Upcoming Wave Research Articles

Constructing graphene oxide-wrapped wolframite-type 3D cube-like CuWO4 composite as a promising redox-active electrode for battery-type supercapacitors

The electronics industry's increasing demand for swift energy storage solutions drives researchers to invest significant resources into enhancing electrode materials. Achieving optimal efficiency throughout the charging process requires meticulous attention to the designing of the morphological, structure and chemical compositions of the electrode materials. Understanding the synergies among elements and structural dynamics is pivotal for maximizing the electrodes' performance. To address these challenges, we propose a groundbreaking approach through a straightforward and cost-effective solid-state reaction method followed by an impregnation technique to design a graphene oxide-wrapped wolframite-type 3D cube-like CuWO4 (GW-CuWO4) composite matrix. This design substantially increases the electrode's surface area (5 times greater than pristine CuWO4 and 12 times greater than sphere-like Na2WO4) and enhances its mesoporous characteristics. We extensively analyzed the physicochemical properties of GW-CuWO4 and compared them with pristine CuWO4 and Na2WO4 using various analytical techniques. The electrochemical performance of all electrodes exhibited battery-type characteristics, with the supercapacitive performance thoroughly investigated and compared. The specific capacity of the GW-CuWO4 composite electrode demonstrated significant results, reaching 520.8 C g−1 at 1.0 A g−1, with outstanding rate capability retaining 93 % capacity even at a high rate of charging current of 10 A g−1. In contrast, the specific capacity and rate capability of pristine CuWO4 were 392.1 C g−1 and 87 %, respectively, and Na2WO4 showed 295.8 C g−1 and 64 %. Additionally, the GW-CuWO4 electrode displayed excellent cyclic performance, retaining 95 % capacity at 10 A g−1 compared to CuWO4 (84 %). The GW-CuWO4 electrode exhibits enhanced electrochemical performance due to the synergistic interactions between its constituent parts and its distinct 3D mesoporous composite network. High conductivity, rich redox reactions, easy electron transfer, short ion diffusion lengths, quick kinetics, and an abundance of active sites for electrochemical reactions are all made possible by this network. Presenting this cutting-edge electrode design builds a fresh framework for producing effective electrodes suited for the upcoming wave of high-performance energy storage devices.

The Challenge of Political Will, Global Democracy and Environmentalism

In 2024, around the world nearly 60 national elections will be held involving billions of people. Many commentators see this as a make-or-break moment in terms of re-establishing democracy and pushing back against rising authoritarian regimes that have been increasing in recent years. This essay explores why –despite worldwide scientific consensus that we are facing ecological collapse –there is little discussion about the climate crisis among the upcoming wave of national elections. This silence around the climate emergency raises several pressing questions: Why is there limited political will on behalf of national leaders when it comes to mitigating the climate crisis? What does this suggest about the state of democracy when political leaders can sidestep and ignore the escalating demands of their constituencies? Finally, what actions can be taken by ordinary people who are increasingly subject to repressive anti-protest laws that prevent them from speaking out against antidemocratic leaders and their political collusion with the fossil fuel sector?

Prevalence of SARS-CoV-2 variants in Prague wastewater determined by nanopore-based sequencing

The early detection of upcoming disease outbreaks is essential to avoid both health and economic damage. The last four years of COVID-19 pandemic have proven wastewater-based epidemiology is a reliable system for monitoring the spread of SARS-CoV-2, a causative agent of COVID-19, in an urban population. As this monitoring enables the identification of the prevalence of spreading variants of SARS-CoV-2, it could provide a critical tool in the fight against this viral disease. In this study, we evaluated the presence of variants and subvariants of SARS-CoV-2 in Prague wastewater using nanopore-based sequencing. During August 2021, the data clearly showed that the number of identified SARS-CoV-2 RNA copies increased in the wastewater earlier than in clinical samples indicating the upcoming wave of the Delta variant. New SARS-CoV-2 variants consistently prevailed in wastewater samples around a month after they already prevailed in clinical samples. We also analyzed wastewater samples from smaller sub-sewersheds of Prague and detected significant differences in SARS-CoV-2 lineage progression dynamics among individual localities studied, e.g., suggesting faster prevalence of new variants among the sites with highest population density and mobility.

