bluuebunny/crossref_metadata_2025_split huggingface dataset:
Identification and functional interpretation of miRNAs affected by rare CNVs in CAKUT
Authors: Mitrovic Kristina , Zivotic Ivan , Kolic Ivana , Djordjevic Ana , Zakula Jelena , Filipovic Trickovic Jelena , Zivkovic Maja , Stankovic Aleksandra , Jovanovic Ivan 
Published: October 2022

AbstractRare copy number variants (CNVs) are among the most common genomic disorders underlying CAKUT. miRNAs located in rare CNVs represent well-founded functional variants for human CAKUT research. The study aimed to identify and functionally interpret miRNAs most frequently affected by rare CNVs in CAKUT and to estimate the overall burden of rare CNVs on miRNA genes in CAKUT. The additional aim of this study was to experimentally confirm the effect of a rare CNV in CAKUT on candidate miRNA’s expression and the subsequent change in mRNA levels of selected target genes. A database of CAKUT-associated rare CNV regions, created by literature mining, was used for mapping of the miRNA precursors. miRNAs and miRNA families, most frequently affected by rare CAKUT-associated CNVs, have been subjected to bioinformatic analysis. CNV burden analysis was performed to identify chromosomes with over/underrepresentation of miRNA genes in rare CNVs associated with CAKUT. A functional study was performed on HEK293 MIR484+/- KO and HEK293 WT cell lines, followed by the analysis of relative miRNA and mRNA target gene levels. 80% of CAKUT patients with underlying rare CNV had at least one miRNA gene overlapping the identified CNV. Network analysis of the most frequently affected miRNAs has revealed the dominant regulation of the two miRNAs, hsa-miR-484 and hsa-miR-185-5p. Additionally, miR-548 family members have shown substantial enrichment in rare CNVs in CAKUT. An over/underrepresentation of miRNA genes in rare CNVs associated with CAKUT was observed in multiple chromosomes, such as chr16, chr20, and chr21. A significant 0.37 fold downregulation of hsa-miR-484, followed by a notable upregulation of MDM2 and APAF1 and downregulation of NOTCH3 was detected in HEK293 MIR484+/- KO compared to HEK293 WT cell lines, supporting the study hypothesis. miRNA genes are frequently affected by rare CNVs in CAKUT patients. Understanding the potential of CNV-affected miRNAs to participate in CAKUT as genetic drivers represent a crucial implication for the development of novel therapeutic approaches.
Genome sequence and characterization of Streptomyces phage Pablito, representing a new species within the genus Janusvirus
Authors: Ongenae Véronique , Azeredo Joana , Kropinski Andrew M. , Rozen Daniel , Briegel Ariane , Claessen Dennis 
Published: October 2022

AbstractStreptomycetes are ubiquitous soil bacteria. Here we report the complete and annotated genome sequence and characterization of Streptomyces phage Pablito, isolated from a soil sample in Haarlem, the Netherlands using Streptomyces lividans as host. This phage was able to infect a diverse range of Streptomyces strains, but none belonging to the sister genus Kitasatospora. Phage Pablito has double-stranded DNA with a genome length of 49,581 base pairs encoding 76 putative proteins, of which 26 could be predicted. The presence of a serine integrase protein indicated the lysogenic nature of phage Pablito. The phage remained stable over a wide range of temperatures (25–45 °C) and at pH ≥ 7.0, but lost infectivity at temperatures above 55 °C or when the pH dropped below 6.0. This newly isolated phage is closely related to Streptomyces phage Janus and Hank144 and considered a new species classified in the genus Janusvirus, within the subfamily Arquattrovirinae.
Visual consequent stimulus complexity affects performance in audiovisual associative learning
Authors: Tót Kálmán , Eördegh Gabriella , Kiss Ádám , Kelemen András , Braunitzer Gábor , Kéri Szabolcs , Bodosi Balázs , Nagy Attila 
Published: October 2022

