Collinear drop Chien, Yang-Ting; Stewart, Iain W.
The journal of high energy physics,
06/2020, Volume:
2020, Issue:
6
Journal Article
Peer reviewed
Open access
A
bstract
We introduce collinear drop jet substructure observables, which are unaffected by contributions from collinear radiation, and systematically probe soft radiation within jets. These ...observables can be designed to be either sensitive or insensitive to process-dependent soft radiation originating from outside the jet. Such collinear drop observables can be exploited as variables to distinguish quark, gluon, and color neutral initiated jets, for testing predictions for perturbative soft radiation in Monte Carlo simulations, for assessing models and universality for hadronization corrections, for examining the efficiency of pileup subtraction methods, and for any other application that leaves an imprint on soft radiation. We discuss examples of collinear drop observables that are based both on clustering and on jet shapes. Using the soft-collinear effective theory we derive factorization expressions for collinear drop observables from QCD jets, and carry out a resummation of logarithmically enhanced contributions at next-to-leading-logarithmic order. We also identify an infinite class of collinear drop observables for which the leading double logarithms are absent.
Among various nanoparticles, superparamagnetic iron oxide nanoparticles (SPIONs) have been increasingly studied for their excellent superparamagnetism, magnetic heating properties, and enhanced ...magnetic resonance imaging (MRI). The conjugation of SPIONs with drugs to obtain delivery nanosystems has several advantages including magnetic targeted functionalization, in vivo imaging, magnetic thermotherapy, and combined delivery of anticancer agents. To further increase the targeting efficiency of drugs through a delivery nanosystem based on SPIONs, additional targeting moieties including transferrin, antibodies, aptamers, hyaluronic acid, folate, and targeting peptides are coated onto the surface of SPIONs. Therefore, this review summarizes the latest progresses in the conjugation of targeting molecules and drug delivery nanosystems based on SPIONs, especially focusing on their performances to develop efficient targeted drug delivery systems for tumor therapy.
Some magnetic nanoparticle-based nanocarriers loaded with drugs were evaluated in patients and did not produce convincing results, leading to termination of clinical development in phase II/III. An alternative strategy for drug delivery systems based on SPIONs is the conjugation of these systems with targeting segments such as transferrin, antibodies, aptamers, hyaluronic acid, folate, and targeting peptides. These targeting moieties can be recognized by specific integrin/receptors that are overexpressed specifically on the tumor cell surface, resulting in minimizing dosage and reducing off-target effects. This review focuses on magnetic nanoparticle-based nonviral drug delivery systems with targeting moieties to deliver anticancer drugs, with an aim to provide suggestions on the development of SPIONs through discussion.
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Anthropogenic activities accompanied by heavy metal waste threaten the environment. Heavy metal pollution alters the soil microbial community composition, and the microorganisms that adapt to this ...stress increase in abundance. The remediation process of contaminated soil not only reduces the concentration of heavy metals but also alters the bacterial communities. High-throughput 16S rDNA sequencing techniques were applied to understand the changes in soil microbial communities. Using the remediation approach of the soil mixing, the concentrations of heavy metals in the contaminated areas were diluted and the soil environment was changed. The change of soil environment as a disturbance contributed to the alteration of microbial diversity of the remediated areas. The pH and heavy metals (Cr, Cu, Ni, and Zn) were the most influential factors driving the changes in community structure. The bacterial community structure was significantly different among sample areas. The decrease of heavy metals in soil may be the important factors that changed the microbial composition. This study provides the better understanding of the changes in composition of microbial communities affected by the remediation process in heavy metal-contaminated soil.
Food Packaging: A Comprehensive Review and Future Trends Han, Jia‐Wei; Ruiz‐Garcia, Luis; Qian, Jian‐Ping ...
Comprehensive reviews in food science and food safety,
July 2018, 2018-Jul, 2018-07-00, 20180701, Volume:
17, Issue:
4
Journal Article
Peer reviewed
Open access
Innovations in food packaging systems will help meet the evolving needs of the market, such as consumer preference for “healthy” and high‐quality food products and reduction of the negative ...environmental impacts of food packaging. Emerging concepts of active and intelligent packaging technologies provide numerous innovative solutions for prolonging shelf‐life and improving the quality and safety of food products. There are also new approaches to improving the passive characteristics of food packaging, such as mechanical strength, barrier performance, and thermal stability. The development of sustainable or green packaging has the potential to reduce the environmental impacts of food packaging through the use of edible or biodegradable materials, plant extracts, and nanomaterials. Active, intelligent, and green packaging technologies can work synergistically to yield a multipurpose food‐packaging system with no negative interactions between components, and this aim can be seen as the ultimate future goal for food packaging technology. This article reviews the principles of food packaging and recent developments in different types of food packaging technologies. Global patents and future research trends are also discussed.
