Transmission Probability Research Articles

Self-consistent modeling of metastable helium exoplanet transits

Absorption of stellar X-ray and extreme ultraviolet (EUV) radiation in the upper atmosphere of close-in exoplanets can give rise to hydrodynamic outflows, which may lead to the gradual shedding of their primordial light element envelopes. Excess absorption by neutral helium atoms in the metastable 2 3S state [He I(2 3S)], at ~10 830 Å, has recently emerged as a viable diagnostic of atmospheric escape. Here we present a public add-on module to the 1D photoionization hydrodynamic code ATES, designed to calculate the He I(2 3S) transmission probability for a broad range of planetary parameters. By relaxing the isothermal outflow assumption, the code enables a self-consistent assessment of the He I(2 3S) absorption depth along with the atmospheric mass-loss rate and the outflow temperature profile, which strongly affects the recombination rate of He II into He I(2 3S). We investigate how the transit signal can be expected to depend upon known system parameters, including host spectral type, orbital distance, and planet gravity. At variance with previous studies, which identified K-type stars as favorable hosts, we conclude that late M dwarfs with Neptune-sized planets orbiting at ~0.05–0.1 AU can be expected to yield the strongest transit signal, well in excess of 30% for near-cosmological He-to-H abundances. More generally, we show that the physics that regulates the population and depletion of the metastable state, combined with geometrical effects, can yield somewhat counterintuitive results, such as a nonmonotonic dependence of the transit depth on orbital distance. These are compounded by a strong degeneracy between the stellar EUV flux intensity and the atmospheric He-to-H abundance, both of which are highly uncertain. Compared with spectroscopy data, now available for over 40 systems, our modeling suggests either that a large fraction of the targets have helium-depleted envelopes or that the input stellar EUV spectra are systematically overestimated. The updated code and transmission probability module are available publicly as an online repository.

Direct numerical simulation of supersonic nanoparticles flow in free-molecule regime using the angular coefficient method

We employ molecular flow methods to numerically simulate the supersonic nanoparticles flow in free-molecule regime. To streamline the computational complexity, interaction forces between the gas and solid particles are disregarded. We first develop a discrete phase model (DPM) method that integrates the non-rigid body collision model, enabling an accurate simulation of nanoparticle diffusion under the influence of the drag force and Brownian motion force. The nanoparticles considered in this study have sizes below 10 nm, and the accuracy of the DPM method is verified by comparing its results with experimental data. Subsequently, we theoretically and numerically investigate the transmission probability and number density of N2 molecules flowing through two-dimensional (2D) channels and three-dimensional (3D) tubes by using the angular coefficient (AC) method and the direct simulation Monte Carlo (DSMC) method. The findings indicate that as the diameter of the nanoparticle (dp) decreases to 1 nm, the diffusion coefficient (D) and the root mean square displacement (x) of nanoparticles approach the N2 molecules. The microscopic velocity of most N2 molecules falls within the range of 62–1400 m/s, and the macroscopic velocity of N2 flow falls within the range of Ma = 1.28–1.35. In contrast to the DSMC method, the AC method exhibits enhanced accuracy even with a reduced number of grids and obviates the process for large-scale sampling. Additionally, the solution time required by the AC method is approximately 1/10 and 1/13–1/32 of the DSMC method in 3D cylindrical tubes and 2D channels, respectively. Moreover, the AC method demonstrates superior adaptability when dealing with complex geometries.

Estimation of introduction and transmission rates of SARS-CoV-2 in a prospective household study.

