bluuebunny/crossref_metadata_2025 huggingface dataset:
Inactivation mechanisms of influenza A virus under pH conditions encountered in aerosol particles as revealed by whole-virus HDX-MS
Authors: David Shannon C. , Vadas Oscar , Glas Irina , Schaub Aline , Luo Beiping , D'angelo Giovanni , Montoya Jonathan Paz , Bluvshtein Nir , Hugentobler Walter , Klein Liviana K. , Motos Ghislain , Pohl Marie , Violaki Kalliopi , Nenes Athanasios , Krieger Ulrich K. , Stertz Silke , Peter Thomas , Kohn Tamar
Published: August 2023

Multiple respiratory viruses, including influenza A virus (IAV), can be transmitted via expiratory aerosol particles, and aerosol pH was recently identified as a major factor influencing airborne virus infectivity. Indoors, small exhaled aerosols undergo rapid acidification to pH ~4. IAV is known to be sensitive to mildly acidic conditions encountered within host endosomes; however, it is unknown whether the same mechanisms could mediate viral inactivation within the more acidic aerosol micro-environment. Here, we identified that transient exposure to pH 4 caused IAV inactivation by a two-stage process, with an initial sharp decline in infectious titers mainly attributed to premature attainment of the post-fusion conformation of viral protein haemagglutinin (HA). Protein changes were observed by hydrogen-deuterium exchange coupled to mass spectrometry (HDX-MS) as early as 10 s post-exposure to acidic conditions. Our HDX-MS data are in agreement with other more labor-intensive structural analysis techniques, such as X-ray crystallography, highlighting the ease and usefulness of whole-virus HDX-MS for multiplexed protein analyses, even within enveloped viruses such as IAV. Additionally, virion integrity was partially but irreversibly affected by acidic conditions, with a progressive unfolding of the internal matrix protein 1 (M1) that aligned with a more gradual decline in viral infectivity with time. In contrast, no acid-mediated changes to the genome or lipid envelope were detected. Improved understanding of respiratory virus fate within exhaled aerosols constitutes a global public health priority, and information gained here could aid the development of novel strategies to control the airborne persistence of seasonal and/or pandemic influenza in the future.

IMPORTANCE

It is well established that COVID-19, influenza, and many other respiratory diseases can be transmitted by the inhalation of aerosolized viruses. Many studies have shown that the survival time of these airborne viruses is limited, but it remains an open question as to what drives their infectivity loss. Here, we address this question for influenza A virus by investigating structural protein changes incurred by the virus under conditions relevant to respiratory aerosol particles. From prior work, we know that expelled aerosols can become highly acidic due to equilibration with indoor room air, and our results indicate that two viral proteins are affected by these acidic conditions at multiple sites, leading to virus inactivation. Our findings suggest that the development of air treatments to quicken the speed of aerosol acidification would be a major strategy to control infectious bioburdens in the air.
Early Ordovician seamounts preserved in the Canadian Cordillera: Implications for the rift history of western Laurentia
Authors: Cobbett Rose N. , Beranek Luke P. , Piercey Stephen J. , Crowley James L. , Colpron Maurice
Published: August 2023

The breakup of the supercontinent Rodinia and development of the western Laurentian rifted margin are in part recorded by Neoproterozoic to mid-Paleozoic igneous and sedimentary rock successions in the Canadian Cordillera. New bedrock mapping and volcanic facies analysis of Early Ordovician mafic rocks assigned to the Menzie Creek Formation in central Yukon allow reconstruction of the depositional environment during the volcanic eruptions, whole-rock geochemical data constrain the melting depth and crust-mantle source regions of the igneous rocks within the study area, and zircon U-Pb age studies provide determination of the precise timing of submarine eruptions. Menzie Creek Formation volcanic rocks are interlayered with continental slope strata and show lithofacies consistent with those of modern seamount systems. Representative seamount facies contain several kilometers of hyaloclastite breccia and pillow basalt with rare sedimentary rocks. Menzie Creek Formation seamounts form a linear array parallel to the Twopete fault, an ancient extensional or strike-slip fault that localized magmatism along the nascent western Laurentian margin. Zircon grains from two volcanic successions yielded high-precision chemical abrasion–thermal ionization mass spectrometry (CA-TIMS) dates of ca. 484 Ma (Tremadocian), which are interpreted as the age of eruption. Menzie Creek Formation rocks are alkali basalt and have oceanic-island basalt–like geochemical compositions. The whole-rock trace element and Nd-Hf isotope compositions are consistent with the partial melting of subcontinental lithospheric mantle at ~75–100 km depth. Post-rift, Early Ordovician seamounts in central Yukon record punctuated eruptive activity along a rift-related fault, the separation of a continental fragment from western Laurentia, or the oblique post-breakup kinematics from the counterclockwise rotation of Laurentia that facilitated local extension in the passive margin.
Impact of serial cardiopulmonary point-of-care ultrasound exams in patients with acute dyspnoea: a randomised, controlled trial
Authors: Arvig Michael Dan , Lassen Annmarie Touborg , Gæde Peter Haulund , Gärtner Stefan Wernblad , Falster Casper , Skov Inge Raadal , Petersen Henrik Ømark , Posth Stefan , Laursen Christian B
Published: August 2023

Background

Serial point-of-care ultrasound (PoCUS) can potentially improve acute patient care through treatment adjusted to the dynamic ultrasound findings. The objective was to investigate if treatment guided by monitoring patients with acute dyspnoea with serial cardiopulmonary PoCUS and usual care could reduce the severity of dyspnoea compared with usual care alone.

