Whereas many carbon cycle models track CO₂ perturbations relative to a pre-industrial equilibrium, this paper uses absolute quantities to describe atmospheric CO₂ sinks, source and flow rates. This method, when combined with the notion of source and sink resistance, and a finite biospheric reservoir, accurately describes ¹⁴C levels between 1820 and 2020 using only five external parameters. The inputs are:- global records of fossil-fuel emissions, records of CO₂ mixing-ratio and listings of atmospheric atomic weapons tests. Over the same period ¹³C flows are also accurately described given a ð¹³C value for fossil fuel and a ð¹³C value for the initial background. This top-down approach differs from complex climate models since it circumvents the necessity to catalogue individual processes. The paper proceeds to use the method to examine the anthropogenic fossil-fuel emissions contributions during the period 1750 to 2020, deducing that around 24% remains in the atmosphere, while 76% has been absorbed in the land, terrestrial biosphere and surface ocean. During the same period 13% of the total CO₂ atmospheric concentration is due to fossil fuels. However, regarding the increase, fossil fuels contributed to 38% of the rise during this period.

Background: Chronic kidney disease, one of the most common diseases in the world, is characterized by irreversible impairment of the kidney’s metabolic, excretory, and endocrine functions. During end-stage renal disease, patients require renal replacement therapy, such as hemodialysis (HD). Protein-energy wasting is a common health problem among HD patients. However, this study aims to assess the nutritional status of HD patients at two HD centers in Jeddah, Saudi Arabia, and to determine its associated factors. Methods: A cross-sectional study was conducted at two different Dialysis Centers in Jeddah, Saudi Arabia; 211 female and male HD patients. Malnutrition was recognized using the Modified-SGA (M-SGA) comprising two parts: medical history and physical examination. Sociodemographic and health status for all patients were also determined. Patients were classified based on their M-SGA score into two groups: normal and malnourished. Results: Overall, 54.5% of the participants showed malnutrition. Unemployment, low muscle strength and mass, high level of medication use, and high dialysis vintage were positively (P<0.05) associated with malnutrition. Conclusion: The M-SGA score indicates a high prevalence of malnutrition among HD patients. These results show the importance of regular assessment and follow-ups for HD patients ensuring better health and nutritional status.

Global warming is one of the problems of human civilization and decarbonization policy is the main solution to this problem. In this work, we propose an alternative method of using the gravity-assist by the asteroids to increase the orbital distance of the Earth from the Sun. We can manipulate the orbit of asteroids in the asteroid belt by solar sailing and propulsion engines to guide them towards the Mars orbit and a gravitational scattering can put asteroids in a favorable direction to provide an energy loss scattering from the Earth. The result would be increasing the orbital distance of the earth and consequently cooling down the Earth’s temperature. We calculate the increase in the orbital distance of the earth for each scattering and investigate the feasibility of performing this project.

The varved sediments of the Pyrenean Lake Montcortès (Pallars Sobirà, Lleida) embody a unique continuous high-resolution (annual) paleoarchive of the last 3000 years for the circum-Mediterranean region. A variety of paleoclimatic and paleoecological records have been retrieved from these uncommon sediments that have turned the lake into a regional reference. Present-day geographical, geological, ecological and limnological features of the lake and its surroundings are reasonably well known but the lack of a local weather station has prevented characterization of current climate, which is important to develop modern-analog studies for paleoclimatic reconstruction and to forecast the potential impacts of future global warming. Here, the local climate of the Montcortès area for the period 1955-2020 is characterized using a network of nearby stations situated along an elevational transect in the same river basin of the lake. The finding of statistically significant elevational gradients for annual and monthly average temperature and precipitation has enabled to estimate these parameters and their seasonal regime for the lake site. A representative climograph has been shaped with these data that can serve as a synthetic descriptive and comparative climatic tool. The same analysis has provided climatic data for modern-analog studies useful to improve the interpretation of sedimentary records in climatic and ecological terms. In addition, the seasonal slope shifting of the climatic elevational gradients has been useful to gain insights about possible future climatic trends under a warming scenario.

Approximately one-third of mankind is chronically exposed to the carcinogenic aflatoxin M1 contained in milk and dairy products and there is no ready to use procedure for decontamination purposes applicable in milk technology. Since β-cyclodextrin is frequently used in food industry, its effect on aflatoxin M1 concentration was investigated during cholesterol removal. So, milk samples were spiked with aflatoxin M1 at the average level 0.89 µg/kg and cholesterol removal was carried out by 2.0% (w/w) β-cyclodextrin addition. As found, average cholesterol concentration decreased by 92.3% while aflatoxin M1 concentration decreased to 0.53 µg/kg, i. e. by 39.1% after the treatment. The procedure itself is easy, inexpensive, and ready to use in milk processing technology on current production lines without any investments, thus fully applicable with a high potential of full aflatoxin M1 milk decontamination efficiency and such way to strengthen considerably the food safety issues associated with milk and dairy products on global level.

Disaggregated population counts are needed to calculate health, economic, and development indicators in Low- and Middle-Income Countries (LMICs), especially in settings of rapid urbanisation. Censuses are often outdated and inaccurate in LMIC settings, and rarely disaggregated at fine geographic scale. Modelled gridded population datasets derived from census data have become widely used by development researchers and practitioners. These datasets are evaluated for accuracy at the spatial scale of the input data which is often much courser (e.g. administrative units) than the neighbourhood or cell-level scale of many applications. We simulate a realistic "true" 2016 population in Khomas, Namibia, a majority urban region, and introduce realistic levels of outdatedness (over 15 years) and inaccuracy in slum, non-slum, and rural areas. We aggregate these simulated realistic populations by census and administrative boundaries (to mimic census data), and generate 32 gridded population datasets that are typical of a LMIC setting using WorldPop-Global-Unconstrained gridded population approach. We evaluate the cell-level accuracy of these simulated datasets using the original "true" population as a reference. In our simulation, we found large cell-level errors, particularly in slum cells, driven by the use of average population densities in large areal units to determine cell-level population densities. Age, accuracy, and aggregation of the input data also played a role in these errors. We suggest incorporating finer-scale training data into gridded population models generally, and WorldPop-Global-Unconstrained in particular (e.g., from routine household surveys or slum community population counts), and use of new building footprint datasets as a covariate to improve cell-level accuracy. It is important to measure accuracy of gridded population datasets at spatial scales more consistent with how the data are being applied, especially if they are to be used for monitoring key development indicators at neighbourhood scales with relevance to small dense deprived areas within larger administrative units.

During the novel coronavirus disease (COVID-19) pandemic, several environmental factors have influenced the activities and the protection policy measures. This has had a major effect on climate change and global environmental catastrophe. In many countries, the strategy of closing various activities such as tourism, industrial production, stopped normal life, transportation, among others. This closure has a positive impact on the environment. However, the massive use of masks and personal protection could significantly increase pollution worldwide. The impact on the environment needs to be calculated to have information for public health actions. In this study, we present a first overview of the potential impacts of COVID-19 on some environmental matrices in Bogota, Colombia.

Free and open source hardware (FOSH) development has been shown to increase innovation and reduce economic costs. This article reviews the opportunity to use FOSH like a sanction to undercut imports and exports from a target criminal country. A formal methodology is presented for selecting strategic national investments in FOSH development to improve both national security and global safety. In this methodology, first the target country that is threatening national security or safety is identified. Next, the top imports from the target country as well as potentially other importing countries (allies) are quantified. Hardware is identified that could undercut imports/exports from the target country. Finally, methods to support the FOSH development are enumerated to support production in a commons-based peer production strategy. To demonstrate how this theoretical method works in practice it is applied as a case study to the current criminal military aggressor nation, who is also a fossil fuel exporter. The results show there are numerous existing FOSH and opportunities to develop new FOSH for energy conservation and renewable energy to reduce fossil fuel energy demand. Widespread deployment would reduce the concomitant pollution, human health impacts, and environmental desecration as well as cut financing of military operations.