Household studies provide an efficient means to study transmission of infectious diseases, enabling estimation of susceptibility and infectivity by person-type. A main inclusion criterion in such studies is usually the presence of an infected person. This precludes estimation of the hazards of pathogen introduction into the household. Here we estimate age- and time-dependent household introduction hazards together with within household transmission rates using data from a prospective household-based study in the Netherlands. A total of 307 households containing 1,209 persons were included from August 2020 until March 2021. Follow-up of households took place between August 2020 and August 2021 with maximal follow-up per household mostly limited to 161 days. Almost 1 out of 5 households (59/307) had evidence of an introduction of SARS-CoV-2. We estimate introduction hazards and within-household transmission rates in our study population with penalized splines and stochastic epidemic models, respectively. The estimated hazard of introduction of SARS-CoV-2 in the households was lower for children (0-12 years) than for adults (relative hazard: 0.62; 95%CrI: 0.34-1.0). Estimated introduction hazards peaked in mid October 2020, mid December 2020, and mid April 2021, preceding peaks in hospital admissions by 1-2 weeks. Best fitting transmission models included increased infectivity of children relative to adults and adolescents, such that the estimated child-to-child transmission probability (0.62; 95%CrI: 0.40-0.81) was considerably higher than the adult-to-adult transmission probability (0.12; 95%CrI: 0.057-0.19). Scenario analyses indicate that vaccination of adults can strongly reduce household infection attack rates and that adding adolescent vaccination offers limited added benefit.

Scanning the Horizon for Environmental Applications of Genetically Modified Viruses Reveals Challenges for Their Environmental Risk Assessment.

The release of novel genetically modified (GM) virus applications into the environment for agricultural, veterinary, and nature-conservation purposes poses a number of significant challenges for risk assessors and regulatory authorities. Continuous efforts to scan the horizon for emerging applications are needed to gain an overview of new GM virus applications. In addition, appropriate approaches for risk assessment and management have to be developed. These approaches need to address pertinent challenges, in particular with regard to the environmental release of GM virus applications with a high probability for transmission and spreading, including transboundary movements and a high potential to result in adverse environmental effects. However, the current preparedness at the EU and international level to assess such GM virus application is limited. This study addresses some of the challenges associated with the current situation, firstly, by conducting a horizon scan to identify emerging GM virus applications with relevance for the environment. Secondly, outstanding issues regarding the environmental risk assessment (ERA) of GM virus applications are identified based on an evaluation of case study examples. Specifically, the limited scientific information available for the ERA of some applications and the lack of detailed and appropriate guidance for ERA are discussed. Furthermore, considerations are provided for future work that is needed to establish adequate risk assessment and management approaches.

Electronic band gaps and transport properties in superlattice based on semi-Dirac material

We investigate the energy band structure and transport properties of electrons in superlattice structure based on semi-Dirac material with one-dimensional periodic potentials of square barriers. The influence of different parameters on transmission probability in superlattice structure is studied. It is found that two new Dirac points are formed in the superlattice structure by adjusting the gap parameter. The position of the new Dirac points can be regulated by changing the size of the potential barrier, the ratio of well width to barrier width, and the gap parameter. Some forbidden bands appear in the transmission probability, the location and width of the forbidden bands can be regulated by changing the system parameters.

Reliability Evaluation of a Wireless Sensor Network in Terms of Network Delay and Transmission Probability for IoT Applications

Reliability is a crucial performance metric for wireless sensor networks (WSNs) because it ensures network functionality even with degraded sensor nodes and wireless connections. Due to the limited availability of power resources associated with the sensor nodes, their efficacy is reduced. In addition, parameters such as the number of neighbours, packet success rate, packet size, and node capacity have a significant impact on how sensor nodes function. Similarly, inter-node distance and signal-to-noise ratio (SNR) have the greatest influence on the functioning of wireless communications in WSNs. Before evaluating the reliability of a WSN, therefore, the node and link reliability must be computed. This paper evaluates the reliability of sensor nodes by taking into account all of the parameters previously mentioned. In addition, the lifetime of each sensor node is estimated in terms of the fractional energy consumed for each wake-up operation and the transmission of packets, respectively. Using the inter-node distance and SNR values, each wireless link’s reliability is determined. Following this, a proposed algorithm evaluates the reliability of WSN by first enumerating all minimal paths between the sensor node and the base station and then converting these minimal paths into their sum-of-disjoint-product terms. Making use of a suitable example network, every step of the proposed method is illustrated. For evaluating the reliability of WSN, the proposed method is simulated in different environments. In addition, the influence of parameters such as inter-node distance, SNR, number of neighbours, packet success ratio, and time on the reliability values of WSN is portrayed and analysed.