Methods

This was a randomised, controlled, blinded-outcome trial conducted in three EDs in Denmark between 9 October 2019 and 26 May 2021. Patients aged ≥18 years admitted with a primary complaint of dyspnoea were allocated 1:1 with block randomisation to usual care, which included a single cardiopulmonary PoCUS within 1 hour of arrival (control group) or usual care (including a PoCUS within 1 hour of arrival) plus two additional PoCUS performed at 2 hours interval from the initial PoCUS (serial ultrasound group). The primary outcome was a reduction of dyspnoea measured on a verbal dyspnoea scale (VDS) from 0 to 10 recorded at inclusion and after 2, 4 and 5 hours.

Results

There were 206 patients recruited, 102 in the serial ultrasound group and 104 in the control group, all of whom had complete follow-up. The mean difference in VDS between patients in the serial ultrasound and the control group was −1.09 (95% CI −1.51 to −0.66) and −1.66 (95% CI −2.09 to −1.23) after 4 and 5 hours, respectively. The effect was more pronounced in patients with a presumptive diagnosis of acute heart failure (AHF). A larger proportion of patients received diuretics in the serial ultrasound group.

Conclusion

Therapy guided by serial cardiopulmonary PoCUS may, together with usual care, facilitate greater improvement in the severity of dyspnoea, especially in patients with AHF compared with usual care with a single PoCUS in the ED. Serial PoCUS should therefore be considered for routine use to aid the physician in stabilising the patient faster.

Trial registration number

NCT04091334.
Photovoltaic thermoelectric cooling system for off-grid vaccine refrigerator: an experimental study
Authors: Khan Nazia Rodoshi , Sharmin Tasnuva , Haque Md. Azazul , Rahman Md. Hamidur
Published: August 2023

The rapidly rising demand for refrigeration technologies, mainly in refrigeration and air conditioning, medical applications, and electronic component cooling, produced much more energy than required. Thermoelectric refrigeration is an innovative way to use additional energy to cool and reserve cooling. In this research, a photovoltaic-thermoelectric refrigeration system capable of sustaining vaccine storage within the limit of 2–8 °C has been established by experimentally optimizing its volume and performance. The design specification is to cool the volume using forced convection to the desired temperature range in less than 30 min and sustain retained heat for at least the next hour. The experimental research is divided into two stages: the first determines the optimal volume of vaccine storage under different testing conditions using only grid power, and the second analyses storage performance using solar energy through photo voltaic (PV) integration. The solar direct drive and the solar drive with battery support have been timed, revealing a holding period of 4 h, 46 min and 5 h, 29 min, respectively. The refrigerator's design criteria, prospective characteristics, and final design are all thoroughly highlighted. Finally, we conclude that this research will likely benefit the modeling and analysis of thermoelectric cooling systems.
Quantum interaction between two entangled non point-like objects in the presence of boundaries
Authors: Wen Dan , Hu Yongshun
Published: August 2023

We explore, in the framework of linearized quantum gravity, the quantum gravitational quadrupole-quadrupole interaction between two entangled non point-like objects in the presence of both Dirichlet and Neumann boundaries. The results show that, compared to the case without boundaries, the interaction can be either enhanced or weakened depending on the geometrical arrangement of the objects with respect to the boundaries. In the limit when the two-object system is placed very close to the Dirichlet boundary, the near-regime interaction potential is larger than that of the pure vacuum case when the two objects are placed perpendicular to the boundary but smaller when parallel to it, while, in the far regime, such strong and weak relations between potentials are just opposite to that in the near regime. And, there exists a new $$r^{-2}$$

r

-
2

far-regime behavior of the interaction potential under the perpendicular configuration. For the case of Neumann boundary, the strong and weak relations between the interaction potentials under perpendicular or parallel configurations and the case without boundary are opposite to the Dirichlet circumstance both in the near and far regimes. Besides, the novel $$r^{-2}$$

r

-
2

far-regime behavior occurs for the parallel rather than perpendicular configuration in the presence of Neumann boundary.
Boson star with parity-odd symmetry in wormhole spacetime
Authors: Yue Yuan , Ding Peng-Bo , Wang Yong-Qiang
Published: August 2023

In this paper, we revisit the model of bosonic matter in the form of a free complex scalar field with a nontrivial wormhole spacetime topology supported by a free phantom field. We obtain a new type of boson star with wormhole solutions, in which the complex scalar field possess full parity-odd symmetry with respect to the two asymptotically flat spacetime regions. When the size of the throat is small, the behavior of boson stars with wormhole approaches that of boson stars. When the size of the throat is intermediate, the typical spiraling dependence of the mass and the particle number on the frequency of the boson stars is replaced by a loop structure. However, as the size becomes relatively large, the loop structure will also disappear. In particular, The complex scalar field could form two boson stars with opposite phase differences with respect to the two spacetime regions in the limit of vanishing throat size. We analyze the properties of this new type of boson stars with wormhole and further show that the wormhole spacetime geometry.
Black hole thermodynamics in the Brans–Dicke–Maxwell theory
Authors: Dehghani M.
Published: August 2023