DNA methylation is an epigenetic mechanism for gene expression modulation and can be used as a predictor of future disease risks. A prospective birth cohort study was performed to clarify the effects of neurotoxicants on child development, namely, the Tohoku Study of Child Development, in Japan. This study aimed to evaluate the association of prenatal exposure to five toxic metals—arsenic, cadmium, mercury, lead (Pb), antimony (Sb), and polychlorinated biphenyls (PCBs, N = 166)—with global DNA methylation in umbilical cord blood DNA. DNA methylation markers, 5-methyl-2’-deoxycytidine (mC) and 5-hydroxymethyl-2’-deoxycytidine (hmC), were determined using liquid chromatography-tandem mass spectrometry. The mC content in cord blood DNA was positively correlated with Pb and Sb levels (r = 0.442 and 0.288, respectively) but not with cord blood PCBs. We also observed significant positive correlations among Pb levels, maternal age, and hmC content (r = 0.159 and 0.243, respectively). The multiple regression analysis among the potential predictors demonstrated consistent positive associations between Pb and Sb levels and mC and hmC content. Our results suggest that global DNA methylation is a promising biomarker for prenatal exposure to Pb and Sb.

Infectious diseases, as COVID-19 is proving, pose a global health threat in an interconnected world. In the last 20 years, resistant infectious diseases such as SARS, MERS, H1N1, Ebola, Zika and now COVID-19 have been impacting global health defences, and aggressively flourishing within the rise of global travel, urbanization, climate change and ecological degradation. In parallel, this extraordinary episode in global human health highlights the potential for artificial intelligence (AI)-enabled disease surveillance to collect and analyse vast amounts of unstructured and real-time data to inform epidemiological and public health emergency responses. The uses of AI in these dynamic environments are increasingly complex, challenging the potential for human autonomous decisions. In this context, our study of qualitative perspectives will consider a responsible AI framework to explore its potential application to disease surveillance in a global health context. Thus far, there is a gap in the literature in considering these multiple and interconnected levels of disease surveillance and emergency health management through the lens of a responsible AI framework.

The 2019 Coronavirus Disease (COVID-19) is a major cause of morbidity and mortality worldwide. Since late November 2021, Omicron variant has emerged as the primary cause of COVID-19 and caused a huge increase in the reported incidence around the world. To date, 32-34 spike mutations have been reported, 15 of which were located in the receptor-binding domain that interacts with the cell surface of the host cells, while the rest were located in the N-terminal domain and around the Furin cleavage site. At present, both the genomic and clinical profiles of this novel variant are being investigated. Here, we aim to discuss the recent reports on the transmissibility and severity of Omicron variant from both the genetic and clinical perspectives. Afterward, we also take the chance to deliver our personal view on the topic.

In dry season paddy farming, the alternate wetting and drying (AWD) irrigation improves water productivity, paddy production, and has the potential to decrease greenhouse gas (GHG) such as methane (CH4) and nitrous oxide (N2O) emissions when compared to continuous flooding (CF). However, there is a lack of research in Bangladesh on the effects of water management on CH4 and N2O emissions. During November 2017–April 2018, participatory on-farm trials were conducted at Feni and Chattogram districts of Bangladesh. Total 105 farmers comprising 20-hectare of land (62 farmers at Feni and 43 farmers at Chattogram district, each location having 10 hectare of land). We compared irrigation water and cost reductions, paddy yield, and CH4 and N2O emissions from paddy fields irrigated using AWD and CF irrigation methods. The CH4 and N2O emissions were determined using the Cool Farm Beta-3 methodology, and the global warming potential (GWP) was estimated using the Intergovernmental Panel on Climate Change-2014 standard approach. The mean results of randomly selected 30 farmers from two locations (15 of each) showed that AWD remarkably decreased irrigation water consumption by about 24% and increased water productivity by 224%. We estimated 23% savings for irrigation costs in AWD. By this time, AWD improved paddy production by 3% over CF. The AWD irrigation resulted in a 47% reduction in cumulative CH4 emissions having a lower CH4 emission factor (0.74 kg ha-1 day-1) than CF (1.39 kg ha-1 day-1). There was no obvious difference in N2O emission between AWD and CF. When compared to CF, AWD decreased the overall GWP by 27% and lowered the GHG intensity by 42%. The CH4 and N2O emissions did not differ substantially between Feni and Chattogram.

The building sector of most tropical countries still use predominantly primary biomass as the principal fuel. This has adverse effects like CO2 emission and deforestation and is associated with issues like poverty, ill-health, and low standard of living. Therefore, energy policies try to improve on the efficiency of firewood and charcoal end-use technologies, to palliate the negative effects. In this research, the global change assessment model (GCAM) is used, to investigate the impact of efficiency improvement on the energy consumption pattern of the building sector of developing countries. The aim of the study is to provide empirical data that would better inform policymakers on the effects of modernizing these primary fuels. The study developed three scenarios with different levels of efficiency improvements. The results show that efficiency improvement rather increases primary biomass consumption and CO2 emission. However, there is a fall in the consumption of traditional biomass in the second half of the modelling period. The increase in biomass-based fuels consumption was seen to be linked to their affordability. Therefore, policymakers need not only elaborate policies that improve biomass efficiency, but also introduce and motivate other clean cooking fuels like butane, biogas, and electricity.

This paper presents an extension of the results obtained in previous work concerning the application of global optimization techniques to the design of finite strategic games with mixed strategies. In that publication the Fuzzy ASA global optimization method was applied to many examples of synthesis of strategic games with one previously specified Nash equilibrium, evidencing its ability in finding payoff functions whose respective games present those equilibria, possibly among others. That is to say, it was shown it is possible to establish in advance a Nash equilibrium for a generic finite state strategic game and to compute payoff functions that will make it feasible to reach the chosen equilibrium, allowing players to converge to the desired profile, con- sidering that it is an equilibrium of the game as well. Going beyond this state of affairs, the present article shows that it is possible to ”impose” multiple Nash equilibria to finite strategic games by following the same reasoning as before, but with a fundamental change: using the same fundamental theorem of Richard McKelvey, modifying the originally prescribed objective function and globally minimizing it. The proposed method, in principle, is able to find payoff functions that result in games featuring an arbitrary number of Nash equilibria, paving the way to a substantial number of potential applications.

New setting is introduced to study the global powerful alliance. Global powerful alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global powerful alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs excluding empty, path, star, and wheel and containing complete, cycle and r-regular-strong are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is used in this way. It’s applied to use the type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-powerful-alliance number and minimal-global-powerful-alliance-neutrosophic number. Two different types of sets namely global-powerful alliance and minimal-global-powerful alliance are defined. Global-powerful alliance identifies the sets in general vision but minimal-global-powerful alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-powerful-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-powerful alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs has an open avenue, in the way that, the family only contains same classes of neutrosophic graphs. The results are about minimal-global-powerful alliance, minimal-global-powerful-alliance number and its corresponded sets, minimal-global-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-powerful alliances, minimal-t-powerful alliance, minimal-t-powerful-alliance number and its corresponded sets, minimal-t-powerful-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-t-powerful alliances. The connections amid t-powerful-alliances are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications and closing remarks. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global powerful alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set and reversely for non-members of set with less members in the way that the set is simultaneously t-offensive and(t-2)-defensive. A set is global if t=0. It leads us to the notion of global powerful alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

