bluuebunny/crossref_metadata_2025_split huggingface dataset:
Phenotype-Based Threat Assessment
Authors: Yang Jing , Eslami Mohammed , Chen Yi-Pei , Das Mayukh , Zhang Dongmei , Chen Shaorong , Roberts Alexandria-Jade , Weston Mark , Volkova Angelina , Faghihi Kasra , Moore Robbie K. , Alaniz Robert C. , Wattam Alice R. , Dickerman Allan , Cucinell Clark , Kendziorski Jarred , Coburn Sean , Paterson Holly , Obanor Osahon , Maples Jason , Servetas Stephanie , Dootz Jennifer , Qin Qing-Ming , Samuel James E. , Han Arum , van Schaik Erin J. , de Figueiredo Paul 
Published: April 2022

SignificanceAssessing the threat posed by bacterial samples is fundamentally important to safeguarding human health. Whole-genome sequence analysis of bacteria provides a route to achieving this goal. However, this approach is fundamentally constrained by the scope, the diversity, and our understanding of the bacterial genome sequences that are available for devising threat assessment schemes. For example, genome-based strategies offer limited utility for assessing the threat associated with pathogens that exploit novel virulence mechanisms or are recently emergent. To address these limitations, we developed PathEngine, a machine learning strategy that features the use of phenotypic hallmarks of pathogenesis to assess pathogenic threat. PathEngine successfully classified potential pathogenic threats with high accuracy and thereby establishes a phenotype-based, sequence-independent pipeline for threat assessment.
Structural conservation among variants of the SARS-CoV-2 spike postfusion bundle
Authors: Yang Kailu , Wang Chuchu , White K. Ian , Pfuetzner Richard A. , Esquivies Luis , Brunger Axel T. 
Published: April 2022

Significance
Emergence of viral pathogens necessitates new approaches to study viral fusion and entry into host cells. A key step in mediating fusion involves the formation of a six-helix bundle within the spike protein. Rapid structural characterization of this state has been difficult, hindering understanding of emerging variants. We developed a method to efficiently determine high-resolution bundle structures by molecular scaffolding and cryogenic electron microscopy. Using this method, we determined bundle structures of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. These structures reveal local effects of mutations on HR1HR2 interactions but global conservation of the bundle architecture among SARS-CoV-2 variants. We predict that inhibitors disrupting the postfusion bundle might be broadly efficacious against variants and even more distantly related lethal viruses.
Protective role of chaperone-mediated autophagy against atherosclerosis
Authors: Madrigal-Matute Julio , de Bruijn Jenny , van Kuijk Kim , Riascos-Bernal Dario F. , Diaz Antonio , Tasset Inmaculada , Martín-Segura Adrián , Gijbels Marion J. J. , Sander Bianca , Kaushik Susmita , Biessen Erik A. L. , Tiano Simoni , Bourdenx Mathieu , Krause Gregory J. , McCracken Ian , Baker Andrew H. , Jin Han , Sibinga Nicholas E. S. , Bravo-Cordero Jose Javier , Macian Fernando , Singh Rajat , Rensen Patrick C. N. , Berbée Jimmy F. P. , Pasterkamp Gerard , Sluimer Judith C. , Cuervo Ana Maria 
Published: April 2022

Significance
Cardiovascular diseases remain the leading cause of death worldwide, with atherosclerosis being the most common source of clinical events. Metabolic changes with aging associate with concurrent increased risk of both type 2 diabetes and cardiovascular disease, with the former further raising the risk of the latter. The activity of a selective type of autophagy, chaperone-mediated autophagy (CMA), decreases with age or upon dietary excesses. Here we study whether reduced CMA activity increases risk of atherosclerosis in mouse models. We have identified that CMA is up-regulated early in response to proatherogenic challenges and demonstrate that reduced systemic CMA aggravates vascular pathology in these conditions. We also provide proof-of-concept support that CMA up-regulation is an effective intervention to reduce atherosclerosis severity and progression.
Exploring the predictive validity of an interpreting aptitude test battery
Authors: Liu Yubo , Zhang Wei 
Published: April 2022

