bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gravitational Wave Radiation from Newborn Accreting Magnetars
Authors: Cheng Quan , Zheng Xiao-Ping , Fan Xi-Long , Huang Xi 
Published: December 2022

Abstract
The observed electromagnetic radiation from some long and short gamma-ray bursts, and neutron stars (NSs), and the theoretical models proposed to interpret these observations together point to a very interesting but confusing problem, namely, whether fall-back accretion could lead to dipole field decay of newborn NSs. In this paper, we investigate the gravitational wave (GW) radiation of newborn magnetars with a fall-back disk formed in both the core-collapse of massive stars and the merger of binary NSs. We make a comparison of the results obtained with and without fall-back accretion-induced dipole-field decay (FADD) involved. Depending on the fall-back parameters, initial parameters of newborn magnetars, and models used to describe FADD, FADD may indeed occur in newborn magnetars. Because of the low dipole fields caused by FADD, the newborn magnetars will be spun up to higher frequencies and have larger masses in comparison with the non-decay cases. Thus the GW radiation of newborn accreting magnetars would be remarkably enhanced. We propose that observation of GW signals from newborn magnetars using future GW detectors may help to reveal whether FADD could occur in newborn accreting magnetars. Our model is also applied to the discussion of the remnant of GW170817. From the post-merger GW searching results of Advanced LIGO and Advanced Virgo we cannot confirm the remnant is a low-dipole-field long-lived NS. Future detection of GWs from GW170817-like events using more sensitive detectors may help to clarify the FADD puzzle.
Mechanically controlled robotic gripper with bistability for fast and adaptive grasping
Authors: Cai Xianyang , Tang Bin 
Published: December 2022

Abstract
This paper presents a novel bistable gripper inspired by the closure motion found in the jaw of a hummingbird. With a bistable characteristic, the robotic gripper can grasp objects rapidly without applying continuous external force. The bistable gripper comprises a linkage-driven mechanism and two bionic jaws consisting of thin elastic polyvinyl chloride sheets with two clamped ends connected by a hinge. The shape of the thin sheets was modeled and optimized using geometric analysis, and the morphing processes of the bionic jaw were analyzed using finite element simulations and experiments. Furthermore, we explored the motion characteristics of the clamps during the snap-through and snap-back processes and divided the motion into two phases: delay and snap. Force and response time tests show that the proposed bistable gripper can achieve fast bending within milliseconds under a low pull force during the snap phase. Grasping experiments demonstrated that the proposed robotic gripper is adaptable for grasping objects of various shapes and weights. After grasping, the bistable gripper can release the target by pulling the actuating rod and automatically return to the open state. This study reveals the unique bending mechanism of thin sheets that can be exploited for fast, versatile, and adaptive grasping. The bistable gripper exhibits the potential to reduce energy consumption and simplify control when performing tasks in unstructured environments such as space and underwater.
Effect of moisture content on the microscopic properties of amorphous cellulose: a molecular dynamics simulations
Authors: Jiang Kaixiang , Yan Zhe , Fang Wenjuan , Zhang Youqiang 
Published: December 2022

Abstract
Performance degradation of cellulose and cellulose-based materials caused by water is an inevitable problem in application processes. In most studies, this was attributed to the fracture and rebuilding of the hydrogen bond network in the system; however, limited attention was paid to the movement, aggregation state, and specific property evolution of cellulose and water during this process. In this study, based on molecular dynamics simulations, the effects of moisture content on the microscopic properties of cellulose are investigated, including the mechanical properties, diffusion coefficient, glass transition temperature, microscopic motion of water molecules, and preferred hydration sites on cellulose. The results show that the mechanical properties of the system increase and then decrease as the water content in the system increases. When the moisture content is 4%, the mechanical properties of cellulose are the best, and the elastic modulus and shear modulus increase by 7.6% and 9.4%, respectively, compared with those of dry cellulose. The glass transition temperature of the system with 4% moisture content increases by 72 K compared with that of dry cellulose. The mean square displacement and diffusion coefficient of water in the system is affected by the water molecules’ polymerisation state and the free water content. In the entire range of water contents studied, hydroxyl groups O2, O3, and O6 of cellulose dominate the reaction with water compared with acetal oxygens O4 and O5. In the system with 4% moisture content, the number of water molecules around the glycosidic bonds O4 are the most minor and cause the least damage to the cellulose structure. A critical water content point of 4% is recommended, and this result is expected to provide a reference for maintaining the excellent and stable properties of cellulose and cellulose-based materials.
Towards advanced divertor configurations on the J-TEXT tokamak
Authors: LIANG Yunfeng , CHEN Zhipeng , WANG Nengchao , CHENG Zhifeng , KNIEPS Alexander , ZHOU Song , RAO Bo , XU Shuai , DREWS Philipp , ZHANG Xiaolong , WANG Hao , WANG Zhaosu , YANG Jie , XU Xin , HUA Jiankun , YANG Qinghu , YAN Wei , LI Cunkai , YANG Yutong , LI Shuhao , LIU Shaocheng , NIE Lin , LONG Ting , LIAO Liang , WANG Fuqiong , SUZUKI Yasuhiro 
Published: December 2022

