bluuebunny/crossref_metadata_2025_split huggingface dataset:
Immunization with matrix-, nucleoprotein and neuraminidase protects against H3N2 influenza challenge in pH1N1 pre-exposed pigs
Authors: Vatzia Eleni , Feest Katherine , McNee Adam , Manjegowda Tanuja , Carr B Veronica , Pauday Basu , Chrun Tiphany , Maze Emmanuel , Morris Susan , Everett Helen , MacLoughlin Ronan , Salguero Francisco , Lambe Teresa , Gilbert Sarah , Tchilian Elma 
Published: September 2022

Abstract
There is an urgent need for influenza vaccines providing broader protection that may decrease the need for annual immunization. We investigated the efficacy of heterologous prime boost immunization with chimpanzee adenovirus (ChAdOx2) and modified vaccinia Ankara (MVA) vectored vaccines, expressing conserved influenza virus nucleoprotein (NP), matrix protein 1 (M1) and neuraminidase (NA) in H1N1pdm09 pre-exposed pigs. We compared the efficacy of intra-nasal, aerosol and intra-muscular vaccine delivery against H3N2 influenza challenge. Aerosol prime boost immunization induced strong local lung T cell and antibody responses and abrogated viral shedding and lung pathology following H3N2 challenge. In contrast, intramuscular immunization induced powerful systemic responses and weak local lung responses but also abolished lung pathology and reduced viral shedding. These results provide valuable insights into the development of a broadly protective influenza vaccine in a highly relevant large animal model and will inform future vaccine and clinical trial design.
Characterization of a novel Escherichia coli recombineering selection/counterselection cassette
Authors: Zhang Guoyi , Zhang Qiong , Wang Junyu , Zhang Jiao , Shang Guangdong 
Published: September 2022

Abstract
Recombineering is a highly efficient DNA cloning and modification technique by using the recombinase-mediated homologous recombination. Selection/counterselection cassette is often used in chromosomal DNA or large episomal DNA manipulation, in which the selection marker is used for the first step cassette selection, while the counterselection marker is used for the second step replacement of the cassette by the target gene. A variety of selection/counterselection cassettes are reported, however, they suffer from the shortcomings of the requirement of pre-engineered strain or specific culture medium. Herein, we report a novel S-tetR-ptetA-ccdB-aacC1-S selection/counterselection cassette that sidesteps the shortcomings. As a proof-of-concept, one-step gene cloning (0.7 kb, 1.7 kb, and 4.2 kb) and two-step Escherichia coli chromosomal gene knock-in (0.7 kb and 4.2 kb) were performed. The gene cloning and gene knock-in efficiencies are high up to 90%. The cassette adds a powerful tool to the recombineering repertoire.
HIV-Sero-prevalence trend among blood donors in Federal Area of Pakistan in 2022
Authors:   Marina Panezai1
Published: September 2022

Abstract
Although blood transfusion is one of the known therapeutic interventions that cuts across a number of clinical disciplines. It is necessary to test all intending blood donors for HIV infection before donation. The aim of this study was to determine the prevalence of HIV among blood donors at PIMS Blood Bank, Islamabad,Pakistan. A retrospective study was conducted in PIMS Blood Bank through the year 2022. Sera from blood donors were tested for the detection of Anti HIV by using Abott ELISA. Data were abstracted from records and analyzed using Microsoft Excel sheet. From the total of 18500 screened blood samples collected, the prevalence of HIV in blood donors in the blood bank was 0.001% in the 2022 from January to July. The age groups 16-23 and 33-41 were the highest prevalence and the age group 45-54 was the lowest prevalence of HIV infection. The prevalence of HIV among male was higher than in female donors . The trend of HIV infection was decreasing for both male and female blood donors.The prevalence of HIV infections among blood donors is still high in this study setting, and needs constant monitoring to evaluate prevention and control strategies to reduce the burden of transfusion-transmissible HIV infections.
Federated learning for 5G-enabled infrastructure inspection with UAVs
Authors: Lekidis Alexios 
Published: September 2022