Abstract
This study explores the validity of a battery of interpreting aptitude tests comprising the SynCloze test, the
Negative Affectivity Scale and the Inventory of Learning Styles in predicting the interpreting performance of Chinese interpreting
trainees. The aptitude test battery was conducted at the beginning of the first semester for 68 post-graduate interpreting
students in four Chinese interpreter training programs. English-Chinese (E-C) and Chinese-English (C-E) consecutive interpreting
(CI) tests that measure the interpreting proficiency of the participants were conducted at the end of the semester. The results of
the correlation and regression analysis indicated that the SynCloze test enjoyed statistically significant predictive power for
both directions of CI and that its predictive power was stronger for C-E CI (β = 0.70) than for E-C CI
(β = 0.48); negative affectivity was found to be a statistically significant predictor for E-C CI
(β = −0.21) but not for C-E CI. Neither the meaning-directed nor the reproduction-directed learning style
could predict interpreting performance. The implications of the findings are discussed in relation to interpreter selection and
training.
Noise equivalent power of a NbTiN-Al-based kinetic inductance detector for terahertz sensing
Authors: Su R F , Shi L L , Zhou T , Yao B Z , Wu J B , Tu X C , Jia X Q , Kang L , Jin B B , Wang H B , Chen J , Wu P H 
Published: April 2022

Abstract
We have designed and fabricated a superconducting hybrid NbTiN-Al kinetic inductance detector (KID) over a broad band centered at 4.3 THz. The detector sensitivity is characterized by changing the bath temperature in a dark environment. Both amplitude and phase readouts are performed. The measured electrical noise equivalent power for phase readout is about 2.6 × 10−18 W · Hz−0.5 at 200 mK. This ultra-sensitive KID, which enables large arrays with frequency domain multiplexing, is promising for imaging instruments in space-based far-infrared observatories.
Dynamical analysis of diversity lump solutions to the (2+1)-dimensional dissipative Ablowitz–Kaup–Newell–Segure equation
Authors: Ma Hongcai , Gao Yidan , Deng Aiping 
Published: April 2022

Abstract
The lump solution is one of the exact solutions of the nonlinear evolution equation. In this paper, we study the lump solution and lump-type solutions of (2+1)-dimensional dissipative Ablowitz–Kaup–Newell–Segure (AKNS) equation by the Hirota bilinear method and test function method. With the help of Maple, we draw three-dimensional plots of the lump solution and lump-type solutions, and by observing the plots, we analyze the dynamic behavior of the (2+1)-dimensional dissipative AKNS equation. We find that the interaction solutions come in a variety of interesting forms.
Fusing atomic W states with Rydberg superatom
Authors: Zhang W Y , Liu Y L , Ji Y Q , Dong L , Xiu X M 
Published: April 2022

Abstract
Quantum entanglement is the basic resource of quantum information processing and quantum computation, especially multi-partite entanglement. The simple and efficient generation of multi-partite entanglement has always been one of the hot topics of scholars. In this paper, we propose a qubit-loss-free fusion scheme for generation of large-scale entangled W states with Rydberg superatom. By sending two superatoms belonging to a k-atom W states and a l-atom W states, respectively, into a cavity, we may obtain a (k + l)-atom W states via detecting the cavity state after interaction. The numerical simulation analysis shows that the fidelity is robust against both spontaneous emission of superatoms and decay of the cavity. In addition, the feasibility analysis indicates this scheme can also be realized in experiment.
QED coherence in matter, syntropy and the coherent domains as storing “devices”
Authors: Caligiuri Luigi Maxmilian 
Published: April 2022