New setting is introduced to study the global offensive alliance. Global offensive alliance is about a set of vertices which are applied into the setting of neutrosophic graphs. Neighborhood has the key role to define this notion. Also, neighborhood is defined based on strong edges. Strong edge gets a framework as neighborhood and after that, too close vertices have key role to define global offensive alliance based on strong edges. The structure of set is studied and general results are obtained. Also, some classes of neutrosophic graphs containing complete, empty, path, cycle, star, and wheel are investigated in the terms of set, minimal set, number, and neutrosophic number. Neutrosophic number is defined in new way. It’s first time to define this type of neutrosophic number in the way that, three values of a vertex are used and they’ve same share to construct this number. It’s called “modified neutrosophic number”. Summation of three values of vertex makes one number and applying it to a set makes neutrosophic number of set. This approach facilitates identifying minimal set and optimal set which forms minimal-global-offensive-alliance number and minimal-global-offensive-alliance-neutrosophic number. Two different types of sets namely global-offensive alliance and minimal-global-offensive alliance are defined. Global-offensive alliance identifies the sets in general vision but minimal-global-offensive alliance takes focus on the sets which deleting a vertex is impossible. Minimal-global-offensive-alliance number is about minimum cardinality amid the cardinalities of all minimal-global-offensive alliances in a given neutrosophic graph. New notions are applied in the settings both individual and family. Family of neutrosophic graphs is studied in the way that, the family only contains same classes of neutrosophic graphs. Three types of family of neutrosophic graphs including m-family of neutrosophic stars with common neutrosophic vertex set, m-family of odd complete graphs with common neutrosophic vertex set, and m-family of odd complete graphs with common neutrosophic vertex set are studied. The results are about minimal-global-offensive alliance, minimal-global-offensive-alliance number and its corresponded sets, minimal-global-offensive-alliance-neutrosophic number and its corresponded sets, and characterizing all minimal-global-offensive alliances. The connection of global-offensive-alliances with dominating set and chromatic number are obtained. The number of connected components has some relations with this new concept and it gets some results. Some classes of neutrosophic graphs behave differently when the parity of vertices are different and in this case, path, cycle, and complete illustrate these behaviors. Two applications concerning complete model as individual and family, under the titles of time table and scheduling conclude the results and they give more clarifications. In this study, there’s an open way to extend these results into the family of these classes of neutrosophic graphs. The family of neutrosophic graphs aren’t study deeply and with more results but it seems that analogous results are determined. Slight progress is obtained in the family of these models but there are open avenues to study family of other models as same models and different models. There’s a question. How can be related to each other, two sets partitioning the vertex set of a graph? The ideas of neighborhood and neighbors based on strong edges illustrate open way to get results. A set is global offensive alliance when two sets partitioning vertex set have uniform structure. All members of set have more amount of neighbors in the set than out of set. It leads us to the notion of global offensive alliance. Different edges make different neighborhoods but it’s used one style edge titled strong edge. These notions are applied into neutrosophic graphs as individuals and family of them. Independent set as an alliance is a special set which has no neighbor inside and it implies some drawbacks for these notions. Finding special sets which are well-known, is an open way to purse this study. Special set which its members have only one neighbor inside, characterize the connected components where the cardinality of its complement is the number of connected components. Some problems are proposed to pursue this study. Basic familiarities with graph theory and neutrosophic graph theory are proposed for this article.

Economic risks for livestock production are caused by volatile commodities and market conditions, but also by environmental drivers like increasing uncertainties due to weather anomalies and global warming. These risks impact the gross margin of farmers and can stimulated investment decisions. For confined pig and poultry production, farmers can reduce the environmental impact by implementing specific adaptation measures to reduce heat stress. A simulation model driven by meteorological data was used to calculate heat stress impact as a projection for 2030. For a business-as-usual livestock building, the indoor climate for several adaptation measures was calculated. The weather-related value-at risk quantified the economic risks caused by global warming and the stochastic component of the weather. The results show that only energy-saving adaptation measures to reduce the inlet air temperature are appropriate to reduce the economic risk to the level of the year 1980. The efficiency of other adaptation measures to reduce heat stress is distinctly lower. The results in this study can support the decision making of farmers concerning adaptation management and investments. It can inform agricultural policy design as well as technological development.

We studies the initial value problem for the fractional Navier-Stokes-Coriolis equations, which obtained by replacing the Laplacian operator in the Navier-Stokes-Coriolis equation by the more general operator $(-\Delta)^\alpha$ with $\alpha>0$. We introduce function spaces of the Besove type characterized by the time evolution semigroup associated with the general linear Stokes-Coriolis operator. Next, we establish the unique existence of global in time mild solutions for small initial data belonging to our function spaces characterized by semigroups in both the scaling subcritical and critical settings.

Many corporations and governments aspire to become Net Zero Carbon Dioxide by 2030-2050. Achieving this goal requires understanding where energy is produced and consumed, the magnitude of CO₂ generation, and the Carbon Cycle. Many prior proposed solutions focus on reducing future CO₂ emissions from continued use of fossil fuels. Examination of these technologies exposes their limitations and shows that none offer a complete solution. For example, bioethanol is shown to be both carbon and energy inefficient. Direct Air Capture technologies are needed to reduce CO₂ already in the air. The most natural form of Direct Air Capture involves letting nature do the work of creating biomass via photosynthesis. However, it is necessary to break the Carbon Cycle by permanently sequestering that biomass carbon in “landfills” modified to discourage decomposition to CO₂ and methane. Tree leaves and biomass grown on-purpose, such as high yield switchgrass, are proposed as good biomass sources for this purpose. Left unsequestered, leaves decompose with a short Carbon Cycle time constant releasing CO₂ back to the atmosphere. While in any given year, leaves represent a small fraction of a tree’s above ground biomass, leaves can represent a substantial fraction of the total biomass generated by a tree when integrated over a tree’s lifetime. Understanding the chemistry of the distinct phases landfills undergo is the key to minimizing or eliminating decomposition. First, the compact cross-linked structure of cellulose and keeping water out will make it difficult for initial depolymerization to release sugars. Air ingress should be minimized to minimize Phase I aerobic decomposition. pH manipulation can discourage acid formation during Phase II. Lignocellulose is low in nutrients needed for anaerobic decomposition. Inhibitors can be added if needed. The goal is to move quickly to the dormant phase where decomposition stops. The cost for Carbon Capture and Storage (CCS) for growing and sequestering high yield switchgrass is estimated to be lower than CCS for steam reforming of methane hydrogen plants (SRM) and supercritical or combined cycle coal power plants. Thus, sequestration of biomass is a natural, carbon efficient, and low-cost method of Direct Capture. Biomass sequestration can provide CO₂ removal on giga tonnes per year scale and can be implemented in the needed timeframe (2030-2050).

This study examined the tail dependency structure of sovereign credit risk and three global risk factors in BRICS countries using copulas approach, which is known for its ability to provide the “true” tail correlation based on the correct marginal distribution. The empirical results show that global market risk sentiment comoves with sovereign CDS spreads across BRICS countries under extreme market events, with Brazil having the highest co-dependency followed by China, Russia, and South Africa. Furthermore, oil price volatility is the second biggest risk factor correlated with sovereign CDS spreads for Brazil and South Africa while exchange rate risk exhibits very small co-dependence with sovereign CDS spreads under extreme market conditions dominated by tail events. On the contrary, exchange rate risk is the second largest risk factor co-moving with China and Russia’s sovereign CDS spreads while oil price volatility exhibits the lowest co-dependence to CDS in these countries. Between oil price and currency risk, evidence of single risk factor dominance is found for Russia where exchange rate risk is largely dominant. These results suggest that BRICS policymakers might consider financial sector regulations that mitigate risks spill-over such as targeted capital controls when markets are distressed.

Heat stress during the grain-filling period is the main abiotic stress factor limiting grain yield and quality in wheat (Triticum aestivum L.). In this study, 64 wheat genotypes were exposed to heat stress during reproduction caused by delayed sowing in two growing seasons. Grain yield, 1000 grain weight (GW), grain hardness (GH), and grain-quality related traits were investigated using wholemeal flour. Heat stress caused a significant decrease in GW through reducing starch content (SC) and a non-compensating rise in protein content (PC), and thereby resulted in lower yield. In addition, significant increases in flour water absorption (WA), Zeleny sedimentation volume (ZT), ash content (AC), lipid content (LC), loaf volume (LV), wet gluten content (WG), dry gluten content (DG), gluten index (GI), and amylopectin content (APC) were found following heat stress. In contrast, decreases in grain moisture content (MC) and amylose content (AMC) induced by heat stress were observed. The heat-tolerant genotypes were superior in grain yield, GW, SC, AMC, and MC. While the sensitive genotypes contained higher PC, LV, GI and AMP. A group of wheat genotypes characterized with a higher yield, AMC, GW, and SC as well as lower PC, WA, GH, ZT, and LV; and was found to be the most heat tolerant by principal component analysis. Decreases in the ratio of carbohydrates to proteins induced by heat stress, and lower protein content of normal grown wheat genotypes were observed. Therefore, lighter weight and smaller grains produce a smaller starchy endosperm with lower quality (less amylose) and higher grain protein content in heat stress compared to normal conditions. Heat stress caused by delayed sowing improves some of the baking-quality related traits. Whether this improvement in grain quality attributes will translate into better human health outcomes requires further investigation.