It has been shown that the exact solutions of four-dimensional (4D) Brans–Dicke–Maxwell (BDM) theory is nothing other than Reissner–Nordström (RN) black hole (BH)s coupled to a trivial constant scalar field (Cai and Myung in Phys Rev D 56:3466, 1997). Here, we show that it is the case only when the scalar potential is taken constant or equal to zero. Then, through obtaining the exact solutions, in the presence of a scalar potential, we show that this theory admits two classes of novel BH solutions which have been affected by a nontrivial scalar hair. Due to conformal invariance of Maxwell’s electrodynamics, multi-horizon BHs can occur which implies the anti-evaporation quantum effect. Inclusion of the scalar hair makes the asymptotic behavior of the solutions non-flat and non-AdS. Our novel solutions recover the RN-AdS BHs when the scalar field is turned off. Thermodynamic quantities of the 4D BDM BHs have been calculated by use of the appropriate methods and under the influence of scalar field. Then, by use of a Smarr-type mass formula, it has been found that the first law of BH thermodynamics is valid for our novel BHs. Thermal stability of the BDM BHs has been analyzed by use of the canonical ensemble and geometrical methods, comparatively.
A propagator approach to the dynamics of three-level laser with input coherent light
Authors: Ayehu Desalegn , Ebrahim Hussien
Published: August 2023

The squeezing and statistical features of the intracavity field produced by a three-level laser coupled to a vacuum reservoir with input coherent field are studied in this paper. Employing the propagator method, we determine the Q-function for the cavity field produced by a driven three-level laser. Using this Q-function, we have calculated the mean intensity, the quadrature variance, and the squeezing spectrum of the cavity field. It has been discovered that, despite the fact that the input coherent field improves the mean intensity of the cavity field, it has no effect on the quadrature squeezing of the cavity field. The degree of squeezing increases with the rate at which atoms are injected into a cavity and a substantial degree of squeezing is found close to the maximum initial injected atomic coherence.
Traveling waves solutions of Hirota–Ramani equation by modified extended direct algebraic method and new extended direct algebraic method
Authors: Ashraf Farrah , Ashraf Romana , Akgül Ali
Published: August 2023

In this paper, new exact traveling wave solutions are obtained by Hirota–Ramani equation. The many exact complex solutions of several types of nonlinear partial differential equations (NPDEs) are presented using the modified extended direct algebraic approach and new extended direct algebraic method, which is among the most effective mathematical techniques for finding a precise solution to NPDEs and put into a framework of algebraic computation. By selecting different bright and solitary soliton forms and by creating various analytical optical soliton solutions for the investigated equation, we hope to demonstrate how the analyzed model’s parameter impacts soliton behavior. It is possible to obtain new, complex solutions for nonlinear equations like the [Formula: see text]-dimensional Hirota–Ramani equation.
FPA-Net: Frequency-Guided Position-Based Attention Network for Land Cover Image Segmentation
Authors: Rubel Al Shahriar , Shih Frank Y.
Published: August 2023

Land cover segmentation has been a significant research area because of its multiple applications including the infrastructure development, forestry, agriculture, urban planning, and climate change research. In this paper, we propose a novel segmentation method, called Frequency-guided Position-based Attention Network (FPA-Net), for land cover image segmentation. Our method is based on encoder–decoder improved U-Net architecture with position-based attention mechanism and frequency-guided component. The position-based attention block is used to capture the spatial dependency among different feature maps and obtain the relationship among relevant patterns across the image. The frequency-guided component provides additional support with high-frequency features. Our model is simple and efficient in terms of time and space complexities. Experimental results on the Deep Globe, GID-15, and Land Cover AI datasets show that the proposed FPA-Net can achieve the best performance in both quantitative and qualitative measures as compared against other existing approaches.
Enhancing Multi-Behavior Recommendations Through Capturing Dynamic Preferences
Authors: Yan Cairong , Guan Xiaopeng , Han Haixia , Zhang Zhaohui , Zhang Yanting
Published: August 2023

Multi-behavior recommendation has gained significant attention in recent years for its ability to outperform single-behavior models. Current research related to multi-behavior models leaves room for improvement in the following two areas. First, the noise carried by individual behaviors and the additional noise generated during behavior processing is often overlooked, and these can ultimately degrade recommendation performance. Second, the specific time period of behavioral interactions and the frequency of interactions within that time period are also not taken into account. To address the above limitations, we propose a multi-behavior recommendation model integrating dynamic preferences (MB-DP) that captures dynamic interests while smoothing and denoising multi-behavior information. MB-DP extracts low and high-order semantics from various behaviors and unifies the measurements to generate interaction predictions. Additionally, it analyzes the interaction time and frequency of each behavior using gated recurrent units to capture the dynamic preferences of users and improve the prediction values. Extensive experimental results on two real-world datasets show that MB-DP significantly improves recommendation performance compared to the state-of-the-art baselines.
Component-Based Test Case Generation and Prioritization Using an Improved Genetic Algorithm
Authors: Priya T. , Prasanna M.
Published: August 2023