Abstract
Developing advanced magnetic divertor configurations to address the coupling of heat and particle exhaust with impurity control is one of the major challenges currently constraining the further development of fusion research. It has therefore become the focus of extensive attention in recent years. In J-TEXT, several new divertor configurations, including the high-field-side single-null poloidal divertor and the island divertor, as well as their associated fundamental edge divertor plasma physics, have recently been investigated. The purpose of this paper is to briefly summarize the latest progress and achievements in this relevant research field on J-TEXT from the past few years.
Qade: solving differential equations on quantum annealers
Authors: Criado Juan Carlos , Spannowsky Michael 
Published: December 2022

Abstract
We present a general method, called Qade, for solving differential equations using a quantum annealer. One of the main advantages of this method is its flexibility and reliability. On current devices, Qade can solve systems of coupled partial differential equations that depend linearly on the solution and its derivatives, with non-linear variable coefficients and arbitrary inhomogeneous terms. We test this through several examples that we implement in state-of-the-art quantum annealers. The examples include a partial differential equation and a system of coupled equations. This is the first time that equations of these types have been solved in such devices. We find that the solution can be obtained accurately for problems requiring a small enough function basis. We provide a Python package implementing the method at gitlab.com/jccriado/qade.
Multi-response optimization of process and reinforcement parameters of hybrid reinforced Al matrix composites using Taguchi- Grey relational analysis
Authors: Ashebir Demeke Abay , Mengesha Getinet Asrat , Sinha Devendra Kumar , Bereda Yodit Birhanu 
Published: December 2022

Abstract
Hybrid aluminum matrix composites (HAMCs) are a new class of advanced composite and hybrid materials that can be customized and engineered to achieve specific properties for specific applications in specific environments. HAMCs are popular in the transportation industry due to their reduced cost and fuel consumption as compared to conventional materials. This research article has mainly focused on multi-response optimization through an L16 orthogonal array experimental design employing Taguchi-based Grey Relational Analysis. It was intended to explore the influence of tetra hybrid reinforced HAMCs synthesized using pure Al matrix with fixed wt% of primary reinforcements (5 wt% SiC and 5 wt% Al2O3) and varying wt% of secondary reinforcements such as (0.5, 2.5, 4.5, and 6.5) wt% of Gr and (0.5, 2.5, 4.5, and 6.5) wt% of SCBA on physicomechanical properties of HAMCs when milling time, compaction pressure, and sintering temperature were varied. The Taguchi-Grey’s relational analysis gave the optimal combination of the process and reinforcement parameters for both the physical and the mechanical properties such as milling time (5 h.), compaction pressure (55 MPa), sintering temperature (450 °C), Gr content (0.5 wt%), and SCBA content (4.5 wt%). At the optimum parameter settings, the average density, porosity, hardness, compressive strength, and ultimate tensile strength were 2.5118 gm cm−3, 0.8653%, 4228.45 MPa, 343.33 MPa, and 1516.41 MPa, respectively. The utilization of Taguchi and GRA methods have significantly confirmed that the influence of compaction pressure was highest among the all the other four parameters. The newly synthesized tetra hybrid reinforced HAMCs have shown superior physicomechanical properties compared to pure Al, and single as well as double reinforced HAMCs. Therefore, it is anticipated that the newly developed tetra hybrid reinforced AMC material will be utilized in heavy-duty, aerospace, medical, automotive, marine, and other applications.
Impact of the COVID-19 pandemic on the carbon footprint of a Philippine university
Authors: Cortes Aiza , dos Muchangos Letícia , Tabornal Krissa Joy , Tolabing Hans Diether 
Published: December 2022