AbstractIn associative learning (AL), cues and/or outcome events are coupled together. AL is typically tested in visual learning paradigms. Recently, our group developed various AL tests based on the Rutgers Acquired Equivalence Test (RAET), both visual and audiovisual, keeping the structure and logic of RAET but with different stimuli. In this study, 55 volunteers were tested in two of our audiovisual tests, SoundFace (SF) and SoundPolygon (SP). The antecedent stimuli in both tests are sounds, and the consequent stimuli are images. The consequents in SF are cartoon faces, while in SP, they are simple geometric shapes. The aim was to test how the complexity of the applied consequent stimuli influences performance regarding the various aspects of learning the tests assess (stimulus pair learning, retrieval, and generalization of the previously learned associations to new but predictable stimulus pairs). In SP, behavioral performance was significantly poorer than in SF, and the reaction times were significantly longer, for all phases of the test. The results suggest that audiovisual associative learning is significantly influenced by the complexity of the consequent stimuli.
Automated clinical coding: what, why, and where we are?
Authors: Dong Hang , Falis Matúš , Whiteley William , Alex Beatrice , Matterson Joshua , Ji Shaoxiong , Chen Jiaoyan , Wu Honghan 
Published: October 2022

AbstractClinical coding is the task of transforming medical information in a patient’s health records into structured codes so that they can be used for statistical analysis. This is a cognitive and time-consuming task that follows a standard process in order to achieve a high level of consistency. Clinical coding could potentially be supported by an automated system to improve the efficiency and accuracy of the process. We introduce the idea of automated clinical coding and summarise its challenges from the perspective of Artificial Intelligence (AI) and Natural Language Processing (NLP), based on the literature, our project experience over the past two and half years (late 2019–early 2022), and discussions with clinical coding experts in Scotland and the UK. Our research reveals the gaps between the current deep learning-based approach applied to clinical coding and the need for explainability and consistency in real-world practice. Knowledge-based methods that represent and reason the standard, explainable process of a task may need to be incorporated into deep learning-based methods for clinical coding. Automated clinical coding is a promising task for AI, despite the technical and organisational challenges. Coders are needed to be involved in the development process. There is much to achieve to develop and deploy an AI-based automated system to support coding in the next five years and beyond.
Potential effects of metal ion induced two-state allostery on the regulatory mechanism of add adenine riboswitch
Authors: Bao Lei , Kang Wen-Bin , Xiao Yi 
Published: October 2022

AbstractRiboswitches normally regulate gene expression through structural changes in response to the specific binding of cellular metabolites or metal ions. Taking add adenine riboswitch as an example, we explore the influences of metal ions (especially for K+ and Mg2+ ions) on the structure and dynamics of riboswitch aptamer (with and without ligand) by using molecular dynamic (MD) simulations. Our results show that a two-state transition marked by the structural deformation at the connection of J12 and P1 (CJ12-P1) is not only related to the binding of cognate ligands, but also strongly coupled with the change of metal ion environments. Moreover, the deformation of the structure at CJ12-P1 can be transmitted to P1 directly connected to the expression platform in multiple ways, which will affect the structure and stability of P1 to varying degrees, and finally change the regulation state of this riboswitch.
A hemispheric two-channel code accounts for binaural unmasking in humans
Authors: Encke Jörg , Dietz Mathias 
Published: October 2022

AbstractSound in noise is better detected or understood if target and masking sources originate from different locations. Mammalian physiology suggests that the neurocomputational process that underlies this binaural unmasking is based on two hemispheric channels that encode interaural differences in their relative neuronal activity. Here, we introduce a mathematical formulation of the two-channel model – the complex-valued correlation coefficient. We show that this formulation quantifies the amount of temporal fluctuations in interaural differences, which we suggest underlie binaural unmasking. We applied this model to an extensive library of psychoacoustic experiments, accounting for 98% of the variance across eight studies. Combining physiological plausibility with its success in explaining behavioral data, the proposed mechanism is a significant step towards a unified understanding of binaural unmasking and the encoding of interaural differences in general.
Hyper clustering model for dynamic network intrusion detection
Authors: Alfoudi Ali Saeed , Aziz Mohammad R. , Alyasseri Zaid Abdi Alkareem , Alsaeedi Ali Hakem , Nuiaa Riyadh Rahef , Mohammed Mazin Abed , Abdulkareem Karrar Hameed , Jaber Mustafa Musa 
Published: October 2022