Developing test cases is the most challenging and crucial step in the software testing process. The initial test data must be optimized using a strong optimization technique due to many testing scenarios and poor testing effectiveness. Test prioritization is essential for testing the developed software products in a production line with a restricted budget in terms of time and money. A good understanding of the trade-off between costs (e.g. time and resources needed) and efficiency (e.g. component coverage) is necessary to prioritize test case scenarios for one or more software products. So, this paper proposes an efficient Multi-objective Test Case Generation and Prioritization using an Improved Genetic Algorithm (MTCGP-IGA) in Component-based Software Development (CSD). A random search-based method for creating and prioritizing multi-objective tests has been employed utilizing numerous cost and efficacy criteria. Specifically, the multi-objective optimization comprises maximizing the Prioritized Range of test cases (PR), Pairwise Coverage of Characteristics (PCC), Fault-Finding Capability (FFC), and minimizing Total Implementation Cost (TIC). For this test prioritizing problem, a unique fitness function is constructed with cost-effectiveness metrics. IGA is a robust search technique that exhibits excellent benefits and significant efficacy in resolving challenging issues, including ample space, multiple-peak, stochastic, and universal optimization. Relying on the use of IGA, this paper classifies, computes the objective function, introduces the Nondominated Sorting Genetic Algorithm-II (NSGA-II) method, evaluates each branch’s proximity on the handling route, and arranges the path set to get the best answer. The outcomes demonstrate that the proposed MTCGP-IGA with NSGA-II performed the best than other baseline algorithms in terms of prioritizing the test cases (mean value of 195.2), PCC (mean score of 0.7828), and FFC (mean score of 0.8136).
Does COVID-19 Epidemic Change the Risk Spillover Characteristics of Chinese Carbon Markets with Energy, Non-Energy Commodity and Stock Markets? Evidence from a Novel Network Method
Authors: Zhu Pengfei , Lu Tuantuan
Published: August 2023

This paper investigates the multi-dimensional risk spillover effects of carbon markets with energy, non-energy commodity and stock markets in China before and after the COVID-19 outbreak, through the DY network with GARCHSK-VaR method. The empirical results denote that the total bidirectional risk spillovers of carbon markets become larger after the COVID-19 outbreak than before the COVID-19 outbreak. Interestingly, in both periods, energy is the largest risk contributor to carbon markets, while carbon markets become the net risk contributors to stock markets under COVID-19. Furthermore, compared with Guangdong pilot, the impacts of Hubei pilot on other markets are stronger in both periods. Finally, the dynamic risk spillover effects have obvious differences between before and after the COVID-19 outbreak.
A HYBRID MEMBERSHIP LATENT DISTANCE MODEL FOR UNSIGNED AND SIGNED INTEGER WEIGHTED NETWORKS
Authors: NAKIS NIKOLAOS , ÇELIKKANAT ABDULKADIR , MØRUP MORTEN
Published: August 2023

Graph representation learning (GRL) has become a prominent tool for furthering the understanding of complex networks providing tools for network embedding, link prediction, and node classification. In this paper, we propose the Hybrid Membership-Latent Distance Model (HM-LDM) by exploring how a Latent Distance Model (LDM) can be constrained to a latent simplex. By controlling the edge lengths of the corners of the simplex, the volume of the latent space can be systematically controlled. Thereby communities are revealed as the space becomes more constrained, with hard memberships being recovered as the simplex volume goes to zero. We further explore a recent likelihood formulation for signed networks utilizing the Skellam distribution to account for signed weighted networks and extend the HM-LDM to the signed Hybrid Membership-Latent Distance Model (sHM-LDM). Importantly, the induced likelihood function explicitly attracts nodes with positive links and deters nodes having negative interactions. We demonstrate the utility of HM-LDM and sHM-LDM on several real networks. We find that the procedures successfully identify prominent distinct structures, as well as how nodes relate to the extracted aspects providing favorable performances in terms of link prediction when compared to prominent baselines. Furthermore, the learned soft memberships enable easily interpretable network visualizations highlighting distinct patterns.
Strong chromatic indices of certain binary operations on graphs
Authors: Thiru Vikram Srinivasan , Balaji S.
Published: August 2023

The strong edge-coloring of a graph G is a proper edge coloring such that all edges adjacent to any given edge receive different colors. Such an assignment of colors defines color classes all of which are induced matchings. The minimum number of color classes required for such an assignment of colors is defined as the strong chromatic index of a graph G. In this article, we discuss the strong chromatic index of graphs obtained by the amalgamation of two graphs, the rooted product of two graphs and the corona product of two graphs.
Superconducting Quantum Circuits Based on 2D Materials
Authors: Lo Cheng-Han , Chen Yung-Hsiang , Lasrado Avishma J. , Kuo Thomas , Chang You-Yi , Hsu Tao-Yi , Chen Yen-Chih , Guo Guo-Ping , Chiu Kuei-Lin
Published: August 2023