Abstract
Electricity infrastructures include assets that require frequent maintenance, as they are exposed into heavy use, in order to produce energy that satisfies customer demands. Such maintenance is currently performed by specialized personnel that is scaffolding to spot damages or malfunctioning equipment. Scaffolding is time-consuming and incurs accident risks. To tackle this challenges, grid operators are gradually using Unmanned Aerial Vehicles (UAVs). UAV trajectories are observed by a centralized operation center engineers for identifying electrical assets. Moreover, asset identification can be further automated through the use of Artificial Intelligence (AI) models. However, centralized training of AI models with UAV images may cause inspection delays when the network is overloaded and requires Cloud environments with enough processing power for model training on the operation center. This imposes privacy concerns as sensitive data is stored and processed externally from the infrastructure facility. This article proposes a federated learning method for UAV-based inspection that leverages a Multi-access Edge Computing platform installed in edge nodes to train UAV data and improve the overall inspection autonomy. The method is applied for the inspection of the Public Power Corporation's Innovation Hub. Experiments are performed with the proposed method as well as with a centralized AI inspection method and demonstrate the federated learning benefits in reliability, AI model processing time and privacy conservation.
Decentralized Multi-Agent Deep Reinforcement Learning: A Competitive-Game Perspective
Authors: Longa Marc Espinós , Tsourdos Antonios , Gokhan Inalhan 
Published: September 2022

Abstract
Deep reinforcement learning (DRL) has been widely studied in single agent learning but require further development and understanding in the multi-agent field. As one of the most complex swarming settings, competitive learning evaluates the performance of multiple teams of agents cooperating to achieve certain goals while surpassing the rest of group candidates. Such dynamical complexity makes the multi-agent problem hard to solve even for niche DRL methods. Within a competitive framework, we study state-of-the-art actor-critic and Q algorithms and analyze in depth their variants (e.g., prioritization, dual networks, etc.) in terms of performance and convergence. For completeness of discussion, we present and assess an asynchronous and prioritized version of proximal policy optimization actor-critic technique (P3O) against the other benchmarks. Results prove that Q-based approaches are more robust and reliable than actor-critic configurations for the given setting. In addition, we suggest incorporating local team communication and combining DRL with direct search optimization to improve learning, especially in challenging scenarios with partial observations.
Does Endorsement from Political Elites Affect Tweeting Behaviour? Studying the Effects of Indian Prime Minister Narendra Modi’s Tweets in 2019
Authors: Neyazi Taberez Ahmed , Ee Tan Khai , Haque Mohammad Amaan 
Published: September 2022

Abstract
Does interactivity on Twitter by political elites yield dividends either in terms of a direct outcome (winning elections) or an indirect outcome (political mobilizations)? We answer this question using a unique dataset of Twitter users (N=27,640) who were among those thanked for their support by the Indian Prime Minister Narendra Modi in his tweets on 16thMarch, 2019 during his campaigning for the general election. We extracted tweets (tweets, retweets and replies) from these users from 10thJanuary (beginning of the campaign) to 19th May 2019 (the day the election ended), which yielded a total of 36.62 million tweets, and proceeded to classify these users based on their activeness on Twitter, for a comprehensive analysis of their Twitter activity over a period of 18 weeks to understand the impact of Modi’s intervention. A controlled intervention analysis using Autoregressive Integrated Moving Average (ARIMA) models was carried out with a control group comprising a similar set of Twitter users (N=27,610) supporting Modi's campaign, but were not mentioned by Modi. Our results suggest that, on average, the aggregate number of tweets shared by users had increased after mentions by Modi. However, our findings do not provide any evidence for the prominence of the activation behavior among less active Twitter users. We discuss the implications of our findings for the use of Twitter by political elites during electoral campaigns. Inferences about political activity on Twitter may also offer important insights into overall political activeness outside Twitter, as evidenced by the use of Twitter activity to capture social trends validated by other studies.
White Blood Cells and Chronic Rhinosinusitis: A Mendelian Randomization Study
Authors: Pongdee Thanai , Bielinski Suzette J , Decker Paul A , Kita Hirohito , Larson Nicholas B 
Published: September 2022