AbstractGenerally, the existing Intrusion Detection Systems (IDS) solutions suffer from low detection accuracy for some attack types compared with the overall detection accuracy of attacks. The data imbalance technically affects the ratio of detection accuracy of low frequent attacks class (e.g. zero‐day attack) compared to attacks with more instances. Therefore, IDS‐based machine learning algorithms potentially suffer from high false‐positive rates. To overcome the limitation of existing solutions, a hyper‐clustering model is proposed for dynamic intrusion detection based on the Density‐Based Spatial Clustering of Applications with Noise (DBSCAN) and cosine similarity. The proposed solution develops the standard DBSCAN by adding a new evolving process based on distance measures between the clusters to overcome the imbalance dataset. Moreover, a new classifier is proposed based on cosine similarity to predict the labelling of abnormal behaviour. The experimental results show that the proposed model outperformed the original DBCAN and the related works. The mean silhouette of the proposed DBSCAN achieves a high score of 0.87 compared to other solutions. Furthermore, the proposed DBSCAN reduces the mean square error from 0.66 to 0.13 and achieves 86.82%, 79.10% and 90.03% in general accuracy on KDDTest+, KDDTest‐21 NSL‐KDD and UNSW‐NB15 benchmark datasets, respectively.
Control of the formation and amplification of pulse bursts in regenerative amplifiers
Authors: Deutschmann‐Olek Andreas , Schrom Katharina , Kugi Andreas 
Published: October 2022

AbstractThis paper presents control strategies to generate bursts of high‐intensity laser pulses with arbitrary envelope from regenerative amplifiers by suitably adjusting the energy of the injected seed pulses. To this end, existing and experimentally validated models are generalized to obtain a dynamical model of the pulse formation and amplification. The resulting model is applicable to standard regenerative amplifiers as well as amplifiers with a detuned cavity specifically designed for the generation of pulse bursts. Utilizing this mathematical model, an optimization‐based algorithm to obtain desired pulse bursts in steady state is presented. Since the quality of these feedforward solutions is limited due to parameter variations and model imprecisions, an adaptation scheme using iterative learning control methods is employed to track the desired burst envelope. Finally, the developed methods are combined with feedback strategies to allow for an operation in unstable regimes and the closed‐loop behaviour is illustrated by simulation scenarios.
Named data network dynamic cache placement strategy based on programmable data plane
Authors: Hou Saifeng , Hu Yuxiang , Tian Le 
Published: October 2022

AbstractAiming at the efficiency and implementation of in‐network cache in Named Data Network, an in‐network cache method based on the programmable data plane was proposed. Set the cache port on the programmable data plane, when the cache policy determined that the content needs to be cached, set the output port as the cache port and forward it to the cache unit for caching. According to the different requirements of different contents on Quality of Service, the request contents were classified. And the cache probability of classified contents was calculated based on the content popularity and the cache cooperation information between nodes. The cache threshold was dynamically set according to the state of cache space occupancy and compared with the cache probability to determine whether to cache the contents. Experimental results show that the proposed cache placement strategy can effectively improve the cache hit ratio and reduce the average transmission latency compared with the traditional cache placement strategy.
Selective harmonic elimination pulse width modulation based hybrid multilevel inverter topology with reduced components
Authors: Wasiq Mohammad , Memon Mudasir Ahmed , Shrivastava Prashant , Mekhilef Saad , Seyedmahmoudian Mehdi , Stojcevski Alex , Horan Ben 
Published: October 2022