Abstract
The Philippines entered its most prolonged lockdown in 2020 when the coronavirus disease (COVID-19) became a pandemic. Additionally, there has been a shift from physical to online classes at all education levels. Against this backdrop, the restrictions imposed on the education sector could have environmental impacts, including on the carbon emission structure. Here, we compare the carbon footprint before and during the pandemic, determine how the pandemic changed the activities that directly affected carbon emissions, and present reduction methods to minimise emissions in the new normal. We calculated emissions before and during the pandemic to achieve these goals, using the data obtained from University of the Philippines (UP) Cebu. The total CO2 emissions of UP Cebu in 2019 were estimated to be 1420.7 tCO2e, which did not significantly differ from the 2018 emissions. In 2020, the total CO2 emissions were estimated to be 555.8 tCO2e, equivalent to a 60.9% decrease from the 2019 emissions. The per capita emissions in UP Cebu for 2019 and 2020 were estimated to be 0.9 tCO2e and 0.3 tCO2e, respectively—both below the national average. The pandemic caused a significant decrease in emissions per activity, except for fuel-related emissions which increased by 305.8%. In the post-COVID-19 world, especially when in-person classes return, UP Cebu must consider concrete strategies to curb its emissions. Specific decarbonisation methods for each activity were simulated and discussed. The results and reduction strategies presented are relevant to UP Cebu and other higher education institutions in the Philippines and Asia with the same characteristics.
Synggen: fast and data-driven generation of synthetic heterogeneous NGS cancer data
Authors: Scandino Riccardo , Calabrese Federico , Romanel Alessandro 
Published: December 2022

Abstract

Summary
Whole-exome and targeted sequencing are widely utilized both in translational cancer genomics and in the setting of precision medicine. The benchmarking of computational methods and tools that are in continuous development is fundamental for the correct interpretation of somatic genomic profiling results. To this aim we developed synggen, a tool for the fast generation of large-scale realistic and heterogeneous cancer whole-exome and targeted sequencing synthetic datasets, which enables the incorporation of phased germline single nucleotide polymorphisms and complex allele-specific somatic genomic events. Synggen performances and effectiveness in generating synthetic cancer data are shown across different scenarios and considering different platforms with distinct characteristics.

Availability and implementation
synggen is freely available at https://bitbucket.org/CibioBCG/synggen/.

Supplementary information
Supplementary data are available at Bioinformatics online.
DockNet: high-throughput protein–protein interface contact prediction
Authors: Williams Nathan P , Rodrigues Carlos H M , Truong Jia , Ascher David B , Holien Jessica K 
Published: December 2022

Abstract

Motivation
Over 300 000 protein–protein interaction (PPI) pairs have been identified in the human proteome and targeting these is fast becoming the next frontier in drug design. Predicting PPI sites, however, is a challenging task that traditionally requires computationally expensive and time-consuming docking simulations. A major weakness of modern protein docking algorithms is the inability to account for protein flexibility, which ultimately leads to relatively poor results.

Results
Here, we propose DockNet, an efficient Siamese graph-based neural network method which predicts contact residues between two interacting proteins. Unlike other methods that only utilize a protein’s surface or treat the protein structure as a rigid body, DockNet incorporates the entire protein structure and places no limits on protein flexibility during an interaction. Predictions are modeled at the residue level, based on a diverse set of input node features including residue type, surface accessibility, residue depth, secondary structure, pharmacophore and torsional angles. DockNet is comparable to current state-of-the-art methods, achieving an area under the curve (AUC) value of up to 0.84 on an independent test set (DB5), can be applied to a variety of different protein structures and can be utilized in situations where accurate unbound protein structures cannot be obtained.