Road networks and socio-demographic factors to explore COVID-19 infection during its different waves

The COVID-19 pandemic triggered an unprecedented level of restrictive measures globally. Most countries resorted to lockdowns at some point to buy the much-needed time for flattening the curve and scaling up vaccination and treatment capacity. Although lockdowns, social distancing and business closures generally slowed the case growth, there is a growing concern about these restrictions' social, economic and psychological impact, especially on the disadvantaged and poorer segments of society. While we are all in this together, these segments often take the heavier toll of the pandemic and face harsher restrictions or get blamed for community transmission. This study proposes a road-network-based networked approach to model mobility patterns between localities during lockdown stages. It utilises a panel regression method to analyse the effects of mobility in transmitting COVID-19 in an Australian context, together with a close look at a suburban population’s characteristics like their age, income and education. Firstly, we attempt to model how the local road networks between the neighbouring suburbs (i.e., neighbourhood measure) and current infection count affect the case growth and how they differ between delta and omicron variants. We use a geographic information system, population and infection data to measure road connections, mobility and transmission probability across the suburbs. We then looked at three socio-demographic variables: age, education and income and explored how they moderate independent and dependent variables (infection rates and neighbourhood measures). The result shows strong model performance to predict infection rate based on neighbourhood road connection. However, apart from age in the delta variant context, the other variables (income and education level) do not seem to moderate the relationship between infection rate and neighbourhood measure. The results indicate that suburbs with a more socio-economically disadvantaged population do not necessarily contribute to more community transmission. The study findings could be potentially helpful for stakeholders in tailoring any health decision for future pandemics.

Impact of spatial and temporal resource distribution on rabies dynamics in the Arctic

In the Arctic, rabies is endemic in the Arctic fox (Vulpes lagopus), posing a significant and ongoing health risk for people and domestic animals. The mechanisms by which rabies is maintained within the low-density fox populations in the Arctic remain unclear. In this study, we developed a spatially explicit individual-based stochastic epidemiological model and performed an uncertainty analysis to better understand Arctic fox rabies dynamics. Rabies persisted in 25.68% of model simulations, with several variables having significant impact on rabies persistence: probability of rabies transmission, spatial and temporal distribution food resources, mean litter size and variability of rabies incubation periods. Where rabies is endemic, we identified 5 key parameters for rabies dynamics: spatiotemporal resource distribution, probability of birth for adult females, mean and standard deviation of litter size, and incubation period of rabies. Our study demonstrates that Arctic rabies can persist in its primary host under conditions consistent with existing empirical data in the literature and showed the important role played by the spatial and temporal distribution of resources. Finally, our results suggest that the ecological impacts of rapid climate warming could decrease the overall persistence of rabies in the Arctic and the associated health risk in Arctic communities.

HA N193D substitution in the HPAI H5N1 virus alters receptor binding affinity and enhances virulence in mammalian hosts

ABSTRACT During the 2021/2022 winter season, we isolated highly pathogenic avian influenza (HPAI) H5N1 viruses harbouring an amino acid substitution from Asparagine(N) to Aspartic acid (D) at residue 193 of the hemagglutinin (HA) receptor binding domain (RBD) from migratory birds in South Korea. Herein, we investigated the characteristics of the N193D HA-RBD substitution in the A/CommonTeal/Korea/W811/2021[CT/W811] virus by using recombinant viruses engineered via reverse genetics (RG). A receptor affinity assay revealed that the N193D HA-RBD substitution in CT/W811 increases α2,6 sialic acid receptor binding affinity. The rCT/W811-HA193N virus caused rapid lethality with high virus titres in chickens compared with the rCT/W811-HA193D virus, while the rCT/W811-HA193D virus exhibited enhanced virulence in mammalian hosts with multiple tissue tropism. Surprisingly, a ferret-to-ferret transmission assay revealed that rCT/W811-HA193D virus replicates well in the respiratory tract, at a rate about 10 times higher than that of rCT/W811-HA193N, and all rCT/W811-HA193D direct contact ferrets were seroconverted at 10 days post-contact. Further, competition transmission assay of the two viruses revealed that rCT/W811-HA193D has enhanced growth kinetics compared with the rCT/W811-HA193N, eventually becoming the dominant strain in nasal turbinates. Further, rCT/W811-HA193D exhibits high infectivity in primary human bronchial epithelial (HBE) cells, suggesting the potential for human infection. Taken together, the HA-193D containing HPAI H5N1 virus from migratory birds showed enhanced virulence in mammalian hosts, but not in avian hosts, with multi-organ replication and ferret-to-ferret transmission. Thus, this suggests that HA-193D change increases the probability of HPAI H5N1 infection and transmission in humans.