Beyond the waves: Unraveling pandemic outcomes with genomic insights and immunity analysis – Evidence from 14 countries

ObjectiveAlthough the World Health Organization and many governments have recategorized COVID-19 as a generally mild to moderately severe disease, consecutive pandemic waves driven by immune escape variants have underscored the need for timely and accurate prediction of the next outbreak. Nevertheless, little attention has been paid to translating genomic data and infection- and vaccine-induced immunity into direct estimates. MethodsWe retrieved epidemiologic and genomic data shortly before pandemic waves across 14 developed countries from late 2021 to mid-2022 and examined associations between early-stage variant competition, infection- and vaccine-induced immunity, and the time intervals between wave peaks. We applied regression analysis and the generalized estimating equation method to construct an inferential model. ResultsEach per cent increase in the proportion of a new variant was associated with a 1.0% reduction in interpeak intervals on average. Curvilinear associations between vaccine-induced immunity and outcome variables were observed, suggesting that reaching a critical vaccine distribution rate may decrease the caseload of the upcoming wave. ConclusionsBy leveraging readily accessible pre-outbreak genomic and epidemiologic data, our results not only substantiate the predictive potential of early variant fractions but also propose that immunity acquired through infection alone may not sufficiently mitigate transmission. Conversely, a rapid and widespread vaccination initiative appears to be correlated with a decrease in disease incidence.

The Impact of Uncertainty on the Control of a Multi-Axis Wave Energy Converter

As global energy demands and climate concerns continue to grow, the need for renewable energy is becoming increasingly clear and wave energy conversion (WEC) systems are receiving growing interest. Over the years, many WEC systems have emerged but most of these systems are designed to extract energy from a single direction of motion. In reality, there are six degrees of freedom that a conversion device can potentially harness and a device that can operate on multiple axes, should be able to more effectively and consistently produce power. However, the design and control of the power take off (PTO) system for a multi-axis device is challenging due to the system complexity and nonlinearity. WEC systems often utilize optimal control techniques for PTO operation and leverage a prediction of the upcoming wave force to ensure power optimization. Prior work has clearly demonstrated that high power production can be achieved when an exact system model is used and the upcoming wave conditions are known, but uncertainty in the underlying model or the wave prediction can degrade performance. PTO control on a multi-axis WEC must leverage predictions of forces in multiple directions and if model predictive strategies are used, must leverage a simplified model of the WEC dynamics to be able to optimize in real time. The uncertainty in these predictions and the model could severely degrade the WEC’s power output. This work examines the control of a multi-axis WEC system, TALOS, and leverages machine learning to predict wave forces over the upcoming time horizon. TALOS is a point-absorber type WEC with multi-axis PTO system. The PTO uses a heavy ball that is attached to the hull with springs and hydraulic cylinders. When the hull is pushed by the external waves, the relative motion between the ball and hull moves the hydraulic cylinders causing them to pump a fluid through a circuit, thereby driving a hydraulic motor to produce electricity. This design has shown promising results in energy output but is more challenging to control since the PTO can move over six degrees of freedom. This paper seeks to quantify wave prediction uncertainty and its seasonal variation and to examine the impact of the uncertainty of the prediction on a model predictive controller’s ability to optimize the power output of TALOS.

Biosensors: An Upcoming Wave of Innovation.

A biosensor uses a biological molecule to measure a chemical reaction. Wearable biosensors that attach to the body externally, including tooth enamel biosensors, contact lens biosensors, sweat biosensors, and skin tattoo biosensors, are in development. Nanoparticle-based biosensors are being developed to allow for the early detection of cancerous biomarkers. Applications relevant to plastic surgery include the development of biosensors that can detect metastatic breast cancer cells, bioimpedance spectroscopy, and intraoperative point-of-care diagnostics.

Molecular mechanisms responsible for SARS-CoV-2 antibody waning and vaccine escape in Omicron sublineages BA.4 and BA.5

Mutations in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome continue to threaten the global landscape of the coronavirus disease 2019 (COVID-19) pandemic. The Omicron variant (B.1.1.529) rapidly displaced previous 'variants of concern' (VoC) in 2021 due to its high rate of transmissibility and multitude of mutations. This global influx of infections saturated healthcare systems, overwhelmed testing capacity and case reporting, and increased the COVID-19 death toll. Global health leaders are now being faced with the most transmissible COVID-19 variants yet, the Omicron sublineages BA.4 and BA.5, which contain additional spike protein (S) mutations from previous Omicron and VoC serotypes. With universally observed antibody waning, increasing vaccine-variant mismatch, and resuming international travel, the stage is set for unprecedented levels of breakthrough infections and superspreading events. In this paper, we raise awareness to these novel variants and provide context for the high likelihood of an upcoming wave of infection capable of inflicting significant disease burden on a global scale.