AbstractIn this paper, a reduced switch count single‐phase hybrid multilevel inverter (MLI) is presented. Level generation unit (LGU) and polarity changing unit (PCU) are the two parts of the presented topology which are connected in series. Other advantages of the proposed topology include the reduced switch count, higher level generation with reduced sources and the possibility of higher‐level generation with lower component counts. A single unit produces an output voltage of 13 levels with the modulation techniques as selective harmonic elimination pulse width modulation (SHEPWM) to improve harmonics. The use of selective harmonic elimination (SHM) is made to improve harmonics. The logical generation unit carries a series connection of multiple switched dc voltage sources with half and full‐bridge configurations. The proposed topology is verified by a hardware bench setup as well as in simulations which are developed in Simulink/MATLAB® environment.
FEM simulation‐based development of a new tunable non‐magnetic RF high voltage capacitor for the new generation of MRI
Authors: Jebri Zaineb , Bord‐Majek Isabelle , Bardet Matthieu , Ousten Yves 
Published: October 2022

AbstractUsing Radio Frequency (RF) waves, magnetic resonance imaging (MRI) systems can make detailed images of human organs for accurate diagnostic processes and disease detection. The overhaul of certain electronic components has become necessary to keep up with the progress of MRI systems. Among the components responsible for image quality, the adjustable non‐magnetic capacitors, also called trimmers, are of great importance. The purpose of this paper is to suggest a new design of a trimmer using non‐magnetic materials, able to hold a high voltage ( >3 kV) and reach a resonance frequency above 100 MHz. Constructional analysis performed on existing commercial trimmers, combined with the electrical Finite Element Method, were carried out to propose a prototype matching the desired specifications. A dielectric shield surrounding the electrodes was sized to ensure voltage withstand. Moreover, the rotor and the worm‐and‐gear set were joined together to combat the vibrations generated by the MRI system. The present study includes the modelling step of the component by numerical simulation, the manufacturing, the electrical performance characterization, and the mechanical solution for tuning capacitance. The final prototype combines electrical performance corresponding to the required specifications in particular a high breakdown voltage (39.7 kV) and a resonance frequency (130 MHz).
The impact of gender diversity on scientific research teams: a need to broaden and accelerate future research
Authors: Love Hannah B. , Stephens Alyssa , Fosdick Bailey K. , Tofany Elizabeth , Fisher Ellen R. 
Published: October 2022

AbstractMultiple studies from the literature suggest that a high proportion of women on scientific teams contributes to successful team collaboration, but how the proportion of women impacts team success and why this is the case, is not well understood. One perspective suggests that having a high proportion of women matters because women tend to have greater social sensitivity and promote even turn-taking in meetings. Other studies have found women are more likely to collaborate and are more democratic. Both explanations suggest that women team members fundamentally change team functioning through the way they interact. Yet, most previous studies of gender on scientific teams have relied heavily on bibliometric data, which focuses on the prevalence of women team members rather than how they act and interact throughout the scientific process. In this study, we explore gender diversity in scientific teams using various types of relational data to investigate how women impact team interactions. This study focuses on 12 interdisciplinary university scientific teams that were part of an institutional team science program from 2015 to 2020 aimed at cultivating, integrating, and translating scientific expertise. The program included multiple forms of evaluation, including participant observation, focus groups, interviews, and surveys at multiple time points. Using social network analysis, this article tested five hypotheses about the role of women on university-based scientific teams. The hypotheses were based on three premises previously established in the literature. Our analyses revealed that only one of the five hypotheses regarding gender roles on teams was supported by our data. These findings suggest that scientific teams may create ingroups, when an underrepresented identity is included instead of excluded in the outgroup, for women in academia. This finding does not align with the current paradigm and the research on the impact of gender diversity on teams. Future research to determine if high-functioning scientific teams disrupt rather than reproduce existing hierarchies and gendered patterns of interactions could create an opportunity to accelerate the advancement of knowledge while promoting a just and equitable culture and profession.
Clustering and flocking of repulsive chiral active particles with non-reciprocal couplings
Authors: Kreienkamp Kim L , Klapp Sabine H L 
Published: October 2022

