isoforms and that they are UV sensitive. Sensitivity of CC cells required dTRPA1 and H2O2 production but not conventional phototransduction molecules. Our results suggest that specific isoforms of dTRPA1 can sense UV light via photochemical production of H2O2. We speculate that UV sensitivity conferred by these isoforms in CC cells may allow young larvae to activate stress response--a function of CC cells--when they encounter strong UV, an aversive stimulus for young larvae

ACETest: Automated Constraint Extraction for Testing Deep Learning Operators

Deep learning (DL) applications are prevalent nowadays as they can help with multiple tasks. DL libraries are essential for building DL applications. Furthermore, DL operators are the important building blocks of the DL libraries, that compute the multi-dimensional data (tensors). Therefore, bugs in DL operators can have great impacts. Testing is a practical approach for detecting bugs in DL operators. In order to test DL operators effectively, it is essential that the test cases pass the input validity check and are able to reach the core function logic of the operators. Hence, extracting the input validation constraints is required for generating high-quality test cases. Existing techniques rely on either human effort or documentation of DL library APIs to extract the constraints. They cannot extract complex constraints and the extracted constraints may differ from the actual code implementation. To address the challenge, we propose ACETest, a technique to automatically extract input validation constraints from the code to build valid yet diverse test cases which can effectively unveil bugs in the core function logic of DL operators. For this purpose, ACETest can automatically identify the input validation code in DL operators, extract the related constraints and generate test cases according to the constraints. The experimental results on popular DL libraries, TensorFlow and PyTorch, demonstrate that ACETest can extract constraints with higher quality than state-of-the-art (SOTA) techniques. Moreover, ACETest is capable of extracting 96.4% more constraints and detecting 1.95 to 55 times more bugs than SOTA techniques. In total, we have used ACETest to detect 108 previously unknown bugs on TensorFlow and PyTorch, with 87 of them confirmed by the developers. Lastly, five of the bugs were assigned with CVE IDs due to their security impacts.Comment: Accepted by ISSTA 202

Lacrimal Gland Microenvironment Changes After Obstruction of Lacrimal Gland Ducts

Purpose: To investigate microenvironment changes of the lacrimal gland after obstruction of lacrimal gland ducts.Methods: The ducts of rat exorbital lacrimal gland were ligated by sutures for different durations. After that, the sutures in some animals were released, and they were observed for 21 days to evaluate the recovery of the lacrimal gland. Slit lamp and tear secretion test was performed to evaluate ocular surface and lacrimal gland function. The lacrimal gland and cornea were harvested and processed for hematoxylin and eosin staining, oil red O staining, LipidTOX staining, Masson staining, quantitative real time polymerase chain reaction, and immunofluorescence staining.Results: After the lacrimal gland ducts were blocked, tear secretion and the weight of the lacrimal gland were reduced. Incidence of corneal neovascularization increased after seven days. Intraglandular ducts dilated and acini destroyed. Long-term ligation induced fibrosis and lipid accumulation of the lacrimal glands. Inflammatory cell infiltrated and inflammatory factors upregulated. Proliferative and apoptotic cells increased. Structure of myoepithelial cells and basement membrane was destroyed. The p63 expression increased whereas Pax6 expression decreased. After suture release, tear secretion and structure of acini could recover in less than seven days after ligation, with a decrease in inflammatory cell infiltration and fibrosis relief. Apoptotic cells and proliferative cells increased at five days thereafter. The structure of the myoepithelial cells and basement membrane could not recover three days after ligation, and the number of mesenchymal cells increased in ligation after five to 14 days.Conclusions: Blockage of the lacrimal gland ducts results in dystrophy of lacrimal gland acini cells, inflammation, and lipid accumulation of the lacrimal gland microenvironment. Long-term duct blockage will cause irreversible lacrimal gland failure

The snoRNA MBII-52 (SNORD 115) is processed into smaller RNAs and regulates alternative splicing

The loss of HBII-52 and related C/D box small nucleolar RNA (snoRNA) expression units have been implicated as a cause for the Prader-Willi syndrome (PWS). We recently found that the C/D box snoRNA HBII-52 changes the alternative splicing of the serotonin receptor 2C pre-mRNA, which is different from the traditional C/D box snoRNA function in non-mRNA methylation. Using bioinformatic predictions and experimental verification, we identified five pre-mRNAs (DPM2, TAF1, RALGPS1, PBRM1 and CRHR1) containing alternative exons that are regulated by MBII-52, the mouse homolog of HBII-52. Analysis of a single member of the MBII-52 cluster of snoRNAs by RNase protection and northern blot analysis shows that the MBII-52 expressing unit generates shorter RNAs that originate from the full-length MBII-52 snoRNA through additional processing steps. These novel RNAs associate with hnRNPs and not with proteins associated with canonical C/D box snoRNAs. Our data indicate that not a traditional C/D box snoRNA MBII-52, but a processed version lacking the snoRNA stem is the predominant MBII-52 RNA missing in PWS. This processed snoRNA functions in alternative splice-site selection. Its substitution could be a therapeutic principle for PW