Abstract
Several macroscopic systems, like in particular living organisms, are characterized by stability and high level of order at mesoscopic / macroscopic scale. These peculiar features cannot be explained by considering just short-range interactions among their elementary constituents (atoms / molecules) and the entropic dynamics governing it. The theory of QED coherence predicts that in condensed matter, when suitable boundary conditions about temperature and density are satisfied (as generally happens in living systems), a quantum phase transition spontaneously occurs, driving the system towards a macroscopic coherent quantum state in which phase tuned oscillations between matter and electromagnetic field take place and ensure long-range correlation and order. In 1944, the italian mathematician Luigi Fantappie formulated the “Principi di una teoria unitaria del mondo fisico e biologico”, according to which living systems are governed by “syntropic” spontaneous phenomena, that are dual with respect the “entropic” ones, characterized by a reduction of entropy with time and whose causes are put in the future with respect the occurring events, able to ensure the organization and stability of living systems. In this paper we show how the results of QED coherence in matter are able to reproduce several of the main features of “syntropic” dynamics so giving it a support based on Quantum Field Theory. Finally, the role of water as a gatherer of quantum information, predicted by the QED coherence theory, is discussed as a possible practical realization of syntropic dynamics.
Macroscopic nonlocal correlations by new data of the Baikal Experiment
Authors: Korotaev S , Budnev N , Serdyuk V , Kiktenko E , Orekhova D , Gorohov J 
Published: April 2022

Abstract
The long-term Baikal experiment on study of macroscopic nonlocal correlations between random dissipative heliogeophysical processes and probe ones in the detectors have revealed prominent features of macroscopic entanglement predicted by action-at-a-distance electrodynamics. These correlations have both the retarded and advanced components with large time shifts. The correlations occur at extremely low frequencies and require long series of observations, so the Baikal experiment is continuing to study their unusual properties. In 2019-2021 new data were obtained on correlation of the signals of spaced detectors with each other and with to the natural processes: solar and hydrodynamic activity in Lake Baikal, as well as with the earthquake. The possibility of forecasting of solar and hydrodynamic activity on nonlocal correlations is demonstrated. Recently we paid attention to relatively short periods and discovered unexpected in-phase diurnal variation in the signals of both deep-sea detectors. This diurnal variation is not related to any hydrological processes. Moreover, this variation turned out in-phase with that one recorded by the remote lab detector (at the longitude difference 67°), that is it occurs in universal time, and cannot be associated with the meteorological or geomagnetic diurnal variations. The source of this signal in nonlocal correlation detectors is unknown yet.
Quantum phase effects for electrically charged particles and redefinition of the momentum operator
Authors: Kholmetskii A.L. , Yarman T. , Missevitch O.V. 
Published: April 2022

Abstract
We analyze the physical meaning of quantum phases for moving electric/magnetic dipoles through a superposition of quantum phases for point-like charges of the dipole, and in this way we disclose two new quantum phases for moving charges, next to the well-known magnetic and electric Aharonov-Bohm phases. We find that a consistent description of the full set of quantum phase effects for charged particles requires to modify the standard definition of the momentum operator via the canonical momentum of a particle towards a more inclusive definition, where this operator is associated with the vector sum of mechanical and interactional electromagnetic (EM) momenta for a charged particle in the EM field. Some principal implications of this result are discussed.
High-accuracy Machine Learning Models to Estimate above Ground Biomass over Tropical Closed Evergreen Forest Areas from Satellite Data
Authors: Tappayuthpijarn Ktawut , Vindevogel Bernd S 
Published: April 2022

Abstract
Quantifying the amount of biomass stored in forested areas has been traditionally done with manual field measurements, which is costly, time consuming and doesn’t scale well over large areas. This paper investigates the possibility to estimate the amount of Above Ground Biomass (AGB) using machine learning models with publicly available satellite data, where a large-scale training dataset has been created from a detailed biomass mapping project in the Democratic Republic of Congo (DRC). Several model architectures including the current state-of-the-art tree-based models were tested along with deep neural network (DNN) ones. It was found that DNN models provide slight improvement in accuracy, whilst can potentially be used for further fine-tuning with smaller local dataset for usage elsewhere outside of the DRC.
A Comparative Study of Geometric and Exponential Laws in Modelling the Distribution of Daily Precipitation Durations
Authors: Hafyani Mounia El , Himdi Khalid El 
Published: April 2022