Ballistic transport and spin-dependent anomalous quantum tunneling in Rashba–Zeeman and bilayer graphene hybrid structures

In this work, we have studied the spin-dependent ballistic transport and anomalous quantum tunneling in bilayer graphene horizontally placed in between two Rashba–Zeeman (RZ) leads under external electric biasing. We investigated the transmission and conductance for the proposed system using scattering matrix formalism and the Landauer–Büttiker formula considering a double delta-like barrier under a set of experimentally viable parameters. We found that the transmission characteristics are notably different for up- and down-spin incoming electrons depending upon the strength of magnetization. Moreover, the transmission of up- and down-spin electrons is found to be magnetization orientation dependent. The maximum tunneling conductance can be achieved by tuning biasing energy and magnetization strength and choosing a material with suitable Rashba spin–orbit coupling (RSOC). This astonishing property of our system can be utilized in fabricating devices, such as spin filters. We found that the Fano factor of our system is 0.4 under strong magnetization conditions, while it reduces to 0.3 under low magnetization conditions. Moreover, we also noticed that the transmission and conductance significantly depend on the Rashba–Zeeman effect. Therefore, considering a suitable RZ material, the tunneling of the electrons can be tuned and controlled. Our result suggests that considering suitable strength and orientation of magnetization with moderate RSOC, one can obtain a different transmission probability for spin species under suitable biasing energy. These results indicate the suitability of the proposed system in fabrication of spintronic devices, such as spin filter, spin transistor, etc.

Chiral tunneling through double barrier structure in twisted graphene bilayer

The paper discusses the chiral tunneling of charge carriers through double barrier structure in twisted graphene bilayer. The theoretical analysis investigates the transmission probability for various system parameters under both symmetric and asymmetric barrier conditions. The results reveal that the transmission probability of quasiparticles in the K cone is mirror symmetric to that of Kθ cone about φ=0. Furthermore, the study shows that the transmission changes gradually from perfect transmission to perfect reflection in the normal direction by increasing the incident energy and the barrier height, which is different from the case of monolayer and AB-stacked bilayer graphene. It is also found that the double barrier structure remains, only in certain cases, perfectly transparent for normal or near-normal incidence. The chiral nature of the quasiparticles in graphene causes the tunneling to be highly dependent on the direction and also on the double barrier structure. Interestingly, this characteristic provides additional parameter that allows us to tune the electronic properties of the twisted graphene bilayer. Additionally, we found that the transmission exhibits some sharp resonance peaks, the number and amplitude of which depend on the system parameters. Our results provide a better understanding of chiral tunneling in twisted graphene bilayers through double barrier structures, which may thus offer efficient tools to control the transport properties in future graphene-based nanodevices like transistors and photodetectors.

New-type 2D iodine materials with tunable electronic transport impacted by the doping of nonmetal elements