The present paper proposes a fractal analysis of the Covid-19 dynamics in 45 European countries. We introduce a new idea of using the box-counting dimension of the epidemiologic curves as a means of classifying the Covid-19 pandemic in the countries taken into consideration. The classification can be a useful tool in deciding upon the quality and accuracy of the data available. We also investigated the reproduction rate, which proves to have significant fractal features, thus enabling another perspective on this epidemic characteristic. Moreover, we studied the correlation between two meteorological parameters: global radiation and daily mean temperature and two Covid-19 indicators: daily new cases and reproduction rate. The fractal dimension differences between the analysed time series graphs could represent a preliminary analysis criterion, increasing research efficiency. Daily global radiation was found to be stronger linked with Covid-19 new cases than air temperature (with a greater correlation coefficient -0.386, as compared with -0.318), and consequently it is recommended as the first-choice meteorological variable for prediction models.

Facing unprecedented global declines in the extent and integrity of ecosystems, the 15^th UN Biodiversity Conference (COP-15) in Kunming, China, presents an opportunity for transformative change. However, a lack of consensus on two key issues – resource mobilization and Access and Benefit Sharing (ABS) associated with Digital Sequence Information (DSI) – risks stalling negotiations for an ambitious ‘Post-2020 Global Biodiversity Framework’ as the next 10-year strategic plan under the Convention on Biological Diversity. We highlight systemic misconceptions concerning the financing of biodiversity and the burden this places on the ABS system. In the context of DSI, we caution that conflating ABS with resource mobilization risks disrupting modern science policy built on open access, with potentially severe ramifications for scientific research and innovation. To resolve these tensions, we call for a recalibration of discussions on ABS in order to maximize the value delivered by biodiversity for all of society, including indigenous peoples and local communities.

Formaldehyde (HCHO) is one of the most important carcinogenic air contaminants. However, the lack of global surface concentration of HCHO monitoring is currently hindering research on outdoor HCHO pollution. Traditional methods are either restricted to small areas or data- demanding for a global scale of research. To alleviate this issue, we adopted neural networks to estimate surface HCHO concentration with confidence intervals in 2019, where HCHO vertical column density data from TROPOMI, in-situ data from HAPs (harmful air pollutants) monitoring network and ATom mission are utilized. Our result shows that the global surface HCHO average concentration is 2.30 μg/m3. Furthermore, in terms of regions, the concentration in Amazon Basin, Northern China, South-east Asia, Bay of Bengal, Central and Western Africa are among the highest. The results from our study provides a first dataset of the global surface HCHO concentration. In addition, the derived confidence interval of surface HCHO concentration adds an extra layer for the confidence to our results. As a pioneer work in adopting confidence interval estimation into AI-driven atmospheric pollutant research and the first global HCHO surface distribution dataset, our paper will pave the way for the rigorous study on global ambient HCHO health risk and economic loss, thus providing a basis for pollutant controlling policies worldwide.

The minimum energy structures of the Si3C5 and Si4C8 clusters are planar and contain planar tetracoordinate carbons (ptCs). These species have been classified, qualitatively, as global () and local () aromatics according to the adaptive natural density partitioning (AdNDP) method, which is an orbital localization method. This work evaluates these species' aromaticity, focusing on confirming and quantifying their global and local aromatic character. For this purpose, we use an orbital localization method based on the partitioning of the molecular space according to the topology of the electronic localization function (LOC-ELF). In addition, the magnetically induced current density is analyzed. The LOC-ELF-based analysis coincides with the AdNDP study (double aromaticity, global and local). Besides, the current density analysis detects global and local ring currents. The strength of the global and local current circuit is significant, involving 4n+2 - and -electrons, respectively. The latter implicates the Si-ptC-Si fragment, which would be related to the 3c-2e -bond detected by the orbital localization methods in this fragment.

This paper extends the concept of weighted graphs to matrix weighted graphs. The consensus algorithms dictate that all agents reach consensus when the weighted graph is connected. However, it is not always the case for matrix weighted graphs. The conditions leading to different types of consensus have been extensively analysed based on the properties of matrix-weighted Laplacians and graph theoretic methods. However, in practice, there is concern on how to pick matrix-weights to achieve some desired consensus, or how the change of elements in matrix weights affects the consensus algorithm. By selecting the elements in the matrix weights, different clusters may be possible. In this paper, we map the roles of the elements of the matrix weights in the systems consensus algorithm. We explore the choice of matrix weights to achieve different types of consensus and clustering. Our results are demonstrated on a network of three agents where each agent has three states.

In this paper, impulsive control on a single-species Markovian jumping ecosystem leads to a stability criterion, and the newly-obtained theorems improve the related existing results. Numerical examples illuminate the effectiveness.

While increasing empirical evidence suggests that global time series forecasting models can achieve better forecasting performance than local ones, there is a research void regarding when and why the global models fail to provide a good forecast. This paper uses anomaly detection algorithms and Explainable Artificial Intelligence (XAI) to answer when and why a forecast should not be trusted. To address this issue, a dashboard was built to inform the user regarding (i) the relevance of the features for that particular forecast, (ii) which training samples most likely influenced the forecast outcome, (iii) why the forecast is considered an outlier, and (iv) provide a range of counterfactual examples to understand value changes, in the feature vector or the predicted value, can lead to a different outcome. Moreover, a modular architecture and a methodology were developed to iteratively remove noisy data instances from the train set, to enhance the overall global time series forecasting model performance. Finally, to test the effectiveness of the proposed approach, it was validated on two publicly available real-world datasets.

This study aims to summarize the literature on sustainable global supply chain management so that researchers and practitioners can see the trends in the area in a single place. Systematic literature review (SLR) or Content analysis is used as a methodology of this literature review, studies that are published within the time frame of 2010 to 2020 are included in this literature. Dimensions to analyze each article includes; year of publications, methodology of research, data collection type, unit of analysis, industry, a country in which data is being collected, respondents’ types, the theory that is used in the study, dimensions of the sustainability and finally the purpose of study either it is to test the already existing theory or building up a new theory. I found that sustainable global supply chain management is an emerging field and there is potential in the area for researchers to explore the area.

Serendipity favors the prepared mind, but how does the brain make that lucky find? Analyzing the cerebral mechanisms behind an exceptional (albeit trivial) discovery, the author suggests that a combination of ‘concept cells’ and the Global Neuronal Workspace Hypothesis could explain how we make great discoveries.

The oil and gas sector has recognised structural integrity assessment of ageing platform for prospective life extension as a rising concern, particularly in encountering the randomness of the harsh ocean environments. This condition leads to uncertainty in wave-in-deck load estimates and a high load level being imposed on offshore structures. This emphasises the necessity of enhanced reliability, as failure might result in inaccessibility because of the uncertainties related to long-distance services, such as accuracy of predictions of loads and responses. Even though the established guidelines present a fundamental assessment, additionally, comprehensive rules are required. This paper performed a reliability analysis incorporating practical approaches that can more accurately represent time-dependent structural deterioration. The following two procedures have been adopted by a majority of significant oil and gas operators to monitor the safety and integrity of these structures: a) Ultimate Strength Assessment (USA) method and b) Reliability Design Assessment (ReDA) method. A comparison of these two reliability approaches was performed on selected ageing jacket structures in the region of the Malaysian sea. The comparative findings, namely, reserve strength ratio (RSR) at various years of the return period (RP) and ratio value for risk of failure regarding the probability of failure (POF), provided a check and balance in strengthening confidence in the results. The findings showed that the structural components might safely survive either using the USA and ReDA method in such conditions, as the reliability indexes were determined to be satisfactory compared to allowable values from ISO 19902 design specifications. Therefore, these evaluations were determined to control the risk level of the structure during the remaining of its lifetime and undertake cost-effective inspections or mitigation strategies when necessary.