Abstract
Wet and dry duration modelling is critical in engineering hydrology. The goal of this study is to model and analyze the wet and dry duration distributions. For this intent, daily rainfall data for Kenitra station were used on the period from 1967 to 2017. To represent the distribution of wet and dry durations, First-order Markov chain, Second-order Markov chain, and truncated negative binomial distribution are applied to represent the distribution of wet and dry durations. To assess the data adherence to the proposed models, the Chi-square and Kolmogorov-Smirnov tests have been used. The Akaike information criterion is applied to determine the most effective model distribution. We go further to investigate the distribution of the number of wet and dry days over a k-day period. This law is implemented using an algorithm based on conditional laws. This work is completed by comparing the calculated moments of the three estimated models to the observed moments of the number of wet/dry days over k consecutive days. The study demonstrates the effectiveness of our method for modelling wet and dry daily precipitation durations.
GIS Mapping of Salt Farms and Salt Supply Chain Actors in the Visayas and Mindanao, Philippines
Authors: Bartolome G J C , Magpantay J P , Delos Reyes J A , Lat A T , Reodica T J I , Manalo C J B 
Published: April 2022

Abstract
The 2010 survey of the Nutrition Council of the Philippines (NCP) revealed dramatic changes in the level of participation of the salt supply chain actors and their production, processing, and marketing activities. Among the industry’s biggest challenges are: salt remains excluded from the list of priority commodities of the government; the changes in weather patterns due to climate change which adversely impact the production cycle; prominence of traditional methods of production; and low productivity of local farms. While remote sensing technologies including geographic information system (GIS) mapping have been widely adopted for the improvement of agricultural productivity in the Philippines, use of such in research that focuses on salt production and supply chain is still very limited. GIS maps are perceived as effective information library and decision support tool that can help the supply chain of the neglected salt industry. This study focused on the mapping of salt farms and their supply chain actors from selected salt production sites in the Visayas and Mindanao islands. Eleven provinces were included in the surveys of market intermediaries and end-consumers who were traced from salt producers. Their geographic coordinates were recorded and satellite and Google Earth images of the supply chain actors were digitized in ArcGIS 10.5 software to generate the maps, physical characteristics of which were examined for possible patterns. Results show that in Mindanao, the market areas (or the salt traders) are concentrated in Zamboanga del Sur particularly in Aurora and Zamboanga City, but the producers are in Alubijid and El Salvador City, Misamis Oriental. In the Visayas, traders are more scattered and are greater in number than in Mindanao.
Evaluating the Effects of Environmental Stress on Leaf Chlorophyll Content as an Index for Tree Health
Authors: Talebzadeh F , Valeo C 
Published: April 2022

Abstract
Chlorophyll content plays a vital role in photosynthetic and biomass production in all plants. Because chlorophyll shows a greater sensitivity to changes in external conditions than do other pigments in foliage, such as carotenoids for example, chlorophyll content in leaves may be a good surrogate for environmental stress, changes in temperature and humidity, as well as in pollutant levels both in the air and in the soil. This paper reviews the potential for chlorophyll content in the leaves of trees as a measure of tree health, resistance to stress and environmental conditions. Because chlorophyll content is shown to decrease dramatically with increases in pollution, non-destructive methods for evaluating the amount of chlorophyll in leaves and its changes over a time may be a sufficient indicator for environmental pollutant levels in the air, in the soil and in the water used by a tree.
Safety of direct oral anticoagulants (DOACs) vs. warfarin for people aged ≥ 75 years with atrial fibrillation: a cohort study
Authors: Mitchell A , Snowball J , Welsh T J , Watson M C , McGrogan A 
Published: April 2022

Abstract

Introduction
Warfarin significantly reduces the risk of stroke in people with atrial fibrillation (AF), but historically has been underused in older people due to complicated dosage regimens. DOACs offer an attractive alternative to warfarin and were shown to be non-inferior in randomised controlled trials, however older people were underrepresented in these trials and there have been few studies investigating outcomes specifically in this high risk group (1).

Aim
To compare the risk of major, non-major, gastrointestinal, and intracranial bleeding between warfarin and DOACs in people aged ≥ 75 years with AF.

