11 research outputs found
Comparative study of classification algorithms for immunosignaturing data
Get PDFabstract: Background
High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data.
Results
We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy.
Conclusions
‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties.The electronic version of this article is the complete one and can be found online at: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-13-13
Analysing QBER and secure key rate under various losses for satellite based free space QKD
Get PDFQuantum Key Distribution is a key distribution method that uses the qubits to
safely distribute one-time use encryption keys between two or more authorised
participants in a way that ensures the identification of any eavesdropper. In
this paper, we have done a comparison between the BB84 and B92 protocols and
BBM92 and E91 entanglement based protocols for satellite based uplink and
downlink in low Earth orbit. The expressions for the quantum bit error rate and
the keyrate are given for all four protocols. The results indicate that, when
compared to the B92 protocol, the BB84 protocol guarantees the distribution of
a higher secure keyrate for a specific distance. Similarly, it is observed that
BBM92 ensures higher keyrate in comparison with E91 protocol.Comment: arXiv admin note: text overlap with arXiv:1906.08115 by other author
Understanding Social Media Users' Perceptions of Trigger and Content Warnings
No full textThe prevalence of distressing content on social media raises concerns about users' mental well-being, prompting the use of trigger warnings (TW) and content warnings (CW). However, varying practices across platforms indicate a lack of clarity among users regarding these warnings. To gain insight into how users experience and use these warnings, we conducted interviews with 15 regular social media users. Our findings show that users generally have a positive view of warnings, but there are differences in how they understand and use them. Challenges related to using TW/CW on social media emerged, making it a complex decision when dealing with such content. These challenges include determining which topics require warnings, navigating logistical complexities related to usage norms, and considering the impact of warnings on social media engagement. We also found that external factors, such as how the warning and content are presented, and internal factors, such as the viewer's mindset, tolerance, and level of interest, play a significant role in the user's decision-making process when interacting with content that has TW/CW. Participants emphasized the need for better education on warnings and triggers in social media and offered suggestions for improving warning systems. They also recommended post-trigger support measures. The implications and future directions include promoting author accountability, introducing nudges and interventions, and improving post-trigger support to create a more trauma-informed social media environment.Master of ScienceIn today's world of social media, you often come across distressing content that can affect your mental well-being. To address this concern, platforms and content authors use something called trigger warnings (TW) and content warnings (CW) to alert users about potentially upsetting content. However, different platforms have different ways of using these warnings, which can be confusing for users.
To better understand how people like you experience and use these warnings, we conducted interviews with 15 regular social media users. What we found is that, in general, users have a positive view of these warnings, but there are variations in how they understand and use them.
Using TW/CW on social media can be challenging because it involves deciding which topics should have warnings, dealing with the different rules on each platform, and thinking about how warnings affect people's engagement with content.
We also discovered that various factors influence how people decide whether to engage with warned content. These factors include how the warning and content are presented and the person's own mindset, tolerance for certain topics, and level of interest.
Our study participants highlighted the need for better education about warnings and triggers on social media. They also had suggestions for improving how these warnings are used and recommended providing support to users after they encounter distressing content.
Looking ahead, our findings suggest the importance of holding content creators accountable, introducing helpful tools and strategies, and providing better support to make social media a more empathetic and supportive place for all users
Precise Emplacement
No full textThe project synopsis deals with the technique of Data-Analytics which is becoming a very influential tool for decision-making today. Software data analytics is key for helping stakeholders make decisions, and thus establishing a measurement and data analysis program is a recognized best practice within the software industry. However, practical implementation of measurement programs and analytics in industry is challenging. In this chapter, we discuss real-world challenges that arise during the implementation of a software measurement and analytics program. We also report lessons learned for overcoming these challenges and best practices for practical, effective data analysis in industry. The main objective of this work is to understand data for decision making. The author here tries to select those locations that are not already crowded with restaurants within the region and have a greater population by using various data science and analysis techniques to reach their goal of selecting optimal locations. The advantages of each area will be clearly expressed so that the best possible final location can be chosen by the stakeholders. The Author initialized a crawler to scrape the data about the areas of cities using Wikipedia web page and the real-time data set. Python’s geocoder library with ArcGIS as a geocode provider, to get the coordinates of the neighborhoods. After which the author applies the clustering algorithm, K-Means, on the data to cluster the neighborhood based on general venue density and analyze & compare the sets in each cluster to conclude the most promising and optimal locations for each restaurant type. Which is then filter out only the target restaurant of interest in each neighborhood, to analyze within the clusters
MM Big Data Applications: Statistical Resultant Analysis of Psychosomatic Survey on Various Human Personality Indicators
No full textNanotechnology: A promising tool for targeted drug delivery
No full textNanotechnology has eventually and strongly engaged in the field of drug delivery. It makes use of the specific properties of the substance at the Nano scale. Their primary goal is to increase therapeutic effects while reducing adverse effects. Due to their improved goods, nanotechnology has become more popular across a variety of industries. The term “Nano medicine” is used to denote the application of nanotechnology in medicine. This Nano medicine is essential for drug delivery, antibacterial, vaccine development, wearable technology, diagnostic and imaging tools, implants, high throughput screening platforms, etc. It makes use of biological, biomimetic, no biological, or hybrid materials. To attain logical drug delivery, it is important to understand the interlink age between nanoparticles and the biological environment, drug release, and targeting cell-surface receptors. We can control disease progression by using nanomaterial including peptide-based nanotubes to prey the vascular endothelial growth factor (VEGF) receptor. Also, the use of herbal medicine has been used since ancient times. The supply of active compounds is shown by the effectiveness of various species of herbal medicine. The essential requirements for extending novel nanotechnology-based medication delivery systems are highlighted in this review
Tape-recorded conversation is a valid evidence or not?