Transmon-type superconducting qubits have become a popular platform for quantum computing due to their robust qubit coherence properties. In recent years, different types of materials have been searched to replace the Al2O3 tunnel barrier in conventional Al-based Josephson junctions, in order to explore new functions of qubits utilizing the distinct nature of the chosen materials. In this report, we introduce our works involving using Weyl semimetals and graphene as a component in Josephson junctions for qubit designs and coupling to coplanar waveguide (CPW) resonators. We fabricate a MoTe2 transmon and investigate whether it exhibits topological properties by tuning the resonator frequency with magnetic flux. Next, we introduce a graphene gatemon, in which the gate-tunability of resonator frequency has been demonstrated and the two-tone spectroscopy has shown a qubit state transition.
Technical Effectiveness Considerations on the Replacement of Missiles with Interceptor UAVs
Authors: Piancastelli Luca , Leon-Cardenas Christian , Sali Merve
Published: August 2023

The large availability of low-cost, mass-produced drones has shaken the economic and production capabilities of most intermediate-range missile (IRM) systems. IRMs are capable of taking out mortars, rockets, unmanned aerial vehicles (UAVs) and missiles from 4 to 100[Formula: see text]km with a unitary cost of the “killer” unit of five figures. The preliminary design of these UAVs may benefit from existing jet models. This study evaluates the cost-effectiveness of these unmanned aerial vehicle interceptors (UAVIs) that can replace the IRMs with reusable small UAVs with booster rockets. This approach reduces the interception costs importantly.
MAN: Memory-augmented Attentive Networks for Deep Learning-based Knowledge Tracing
Authors: He Liangliang , Li Xiao , Wang Pancheng , Tang Jintao , Wang Ting
Published: August 2023

Knowledge Tracing (KT) is the task of modeling a learner’s knowledge state to predict future performance in e-learning systems based on past performance. Deep learning-based methods, such as recurrent neural networks, memory-augmented neural networks, and attention-based neural networks, have recently been used in KT. Such methods have demonstrated excellent performance in capturing the latent dependencies of a learner’s knowledge state on recent exercises. However, these methods have limitations when it comes to dealing with the so-called Skill Switching Phenomenon (SSP), i.e., when learners respond to exercises in an e-learning system, the latent skills in the exercises typically switch irregularly. SSP will deteriorate the performance of deep learning-based approaches for simulating the learner’s knowledge state during skill switching, particularly when the association between the switching skills and the previously learned skills is weak. To address this problem, we propose the Memory-augmented Attentive Network (MAN), which combines the advantages of memory-augmented neural networks and attention-based neural networks. Specifically, in MAN, memory-augmented neural networks are used to model learners’ longer term memory knowledge, while attention-based neural networks are used to model learners’ recent term knowledge. In addition, we design a context-aware attention mechanism that automatically weighs the tradeoff between these two types of knowledge. With extensive experiments on several e-learning datasets, we show that MAN effectively improve predictive accuracies of existing state-of-the-art DLKT methods.
Is Someone There or Is That the TV? Detecting Social Presence Using Sound
Authors: Georgiou Nicholas C. , Ramnauth Rebecca , Adeniran Emmanuel , Lee Michael , Selin Lila , Scassellati Brian
Published: August 2023

Social robots in the home will need to solve audio identification problems to better interact with their users. This article focuses on the classification between (a)
natural
conversation that includes at least one co-located user and (b)
media
that is playing from electronic sources and does not require a social response, such as television shows. This classification can help social robots detect a user’s social presence using sound. Social robots that are able to solve this problem can apply this information to assist them in making decisions, such as determining when and how to appropriately engage human users. We compiled a dataset from a variety of acoustic environments that contained either
natural
or
media
audio, including audio that we recorded in our own homes. Using this dataset, we performed an experimental evaluation on a range of traditional machine learning classifiers and assessed the classifiers’ abilities to generalize to new recordings, acoustic conditions, and environments. We conclude that a C-Support Vector Classification (SVC) algorithm outperformed other classifiers. Finally, we present a classification pipeline that in-home robots can utilize, and we discuss the timing and size of the trained classifiers as well as privacy and ethics considerations.
Tracking Socio-Economic Development in Rural India over Two Decades Using Satellite Imagery
Authors: Gulgulia Anant , Gupta Aman , Sarashetti Akshay P , Sinha Aaditya , Seth Aaditeshwar
Published: August 2023

Longitudinal analysis of socio-economic development at sub-national scales can reveal valuable insights about which areas tend to develop faster than others and why. However, such analysis is difficult to conduct with traditional data sources such as censuses and surveys which are not repeated frequently and may require assumptions for imputation of values at non-surveyed locations. Indicators of socio-economic development based on satellite data have emerged as a proxy to track development at fine spatial and temporal scales. We build a model using daytime and nightlights satellite data to estimate an index of socio-economic development at the village level in India. We evaluate our model for temporal robustness and use it to produce estimates at three time points over a two-decade period. We then use these estimates to understand the effect on village-level development of factors such as the geographic distance of a village to hubs of economic activity and the inequality of development in the district. Our findings provide evidence of the possible impact that policy changes during this period have had on village development.
Real-Time Fixed Priority Scheduling Synthesis using Affine DataFlow Graphs: from Theory to Practice
Authors: Honorat Alexandre , Tran Hai Nam , Gautier Thierry , Besnard Loïc , Bhattacharyya Shuvra S. , Talpin Jean-Pierre
Published: August 2023