Abstract
Background
Risk factors for the pathogenesis of chronic rhinosinusitis (CRS) remain largely undetermined, which is likely due to the heterogeneity of the disease. White blood cell counts have been largely unexplored as a risk factor for CRS even though different types of white blood cells are involved in the inflammatory process of CRS.
Objective
To investigate causal associations between different types of white blood cells on risk of CRS utilizing a Mendelian randomization (MR) analysis.
Methods
A two-sample MR analysis was performed using respective GWAS summary statistics for the exposure traits (neutrophil count, eosinophil count, basophil count, lymphocyte count, and monocyte count) and outcome trait (CRS). For the exposure traits, the European Bioinformatics Institute database of complete GWAS summary data was used. For the outcome trait, summary statistics for CRS GWAS were obtained from FinnGen. Primary analysis for MR was performed using inverse-variance weighted two-sample MR. Sensitivity analyses included weighted median, MR-Egger, and MR-PRESSO (raw and outlier-corrected).
Results
Eosinophils were associated with CRS (OR = 1.55 [95%CI 1.38,1.73]; p = 4.3E-14). Eosinophil results were similar across additional MR methods. MR results did not demonstrate significant causal relationships between neutrophils, lymphocytes, monocytes, or basophils with CRS. No significant pleiotropic bias was observed.
Conclusions
In a two-sample MR analysis, a potential causal link between blood eosinophil counts and CRS has been demonstrated. In addition, causal relationships between blood counts among other white blood cell types and CRS were not found. Further studies involving genetic variation in CRS are needed to corroborate genetic causal effects for CRS.
Effects of Climate Change on Temperature and Precipitation in the Lake Toba Region Based on ERA5-Land Data with Quantile Mapping Bias Correction
Authors: Irwandi Hendri , Rosid Mohammad Syamsu , Mart Terry 
Published: September 2022

Abstract
Climate change is a serious problem that can cause global variations in temperature and rainfall patterns. This global variation can affect the water availability of lakes. In this study, trends in temperature and rainfall in the Lake Toba area for 40 years (1981–2020) were analyzed using ERA5-Land data corrected with observation station data utilizing the quantile mapping bias correction method. Corrected ERA5-Land data were used in this study to show spatial patterns and trends. The Mann-Kendall and Sen slope tests were carried out to see the magnitude of the trend. A comparison of temperature and rainfall against their baseline period (1951–1980) was also investigated. The results of this study show that climate change has affected the trend of increasing temperature and rainfall in the Lake Toba area, with an increase in temperature of 0.006°C per year and an average rainfall of 0.71 mm per year. In general, significant changes in the increase of temperature and rainfall occurred in the last decade, with an increase in temperature of 0.24°C and rainfall of 22%. The study of the impact of climate change expected to be useful for policymakers in managing water resources in the Lake Toba area.
Cross-validation of correlation networks using modular structure
Authors: Neuman Magnus , Jonsson Viktor , Calatayud Joaquín , Rosvall Martin 
Published: September 2022

Abstract
Correlation networks derived from multivariate data appear in many applications across the sciences. These networks are usually dense and require sparsification to detect meaningful structure. However, current methods for sparsifying correlation networks struggle with balancing overfitting and underfitting. We propose a module-based cross-validation procedure to threshold these networks, making modular structure an integral part of the thresholding. We illustrate our approach using synthetic and real data and find that its ability to recover a planted partition has a step-like dependence on the number of data samples. The reward for sampling more varies non-linearly with the number of samples, with minimal gains after a critical point. A comparison with the well-established WGCNA method shows that our approach allows for revealing more modular structure in the data used here.
Improving quality of life post-tumor craniotomy using personalized, parcel-guided TMS: safety and proof of concept
Authors: Tang Si Jie , Holle Jonas , Lesslar Olivia , Teo Charles , Sughrue Michael , Yeung Jacky 
Published: September 2022