Availability and implementation
DockNet is available at https://github.com/npwilliams09/docknet and an easy-to-use webserver at https://biosig.lab.uq.edu.au/docknet. All other data underlying this article are available in the article and in its online supplementary material.

Supplementary information
Supplementary data are available at Bioinformatics online.
Medial temporal tau predicts memory decline in cognitively unimpaired elderly
Authors: Kwan Angela T H , Arfaie Saman , Therriault Joseph , Azizi Zahra , Lussier Firoza Z , Tissot Cecile , Chamoun Mira , Bezgin Gleb , Servaes Stijn , Stevenon Jenna , Rahmouni Nesrine , Pallen Vanessa , Gauthier Serge , Rosa-Neto Pedro 
Published: December 2022

AbstractAlzheimer’s disease can be detected in living people using in vivo biomarkers of amyloid-β and tau, even in the absence of cognitive impairment during the preclinical phase. [18F]-MK-6420 is a high-affinity PET tracer that quantifies tau neurofibrillary tangles, but its ability to predict cognitive changes associated with early Alzheimer’s disease symptoms, such as memory decline, is unclear. Here, we assess the prognostic accuracy of baseline [18F]-MK-6420 tau-PET for predicting longitudinal memory decline in asymptomatic elderly individuals. In a longitudinal observational study, we evaluated a cohort of cognitively normal elderly participants (n = 111) from the translational biomarkers in ageing and dementia study (data collected between October 2017 and July 2020, with a follow-up period of 12 months). All participants underwent tau-PET with [18F]-MK-6420 and amyloid-β PET with [18F]-AZD-4694. The exclusion criteria included the presence of head trauma, stroke or other neurological disorders. There were 111 eligible participants selected based on the availability of amyloid-β PET, tau-PET, MRI and APOEɛ4 genotyping. Among these participants, the mean standard deviation age was 70.1 (8.6) years; 20 (18%) were tau-PET-positive and 71 of 111 (63.9%) were women. A significant association between the baseline Braak Stages I–II [18F]-MK-6240 standardized uptake value ratio positivity and change in composite memory score were observed at the 12-month follow-up, after correcting for age, sex and years of education [logical memory and Rey Auditory Verbal Learning Test, standardized beta = −0.52 (−0.82–0.21), P &lt; 0.001, for dichotomized tau-PET and −1.22 (−1.84−(−0.61)], P &lt; 0.0001, for continuous tau-PET]. Moderate cognitive decline was observed for A + T + over the follow-up period, whereas no significant change was observed for A−T+, A + T- and A-T-, although it should be noted that the A−T + group was small. Our results indicate that baseline tau neurofibrillary tangle pathology is associated with longitudinal changes in memory function, supporting the use of [18F]-MK-6420 PET to predict the likelihood of asymptomatic elderly individuals experiencing future memory decline. Overall, [18F]-MK-6420 PET is a promising tool for predicting memory decline in older adults without cognitive impairment at baseline. This is of critical relevance as the field is shifting towards a biological model of Alzheimer’s disease defined by the aggregation of pathologic tau. Therefore, early detection of tau pathology using [18F]-MK-6420 PET provides us with hope that living patients with Alzheimer’s disease may be diagnosed during the preclinical phase before it is too late.
Electoral Politics of Disaster: how earthquake and pandemic relief was used to earn votes
Authors: Imami Drini , Pojani Dorina , Merkaj Elvina 
Published: December 2022

AbstractDisasters can be good for incumbent governments. Amidst an emergency, budgets can be revised and reallocated in a hurry, framing the government as a ‘saviour,’ issuing contracts to the government’s business clientele and/or prioritising the electoral base more than the victims. Thus elected officials can curry favour with voters and increase their chances of retaining their seats. We examine this claim in the context of Albania, a middle-income country with weak public institutions. We show that the relief for two calamities, a destructive earthquake in 2019 and the Covid-19 pandemic, was used by the government to mobilise votes, thereby increasing the likelihood of electoral success in 2021. Both earthquake relief funding and Covid-19 vaccination rates spiked right before the elections only to drop soon afterwards. This phenomenon, known as the Electoral Politics of Disaster (EPD), poses a risk for the national economy, public health, spatial planning and democracy.
Emati: a recommender system for biomedical literature based on supervised learning
Authors: Kart Özge , Mestiashvili Alexandre , Lachmann Kurt , Kwasnicki Richard , Schroeder Michael 
Published: December 2022