Special structures and good characteristics make 2D iodine structures more appealing and valuable at high pressures. The electrical transport of such 2D iodine structures is theoretically studied here, taking the doping of nonmetal elements into account. Most doped devices show considerably greater equilibrium conductance than the original device. Devices with the dopants in lower atomic numbers show higher conductance. The transmission spectrum all around EF can be improved by the doping of nonmetal elements. Essentially, DDOS can well explain the variations in electron transmission probability caused by the doping of nonmetal atom for most doped devices, serving as one main inherent factor in electron transport. The influence of nonmetal dopants on transmission eigenstates varies according to the main group, essentially depending on the number of transferring channels and the strength of transmission eigenstates. Influenced by the bias, the conductance of such innovative devices fluctuates but with varied amplitudes. Every doping mode can enhance the conductance by applying the bias and such biases for all doping modes must cover lower biases. Unlike the dopants in larger atomic numbers, the devices with the dopants in smaller atomic numbers show much difference in size between the voltage interval that enhances and the voltage interval that weakens. The current grows linearly with bias. Nonmetal doping enables the current to increase at low voltages and decrease at high voltages, compared with the undoped device. The improved and attenuated effect on the current is good for doped devices with nonmetal elements in smaller atomic numbers, but poor in higher atomic numbers. These discoveries contribute significantly to our understanding of the effects of defects and elemental adsorption on electrical characteristics and give strong evidence for the use of new-type 2D iodine materials in controlled electronics and sensors.

Ultra-thin van der Waals magnetic tunnel junction based on monoatomic boron vacancy of hexagonal boron nitride.

We present a novel strategy to create a van der Waals-based magnetic tunnel junction (MTJ) comprising a three-atom layer of graphene (Gr) sandwiched with hexagonal boron nitride (hBN) layers by introducing a monoatomic boron vacancy in each hBN layer. The magnetic properties and electronic structure of the system were investigated using density functional theory (DFT) and the transmission probability of the MTJ was investigated using the Landauer-Büttiker formalism within the non-equilibrium Green function method. The Stoner gap was created between the spin-majority channel and the spin-minority channel on the local density of states of the hBN monoatomic boron-vacancy (VB) near the Fermi energy, creating a possible control of the spin valve by considering two magnetic alignment of hBN(VB) layers, anti-parallel configuration (APC) and parallel configuration (PC). The transmission probability calculation results showed a high electron transmission in the PC of the hBN(VB) layers and a low transmission when the APC was considered. A high tunneling magnetoresistance (TMR) ratio of approximately 400% was observed when comparing the APC and PC of the hBN(VB) layers in hBN(VB)/Gr/hBN(VB), giving the highest TMR ratio for the thinnest MTJ system.

Assessment of tuberculosis transmission probability in three Thai prisons based on five dynamic models.

This study aimed to assess and compare the probability of tuberculosis (TB) transmission based on five dynamic models: the Wells-Riley equation, two Rudnick & Milton-proposed models based on air changes per hour (ACH) and liters per second per person (L/s/p), the model proposed by Issarow et al, and the Applied Susceptible-Exposed-Infected-Recovered (SEIR) TB transmission model. This study also aimed to determine the impact of model parameters on such probabilities in three Thai prisons. A cross-sectional study was conducted using data from 985 prison cells. The TB transmission probability for each cell was calculated using parameters relevant to the specific model formula, and the magnitude of the model agreement was examined by Spearman's rank correlation and Bland-Altman plot. Subsequently, a multiple linear regression analysis was conducted to investigate the influence of each model parameter on the estimated probability. Results revealed that the median (Quartiles 1 and 3) of TB transmission probability among these cells was 0.052 (0.017, 0.180). Compared with the pioneered Wells-Riley's model, the remaining models projected discrepant TB transmission probability from less to more commensurate to the degree of model modification from the pioneered model as follows: Rudnick & Milton (ACH), Issarow et al., and Rudnick & Milton (L/s/p), and the applied SEIR models. The ventilation rate and number of infectious TB patients in each cell or zone had the greatest impact on the estimated TB transmission probability in most models. Additionally, the number of inmates in each cell, the area per person in square meters, and the inmate turnover rate were identified as high-impact parameters in the applied SEIR model. All stakeholders must urgently address these influential parameters to reduce TB transmission in prisons. Moreover, further studies are required to determine their relative validity in accurately predicting TB incidence in prison settings.

Modeling transmission of avian influenza viruses at the human-animal-environment interface in Cuba.