The major drawback of using static schedules to execute dataflow applications is their high inflexibility. In real-time systems, periodic schedules make it easier to assert safety guarantees and to decrease the schedule size, but their characteristics remain hard to compute. This article presents an approach to automatically generate fixed priority schedules from a dataflow specification. To do so, precedence dependencies between actors in the dataflow graphs are abstracted, as well as the task periods, by usingaffine relations. This abstraction allows us to synthesize schedules efficiently considering two main objectives: the maximization of throughput and the minimization of buffer sizes. Given a dataflow graph to execute in a real-time environment, we transform it into an Affine DataFlow Graph (ADFG) and compute the task priorities, their mapping, the number of delays in the buffers, and the buffer sizes. This article is the first to present an overview of both theoretical and practical aspects of ADFG. On the theoretical side, it presents corrections and improvements on the fixed priority case. On the practical side, benchmark evaluations demonstrate the robustness and maturity of the approach that our scheduling synthesizer implements. Synthesized schedules are evaluated by using scheduling simulation and real-time implementation. Last but not least, the synthesized periods reach the optimal throughput if enough processors are available, and most of the time the periods reach the maximal processor utilization factor in the uni-processor case. Moreover, execution time of the synthesis is about only one second for the main proposed algorithms.
Clinical Phenotyping with an Outcomes-driven Mixture of Experts for Patient Matching and Risk Estimation
Authors: Hurley Nathan C. , Dhruva Sanket S. , Desai Nihar R. , Ross Joseph R. , Ngufor Che G. , Masoudi Frederick , Krumholz Harlan M. , Mortazavi Bobak J.
Published: August 2023

Observational medical data present unique opportunities for analysis of medical outcomes and treatment decision making. However, because these datasets do not contain the strict pairing of randomized control trials, matching techniques are to draw comparisons among patients. A key limitation to such techniques is verification that the variables used to model treatment decision making are also relevant in identifying the risk of major adverse events. This article explores a deep mixture of experts approach to jointly learn how to match patients and model the risk of major adverse events in patients. Although trained with information regarding treatment and outcomes, after training, the proposed model is decomposable into a network that clusters patients into phenotypes from information available before treatment. This model is validated on a dataset of patients with acute myocardial infarction complicated by cardiogenic shock. The mixture of experts approach can predict the outcome of mortality with an area under the receiver operating characteristic curve of 0.85 ± 0.01 while jointly discovering five potential phenotypes of interest. The technique and interpretation allow for identifying clinically relevant phenotypes that may be used both for outcomes modeling as well as potentially evaluating individualized treatment effects.
Byzantine Machine Learning: A Primer
Authors: Guerraoui Rachid , Gupta Nirupam , Pinot Rafael
Published: August 2023

The problem of Byzantine resilience in distributed machine learning, a.k.a.
Byzantine machine learning
, consists of designing distributed algorithms that can train an accurate model despite the presence of Byzantine nodes—that is, nodes with corrupt data or machines that can misbehave arbitrarily. By now, many solutions to this important problem have been proposed, most of which build upon the classical stochastic gradient descent scheme. Yet, the literature lacks a unified structure of this emerging field. Consequently, the general understanding on the principles of Byzantine machine learning remains poor. This article addresses this issue by presenting a primer on Byzantine machine learning. In particular, we introduce three pillars of Byzantine machine learning, namely the concepts of
breakdown point
,
robustness
, and
gradient complexity
, to curate the efficacy of a solution. The introduced systematization enables us to (i) bring forth the merits and limitations of the state-of-the-art solutions, and (ii) pave a clear path for future advancements in this field.
Key Physical Processes in the Circumgalactic Medium
Authors: Faucher-Giguère Claude-André , Oh S. Peng
Published: August 2023

Spurred by rich, multiwavelength observations and enabled by new simulations, ranging from cosmological to subparsec scales, the past decade has seen major theoretical progress in our understanding of the circumgalactic medium (CGM). We review key physical processes in the CGM. Our conclusions include the following:
▪The properties of the CGM depend on a competition between gravity-driven infall and gas cooling. When cooling is slow relative to free fall, the gas is hot (roughly virial temperature), whereas the gas is cold (T ∼ 104 K) when cooling is rapid.▪Gas inflows and outflows play crucial roles, as does the cosmological environment. Large-scale structure collimates cold streams and provides angular momentum. Satellite galaxies contribute to the CGM through winds and gas stripping.▪In multiphase gas, the hot and cold phases continuously exchange mass, energy, and momentum. The interaction between turbulent mixing and radiative cooling is critical. A broad spectrum of cold gas structures, going down to subparsec scales, arises from fragmentation, coagulation, and condensation onto gas clouds.▪Magnetic fields, thermal conduction, and cosmic rays can substantially modify how the cold and hot phases interact, although microphysical uncertainties are presently large.
Key open questions for future work include the mutual interplay between small-scale structure and large-scale dynamics, and how the CGM affects the evolution of galaxies.
Fe/Ni-Doped Co5.47N Nanoparticles Integrated on Nitrogen-Doped Vertical Reduced Graphene Oxide Arrays for Overall Water Splitting in Wide pH Range
Authors: Kong Yun , Guo Kaiming , Liu Rong , Yan Banrui , Shaik Firdoz , Jiang Bin
Published: August 2023

