Miracle-dz/UniFAR-FTUs huggingface dataset:
A Ul Small Nuclear Ribonucleoprotein Particle with Altered Specificity Induces Alternative Splicing of an Adenovirus ElA mRNA Precursor

We have altered the specificity of Ul small nuclear RNA by replacing its 5' splice site recognition sequence (nucleotides 3 to 11) with sequences complementary to other regions of either the adenovirus ElA or the rabbit ,-globin mRNA precursor. We then used a HeLa cell transient expression assay to test whether such altered Ul small nuclear ribonucleoprotein particles (snRNPs) could interfere with splicing of the targeted mRNA precursors. The altered Ul snRNPs were able to cause novel splicing of the EIA mRNA precursor, minor changes in the ratio of EIA 12 to 13S mRNAs, and modest nuclear accumulation of P-globin mRNA precursors with either one of the two introns removed. Most of the altered Ul snRNPs did not affect the level of mature cytoplasmic mRNA significantly, but in one case an altered Ul snRNP (c.d) whose intended target was located downstream from the adenovirus EIA 12S 5' splice site was able to reduce the level of cytoplasmic 12S mRNA by approximately 60% and that of 13S mRNA by 90%. This dI snRNP induced an additional EIA splice, resulting in the appearance of 10 and 11S EIA mRNAs normally found only late in adenovirus infection. Thus, a trans-acting factor can induce alternative splicing. Surprisingly, the effects of ot1 on EIA splicing were not abolished by deleting the intended target sequence on the mRNA precursor. The splicing of mRNA precursors requires four distinct small nuclear ribonucleoprotein
ADAPTATION OF CYBER INCIVILITY SCALE INDONESIA VERSION

This research, divided into two studies, aimed to modify, and adapt the cyber incivility scale compiled by Lim and Teo (2009) in the Indonesian language and culture. Study 1, namely the process of translating the items and testing their suitability, involving six translators, three expert reviewers, and 10 participants for cognitive debriefing purposes. Meanwhile, Study 2 involved 232 workers in Indonesia who occupied structural leadership positions. The subjects consisted of 126 women (54.5%) and 106 men (45.5%) with a mean age of 36.9 years ( SD = 8.64; min = 20 years; max = 64 years). At this stage, a trial of the cyber incivility scale was carried out. The scale was adapted with confirmatory factor analysis using AMOS version 22. The entire adaptation process referred to the procedures of the 2016 International Test Commission (ITC) Guidelines for Test Adaptation. The CFA results of the goodness of fit test showed fit values (CFI = .972; TLI = .966; RMSEA = .063, GFI = .909, p = .000). Therefore, it could be concluded that the cyber incivility measurement model in this study was following the cyber incivility theory of Lim and Teo (2009) with two factors. Overall, this research showed that the Indonesian version of the cyber incivility scale is valid and reliable, thus applicable to measure the cyber incivility in the context of the perpetrator in Indonesia.
Pragmatic randomised, controlled trial of impregnated central venous catheters for preventing bloodstream infection in children

10 Background : Impregnated central venous catheters (CVCs) are recommended for adults to reduce 11 bloodstream infection (BSI) but not for children due to a lack of evidence for their effectiveness. 12 Methods: Randomised trial of children admitted to 14 English paediatric intensive care units (PICUs). 13 The primary outcome, time to first BSI between 48 hours after randomisation and 48 hours after 14 CVC removal, was compared for any impregnation (antibiotic or heparin) versus standard CVCs 15 (primary analyses) and in pair-wise comparisons of all three CVC types (secondary analyses). 16 Findings : BSI occurred in 3.59% (18/502) randomised to standard CVC, 1.44% (7/486) to antibiotic 17 and 3.42% (17/497) to heparin CVC. Primary analyses showed no effect of impregnated (antibiotic or 18 heparin) compared with standard CVCs (hazard ratio for time to first BSI 0.71; 95%CI 0.37-1.34) 19 Secondary analyses showed antibiotic CVCs were superior to standard (HR 0.43; 0.20-0.96) and to 20 heparin CVCs (HR 0.42; 0.19-0.93), but heparin did not differ from standard (HR 1.04; 0.53-2.03). 21 Clinically important and statistically significant absolute risk differences were found only for 22 antibiotic vs standard (-2.15%; 95%CI: -4.09, -0.20; number needed to treat=47; 95%CI: 25, 500) and 23 antibiotic vs heparin CVCs (-1.98%; -0.06; NNT=51; 26, 1667). to thrombosis, mortality by 24 and not differ
A blind signal detection algorithm for passive location system based on troposcatter