Abstract
Purpose
Deficits in neuro-cognitive function is not uncommon for patients who have undergone surgical removal of brain tumors. Our goal is to evaluate the safety and efficacy of repetitive Transcranial Magnetic Stimulation (rTMS) as a non-invasive tool for the treatment of neuro-cognitive dysfunction following craniotomy.
Methods
We present a retrospective review of individualized rTMS in twelve patients from Cingulum Health from December 2019 to July 2021 who presented with new onset neuro-cognitive deficits following craniotomy. Multiple cortical targets were selected based on the patient’s neurological disorder, associated networks, and anomalies in the functional connectivity of the brain as determined by machine-learning. TMS treatment was performed for 5 consecutive days. EuroQol quality of life (EQ-5D), functional extremity scales, and neuropsychiatric questionnaires related to the patient’s deficit were assessed prior to, after, and during two-month follow-up of rTMS treatment.
Results
Nine patients had unilateral functional deficits in either upper, lower, or both limbs. One patient reported post-operative depression, another experienced short term memory difficulties, and a third reported hypobulia. All twelve patients reported significantly improved EQ5D after rTMS treatment and during follow-up. More than half of the patients with lower and upper functional deficits had a 9-point improvement during follow-up. In the patient who developed depression, an 88% reduction in depressive symptoms based on the Beck’s Depression Inventory (BDI) was observed during follow-up. No adverse events, such as seizures, occurred.
Conclusion
The personalized functional connectivity approach to rTMS treatment may be effective and safe for patients with post-craniotomy neuro-cognitive dysfunction.
Terahertz Channel Performance in Emulated Falling Rain
Authors: Li Peian , Wang Jianchen , Zhao Liangbin , Ma Jianjun , Sun Houjun , Bu Xiangyuan , An Jianping 
Published: September 2022

Abstract
The ever-increasing capacity demand (up to Tbps) in wireless connectivity is supposed can be satisfied by using terahertz frequency band ranging from 100 GHz to 10 THz. This has been proved over short channel distances in laboratory with high order modulation schemes (such as QPSK, QAM) employed. However, in outdoor adverse weathers, investigations on channel performance are not enough due to difficulties in outdoor measurements, and then more concentrations are still required. In this article, we report performance of terahertz channels in emulated falling rain in our lab by utilizing a broadband-pulsed terahertz channel and a 16-QAM modulated data stream. We observe that, the variability of raindrop size distribution is a major source of uncertainty in theoretical precipitation. We also find that the channel degradation in falling rain is mainly due to power attenuation, instead of phase dispersion which is negligible in our measurement.
Assimilative capacity and water quality modeling of rivers: a review
Authors: Darji Jalpa , Lodha Pradeep , Tyagi Sanjiv 
Published: September 2022

Abstract
The rivers rejuvenate themselves by traveling over a distance, thereby they assimilate the pollution load and cause their own self-cleansing, also termed ‘Self-purification capacity’. To ascertain such assimilative capacity of the river system, various water quality models (WQMs) were studied. Out of numerous WQMs, six models including QUAL2Kw, WASP, SWAT, SIMCAT, MIKE-11, and CE-QUAL-W2 were selected and studied on the basis of their development, characteristics, capabilities and strengths, model input, governing equations, application, assumptions and limitations. A comparison based on such a study showing input variables and data, assumptions and limitations, strengths, and specific characteristics has been carried out and tabulated. While the selection of a model is based on the problem for which the decision-making is to be done. Of all the models, QUAL2Kw and WASP have been found to be advantageous over the rest. For a complex river system, a single model may not work and in such cases, a combination may be tried. A model finally selected for a problem must be calibrated so as to have minimum errors and maximum accuracy.
Modeling of the As (III) adsorption using Fe impregnated polyethylene terephthalate char matrix: A statistical approach
Authors: Sawood Ghazi Mohd , Gautam Shashi Bala , Mishra Ashutosh , Dixit Shobhit , Singh Neeta 
Published: September 2022

Abstract
The present research aimed to analyse the impact of economical Fe impregnated polyethylene terephthalate (PET) char (PETC-Fe) for adsorption of As (III) through series of column experiments. For an inlet arsenite concentration of 1,000 μg/L, PETC-Fe exhibits excellent uptake capacity of 1,892 μg/g. Central composite design (CCD) in response surface methodology (RSM) was used to evaluate the influence of various process variables on the response function (breakthrough time) for optimization and assessment of interaction effects. The breakthrough time is more responsive to influent As (III) concentration and bed height than inlet flow rate, according to the perturbation plot. Adams–Bohart, Bed Depth Service Time (BDST) model, and Thomas models were used to model the dynamics of the adsorption system. The BDST model suited the experimental data well in the early part of the breakthrough curve, but there were minor variations over the breakpoints. Despite the fact that the experimental values and the data sets estimated using the Adams–Bohart model followed a similar pattern, they differed slightly. The PETC-Fe was found to be a sustainable and highly economical adsorbent, with a desorption performance of more than 97%, indicating the adsorbent's reusability. This adsorbent's excellent As (III) uptake capacity and regeneration performance imply that it might be used in industrial/domestic applications, and the information obtained could aid in future scaling up of the adsorption system.
Photocatalysis process to treat polluted water by azo dye Cibacron Brilliant Yellow 3G-P
Authors: Radia Djouder , Fouzia Touahra , Rachida Rihani , Wahib Naceur Mohamed , Bentahar Fatiha 
Published: September 2022