Abstract
Recently, non-reciprocal systems have become a focus of growing interest. Examples occur in soft and active matter, but also in engineered quantum materials and neural (brain) networks. Here, we investigate the impact of non-reciprocity on the collective behavior of a system of (dry) chiral active matter. Specifically, we consider a mixture of ‘circle swimmers’ with steric interactions and non-reciprocal alignment couplings. Based on hydrodynamic equations which we derive from a set of Langevin equations, we explore the interplay of non-reciprocity, finite size, and chirality. We first consider, as a reference, one-species systems with reciprocal couplings. Based on a linear stability analysis and numerical simulations, we here observe three different types of collective behavior, that is, flocking, motility-induced phase separation, and a combination of both. Turning then to a non-reciprocal system, we find that non-reciprocity can turn otherwise stationary instabilities into oscillatory ones, affect the relative orientation of flocks, and, crucially, change the general type of instability. This illustrates the drastic impact of non-reciprocity on the emergent collective dynamics of chiral active matter systems, with potentially far-reaching biological implications.
Honeybees modify flight trajectories in turbulent wind
Authors: Hejazi Bardia , Küchler Christian , Bagheri Gholamhossein , Bodenschatz Eberhard 
Published: October 2022

AbstractIn windy conditions, the air is turbulent. The strong and intermittent velocity variations of turbulence are invisible to flying animals. Nevertheless, flying animals, not much larger than the smallest scales of turbulence, manage to maneuver these highly fluctuating conditions quite well. Here we quantify honeybee flight with time-resolved three-dimensional tracking in calm conditions and controlled turbulent winds. We find that honeybee mean speed and acceleration are only weakly correlated with the strength of turbulence. In flight, honeybees accelerate slowly and decelerate rapidly, i.e., they break suddenly during turns and then accelerate again. While this behavior is observed in both calm and turbulent conditions, it is increasingly dominant under turbulent conditions where short straight trajectories are broken by turns and increased maneuvering. This flight-crash behavior is reminiscent of turbulence itself. Our observations may help the development of flight strategies for miniature flying robotics under turbulent conditions.
Understanding recent tropospheric ozone trends in the context of large internal variability: a new perspective from chemistry-climate model ensembles
Authors: Fiore Arlene M , Hancock Sarah E , Lamarque Jean-François , Correa Gustavo P , Chang Kai-Lan , Ru Muye , Cooper Owen , Gaudel Audrey , Polvani Lorenzo M , Sauvage Bastien , Ziemke Jerry R 
Published: October 2022

Abstract
Observational records of meteorological and chemical variables are imprinted by an unknown combination of anthropogenic activity, natural forcings, and internal variability. With a 15-member initial-condition ensemble generated from the CESM2-WACCM6 chemistry-climate model for 1950–2014, we extract signals of anthropogenic (‘forced’) change from the noise of internally arising climate variability on observed tropospheric ozone trends. Positive trends in free tropospheric ozone measured at long-term surface observatories, by commercial aircraft, and retrieved from satellite instruments generally fall within the ensemble range. CESM2-WACCM6 tropospheric ozone trends are also bracketed by those in a larger ensemble constructed from five additional chemistry-climate models. Comparison of the multi-model ensemble with observed tropospheric column ozone trends in the northern tropics implies an underestimate in regional precursor emission growth over recent decades. Positive tropospheric ozone trends clearly emerge from 1950 to 2014, exceeding 0.2 DU yr−1 at 20–40 N in all CESM2-WACCM6 ensemble members. Tropospheric ozone observations are often only available for recent decades, and we show that even a two-decade record length is insufficient to eliminate the role of internal variability, which can produce regional tropospheric ozone trends oppositely signed from ensemble mean (forced) changes. By identifying regions and seasons with strong anthropogenic change signals relative to internal variability, initial-condition ensembles can guide future observing systems seeking to detect anthropogenic change. For example, analysis of the CESM2-WACCM6 ensemble reveals year-round upper tropospheric ozone increases from 1995 to 2014, largest at 30 S–40 N during boreal summer. Lower tropospheric ozone increases most strongly in the winter hemisphere, and internal variability leads to trends of opposite sign (ensemble overlaps zero) north of 40 N during boreal summer. This decoupling of ozone trends in the upper and lower troposphere suggests a growing prominence for tropospheric ozone as a greenhouse gas despite regional efforts to abate warm season ground-level ozone.