Abstract To improve detection performance of passive location system based on troposcatter, we propose a blind signal detection algorithm. According to our algorithm, complementary ensemble empirical mode decomposition decomposes the received signal into several intrinsic mode functions (IMFs). To reconstruct the signal and background noises, difference between the entropy of adjacent IMFs is utilized as a standard. Different IMFs are utilized to estimate threshold of energy detection algorithm and energy level of received signal. Simulation examples indicate that the proposed algorithm can blindly and effectively detect the signal.
from its genome

Microbial virulence is a complex and often multifactorial phenotype, intricately linked to a pathogen’s evolutionary tra-jectory. Toxicity, the ability to destroy host cell membranes, and adhesion, the ability to adhere to human tissues, are the major virulence factors of many bacterial pathogens, including Staphylococcus aureus. Here, we assayed the toxicity and adhesiveness of 90 MRSA (methicillin resistant S. aureus ) isolates and found that while there was remarkably little variation in adhesion, toxicity varied by over an order of magnitude between isolates, suggesting different evolutionary selection pressures acting on these two traits. We performed a genome-wide association study (GWAS) and identified a large number of loci, as well as a putative network of epistatically interacting loci, that significantly associated with toxicity. Despite this apparent complexity in toxicity regulation, a predictive model based on a set of significant single nucleotide polymorphisms (SNPs) and insertion and deletions events (indels) showed a high degree of accuracy in predicting an isolate’s toxicity solely from the genetic signature atthese sites. Our resultsthus highlight the potentialof usingsequence data todetermine clinically relevant parameters and have further implications for understanding the microbial virulence of this opportunistic pathogen.
En route truck–drone parcel delivery for optimal vehicle routing strategies

Recently, several prominent logistic companies in Europe and the USA are seriously considering the idea of using drones launched from trucks and working in parallel to deliver packages. In the relevant literature, a novel problem formulation called travelling salesman problem with drone has been introduced, and some modelling and solution approaches have been presented. Existing approaches are based on the main assumption that the truck can dispatch and pick up a drone only at a node, i.e. the depot or a customer location. Here, the authors present a novel approach aimed to maximise the drone usage in parcel delivering. The authors consider that a truck can deliver and pick a drone up not only at a node but also along a route arc ( en route ). In this way, the operations of a drone are not strictly related to the customers' position, but it can serve a wider area along the route. The authors tested the proposed heuristic on benchmark instances and analysed the benefits introduced with the en route approach.
ITI-CERTH participation in ActEV and AVS Tracks of TRECVID 2021

In this report, the overview of the runs during the TRECVID 2021 by the ITI-CERTH team are presented. ITI-CERTH participated in the Ad-hoc Video Search (AVS) and Activities in Extended Video (ActEV) tasks. For the AVS task, our participation is based on an attention-based cross-modal deep network architecture. As part of training this architecture, we experimented with a new hard-negative mining approach. For the ActEV task, we improve our framework, in terms of more accurate performance, by addressing the classification problem as multi-label rather than a single-label.
TECHNICAL EFFICIENCY ANALYSIS OF CONTAINER TERMINALS IN TANJUNG PERAK, SURABAYA, EAST JAVA

Container Terminals in Tanjung Perak Port is a trading center in the Eastern Indonesia Region (KTI) with a total throughput of 3.6 million TEUs in 2020. The utility/level of use of terminal facilities, consisting of the pier/ berth occupancy ratio (BOR), has reached 60%. The field/yard occupancy ratio (YOR) is 65%, while the maximum utility is 70% (UNCTAD). It is neces sary to explore the technical efficiency of each container terminal using the stochastic frontier analysis (SFA) because it can also capture the inefficiency effects. This study is built from the analysis of production factors in the pe riod of 2009-2020, where the variables used are capital (k) using company asset data, labor variable (l) using data on the number of human resourc -es, energy variable (e) using energy cost data (fuel oil/fuel, electricity, and water). The inefficiency variables are port draught (d) and loading and un loading productivity (p). The container terminal in Tanjung Perak has a rel atively high technical efficiency value of 0.94. This shows that the terminal operation is quite optimum and is approaching the maximum point. The overall average elasticity is 2.01, which can be categorized as an increasing return to scale. The elasticity of assets has the most significant proportion, so it can be concluded that the port is capital intensive. Next, it’s found that the higher productivity 1% increase in loading and unloading productivity, the more inefficiency with a relatively minimal value of 0.11%. Finally, an increase of 1% in depth will increase efficiency by 10.89%.
The EuroPat Corpus: A Parallel Corpus of European Patent Data