A State-of-the-Art Review of Radioactive Decontamination Technologies: Facing the Upcoming Wave of Decommissioning and Dismantling of Nuclear Facilities

The average share of nuclear energy in electricity production is expected to increase under the background of the global pursuit towards carbon neutrality. Conjugating with its rapid development, the wave of decommissioning and dismantling (D&D) of nuclear facilities is coming. The surface decontamination is a prerequisite to D&D, which will make it easier and reduce the volume of radioactive wastes. However, there are no comprehensive studies on the decontamination methods, which is not helpful for the sustainable development of nuclear energy and environment protection. Therefore, in this work, the current status and future trends of global energy and nuclear energy are first analyzed. Then, various decontamination approaches are comparatively studied, including cleaning mechanisms, application subjects, and intrinsic advantages and disadvantages. Finally, the criteria and factors for selecting a decontamination process, the challenges, and future studies are directed. Among the mechanical methods, laser-based cleaning is high-speed, having automation ability, and thus is promising, although it creates a dust and airborne contaminant hazard. In further studies, factors such as selecting a proper laser facility, optimizing operating parameters, and designing a high-efficiency dust collection system could be studied. Regarding the chemical method, chemical gels are good for decontaminating complex shapes and vertical and overhead surfaces. In addition, they can enhance other decon agents’ efficiency by improving contact time. However, the formulation of colloidal gels is complex and no gel type is useful for all contaminants. Therefore, novel and versatile gels need be developed to enlarge their application field. Combining various decontamination methods will often have better results and thus a reasonable and effective combination of these decontamination methods has become the main direction.

SARS-CoV-2 Seroprevalence Among Health Care Workers in Major Private and Public Hospitals With COVID-19 Patient's Referral in Tehran, Iran.

Estimating the prevalence of SARS-CoV-2 antibody seropositivity among health care workers (HCWs) is crucial. In this study, the seroprevalence of anti-SARS-CoV-2 antibodies among HCWs of five hospitals of Tehran, Iran with high COVID-19 patient's referrals from April to June, 2020, was assessed. In this cross-sectional study, HCWs from three public and two private hospitals, selected randomly as a pilot, were included. Participants were asked questions on their demographic characteristics, medical history, hospital role, and usage of personal protective equipment (PPE). Iran FDA-approved SARS-CoV-2 ELISA kits were used to detect IgG and IgM antibodies in blood samples. The seroprevalence was estimated on the basis of ELISA test results and adjusted for test performance. Among the 2,065 participants, 1,825 (88.4%) and 240 (11.6%) HCWs were recruited from public and private hospitals, respectively. A total of 340 HCWs were tested positive for SARS-CoV-2-specific IgG or IgM antibodies, and 17.9% of seropositive individuals were asymptomatic. The overall test performance-adjusted seroprevalence estimate among HCWs was 22.6 (95% CI: 20.2–25.1), and PPE usage was significantly higher among HCWs of public vs. private hospitals (66.5 vs. 20.0%). This study found that seroprevalence of SARS-CoV-2 among HCWs was higher in private hospitals (37.0%; 95% CI: 28.6–46.2) than public hospitals (20.7%; 95% CI: 18.2–23.3), and also highest among assistant nurses and nurses, and lowest among janitor or superintendent categories. The PPE usage was especially suboptimal among HCWs in private hospitals. Continued effort in access to adequate PPE and regular screening of hospital staff for detecting asymptomatic personnel, especially during the upcoming wave of infection, are warranted.