It is necessary to rationally develop iron group metal nitrides with noble-metal-like electronic structures as catalysts for water splitting. Here we report a novel electrocatalyst consisting of Fe/Ni-doped Co5.47N Nanoparticles integrated with N-doped vertically reduced graphene oxide arrays (N-VrGO) (Fe, Ni-Co5.47N@N-rGO) for overall water splitting. The suitable amount of metal addition, the vertical structure of N-VrGO, and the synergistic effect of N in N-VrGO and N in Fe, Ni-Co5.47N result in the enhanced electrocatalytic performance of Fe, Ni-Co5.47N@N-VrGO-2 catalyst in a wide pH range. It has lower overpotentials for hydrogen evolution reactions (94 mV, 121 mV) and oxygen evolution reactions (234 mV, 318 mV) in 1 M KOH and 0.5 M H2SO4 electrolytes, respectively. The Fe, Ni-Co5.47N@N-VrGO-2 catalyst exhibits a good Faraday efficiency (about 90%) and outstanding stability (over 12 h). The synergistic effect of N in N-VrGO and N in Fe, Ni-Co5.47N promotes the electron rearrangement on the metal surface and further enhances the electrocatalytic performance of the catalyst. This work helps to better understand the synergistic interaction between iron group metal compounds and heteroatom-doped VrGO, and helps to more rationally select the substrates for iron group metal compounds.
Older females but not males exhibit increases in cerebral blood velocity, despite similar pulsatility increases after high-intensity resistance exercise
Authors: Marôco João L. , Rosenberg Alexander J. , Grigoriadis Georgios , Lefferts Elizabeth C. , Fernhall Bo , Baynard Tracy
Published: August 2023

Sex differences in resting cerebral hemodynamics decline with advancing age as females experience larger reductions in cerebral blood velocity and steeper pulsatility increases than males. However, an exercise-mediated hypertensive stimulus might reveal sex differences in cerebral hemodynamics not apparent at rest. Following high-intensity resistance exercise, older females but not males exhibit increases in cerebral blood velocity, despite similar increases in cerebral pulsatility. The susceptibility to cerebrovascular abnormalities following exercise-mediated hypertensive stimulus appears similar between sexes.
Few‐Shot Relation Extraction via the Entity Feature Enhancement and Attention‐Based Prototypical Network
Authors: Li Ren , Xiao Qiao , Yang Jianxi , Ren Hao , Chen Yu
Published: August 2023

In order to overcome the problems that the feature representation and classification effect of the existing methods need to be improved in complex contexts, this paper presents a novel few‐shot relation extraction approach via the entity feature enhancement and attention‐based prototypical network. The proposed model uses the pretrained RoBERTa model as the encoder while using the BiLSTM module for directional feature extraction. We further incorporate the entity feature enhancement module to improve the feature representation ability of the model. At last, the attention‐based prototypical network is used to predict relations. The experimental results show that the proposed method not only outperforms the baseline models on the datasets from the bridge inspection and health domains but also achieves competitive results on the FewRel dataset in the general domain.
Comparative Analysis of Swirl Burner and Cross Jet Burner in Terms of Efficiency and Environmental Performance
Authors: Zhumagulov Mikhail G. , Dolgov Maxim V. , Baubek Askar A. , Gribkov Alexander M.
Published: August 2023

The article contains a comparative analysis of two types of burners used in different methods of fuel-air mixture preparation: (1) vortex mixing and (2) mixing with transverse jets. The analysis was carried out in order to determine which one of the two burning devices is more efficient and has better environmental performance. In device no. 1, conditions for the fuel-air mixture formation are created by vortex turbulence. The basic principle lying at the core of this design is a vortex flow inside, which provokes a more intense mixing of fuel and air. Moreover, preliminary physical and thermal treatment of the fuel-air mixture has a positive effect on its environmental performance. In contrast, in device no. 2 based on transverse jets’ active mixture formation is achieved through collision of air and fuel flows at an angle close to 90°. The research was based on an experiment carried out with the use of a laboratory firing stand. Flue gas samples were analyzed in order to compare the main harmful air emission indicators with TESTO 350-XL gas analyzer. A propane-butane mixture of 60% C3H8 (propane) and 40% C4H10 (butane) was used as the main fuel. Some indicators were determined after the experiment: measurement units conversion from “ppm” to “mg/m3,” excess air ratio α and equivalence ratio φ, flue gas concentrations recalculation taking oxygen into account, fuel calorific value, and heat release rate. The analysis results are as follows: (i) the swirl burner shows better performance in terms of nitrogen oxides (NOx) emissions; there is a 1.75-fold difference in total NOx emissions compared to the cross jet burner; (ii) the burner on transverse jets is 10 times more efficient than the swirl burner in terms of carbon monoxide (CO) emissions.
First Whole Genome Sequencing of Crimean–Congo Hemorrhagic Fever Virus (CCHFV) in Tick Species within Ghana
Authors: Bentil Ronald Essah , Addo Seth Offei , Mosore Mba-tihssommah , Kumordjie Selassie , Yeboah Clara , Agbodzi Bright , Behene Eric , Tagoe Janice , Baako Bernice Olivia Ama , Asoala Victor , Ampadu Richard Osei , Mingle Daniel Lartei , Nyarko Edward O. , Fox Anne T. , Letizia Andrew G. , Diclaro Joseph William , Sanders Terrel , Oduro Daniel , Nimo-Paintsil Shirley C. , Harwood James , Dadzie Samuel Kweku
Published: August 2023