The increasing geographical spread of highly pathogenic avian influenza viruses (HPAIVs) is of global concern due to the underlying zoonotic and pandemic potential of the virus and its economic impact. An integrated One Health model was developed to estimate the likelihood of Avian Influenza (AI) introduction and transmission in Cuba, which will help inform and strengthen risk-based surveillance activities. The spatial resolution used for the model was the smallest administrative district ("Consejo Popular"). The model was parameterised for transmission from wild birds to poultry and pigs (commercial and backyard) and then to humans. The model includes parameters such as risk factors for the introduction and transmission of AI into Cuba, animal and human population densities; contact intensity and a transmission parameter (β). Areas with a higher risk of AI transmission were identified for each species and type of production system. Some variability was observed in the distribution of areas estimated to have a higher probability of AI introduction and transmission. In particular, the south-western and eastern regions of Cuba were highlighted as areas with the highest risk of transmission. These results are potentially useful for refining existing criteria for the selection of farms for active surveillance, which could improve the ability to detect positive cases. The model results could contribute to the design of an integrated One Health risk-based surveillance system for AI in Cuba. In addition, the model identified geographical regions of particular importance where resources could be targeted to strengthen biosecurity and early warning surveillance.

An Optimization Framework for Active Physical-Layer Authentication

This paper concerns the problem of the parameter optimization of an active Physical-Layer Authentication (PLA) scheme, which is crucial for minimizing the distortion on the base signal carrying the original message caused by embedding a tag. An inappropriate parameter may significantly lower the efficiency of the entire period of message transmission. In this paper, we propose an optimization framework for an active PLA scheme and further propose a new systematic metric, defined as Secure Authentication Efficiency (SAE). In the proposed framework, we minimize the aforementioned distortion by tuning three parameters, i.e., the Probability of Message Transmission (PMT), the Probability of Message Outage (PMO), and the Probability of Secure Authentication (PSA). The proposed optimization framework deepens the understanding of the correlation between the parameters of an active PLA scheme and the conditions of a wireless channel, and allows us to systematically optimize the parameters of the active PLA scheme. Then, we establish an objective function by maximizing the SAE with both PMT and PMO constraints. We implement our approach and conduct extensive performance comparisons. Our experimental results show that when the SNR at the receiver is more than 15 dB, our approach achieves an average SAE of greater than 80%, whereas the prior scheme without parameter optimization degenerates to zero SAE under some conditions, e.g., high SNR at adversary or high communication rate.

In Silico Assessment for Risk of Possible Human Transmission of FCoV‐23

Since the pandemic in 2019, coronaviruses (CoVs) have been a great concern for public health burden. The fact that CoVs can infect all animals including domestic ones and livestock points to a future pandemic even though interaction between human and wildlife animals is restricted. Moreover, interspecies transmission abilities of CoVs by mutations make them drastically risky not only for humans but also for animal health. Recently, a new CoV outbreak in cats in Cyprus, the so‐called FCoV‐23, has been realized. In addition to worries over animal health, any possible transmission to humans is now controversial. However, there have been limited characterization studies on FCoV‐23. Thus, we aimed to assess the possible transmission of FCoV‐23 to humans using in silico prediction tools. Accordingly, we first checked the binding affinities of receptor binding domain (RBD) of FCoV‐23 against feline target protein and its human homolog. Next, we randomly and rationally created mutations on the RBD sequence and evaluated the binding affinities using protein docking tools. Our results underlined that multiple mutations at the same time were needed for increased binding affinity towards human target protein, demonstrating that the probability of transmission to humans was extremely low when mutation rates were regarded. Still, further molecular studies are required to comprehensively conclude the possible transmission risk.