Mathematical Modeling of COVID-19 and Prediction of Upcoming Wave

We investigate the problem of mathematical modeling of new corona virus (COVID-19) spread in practical scenarios in various countries, specifically in India, the United States of America (USA), France, Brazil, and Turkey. We propose a mathematical model to characterize COVID-19 disease and predict the new/upcoming wave of COVID-19. This prediction is very much required to prepare medical set-ups and proceed with future plans of action. A mixture Gaussian model is proposed to characterize the COVID-19 disease. Specifically, the data corresponding to new active cases of COVID-19 per day is considered, and then we try to fit the data to a mathematical function. It is observed that the Gaussian mixture model is suitable to characterize the new active cases of COVID-19. Further, it is assumed that there are N waves of COVID-19 and the information of each upcoming wave is present in the current and previous waves as well. By using this concept, prediction of the upcoming wave can be performed. A close match between analytical results and the available results shows the correctness of the considered model.

Beware of the echo: the evolution of Egypt’s population and labor force from 2000 to 2050

ABSTRACT I argue in this paper that although recent developments had temporarily reduced demographic pressures on the Egyptian labor market, such pressures will return with a vengeance in the next decade. The sizable echo generation born between 2005 and 2015 is the reflection of the large youth bulge generation born in the early 1980s; a reflection that was further compounded by rising fertility rates in the late 2000s and early 2010s. As the echo generation reaches working age, the net annual increase to the labor force will rise from 575 thousand per year in 2020–25 to 800 thousand per year in 2030–35, which will pose a major job creation challenge. This upcoming wave of new entrants will also be substantially more educated, with 50–60 percent having secondary or post-secondary education, and another third having university education or higher. To accommodate this upcoming growth in labor supply and absorb the stock of existing unemployed and discouraged workers, I estimate that employment growth would have to reach 2.7 percent per year, something that would require sustained GDP growth rates in excess of 6 percent per year. The quality of jobs created by the Egyptian economy would also have to improve substantially to satisfy the higher aspirations of the increasingly educated new entrants and curtail the rising rates of discouragement among female new entrants.

Analysis of mutational spectra in SARS-CoV-2 spike protein and its course of evolution to predict the ‘Alarming Variants’ for the upcoming wave of pandemic

COVID-19 disease extended to different parts of the globe developing variations in the SARS-CoV-2 viral sequence since its emergence. Some of those variations had functional implications with major concerns, which the WHO termed as ‘Variant of Concern’ during the second wave of infection. The signatures of VOCs are specific to countries where they are observed and are popularly recognized with the country names. It is noteworthy to mention that some new mutations are always evolving and it is expected that some of these new mutations could play a havoc role in hitting the upcoming wave of the pandemic. This work aimed to list all the mutations of the Spike protein that evolved with time and how they have increased their presence in a given course of time (three-time point analysis) and stabilized in the SARS-COV-2 infected population. The mutations that will play predominant role in the upcoming pandemic wave are mentioned here:T19I, V213G, D405N, R408S,G142D, G339D, K417N, N440K, D614G, Q954H, N969K mutations in India; G142D, G339D, S373P, S375F, K417N, N440K, S477N, T478K, Q493R, Q498R, N501Y, Y505H, D614G, H655Y, N679K, P681H, N764K, D796Y, Q954H, N969K in South Africa; T95I, G339D, S373P, S375F, N501Y, D614G, H655Y in Brazil; G339D, S373P, S375F, K417N, N440K, N501Y, D614G, P681H in the UK.

Mathematical modeling and estimation for next wave of COVID-19 in Poland

We investigate the problem of mathematical modeling of new corona virus (COVID-19) in Poland and tries to predict the upcoming wave. A Gaussian mixture model is proposed to characterize the COVID-19 disease and to predict a new / future wave of COVID-19. This prediction is very much needed to prepare for medical setup and continue with the upcoming program. Specifically, data related to the new confirmed cases of COVID-19 per day are considered, and then we attempt to predict the data and statistical activity. A close match between actual data and analytical data by using the Gaussian mixture model shows that it is a suitable model to present new cases of COVID-19. In addition, it is thought that there are N waves of COVID-19 and that information for each future wave is also present in current and previous waves as well. Using this concept, predictions of a future wave can be made.