Abstract
The scientific literature continues to grow at an ever-increasing rate. Considering that thousands of new articles are published every week, it is obvious how challenging it is to keep up with newly published literature on a regular basis. Using a recommender system that improves the user experience in the online environment can be a solution to this problem. In the present study, we aimed to develop a web-based article recommender service, called Emati. Since the data are text-based by nature and we wanted our system to be independent of the number of users, a content-based approach has been adopted in this study. A supervised machine learning model has been proposed to generate article recommendations. Two different supervised learning approaches, namely the naïve Bayes model with Term Frequency-Inverse Document Frequency (TF-IDF) vectorizer and the state-of-the-art language model bidirectional encoder representations from transformers (BERT), have been implemented. In the first one, a list of documents is converted into TF-IDF–weighted features and fed into a classifier to distinguish relevant articles from irrelevant ones. Multinomial naïve Bayes algorithm is used as a classifier since, along with the class label, it also gives the probability that the input belongs to this class. The second approach is based on fine-tuning the pretrained state-of-the-art language model BERT for the text classification task. Emati provides a weekly updated list of article recommendations and presents it to the user, sorted by probability scores. New article recommendations are also sent to users’ email addresses on a weekly basis. Additionally, Emati has a personalized search feature to search online services’ (such as PubMed and arXiv) content and have the results sorted by the user’s classifier.
Database URL: https://emati.biotec.tu-dresden.de
Identification of birch lncRNAs and mRNAs responding to salt stress and characterization of functions of lncRNA
Authors: Jia Yaqi , Zhao Huimin , Niu Yani , Wang Yucheng 
Published: December 2022

Abstract
Long noncoding RNAs (lncRNAs) are important in abiotic stress tolerance. Here, we identified salt-responsive genes and lncRNAs in the roots and leaves of Betula platyphylla Suk. (birch), and characterized their lncRNAs functions. In total, 2660 mRNAs and 539 lncRNAs responding to salt treatment were identified using RNA-seq. The salt-responsive genes were substantially enriched in ‘cell wall biogenesis’ and ‘wood development’ in the roots and were enriched in ‘photosynthesis’ and ‘response to stimulus’ in the leaves. Meanwhile, the potential target genes of the salt-responsive lncRNAs in roots and leaves were both enriched in ‘nitrogen compound metabolic process’ and ‘response to stimulus’. We further built a method for quickly identifying abiotic stress tolerance of lncRNAs, which employed transient transformation for overexpression and knock-down of the lncRNA, enabling gain- and loss-of-function analysis. Using this method, 11 randomly selected salt-responsive lncRNAs were characterized. Among them, six lncRNAs confer salt tolerance, two lncRNAs confer salt sensitivity, and the other three lncRNAs are not involved in salt tolerance. In addition, a lncRNA, LncY1, was further characterized, which improves salt tolerance by regulating two transcription factors, BpMYB96 and BpCDF3. Taken together, our results suggested that lncRNAs play important roles in the salt response of birch plants.
An Intrinsic Characterization of Moment Functionals in the Compact Case
Authors: Infusino Maria , Kuhlmann Salma , Kuna Tobias , Michalski Patrick 
Published: December 2022

Abstract
We consider the class of all linear functionals $L$ on a unital commutative real algebra $A$ that can be represented as an integral w.r.t. to a Radon measure with compact support in the character space of $A$. Exploiting a recent generalization of the classical Nussbaum theorem, we establish a new characterization of this class of moment functionals solely in terms of a growth condition intrinsic to the given linear functional. To the best of our knowledge, our result is the first to exactly identify the compact support of the representing Radon measure. We also describe the compact support in terms of the largest Archimedean quadratic module on which $L$ is nonnegative and in terms of the smallest submultiplicative seminorm w.r.t. which $L$ is continuous. Moreover, we derive a formula for computing the measure of each singleton in the compact support, which in turn gives a necessary and sufficient condition for the support to be a finite set. Finally, some aspects related to our growth condition for topological algebras are also investigated.