Methods
A cohort of patients aged ≥ 75 years with a diagnosis of AF was extracted from the Clinical Practice Research Datalink (CPRD). Patients could enter the study on the date of their first prescription for warfarin or a DOAC between 1/1/2013 and 27/12/2017. Patients were censored on the date of the outcome, death, or leaving the general practice. Switching between anticoagulants and unexposed periods were measured using prescription mapping. Crude and adjusted hazard rates of the risk of bleeding were calculated using a Cox proportional hazards model with oral anticoagulant prescribing as a time varying covariate.

Results
The cohort included 10,149 patients in the warfarin group and 10,237 in the DOAC group. The groups had similar characteristics and the average age was 81 in the warfarin group and 82 in the DOAC group. The table summarises the results. Whilst major and non-major bleeding was similar between all DOACs and warfarin, rivaroxaban was associated with higher risk and apixaban lower risk when analysed separately. Risk of gastrointestinal bleeding was higher with all DOACs and rivaroxaban than warfarin but apixaban was not significantly different. Few intracranial events occurred (n=131).

Conclusion
The results indicate that DOACs as a group are not significantly different to warfarin, however when analysed separately, apixaban may be safer. While the study relies on prescription data and hence it is not known if patients were taking the medications, the large cohort studied is representative of older people who are prescribed these medications in UK primary care.

Reference
(1) Mitchell A, Watson MC, Welsh T, McGrogan A. Effectiveness and safety of direct oral anticoagulants versus vitamin K antagonists for people aged 75 years and over with atrial fibrillation: A systematic review and meta-analyses of observational studies. Journal of Clinical Medicine. 2019; 8 (554).
Machine Learning and the Platformization of the Military: A Study of Google's Machine Learning Platform TensorFlow
Authors: Hoijtink Marijn , Planqué-van Hardeveld Anneroos 
Published: April 2022

Abstract
Against the background of the growing use of machine learning (ML) based technologies by the military, our article calls for an analytical perspective on ML platforms to understand how ML proliferates across the military and to what effects. Adopting a material–technical perspective on platforms as developed within new media studies, and bringing this literature to critical security studies, we suggest that a focus on platforms and the technical work they do is needed to understand how digital technologies are emerging and shaping security practices. Through a detailed study of Google's open-source ML platform TensorFlow and a discussion of the US Department of Defense Algorithmic Warfare Cross-Functional Team, or Project Maven, we make two broader contributions. First, we identify a broader “platformization” of the military, with which we refer to the growing involvement and permeation of the (technomaterial) ML platform as the infrastructure that enables new practices of decentralized and experimental algorithm development across the military. Second, we draw out how this platformization is accompanied by new entanglements between the military and actors in the corporate domain, especially Big Tech, which play a key role in this context, as well as the open-source community that is organized around these platforms.
Distinguishing gravitational and emission physics in black hole imaging: spherical symmetry
Authors: Kocherlakota Prashant , Rezzolla Luciano 
Published: April 2022

ABSTRACT
Imaging a supermassive black hole and extracting physical information requires good knowledge of both the gravitational and the astrophysical conditions near the black hole. When the geometrical properties of the black hole are well understood, extracting information on the emission properties is possible. Similarly, when the emission properties are well understood, extracting information on the black hole geometry is possible. At present however, uncertainties are present both in the geometry and in the emission, and this inevitably leads to degeneracies in the interpretation of the observations. We explore here the impact of varying geometry and emission coefficient when modelling the imaging of a spherically accreting black hole. Adopting the Rezzolla–Zhidenko parametric metric to model arbitrary static black holes, we first demonstrate how shadow-size measurements leave degeneracies in the multidimensional space of metric-deviation parameters, even in the limit of infinite-precision measurements. Then, at finite precision, we show that these degenerate regions can be constrained when multiple pieces of information, such as the shadow-size and the peak image intensity contrast, are combined. Such degeneracies can potentially be eliminated with measurements at increased angular resolution and flux sensitivity. While our approach is restricted to spherical symmetry and hence idealized, we expect our results to hold also when more complex geometries and emission processes are considered.