People living in slums and other deprived areas in low- and middle-income country (LMIC) cities are under-represented in censuses, and subsequently in "top-down" gridded population estimates. Modelled gridded population data are a unique source of disaggregated population information to calculate local development indicators such as the Sustainable Development Goals (SDGs). This study evaluates if, and how, WorldPop-Global (WPG) -Unconstrained and -Constrained “top-down” datasets might be improved in a simulated realistic LMIC urban population by incorporating slum profile population counts into model training. We found that the WPG-Unconstrained model with or without slum training data grossly underestimated population in urban deprived areas while grossly overestimating population in rural areas. SDG 11.1.1, the percent of population living in slums, for example, was estimated to be 20% or less compared to a "true" value of 29.5%. The WPG-Constrained model, which included building auxiliary datasets, far more accurately estimated the population in all grid cells (including rural areas), and the inclusion of slum training data further improved estimates such that SDG 11.1.1 was estimated at 27.1% and 27.0%, respectively. Inclusion of building metrics and slum training data in “top-down” gridded population models can substantially improve grid cell-level accuracy in both urban and rural areas.

The main objective of this communication is to describe the ‘Global Salt Cycle’. Giant salt accumulations are commonly found along continental margins of former rifts. The first stage in the accumulation process is saturation of newly formed oceanic crust with seawater. Final mobilisation and accumulation of the salts occurs during rifting, localised in the vicinity of relict subduction zones. Oceanic crust is created along the spreading ridges in the deep oceans of the Earth. It exchanges mass and energy with seawater in hydrothermal circulation cells that penetrate deep into the new and fractured crust. Water-rock interactions include the formation of hydrated and hydroxylated minerals, e.g., serpentinites and clay minerals. By incorporating hydroxyl groups and water in their crystal lattices, the salinity of remaining brines increases. Subduction of oceanic crust and serpentinised lithosphere transports water, hydrated minerals, and marine salts deep into the crust and mantle. Upon pressurisation and heating of the subducting slab, different parts of this water are expelled at different depths/temperatures. The resulting fluids will contain salts brought in with the slab, as well as new salts formed by water-rock interaction. The combination of elevated pressures and temperatures, water, salinity, and CO2, create permeability in the normally impermeable, peridotitic mantle, by altering the fluid-rock dihedral angles of mineral grains. This P/T-determined intergranular permeability allows ascent of saline fluids, under lithostatic pressure, within the mantle wedge, or the slab itself. The fluids produce a mechanically weakened and buoyant zone within the mantle wedge due to high pore pressure between mineral grains and reduced mantle density. During the lifetime of a subduction zone, a substantial accumulation of saline fluids within the mantle wedge and crust, is evident. Deep, fluid reservoirs accumulate between the subduction trench and the volcanic front. They may exist for hundreds of millions of years, even after the extinction of the subduction zone. Saline fluids may escape to the surface along deep faults, due to overfilling of available pores/fractures. Fluids within the mantle wedge may form rock melts or exist as supercritical, mineral rich fluids. The combination of reduced pressure due to rifting, and a saline and buoyant mantle, creates a mantle circulation that brings the accumulated, saline fluids, to crustal levels. Salts will therefore accumulate during initial stages of rifting as a result of massive fluid expulsion, phase change and boiling of mantle fluids. No extra energy is required to produce phase change and boiling. The result is formation of solid salts or dense brines/slurries invading fractured crustal rocks, or escaping to the surface/seabed. This process may take place both before and after the sea has invaded a continental rift.

Cervical cancer is a worldwide public health problem with a high rate of illness and mortality among women. In this study, we proposed a novel framework based on Faster RCNN-FPN ar-chitecture for the detection of abnormal cervical cells in cytology images from cancer screening test. We extended the Faster RCNN-FPN model by infusing deformable convolution layers into the feature pyramid network (FPN) to improve scalability. Furthermore, we introduced a global contextual aware module alongside the Region Proposal Network (RPN) to enhance the spatial correlation between the background and the foreground. Extensive experimentations with the proposed deformable and global context aware (DGCA) RCNN were carried out using the cer-vical image dataset of “Digital Human Body" Vision Challenge from the Alibaba Cloud TianChi Company. Performance evaluation based on the mean average precision (mAP) and receiver operating characteristic (ROC) curve has demonstrated considerable advantages of the proposed framework. Particularly, when combined with tagging of the negative image samples using tra-ditional computer-vision techniques, 6-9% increase in mAP has been achieved. The proposed DGCA-RCNN model has potential to become a clinically useful AI tool for automated detection of cervical cancer cells in whole slide images of Pap smear.

Abstract: Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urban interface. Herein, we propose a framework that jointly uses remote sensing derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach for two U.S. study sites against historical settlement extents derived from the Historical Settlement Data Compilation for the US, HISDAC-US, achieving Area-under-the-Curve values >0.9. Our results are largely in agreement with model-based urban areas from the HYDE database, and demonstrate that the integration of remote sensing derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization, and long-term land cover change in countries where historical maps are available.

Nested structure is a structural feature that is conducive to system stability formed by the co-evolution of species in mutualistic ecosystems, and reflects the ability of ecosystem stability to be restored to a stable state again after being destroyed. The co-opetition relationship and value flow between industrial sectors in the global value chain are similar to the mutualistic ecosystem, and the pattern of the global economic system is always changing in dynamic equilibrium. Nestedness theory is used in this article to define the generalist and specialist sectors in the global value chain to analyze the changes in the global supply pattern. Then we study the mechanism of the global economic system to reach a stable equilibrium and the role of different sectors in the steady of the economic system, so as to provide countermeasures for enhancing the stability of the global economic system. At the end of the article, the domestic trade network, export trade network and import trade network of each country are extracted, and an econometric model is designed to analyze how the microstructure of the production system affects a country’s macroeconomic performance, thereby deriving the conclusion that the stability of the international trade network is crucial to a country's economic development.

Over recent years globalisation has occasioned a dramatic rise in cross-cultural interactions – until this was disrupted by the COVID-19 pandemic (OECD 2018, Nelson & Luetz 2021). The ability to competently engage in a multicultural world is often considered the “literacy of the future” (UNESCO 2013, OECD 2018). Global interconnectedness has brought studies into intercultural competence to centre stage (UNDP 2004, Bissessar 2018, Nelson et al. 2019). This has increased the demand for cross-cultural education experiences that facilitate such learning. However, there is a dearth of empirical research into the issues and effects surrounding short-term cross-cultural educational experiences for adolescents. This mixed methods study extends previous research by looking specifically into what impact short-term cross-cultural experiences may have on the formation of intercultural competence and emotional intelligence of Australian high school students. This study used two instruments for measuring intercultural competence and emotional intelligence in a pre- and posttest quasi-experimental design (n=14), the GENE Scale and TEQ. Moreover, it conducted in-depth post experience qualitative interviews (n=7) that broadly followed a phenomenological paradigm of inquiry. The findings suggest that fully embodied cross-cultural immersive experiences offer benefits in areas of intercultural competence and emotional intelligence and can offer meaningful application in areas of current affairs. A greater understanding of the linkages between immersive cross-cultural experiences and intercultural competence offers prospects for policy makers, educators, pastoral carers, and other relevant stakeholders who might employ such experiential learning to foster more interculturally and interracially harmonious human relations.