Impact of Tobacco Consumption During COVID-19 Lockdown: Insights from Employees at a Government Medical College in Gujarat

Background: Tobacco consumption is consistently harmful to one's well-being, and for individuals with respiratory conditions, it can elevate the likelihood of contracting infections, raise the potential for complications, and enhance the probability of transmission. In this study awareness about the association and the impact of the lockdown on tobacco use among current tobacco users of Government Medical College, Gujarat was assessed. Objectives: To evaluate the level of insight regarding the connection between COVID-19 and tobacco use and to assess the influence of COVID-19 related lockdown measures on the rate of tobacco consumption among current tobacco users at Government Medical College, Gujarat. Methods: A study was conducted among Class 3 & Class 4 employees of Government Medical College using convenient sampling technique. Study population who was ready to participate in the study and had been actively engaged in the 10-month counselling program from January 2020 to November 2020. Data was gathered through a pre-tested closed-ended questionnaire. Statistical analysis was carried out using the SPSS software (version 22). Ethical approval was obtained from the Institute Ethical Committee, and written informed consent was acquired from all the participants. Results: A significant majority, comprising 68% of tobacco users, lacked awareness of the link between tobacco use and COVID-19. Among the 173 current tobacco users, 49 of them successfully abstained from tobacco use during the lockdown period. The primary reasons cited for this change were the unavailability and higher prices of tobacco products. Conclusions: The level of awareness regarding the connection between tobacco and COVID-19 played a crucial role in motivating tobacco users to discontinue their tobacco consumption.

Efficient spin filtering through Fe4GeTe2-based van der Waals heterostructures.

Utilizing ab initio simulations, we study the spin-dependent electronic transport characteristics within Fe4GeTe2-based van der Waals heterostructures. The electronic density of states for both free-standing and device-configured Fe4GeTe2 (F4GT) confirms its ferromagnetic metallic nature and reveals a weak interface interaction between F4GT and PtTe2 electrodes, enabling efficient spin filtering. The ballistic transport through a double-layer F4GT with a ferromagnetic configuration sandwiched between two PtTe2 electrodes is predicted to exhibit an impressive spin polarization of 97% with spin-up electrons exhibiting higher transmission probability than spin-down electrons. Moreover, we investigate the spin transport properties of Fe4GeTe2/GaTe/Fe4GeTe2 van der Waals heterostructures sandwiched between PtTe2 electrodes to explore their potential as magnetic tunnel junctions in spintronic devices. The inclusion of monolayer GaTe as a 2D semiconducting spacer between F4GT layers results in a tunnel magnetoresistance of 487% at a low bias and decreases with increasing bias voltage. Overall, our findings underscore the potential of F4GT/GaTe/F4GT heterostructures in advancing spintronic devices based on van der Waals materials.

Herd‐Level Modeling of Bovine Viral Diarrhea Virus (BVDV) Transmission in Cattle Herds in Southern Chile: Linking Within and Between‐Herd Dynamics

Bovine viral diarrhea (BVD) represents a serious threat to the cattle sector in Chile, indicating the need for a regionally defined control program. Ex-ante evaluations of program options using simulation modeling have proven to be a successful approach in providing decision‐makers with relevant supporting insights in that respect. Given the complexity of bovine viral diarrhea virus (BVDV) infection dynamics, simulation of BVD spread in a metapopulation requires detailed consideration of both within and between herd transmission dynamics. The aims of the study are (i) to investigate the dynamics of BVDV transmission in cattle herds in southern Chile by linking a within‐herd transmission model (WHM) that accounts for the BVDV’s unique characteristics with a between‐herd model (BHM) that meets the demands for further regional control strategy evaluation; (ii) to suggest and discuss criteria for evaluation of the model approach and plausibility for later research and for support decision‐making. This resulted in bringing forth a modeling rationale for complex disease spread simulation in metapopulations. BHM simulations under this approach show outcomes that agree with BVDV’s known situation in Chile; dairy herds prevalence at endemic equilibrium reaches and maintains 75%, which agrees with estimations of BVDV active infection in dairy herds in southern Chile (77%). For the entire herd population, the infection always reaches endemic levels with a large proportion of infected herds (median = 60%), where herd prevalence was higher in the dairy herd class than in the remaining categories. Transmission probability variation affects the new infections picked, prevalence at endemic levels, and the velocity in which the infection spreads between herds. The fact that the presented approach was able to model a complex infection dynamic such BVDV, with sufficient confidence, provides evidence that this approach can be used to explore mitigation strategies to control BVDV in southern Chilean herds.