Abstract
The main objective of this study was to investigate the photodegradation of azo dye Cibacron Brilliant Yellow 3G-P using Anatase, Degussa-P25 and ZnO. These semi-conductors were characterized using XRD, BET and TEM-EDX. The variation of the amount of semi-conductors significantly affect the rate of color removal. The decolorization rate increased as the catalyst dosage was increased. Other parameters were also studied, such as stirring speed, pH, and initial dye concentration. It was found that the rate of decolorization increases with the increase of stirring speed. Decolorization of about 30, 60 and 80% was respectively achieved in the case of Anatase, Degussa-P25 and ZnO at low stirring speed (50rpm). At pH = 3, the degradation rate was found to be higher than the alkaline pH, about 95.58 and 85.71% of color has been decolorized with Anatase and Degussa-P25 respectively. While using ZnO, the color removal reached maximum in acidic and alkaline solutions, more than 95% of dye was decolorized. The concentrations dye solutions less than 80ppm led to the removal rate of about 95% in the case of ZnO, while it was only about 8–15% in the case of TiO2 with the concentration more than 20 ppm.
Zika Virus NS2B-NS3 Protease: Quantum Chemical Properties Insights
into Designing Inhibitory Peptides
Authors: Silva João Vitor , Savino Débora , Hirata Mario Hiroyuki , Ferreira Gláucio Monteiro , Giarolla Jeanine 
Published: September 2022

Background:
Zika fever affects poor and vulnerable populations, presenting cycles observed
in, at least 86 countries, with no vaccine prevention or treatment available. It is known that the genus
Flavivirus causes Zika Virus (ZIKV), as Dengue and Yellow Fever, whose genetic material decodes,
among other proteins, a series of non-structural (NS) proteins essential for viral replication, such as
NS2B-NS3 protease. Additionally, chemical and biological systems are commonly studied using
molecular modeling approaches allowing, among several other processes, to elucidate mechanisms of
action, molecule reactivity and/or chemical properties and the design of new drugs. Thus, considering
the in silico complexes between the biological target and the bioactive molecule, it is possible to
understand better experimental results based on molecular properties, which are compared with the
findings of the biological activity.

Objective:
Accordingly, this study aimed to present computational docking simulations of five
previously reported active peptides against NS2B-NS3 protease of ZIKV and analyze some quantum
chemical properties to identify the main contribution to improving the action.

Methods:
The compounds were described by Rut and coworkers (2017) and Hill and coworkers (2018),
submitted to docking simulation in Gold software and quantum chemical properties calculations in
Wavefunction Spartan software.

Results:
Total energy, electrophilicity index (ω) and energy gap (GAP) appeared to be the best
properties to justify the peptide's biological activity.
Moreover, the most promising compound (P1, Km 4.18 μM) had the best value of total energy (-
2763.04001 au), electrophilicity index (8.04 eV) and GAP (6.49 eV), indicating an energetically
favorable molecule with good interaction with the target and, when compared to other peptides,
presented moderate reactivity. P4 showed the highest electrophilicity index value (28.64 eV), which
justified the interaction ability visualized in the docking simulation. However, its GAP value (4.24 eV)
was the lowest in the series, suggesting high instability, possibly validating its low biological activity
value (Km 19 uM). GAP was important to understand the chemical instability, and high values can
promote damage to biological response.

Conclusion:
Furthermore, it was also noted that high electron affinity, related to the electrophilicity
index, promoted electron-accepting characteristics, which was important to improve the biological
activity of the peptides. A larger compound series must be studied to access features more precisely.
However, these results have paramount importance in guiding future effort in this extremely-need
health area.