The intramolecular ionic Diel-Alder (IIDA) reactions of two dieniminiums have been studied within the Molecular Electron Density Theory (MEDT) at the B97XD/6-311G(d,p) computational level. ELF topological analysis of dieniminiums shows that its electronic structure can been seen as the sum of those of butadiene and ethaniminium. The superelectrophilic character of dieniminiums accounts for the high intramolecular global electron density transfer taking place between the diene and iminium frameworks at the transition state structures (TSs) of these IIDA reactions. The activation enthalpy associated to the IIDA reaction of the experimental dieniminium, 8.7 kcal·mol-1, is closer to that of the ionic Diels-Alder (I-DA) reaction between butadiene and ethaniminium, 9.3 kcal·mol-1. However, the activation Gibbs free energy of the IIDA reaction is 12.7 kcal·mol-1 lower than that of the intermolecular I-DA reaction. The strong exergonic character of the IIDA reaction, higher than 17 kcal·mol-1, makes the reaction irreversible. These IIDA reactions present a total re/exo and si/endo diastereoselectivity, which is controlled by the most favourable chair conformation of the tetramethylene chain. Electron localization function (ELF) topological analysis of the single bond formation indicates that these IIDA reactions take place through a non-concerted two-stage one-step mechanism. Finally, ELF and atoms-in-molecules (AIM) topological analyses of the TS associated to inter and intramolecular processes show the great similitude among them.

This paper concerns a new methodology for accuracy assessment of global positioning system verified experimentally with LiDAR (Light Detection and Ranging) data alignment at continent scale for autonomous driving safety analysis. Accuracy of GPS (Global Positioning System) positioning of an autonomous driving vehicle within a lane on the road is one of the key safety considerations. Safety is addressed as a geometry of the problem, where the aim is to maintain knowledge that the vehicle (its bounding box) is within its lane. Accuracy of GPS positioning is checked by comparing it with mobile mapping tracks in the recorded high definition source. The aim of the comparison is to see if the GPS positioning remains accurate up to the dimensions of the lane where the vehicle is driving. For this reason, a new methodology is proposed. Methodology is composed of six elements: 1) Mobile mapping system minimal setup, 2) Global positioning data processing, 3) LiDAR data processing, 4) Alignment algorithm, 5) Accuracy assessment confirmation and 6) Autonomous driving safety analysis. The research challenge is to assess positioning accuracy of moving cars taking into account the constraints of the coverage of limited access highways in the United States of America. The available coverage limits the possibility of repeatable measurements and introduces an important challenge being the lack the ground truth data. State-of-the-art methods are not applicable for this particular application, therefore a novel approach is proposed. The method is to align all the available LiDAR car trajectories to confirm the GNSS+INS (Global Navigation Satellite System + Inertial Navigation System) accuracy. For this reason, the use of LiDAR metric measurements for data alignment implemented using SLAM (Simultaneous Localization and Mapping) was investigated, assuring no systematic drift by applying GNSS+INS constraints. SLAM implementation used state-of-the-art observation equations and the Weighted Non-Linear Least Square optimization technique that enables integration of the required constraints. The methodology was verified experimentally using arbitrarily chosen measurement instruments (NovAtel GNSS+INS, LiDAR Velodyne HDL32) mounted onto mobile mapping systems. The accuracy was assessed and confirmed by the alignment of 32785 trajectories with total length of 1,159,956.9~km and of total $186.4*10^{9}$~optimized parameters (six degrees of freedom of poses) that cover the United States region in the 2016--2019 period. It is demonstrated that the alignment improves the trajectories, thus final map is consistent. The proposed methodology extends the existing methods of global positioning system accuracy assessment focusing on realistic environmental and driving conditions. The impact of global positioning system accuracy on autonomous car safety is discussed. It is shown that 99\% of the assessed data satisfies the safety requirements (driving within lanes of 3.6~m) for Mid-Size (width 1.85~m, length 4.87~m) vehicle and 95\% for 6-Wheel Pickup (width 2.03--2.43~m, length 5.32--6.76~m). The conclusion is that this methodology has great potential for global positioning accuracy assessment at global scale for autonomous driving applications. LiDAR data alignment is introduced as a novel approach to GNSS+INS accuracy confirmation. Further research is needed to solve the identified challenges.

Precipitation gauges are critical for measuring precipitation rates at regional and global scales and are often used to calibrate precipitation rates estimated from other instruments such as satellites. However, precipitation measured at the gauges is affected by gauge-undercatch that is often larger for solid precipitation. In the present work, two popular gauge-undercatch correction factors are assessed: one utilizes a dynamic correction model and is used in the Global Precipitation Climatology Centre (GPCC) Monitoring product and the other one employs a fixed climatology and is used in the Global Precipitation Climatology Project (GPCP) product. How much the choice of correction factors can impact the total estimate of precipitation was quantified over land at seasonal, annual, regional, and global scales. The correction factors are also compared as a function of the environmental variables used in their development, among those are near-surface air temperature, relative humidity, wind speed, elevation, and precipitation intensity. Results show that correction factors can increase the annual precipitation rate based on the gauges by ~9.5 % over the global land (excluding Antarctica), although this amount can vary from ~6.3% (in boreal summer) to more than 10% (in boreal winter), depending on the season and the method used for gauge-undercatch correction. Annual variations of correction factors can also be large, so the use of the fixed climatology correction factors requires caution. Given their magnitudes and differences, selection of appropriate correction factors can have important implications in refining the water and energy budget calculations.

The ionic Diels-Alder (I-DA) reactions of a series of six iminium cations with cyclopentadiene have been studied within the Molecular Electron Density Theory (MEDT). The superelectrophilic character of iminium cations,  > 8.20 eV, accounts for the high reactivity of these species participating in I-DA reactions. The activation energies are found between 13 and 20 kcal·mol-1 lower in energy than those associated to the corresponding Diels-Alder (DA) reactions of neutral imines. These reactions are low endo selective as a consequence of the cationic character of the TSs, but highly regioselective. Solvents have poor effects on the relative energies, and an unappreciable effect in the geometries. In dichloromethane the activation energies increase slightly as a consequence of the better solvation of the iminium cations than the cationic TSs. ELF topological analysis of the bonding changes along the I-DA reactions shows that they are very similar to those in polar DA reactions. The present MEDT study makes it possible establishing that the global electron density transfer (GEDT) taking place at the TSs of I-DA reactions, and not steric (Pauli) repulsions such as have been recently proposed, are responsible for the features of these type of DA reactions.

Metabolic pathways provide key information to achieve a better understanding of life and all its processes; this is useful information for the improvement of medicine, agronomy, pharmacy, and other similar areas. The main analysis tool used to study these pathways is based on the idea of pathway comparison, using graph data structures. Metabolic pathway comparison has been defined as a computationally complex task \cite{ay2011submap,abaka2013campways}. In previous work from 2017, two different approaches that simplify the problem of comparing pathways represented as graphs were introduced. The first algorithm consists of the transformation of a two-dimensional graph structure, representing a metabolic pathway, to a one-dimensional structure and thus aligning the corresponding data using a reduced 1 dimension string. The second algorithm consists of performing a paired analysis between reactions in pathways and thus eliminating all similarities, finally, showing these differences to the user. The suggestion is to use the information provided by these algorithms as a previous analysis to a deeper, more expensive, comparison tool use. Here we provide an extension of this work with more data and deeper analysis. These methods have shown to be an effective way to treat the problem of metabolic pathway comparison as listed in the discussion and results section. Our results show evidence of a quick, simple and effective way to resolve the described problem.

Increased severity of droughts, due to anthropogenic activities and global warming has imposed a severe threat on agricultural productivity ever before. This has further advanced the need for some eco-friendly approaches to ensure global food security. In this regard, application of plant growth-promoting rhizobacteria (PGPR) can be beneficial. PGPR through various mechanisms viz. osmotic adjustments, increased antioxidant, phytohormone production, regulating stomatal conductivity, increased nutrient uptake, releasing Volatile organic compounds (VOCs), and Exo-polysaccharide (EPS) production, etc not only ensures the plant’s survival during drought but also augment its growth. This review, extensively discusses the various mechanisms of PGPR in drought stress tolerance. We have also summarized the recent molecular and omics-based approaches for elucidating the role of drought responsive genes. The manuscript presents an in-depth mechanistic approach to combat the drought stress and also deals with designing PGPR based bioinoculants. Lastly, we present a possible sequence of steps for increasing the success rate of bioinoculants.