We present the EuroPat corpus of patent-specific parallel data for 6 official European languages paired with English: German, Spanish, French, Croatian, Norwegian, and Polish. The filtered parallel corpora range in size from 51 million sentences (Spanish-English) to 154k sentences (Croatian-English), with the unfiltered (raw) corpora being up to 2 times larger. Access to clean, high quality, parallel data in technical domains such as science, engineering, and medicine is needed for training neural machine translation systems for tasks like online dispute resolution and eProcurement. Our evaluation found that the addition of EuroPat data to a generic baseline improved the performance of machine translation systems on in-domain test data in German, Spanish, French, and Polish; and in translating patent data from Croatian to English. The corpus has been released under Creative Commons Zero, and is expected to be widely useful for training high-quality machine translation systems, and particularly for those targeting technical documents such as patents and contracts.
Exploring Methods of Collecting Accessibility Feedback Exploring Methods of Collecting Accessibility Feedback

Accessibility, the practice of making a website or application easily usable and understandable by people with disabilities, is essential to ensuring that all users are able to participate equally in using the Web. However, currently many websites have accessibility issues. This study interviews 11 software developers and designers to learn about the methods that they use to collect accessibility feedback during the development and maintenance of websites and mobile applications. The research revealed a lack of standardized accessibility education at the post-secondary level, as well as a myriad of methods used to obtain accessibility feedback from automatic accessibility checkers to user testing. This work attempts to bring awareness of different current methods used, as well as current gaps in accessibility feedback methods where new methods and tools could be introduced.
Throughput Analysis of EERP Protocol

Abstract: Grouping techniques in WSN for Energy effectiveness has been tended to by different specialists because of promising upgrades in the exhibitions. The Energy utilization despite everything has an open door for development regarding multifaceted nature decrease, decrease in Energy utilization and lifetime of the system. The work introduced in this paper contributes a novel methodology for Energy efficiency in WSN. The throughput and packet delivery comparative analysis is performed in which EERP outperforms the LEACH protocol. Keywords: LEACH, WSN, K-medoid, clustering, routing
Survey on Machine learning Applications in Cyber Security Problems

: This study suggested that the works previously done on machine learning (ML) based applications in Cyber Security. The organization of review on the existing published works is not historic and instead thematic. The paper comprises into the contains related works based on ML for DGA generated domain name detection, intrusion detection, network traffic data analysis, spam, and phishing activities data analysis, malware data analysis, and Android malware data analysis respectively. This study helps to understand cybersecurity and use of Machine learning application.
Deep Policy Learning for Perfect Rectangle Packing

Perfect Rectangle Packing consists in solving a puzzle where the goal is to fit many small rectangles in a larger rectangle without creating holes. It has been previously addressed with Monte Carlo Tree Search algorithms. In this paper we train a neural network on solved instances of Perfect Rectangle Packing that are easy to generate. The trained neural network enables to derive a policy that is used as a prior by Monte Carlo search. The learned policy outperforms a random policy
Making Shopping Easy for People with Visual Impairment Using Mobile Assistive Technologies

People with visual impairment face various difficulties in their daily activities in comparison to people without visual impairment. Much research has been done to find smart solutions using mobile devices to help people with visual impairment perform tasks like shopping. One of the most challenging tasks for researchers is to create a solution that offers a good quality of life for people with visual impairment. It is also essential to develop solutions that encourage people with visual impairment to participate in social life. This study provides an overview of the various technologies that have been developed in recent years to assist people with visual impairment in shopping tasks. It gives an introduction to the latest direction in this area, which will help developers to incorporate such solutions into their research.
Urban Trajectory Analytics: Day-of-Week Movement Pattern Mining Using Tensor Factorization

This paper demonstrates the use of non-negative tensor factorization to extract underlying spatio-temporal movement patterns from large-scale urban trajectory data. Individual trajectory data obtained from public transport smart card systems and roadside Bluetooth detectors are represented as a dynamic graph of region-to-region flows to obtain structured data describing flow interactions between regions across time-of-day and day-of-week. Tensor factorization is then applied to these dynamic graphs to characterize traveler movements on different days of the week. The results unveil distinct day-of-week patterns in public transport passenger and roadway vehicle movements, providing insight into the diverse aspects of urban mobility.
A NETWORK AND AGENT BASED MODEL OF POLITICAL POLARIZATION

In this thesis I discuss the model from the paper ”Polarization and Tipping Points” which I coauthored [1]. I go into depth about the decisioning and reasoning behind multiple features of the model and discuss possible future improvements and potential future research. During this, I highlight some of my own speciﬁc contributions to the model and paper. In addition to giving background to the model we used to analyze political polarization, I give a background in the current academic literature surrounding political polarization as a whole.
Liquefied Natural Gas as a New Hazard; Learning Processes in Norwegian Fire Brigades