Research on Unrealistic Optimism among HoReCa Workers as a Possible Future Hotspot of Infections

As we are facing a new surge of the highly infectious delta variant of COVID-19, there is an urgent need for research to reduce the harm before this next wave hits. In the present paper, we present data that is alarming. We have found that HoReCa (hotels, restaurants, and catering services) workers, who are highly exposed to many new social interactions in close contact, present an unrealistic optimism (UO) bias: they perceive themselves as less at risk to this virus in comparison to others. From the literature, we already know that individuals holding this view are less involved in preventive actions and present more risky behaviors. In the face of the delta variant, this leads to the conclusion that restaurants will be new hot spots. What is more, we found that these unrealistic expectations are more pervasive: workers of the restaurant industry estimate low chances of bankruptcy, which may lead to unrealistic salary expectations, leading owners to a new upcoming wave of crisis: COVID-19 and bankruptcy—both of which may be caused by their workers.

Diversifying Arena of Drug Synthesis: In the Realm of Lipase Mediated Waves of Biocatalysis

Hydrolases, being most prominent enzymes used in industrial processes have left no stone unturned in fascinating the pharmaceutical industry. Lipases, being a part of acyl hydrolases are the ones that function similarly to esterases (except an interfacial action) wherein they generally catalyze the hydrolysis of ester bonds. Be it in terms of stereoselectivity or regioselectivity, lipases have manifested their promiscuous proficiency in rendering biocatalytic drug synthesis and intermediates thereof. Industrial utilization of lipases is prevalent since decades ago, but their distinctive catalytic competencies have rendered them suitable for maneuverability in various tides of biocatalytic industrial process development. Numbers of exquisite catalysts have been fabricated out of lipases using nanobiotechnology whereby enzyme reusability and robustness have been conferred to many of the organic synthesis procedures. This marks a considerable achievement of lipases in the second wave of biocatalysis. Furthermore, in the third wave an advent of genetic engineering has fostered an era of customized lipases for suitable needs. Be it stability or an enhanced efficacy, genetic engineering techniques have ushered an avenue for biocatalytic development of drugs and drug intermediates through greener processes using lipases. Even in the forthcoming concept of co-modular catalytic systems, lipases may be the frontiers because of their astonishing capability to act along with other enzymes. The concept may render feasibility in the development of cascade reactions in organic synthesis. An upcoming wave demands fulfilling the vision of tailored lipase whilst a far-flung exploration needs to be unveiled for various research impediments in rendering lipase as a custom fit biocatalyst in pharmaceutical industry.

Is Health Consciousness Important at the Time of Coronavirus? The Case of Slovakia and Hungary

The whole world is trying to keep the coronavirus under control. However, it is certain that the consequences of coronavirus do not affect the world economy but also health care and health-conscious consumer behaviour. The first wave of coronavirus came under control when the second wave appeared. What impact will this wave have on consumers’ health consciousness? The article focuses on examining the difference between the level of health consciousness at the time of the decline of the first wave and the release of measures against coronavirus and the second upcoming wave of the mutated version of the virus. The main goal of the state is to examine the level of health consciousness and follow the recommendations of W.H.O. against the spread of coronavirus in Slovakia and Hungary during the decline and re-emergence of coronavirus. The research consisted of two phases - the first phase after the first wave of the pandemic and the second during the onset of the second phase. The one-way ANOVA test and linear regression analysis were used to explore the relationship between health consciousness and W.H.O’s recommendations in the fight against coronavirus. The results indicate a close connection in the conditions of Slovakia and Hungary. At the same time, we concluded that health consciousness changes due to the acuteness of the situation. The results can be used in many fields (medicine, sociology, psychology, marketing), both theories and practice. Implications for Central European audience: European countries, as well as the whole world, are fighting the coronavirus. Preliminary results suggest that the second wave will bring more infected. Health consciousness and prevention provide the best opportunity to fight coronavirus in times without an effective vaccine. It is, therefore, the role of the responsible authorities to examine the level of health consciousness and to try to influence it positively. The results suggest that only proper consumer information and adherence to the basic recommendations of W.H.O. can positively affect the level of health consciousness.