Crimean–Congo hemorrhagic fever (CCHF) is a serious viral zoonotic disease spread by ticks and caused by the Crimean–Congo hemorrhagic fever virus (CCHFV). The emergence and reemergence of CCHF in various nations in the Eastern Mediterranean Region over the last decade have shown a growing risk of the disease spreading to new areas, especially in population-dense and livestock trade-dominant areas. There is a lack of updated information on the risk of CCHFV in the Greater Accra and Upper East Regions of Ghana. Due to the paucity of available data, this study sought to identify the tick species diversity in Ghana and to ascertain the CCHFV strains they may carry. A total of 705 ticks were collected from 188 cattle and 11 horses and morphologically identified. Three tick genera (Hyalomma, Amblyomma, and Rhipicephalus) were observed, with the predominant species being Hyalomma rufipes (n = 290, 41.1%). The CCHFV infection rates of 0.78%, 0.69%, and 0.64% were recorded in Hyalomma truncatum, H. rufipes, and Amblyomma variegatum, respectively. No infection was detected in the Rhipicephalus species. Furthermore, a strain was successfully recovered using next-generation sequencing. The strain belongs to genotype 3 and shared 98.9% nucleotide identity with DQ211641_Mauritania_1984 and MF287636_Spain_2016. Findings from this study suggest the possible importation of the virus into the country through trade, and potentially, a public health threat to humans who may have primary contact with livestock.
Stabilization of Double Inverted Pendulum Systems Based on Hierarchical Sliding Mode Control Techniques
Authors: Idrees Muhammad , Ullah Zia , Younis Jihad , Ahmad Sohail , Ahmad Hafeez
Published: August 2023

The double rotary inverted pendulum (DRIP) system belongs to the class of under‐actuated mechanical systems, and it is a highly nonlinear, unstable, and benchmark system to test the different control techniques. This paper successfully designed the nonlinear hierarchical sliding mode control (HSMC) techniques to stabilize the DRIP system. We compare the performance of these techniques numerically with each other and with the previously designed control technique. We propose an aggregated HSMC technique as it has a much shorter stabilization time than other designed techniques.
Removal of Wall-Adherent Inferior Vena Cava Thrombus with a Combined Approach Using Vacuum-Assisted Thrombectomy and a Rotational Thrombectomy Device
Authors: Kaemmel Julius , Heck Roland , Lanmüller Pia , Falk Volkmar , Starck Christoph
Published: August 2023

Introduction. Large thrombi in the inferior vena cava pose a high risk for a pulmonary embolism. Percutaneous extracorporeal circulation-based vacuum-assisted thrombus aspiration is a viable option for removal. Wall adherence of thrombotic material can compromise procedural success. Case Report. A 46-year-old female presented with a subtotal thrombotic occlusion of the inferior vena cava and the proximal right common iliac vein after weaning from extracorporeal life support. Due to severe wall adherence of the thrombotic material, the patient was treated with the combination of percutaneous extracorporeal circulation-based thrombus aspiration using the AngioVac system and a rotational thrombectomy device.
Investigating Infectious Organisms of Public Health Concern Associated with Wild Meat
Authors: Moloney Georgia Kate , Gaubert Philippe , Gryseels Sophie , Verheyen Erik , Chaber Anne-Lise
Published: August 2023

The wild meat trade poses a significant threat to public health as it facilitates the spillover of zoonotic pathogens through high-risk activities such as the hunting, butchering, trade, and consumption of wild animals. Despite the health risks and association with marking epidemics including SARS, Ebola, and COVID-19, the global wild meat trade continues to thrive. To summarize the evidence available, primary literature published between 2000 and 2022 was systematically and critically assessed for evidence of zoonotic pathogens or other infectious organisms detected in samples directly from wild meat, from animals hunted for wild meat, or from humans exposed through high-risk activities. Within the 97 articles analyzed, a total of 114 pathogen genera (15 viruses, 40 bacteria, 54 parasites, and 5 fungi) were detected in wild meat animals belonging to 168 vertebrate species including mammals, reptiles and birds sampled in 32 countries. In the context of wild meat specifically, infectious organisms were differentiated between those with zoonotic potential (32% of reported genera), ectoparasitic vectors (1%), and possible opportunistic or environmental contaminants. Thirteen viral, four bacterial, and one parasitic genera were also documented in humans participating in wild meat trade activities, supporting pathogen spillover potential. Most studies employed a targeted approach to evaluate the presence of (i.e., polymerase chain reaction (PCR); n = 65) or exposure to (i.e., ELISA; n = 19) a specific pathogen, while only one study employed broad-spectrum metabarcoding techniques. The diversity of infectious organisms associated with wild meat are highlighted through this review and could be used to guide policy development. However, the common use of a selected set of targeted detection assays likely biases the exploration of pathogen diversity, therefore potentially preventing the discovery of “disease x”. The global health risk demonstrated should make the illegal wild meat trade a priority for law-enforcement agencies and future research.