Monitoring of the surface operations using movement and surveying radar (MSR) can prevent loss of life, equipment, production and loss of the mine. Slope monitoring using MSR is an important aspect of open-pit mining as it provides real-time movement of deformation data for the slope. It is therefore important that the radar is accurately geo-referenced in order to provide accurate real-time movement data. Geo-referencing is defined as the process of determining an instrument’s position (in the form of Easting, Northing, Height) as well as the orientation with respect to the mine’s local coordinate system. This helps in getting geo-referenced data points from the radar that are identified by a unique set of coordinates in relation to the mine’s coordinate system which allows the radar to track movement for a specific set of coordinates. In this research, we assess the performance of geo-referencing a radar using the total station method and compare it with the integration of Advance Navigation – Spatial Dual GPS system connected via RS422 on the MSR. This includes usage of the Spatial Dual navigation coordinates output to calculate the radar’s position relative to the mine local coordinates and mapping the radar’s azimuth, elevation and Range (Az, El and Rl) values to the measured pit-slope data points. Furthermore, a comparison of key attributes of both methods of geo-referencing is performed using a matrix system and giving an overall performance appraisal of both systems. Integrating a navigation system allows the radar to have an auto geo-referencing functionality that will reduce the time spent in completing this process. The findings reveal that the GPS obtained a higher score than the total station with prism method on the weighted matrix system. The total station was found to be more accurate than the GPS however, the deployment time for the GPS is quicker than that of the total station. This is important for different operation such as strip and open-pit mining to choose the preferred method of geo-referencing depending on the level of accuracy required.

The research examines the relationship between self-rated health situation and personal percep-tion of heat waves, and how social linkage of communities would be a moderator variable in residents’ perception of heat waves in Taiwan. This study uses the questionnaire conducted by Sinica “Responsive Capacity under Heat Wave: The Perspectives of the Locals”(2019), using OLS method for estimating the unknown parameters in multiple regression model. The author finds that the correlation of self-rated health situation and perception toward heat is significantly posi-tive. Also, social linkage in communities affects strongly as a moderator variable: While the sat-isfaction to with their community could reduce negative reaction to heat, contacts with neighbors could increase possibility people feel uncomfortable in high-temperature situation. This study ex-hibits the effects of social environment on community, and expects further related researches or practices to strengthen capability to resist heat wavesƒ for Taiwanese residents.

To safeguard against meat supply shortages during pandemics or other catastrophes, this study analyzed the potential to provide the average household’s entire protein consumption using either soybean production or distributed meat production at the household level in the U.S. with: 1) pasture-fed rabbits, 2) pellet and hay-fed rabbits, or 3) pellet-fed chickens. Only using the average backyard resources, soybean cultivation can provide 80%-160% of household protein and 0%-50% of a household’s protein needs can be provided by pasture-fed rabbits using only the yard grass as feed. If external supplementation of feed is available, raising 52 chickens while also harvesting the concomitant eggs or alternately 107 grain-fed rabbits can meet 100% of an average household’s protein requirements. These results show that resilience to future pandemics and challenges associated with growing meat demands can be incrementally addressed through backyard distributed protein production. Backyard production of chicken meat, eggs, and rabbit meat reduces environmental costs of protein due to savings in production, transportation, and refrigeration of meat products and even more so with soybeans. Generally, distributed production of protein was found to be economically competitive with centralized production of meat if distributed labor costs were ignored.

The use of different primary energy sources in human society has led to two major polluting emissions in the environment: energy (mostly heat), and chemical substances (mostly carbon dioxide). In this paper, the total global anthropogenic emissions of heat to the atmosphere during the industrial era (years 1850-2018) were determined and their effect on the change of global atmospheric temperature was calculated. The concept of a theoretical three-phase Earth reactor was introduced to estimate global atmospheric temperature increase caused by anthro-pogenic heat emissions. The resulting calculations closely approximated the actual atmospheric temperature change recorded during the last 170-year period. These results suggest that the temperature change of the atmosphere (global warming) is entirely due to anthropogenic heat emissions.

Background: global longitudinal strain (GLS) measures myocardial deformation and is a sensitive modality for detecting subclinical myocardial dysfunction and predicting cardiac outcomes. The accuracy of speckle-tracking echocardiography (STE) is dependent on temporal resolution. A novel software enables relatively high frame rate (Hi-FR) (~200 fps) echocardiographic images acquisition which empowers us to investigate the impact of Hi-FR imaging on GLS analysis. The goal of this pilot study was to demonstrate the feasibility of Hi-FR for STE. Methods: In this prospective study, we acquired echocardiographic images using clinical scanners on patients with normal left ventricular systolic function using Hi-FR and conventional frame rate (Reg-FR) (~50 FPS). GLS values were evaluated on apical 4-, 2- and 3-chamber images acquired in both Hi-FR and Reg-FR. Inter-observer and intra-observer variabilities were assessed in Hi-FR and Reg-FR. Results: There were 143 resting echocardiograms with normal LVEF included in this study. The frame rate of Hi-FR was 190 ± 25 and Reg-FR was 50 ± 3, and the heart rate was 71 ± 13. Strain values measured in Hi-FR were significantly higher than those measured in Reg-FR (all p < 0.001). Inter-observer and intra-observer correlations were strong in both Hi-FR and Reg-FR. Conclusions: We demonstrated that strain values were significantly higher using Hi-FR when compared with Reg-FR in patients with normal LVEF. It is plausible that higher temporal resolution enabled the measurement of myocardial strain at desired time point. The result of this study may inform clinical adoption of the novel technology. Further investigations are necessary to evaluate the value of Hi-FR to assess myocardial strain in stress echocardiography in the setting of tachycardia.

In light of the urgency raised by the COVID-19 pandemic, global investment in wildlife virology is likely to increase, and new surveillance programs will identify hundreds of novel viruses that might someday pose a threat to humans. Our capacity to identify which viruses are capable of zoonotic emergence depends on the existence of a technology—a machine learning model or other informatic system—that leverages available data on known zoonoses to identify which animal pathogens could someday pose a threat to global health. We synthesize the findings of an interdisciplinary workshop on zoonotic risk technologies to answer the following questions: What are the prerequisites, in terms of open data, equity, and interdisciplinary collaboration, to the development and application of those tools? What effect could the technology have on global health? Who would control that technology, who would have access to it, and who would benefit from it? Would it improve pandemic prevention? Could it create new challenges?

In this paper we investigate the global asymptotic stability of following system ofhigher order difference equations with quadratic terms:xn+1=A+Byn/yn−m^2, yn+1=A+Bxn/xn−m^2, where A and B are positive numbers and the initial values are positive numbers.We also study the boundedness, rate of convergence and oscillation behaviour of thesolutions of related system.

Health innovations are generally oriented on a techno-economic vision. In this perspective, technologies are seen as an end in themselves, and there is no arrangement between the technical and the social values of innovation. This vision prevails in sanitary crises, in which management is carried out based on the search for punctual, reactive, and technical solutions to remedy a specific problem without a systemic/holistic, sustainable, or proactive approach. This paper attempts to contribute to the literature on the epistemological orientation of innovations in the field of public health. Taking the Covid-19 and Ebola crises as examples, the primary objective is to show how innovation in health is oriented towards a techno-economic paradigm. Second, we propose a repositioning of public health innovation towards a social paradigm that will put more emphasis on the interaction between social and health dimensions in the perspective of social change.