Abstract
Intelligent translation software is one of the important tools for people to learn, but the existing intelligent translation system usually needs to be further improved in terms of the ...flexible application of phrases and the accurate expression of professional vocabulary. The translation system based on deep learning designed in this paper mainly includes professional vocabulary database module, memory analysis module, English translation module and correction module. The professional vocabulary module accurately classifies words related to various disciplines. The memory analysis module compares the professional vocabulary usage in published documents on the Internet to analyze and memorize, so as to recommend relatively accurate professional vocabulary to enter the translation module. Need to enter the correction module to complete the correction of grammar and phrases, and finally complete the translation task with higher accuracy.
The influence of Artificial Intelligence (AI) tool usage on students' learning ability has received much attention from the society. The present study reviews prior studies examining the effect of AI ...on learning motivation in English as a Foreign Language (EFL) classrooms. Previous studies examinethe effects of AI on EFL students' motivation using a mixed-methods approach. The findings reveal a significant correlation between AI usage and student motivation. Other studies focuses on AI-assisted language learning's impact on English learning outcomes, self-regulated learning as well as L2 motivation, among EFL learners. AI-mediated instruction is proved to positively influences English learning motivation, self-regulated learning and learning outcomes. Additionally, findings from interview suggest learners' positive perceptions of AI platforms. Moreover, evidence from meta-analysis and studies on VR learning program demonstrate the beneficial role of AI on learning. The present study underscore AI's potential to enhance learning motivation in EFL contexts. Furthermore, more researches on AI's application to EFL instruction can be done in the future.
A synthesis of 4‐substituted chroman‐3‐one derivatives has been developed through a gold(III) catalyzed oxidation‐cyclization of ynones in good to excellent yield using easily prepared substrates. A ...broad range of synthetically useful functional groups (halide, alkene, alkyne, phenolic hydroxyl) were tolerated. Further application of this method paves a new way to prepare the skeleton of oblarotenoids. A cascade oxidative cyclization for construction of pyrano2,3‐cchromen‐1(5H)‐one derivatives is also presented.
Summary
Heat stress induces misfolded protein accumulation in endoplasmic reticulum (ER), which initiates the unfolded protein response (UPR) in plants. Previous work has demonstrated the important ...role of a rice ER membrane‐associated transcription factor OsbZIP74 (also known as OsbZIP50) in UPR. However, how OsbZIP74 and other membrane‐associated transcription factors are involved in heat stress tolerance in rice is not reported. In the current study, we discovered that OsNTL3 is required for heat stress tolerance in rice. OsNTL3 is constitutively expressed and up‐regulated by heat and ER stresses. OsNTL3 encodes a NAC transcription factor with a predicted C‐terminal transmembrane domain. GFP‐OsNTL3 relocates from plasma membrane to nucleus in response to heat stress and ER stress inducers. Loss‐of‐function mutation of OsNTL3 confers heat sensitivity while inducible expression of the truncated form of OsNTL3 without the transmembrane domain increases heat tolerance in rice seedlings. RNA‐Seq analysis revealed that OsNTL3 regulates the expression of genes involved in ER protein folding and other processes. Interestingly, OsNTL3 directly binds to OsbZIP74 promoter and regulates its expression in response to heat stress. In turn, up‐regulation of OsNTL3 by heat stress is dependent on OsbZIP74. Thus, our work reveals the important role of OsNTL3 in thermotolerance, and a regulatory circuit mediated by OsbZIP74 and OsNTL3 in communications among ER, plasma membrane and nucleus under heat stress conditions.
With the increase of COVID-19 cases worldwide, an effective way is required to diagnose COVID-19 patients. The primary problem in diagnosing COVID-19 patients is the shortage and reliability of ...testing kits, due to the quick spread of the virus, medical practitioners are facing difficulty in identifying the positive cases. The second real-world problem is to share the data among the hospitals globally while keeping in view the privacy concerns of the organizations. Building a collaborative model and preserving privacy are the major concerns for training a global deep learning model. This paper proposes a framework that collects a small amount of data from different sources (various hospitals) and trains a global deep learning model using blockchain-based federated learning. Blockchain technology authenticates the data and federated learning trains the model globally while preserving the privacy of the organization. First, we propose a data normalization technique that deals with the heterogeneity of data as the data is gathered from different hospitals having different kinds of Computed Tomography (CT) scanners. Secondly, we use Capsule Network-based segmentation and classification to detect COVID-19 patients. Thirdly, we design a method that can collaboratively train a global model using blockchain technology with federated learning while preserving privacy. Additionally, we collected real-life COVID-19 patients' data open to the research community. The proposed framework can utilize up-to-date data which improves the recognition of CT images. Finally, we conducted comprehensive experiments to validate the proposed method. Our results demonstrate better performance for detecting COVID-19 patients.
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