In honor of John Bissett: authoritative guidelines on molecular identification of Trichoderma

Modern taxonomy has developed towards the establishment of global authoritative lists of species that assume the standardized principles of species recognition, at least in a given taxonomic group. However, in fungi, species delimitation is frequently subjective because it depends on the choice of a species concept and the criteria selected by a taxonomist. Contrary to it, identification of fungal species is expected to be accurate and precise because it should predict the properties that are required for applications or that are relevant in pathology. The industrial and plant-beneficial fungi from the genus Trichoderma (Hypocreales) offer a suitable model to address this collision between species delimitation and species identification. A few decades ago, Trichoderma diversity was limited to a few dozen species. The introduction of molecular evolutionary methods resulted in the exponential expansion of Trichoderma taxonomy, with up to 50 new species recognized per year. Here, we have reviewed the genus-wide taxonomy of Trichoderma and compiled a complete inventory of all Trichoderma species and DNA barcoding material deposited in public databases (the inventory is available at the website of the International Subcommission on Taxonomy of Trichodermawww.trichoderma.info). Among the 375 species with valid names as of July 2020, 361 (96%) have been cultivated in vitro and DNA barcoded. Thus, we have developed a protocol for molecular identification of Trichoderma that requires analysis of the three DNA barcodes (ITS, tef1, and rpb2), and it is supported by online tools that are available on www.trichokey.info. We then used all the whole-genome sequenced (WGS) Trichoderma strains that are available in public databases to provide versatile practical examples of molecular identification, reveal shortcomings, and discuss possible ambiguities. Based on the Trichoderma example, this study shows why the identification of a fungal species is an intricate and laborious task that requires a background in mycology, molecular biological skills, training in molecular evolutionary analysis, and knowledge of taxonomic literature. We provide an in-depth discussion of species concepts that are applied in Trichoderma taxonomy, and conclude that these fungi are particularly suitable for the implementation of a polyphasic approach that was first introduced in Trichoderma taxonomy by John Bissett (1948–2020), whose work inspired the current study. We also propose a regulatory and unifying role of international commissions on the taxonomy of particular fungal groups. An important outcome of this work is the demonstration of an urgent need for cooperation between Trichoderma researchers to get prepared to the efficient use of the upcoming wave of Trichoderma genomic data.

Plug-in over Plug-in Evaluation in Heterogeneous 5G Enabled Networks and Beyond

With the cool upcoming wave of 5G, currently, the networking and telecommunication industries are facing various digital transformations, which are changing the very fundamental nature of the existing network management infrastructure. Besides the Internet of Things (IoT) domain, we also notice that the 5G network in itself is composed of millions of heterogeneous physical entities and nodes, multiple domains, complex protocols and technologies, different gateways, and so on. This heterogeneity imposes critical impacts on the application specific quality of service (QoS) requirements, performance and utilization of network resources, and data and user security. In order to alleviate the above impacts, researchers propose to use different technologies such as software-defined networking, network function virtualization, blockchain, and artificial intelligence in 5G-enabled IoT networking. We notice that the layers over layers (of protocols and technologies) act like a plug-in over plug-in (PoP) in the network in order to accomplish various aims, including meeting QoS demands, enhancing security, load balancing, and so on. On one hand, we agree that this integration of different technologies in 5G networks bring numerous advantages, but on the other hand, we realize that this has posed a lot of unique critical issues in modern 5G network management. In this article, we point out that this straightforward approach of PoP is eventually not a healthy approach for network transformation. In this regard, using open source MANO (OSM), we provide a proof of concept (PoC) to show that at varying degrees of heterogeneity, PoP adds the delay in the VNF deployment process and further impacts the VIM CPU performance. This eventually affects the QoS requirements of IoT nodes or applications. Following this, we propose a high-level holistic approach that helps to alleviate the PoP issue. Finally, in this context, we also discuss the associated challenges and research opportunities.

Prediction of local COVID-19 spread in Heidelberg

Since the first identified case of COVID-19 in Wuhan, China, the disease has developed into a pandemic, imposing a major challenge for health authorities and hospitals worldwide. Mathematical transmission models can help hospitals to anticipate and prepare for an upcoming wave of patients by forecasting the time and severity of infections. Taking the city of Heidelberg as an example, we predict the ongoing spread of the disease for the next months including hospital and ventilator capacity and consider the possible impact of currently imposed countermeasures.

Prediction of local COVID-19 spread in Heidelberg.

Since the first identified case of COVID-19 in Wuhan, China, the disease has developed into a pandemic, imposing a major challenge for health authorities and hospitals worldwide. Mathematical transmission models can help hospitals to anticipate and prepare for an upcoming wave of patients by forecasting the time and severity of infections. Taking the city of Heidelberg as an example, we predict the ongoing spread of the disease for the next months including hospital and ventilator capacity and consider the possible impact of currently imposed countermeasures.