No full textThe Electronic form of evidence is the requirement in the current scenario of the judiciary. The evidence of tape recorded conversation is emerging nowadays in the cases related to prevention of corruption act, electronic media is used by all over the world with the latest version and updated technologies and that is the reason why the admissibility of the evidence depends on the nature and the evidentiary value of such tape recorded conversation. we have seen that after the Indian technology act, 2000 and amendment in the evidence act, 1872 that the tape-recorded conversation is considered as one of the evidentiary document but the admissibility is still the matter of evidentiary value. Prior to the year 2000, the court used to considered only oral or written document and the judges were overburdened with the pending cases and the relation between law and technology was raised many times before court of law. Tapping telephonic conversation by special authority is not the violation of fundamental right and the rights of article 20(3) Indian constitution is not available, it is excluded from the right to privacy, The connection amongst law and innovation has not generally been a simple one. Now, the evidence of telephonic conversation is freely taken after the major amendment in section 3 of Indian evidence act, 1872 with respect to the section 92 of Indian technology act, 2000, Indian technology act has somehow clarify the concept of admissibility of evidence that's why the evidence act and technology act are considered as the two wheels of the court of criminal procedure. Section 2 of Indian technology act deals with the information received, sent, contained in chip or microchip and stored in media whether in magnetic form or optical.
Triggering the Untriggered: The First Einstein Probe-detected Gamma-Ray Burst 240219A and Its Implications
No full textYin, Yi-Han Iris et al.-- Full list of authors: Yin, Yi-Han Iris; Zhang, Bin-Bin; Yang, Jun; Sun, Hui; Zhang, Chen; Shao, Yi-Xuan; Hu, You-Dong; Zhu, Zi-Pei; Xu, Dong; An, Li; Gao, He; Wu, Xue-Feng; Zhang, Bing; Castro-Tirado, Alberto Javier; Pandey, Shashi B.; Rau, Arne; Lei, Weihua; Xie, Wei; Ghirlanda, Giancarlo; Piro, Luigi; O'Brien, Paul; Troja, Eleonora; Jonker, Peter; Yu, Yun-Wei; An, Jie; Chen, Run-Chao; Chen, Yi-Jing; Dong, Xiao-Fei; Eyles-Ferris, Rob; Fan, Zhou; Fu, Shao-Yu; Fynbo, Johan P. U.; Gao, Xing; Huang, Yong-Feng; Jiang, Shuai-Qing; Jiang, Ya-Hui; Julakanti, Yashaswi; Kuulkers, Erik; Lao, Qing-Hui; Li, Dongyue; Ling, Zhi-Xing; Liu, Xing; Liu, Yuan; Mou, Jia-Yu; Pan, Xin; Wei, Daming; Wu, Qinyu; Yadav, Muskan; Yang, Yu-Han; Yuan, Weimin; Zhang, Shuang-Nan.-- Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any furtherm distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOIThe Einstein Probe (EP) achieved its first detection and localization of a bright X-ray flare, EP240219a, on 2024 February 19, during its commissioning phase. Subsequent targeted searches triggered by the EP240219a alert identified a faint, untriggered gamma-ray burst (GRB) in the archived data of Fermi Gamma-ray Burst Monitor (GBM), Swift Burst Alert Telescope (BAT), and Insight-HXMT/HE. The EP Wide-field X-ray Telescope (WXT) light curve reveals a long duration of approximately 160 s with a slow decay, whereas the Fermi/GBM light curve shows a total duration of approximately 70 s. The peak in the Fermi/GBM light curve occurs slightly later with respect to the peak seen in the EP/WXT light curve. Our spectral analysis shows that a single cutoff power-law (PL) model effectively describes the joint EP/WXT–Fermi/GBM spectra in general, indicating coherent broad emission typical of GRBs. The model yielded a photon index of ∼–1.70 ± 0.05 and a peak energy of ∼257 ± 134 keV. After detection of GRB 240219A, long-term observations identified several candidates in optical and radio wavelengths, none of which was confirmed as the afterglow counterpart during subsequent optical and near-infrared follow-ups. The analysis of GRB 240219A classifies it as an X-ray-rich GRB (XRR) with a high peak energy, presenting both challenges and opportunities for studying the physical origins of X-ray flashes, XRRs, and classical GRBs. Furthermore, linking the cutoff PL component to nonthermal synchrotron radiation suggests that the burst is driven by a Poynting flux-dominated outflow.© 2024. The Author(s)We gratefully acknowledge the HXMT team for providing the
Insight-HXMT light-curve data of this event. We acknowledge
the support by the National Key Research and Development
Programs of China (2022YFF0711404, 2022SKA0130102, and
2021YFA0718500), the National SKA Program of China
(2022SKA0130100), the National Natural Science Foundation
of China (grant Nos. 11833003, U2038105, U1831135,
12121003, 12393811, and 13001106), the science research grants
from the China Manned Space Project with NO. CMS-CSST2021-B11, and the Fundamental Research Funds for the Central
Universities. This work is supported by the CNSA program
D050102. Part of the funding for GROND (both hardware as well
as personnel) was generously granted from the Leibniz Prize to
Prof. G. Hasinger (DFG grant HA 1850/28-1).With funding from the Spanish government through the "Severo Ochoa Centre of Excellence" accreditation (CEX2021-001131-S).Peer reviewe