The innovation and utilization of new products leads to technological changes in contemporary societies and a need for the Fire Brigades (FBs) to update their expertise regarding the challenges these new products may represent. The present study examines learning processes for nine fire brigades in Norway, selected where Liquefied Natural Gas (LNG) facilities are in their jurisdiction and/or because they have handled LNG road accidents. The process of acquiring the necessary new knowledge and skills is researched inductively, and each FB is viewed as a unit in the Norwegian fire and rescue community, i.e., a multi-unit learning organization. Kolb’s learning cycle is used to discuss the findings. Large variations in learning processes were used in the different FBs, varying from short classroom courses held by external consultants to a series of learning episodes planned and directed by FB personnel. It was found that each FB focused locally and independently from other FBs when acquiring new knowledge. There was very limited knowledge transfer from FBs experienced with LNG facilities to “newcomers”. There is no established national knowledge-sharing network on LNG. There are, however, regional partner groups, mainly involving the FB and a distribution company, mentioned by all studied FBs to be the most important partner for learning. The inter-municipal committee against acute pollution (IUA) was the second most important learning cooperation partner. It was, however, discovered that LNG test releases gave rise to observations regarding the extension of the flammable cloud versus the visible cloud that was interpreted wrongly due to the lack of theoretical understanding of the influence of the air relative humidity. This was explained to one regional partner group that invited, and therefore asked, an academic about this issue during a training session. This partner group arranged demonstrations for all FBs involved along the path of LNG transport from the production site to their end-users. Surprisingly, there was very limited knowledge exchange between partner groups in different geographical regions, though one of these was certainly more knowledgeable. The present study revealed that knowledge sharing must be improved, at least when it comes to potential LNG incidents.
Variational Iteration Method for Solving an Infectious Disease Model

In this paper, we present a deterministic model that captures the essential dynamics of infectious diseases. Variational Iteration Method (VIM) is applied to attempt the series solution of the model. The efficiency of the VIM in solving the model is confirmed by classical fourth-order Runge-Kutta method implemented in Maple 18. The comparisons between the VIM and Runge-Kutta (RK4) solutions are made and there exists positive correlation between the results obtained by the two methods. The outcome of comparison between the VIM and RK4 validates the potential of the VIM in coping with the analysis of modern epidemics.
Best Response in Alternating-Offers Negotiation

I address the problem of responding to common heuristic strategies in bilateral alternating-offers negotiations. Existing work has identified best responses to one limited class of heuristics, the static acceptance model, and has provided approximate best-response algorithms for the more general class of time-dependent acceptance models. I extend this work to the two-sided negotiation case; provide a fast exact algorithm for computing a best response to time-dependent agents, which include time-based aspiration agents; and then generalize this response to the class of k -history dependent agents, which includes tit-for-tat agents.
Food for Thought: Food Preferential Regions in the Human Brain

Existing research has demonstrated functional selectivity in the brain for high level categories of faces, places, bodies, and sensory and motor processes. Food, de-spite its abundance and importance, has not been considered as a category for which there is a visual selective region, perhaps because of its lack of visual coherence. In this paper, we investigate responsiveness to food in a large scale natural setting via several statistical methods performed on high-resolution fMRI response dataset to natural scenes. We identify two regions consistent across all participants in the high level visual cortex that appear to be functionally selective for food.
Quality increases as the error rate decreases

In this paper we propose an approach to the design of processes and software that aims at decreasing human and software errors, that so frequently happen, making affected people using and wasting a lot of time for the need of fixing the errors. We base our statements on the natural relationship between quality and error rate, increasing the latter as the error rate decreases. We try to classify errors into several types and address techniques to reduce the likelihood of making mistakes, depending on the type of error. We focus on this approach related to organization, management and software design that will allow to be more effective and efficient in this period where mankind has been affected by a severe pandemic and where we need to be more efficient and effective in all processes, aiming at an industrial renaissance which we know to be not too far and easily reachable once the path to follow has been characterized, also in the light of the experience.
Efficient Secure and Verifiable Location-Based Skyline Queries over Encrypted Data

Supporting secure location-based services on encrypted data that is outsourced to cloud computing platforms remains an ongoing challenge for efficiency due to expensive ciphertext calculation overhead. Furthermore, since the clouds may not be trustworthy or even malicious, data security and result authenticity has caused huge concerns. Unfortunately, little work can enable query efficiency, dataset confidentiality and result authenticity to be commendably guaranteed. In this paper, we demonstrate the potential of supporting secure and verifiable location-based skyline queries (SVLSQ). First, we devise a novel and unified structure, named semi-blind R-tree (SR-tree), which protects the query unlinkability. Based on SR-tree, we propose an authenticated data structure, named secure and verifiable scope R-tree (SVSR-tree). Then, we develop several secure protocols based on SVSR-tree to accelerate the query efficiency and reduce the size of verification objects. Our method avoids compromising the privacy of datasets, queries, results and access patterns. Meanwhile, it authenticates the soundness and completeness of the skyline results while preserving privacy. Finally, we analyze the complexity and security of SVLSQ. Findings from the performance evaluation illustrate that SVLSQ is a dramatically efficient method in terms of query (no less than 3 orders of magnitude faster than other solutions) and verification.