In Secondary Education, the focus of History teaching must be on the development of global citizenship. The present research was a study contextualized in the Fiesta de la Historia Youth Congress in Seville (Spain). A documentary analysis with a descriptive and interpretive design was made of 63 projects of inquiry that pupils carried out. The main objectives were to assess the incidence of the proposal in terms of participation, and to determine whether the pupils' projects followed a logic of inquiry about socially relevant problems which favours the construction of global citizenship. The results point to a low incidence of schools participating in this initiative. The projects of inquiry analysed present for the most part themes related to the historical and social heritage of the locality. The proposals are approached as problems of a specific discipline, and are worked on through a method based on a pseudoscientific research process. The findings indicate the need to continue implementing initiatives based on school inquiry that allow the teaching of History to be articulated around relevant social problems, with the objective being to develop citizenship skills.

Access to reliable, clean, modern cooking enhances life chances. One option is photovoltaic cooking systems. Accurate solar data is needed to ascertain to what extent these can satisfy the needs of local people. This paper investigates how to choose the most accurate satellite derived solar irradiance database for use in Africa. This is necessary because there is a general shortage of ground measurements for Africa. The solar data is needed to model the output of solar cooking systems, for instance, a solar panel, battery and electric pressure cooker. Four easily accessible satellite databases are validated against ground measurements using a range of statistical tests. Results demonstrate the impact of the mathematical measure used and the phenomenon of balancing errors. Fitting of the satellite model to appropriate climate zone and/or nearby measurements improves accuracy, as does higher spatial and temporal resolution of input parameters. That said, all the four databases reviewed were found to be suitable for simulating PV yield in East Africa.

The majority of urban inhabitants in low- and middle-income country (LMIC) cities live in deprived urban areas. However, statistics and data (e.g., local monitoring of Sustainable Development Goals - SDGs) are hindered by the unavailability of spatial data at metropolitan, city and sub-city scales. Deprivation is a complex and multidimensional concept, which has been captured in existing literature with a strong focus on household-level deprivation while giving limited attention to area-level deprivation. Within this scoping review, we build on existing literature on household- as well as area-level deprivation frameworks to arrive at a combined understanding of how urban deprivation is defined with a focus on LMIC cities. The scoping review was enriched with local stakeholder workshops in LMIC cities to arrive at our framework of Domains of Deprivations, splitting deprivation into three different scales and nine domains. (1) Socio-Economic Status and (2) Housing Domains (Household scale); (3) Social Hazards & Assets, (4) Physical Hazards & Assets, (5) Unplanned Urbanization and (6) Contamination (Within Area scale); and (7) Infrastructure, (8) Facilities & Services and (9) city Governance (Area Connect scale). The Domains of Deprivation framework provides a clear guidance for collecting data on various aspects of deprivation, while providing the flexibility to decide at city level which indicators are most relevant to explain individual domains. The framework provides a conceptual and operational base for the Integrated Deprived Area Mapping System (IDEAMAPS) Project for the creation of a data ecosystem, which facilitates the production of routine, accurate maps of deprived “slum” areas at scale across cities in LMICs. The Domains of Deprivation Framework is designed to support diverse health, poverty, and development initiatives globally to characterize and address deprivation in LMIC cities.

Reef-dwelling calcifiers face numerous environmental stresses associated with anthropogenic carbon dioxide emissions, including ocean acidification and warming. Photosymbiont-bearing calcifiers, such as large benthic foraminifera, are particularly sensitive. To gain insight into their resistance and adaptive mechanisms to climate change, Amphistegina lobifera from the Gulf of Aqaba were cultured under elevated pCO2 (492, 963, and 3182 ppm) fully-crossed with elevated temperature (28°C and 31°C) for two months. Differential protein abundances in host and photosymbionts amongst treatments were investigated alongside physiological responses and microenvironmental pH variations. Over 1000 proteins were identified, of which one-third varied significantly between treatments. Thermal stress induced protein depletions, along with reduced holobiont growth. Elevated pCO2 caused only minor proteomic alterations and color changes. However, combined stressors reduced pore sizes and increased microenvironmental pH, indicating adaptive modifications to gas exchange. Notably, substantial proteomic variations at moderate-pCO2 and 31°C indicate cellular stress, while stable physiological performance at high-pCO2 and 31°C is scrutinized by putative decreases in test stability. Our experiment shows that the effects of climate change can be missed when stressors are assessed in isolation, and that physiological responses should be assessed across organismal levels to make more realistic predictions for the fate of reef calcifiers.

Influenza epidemics in temperate regions display dynamics that are characterized by pronounced seasonal peaks during the winter. The general lack of influenza cases during the off-season may result from the virus physically disappearing at the end of the season, in which case it must be imported annually. Alternatively, it may result from persistent asymptomatic carriers or unnoticed local transmission chains that develop into local epidemics as conditions become conducive. Here I attempt to understand these differing explanations by analyzing the global distribution of the four major subtypes that comprise influenza over a period of 18 years based on FluNet data, the surveillance network and database compiled by the WHO, and the NCBI influenza data resource, a repository of relevant genetic information. Examining the annual proportion of each subtype, I find considerable variations in subtype annual proportions between the regions. Moreover, I find that seasonal influenza subtypes can remain confined to specific temperate regions, without showing measurable global presence. These results indicate that although largely undetected during the off-season, influenza is likely to persist locally, and imply a ‘local-global’ model where annual influenza epidemics are a mixture of local strains undergoing reactivation together with an influx of global variants.

How much is religion quantitatively involved in global climate politics? After assessing the role of the Conference of Parties to the United Nations Framework Convention on Climate Change from a normative perspective, this descriptive, transdisciplinary and unconventional study offers the first comprehensive quantitative examination of religious nongovernmental organizations that formally participate in its annual meetings, the largest attempts to solve the climate crisis through global governance. This study finds that although their numbers are growing, only about 3 percent of registered nongovernmental organizations accredited to participate in the conference are overtly religious in nature — and that more than 80 percent of those faith-based groups are Christian. Additionally, this study finds that religious nongovernmental organizations that participate in the conference are mostly from the Global North. The results call for greater participation of religious institutions in the international climate negotiations in order for society to address the planetary emergency of climate change.

Particle swarm optimization (PSO) is an effective algorithm to solve the optimization problem in case that derivative of target function is inexistent or difficult to be determined. Because PSO has many parameters and variants, I propose a general framework of PSO called GPSO which aggregates important parameters and generalizes important variants so that researchers can customize PSO easily. Moreover, two main properties of PSO are exploration and exploitation. The exploration property aims to avoid premature converging so as to reach global optimal solution whereas the exploitation property aims to motivate PSO to converge as fast as possible. These two aspects are equally important. Therefore, GPSO also aims to balance the exploration and the exploitation. It is expected that GPSO supports users to tune parameters for not only solving premature problem but also fast convergence.

Many corporations aspire to become Net Zero Carbon Dioxide by 2030-2050. This paper examines what it will take. It requires understanding where energy is produced and consumed, the magnitude of CO2 generation, and the Carbon Cycle. Reviews are provided for prior technologies for reducing CO2 emissions from fossil to focus on their limitations and to show that none offer a complete solution. Both biofuels and CO2 sequestration reduce future CO2 emissions from fossil fuels. They will not remove CO2 already in the atmosphere. Planting trees has been proposed as one solution. Trees are a temporary solution. When they die, they decompose and release their carbon as CO2 to the atmosphere. The only way to permanently remove CO2 already in the atmosphere is to break the Carbon Cycle by growing biomass from atmospheric CO2 and sequestering biomass carbon. Permanent sequestration of leaves is proposed as a solution. Leaves have a short Carbon Cycle time constant. They renew and decompose every year. Theoretically, sequestrating a fraction of the world’s tree leaves can get the world to Net Zero without disturbing the underlying forests. This would be CO2 capture in its simplest and most natural form. Permanent sequestration may be achieved by redesigning landfills to discourage decomposition. In traditional landfills, waste undergoes several stages of decomposition, including rapid initial aerobic decomposition to CO2, followed by slow anaerobic decomposition to methane and CO2. The latter can take hundreds to thousands of years. Understanding landfill chemistry provides clues to disrupting decomposition at each phase.

Affordable Housing, the basic human necessity has now become a critical problem in global cities with direct impacts on people's well-being. While a well-functioning housing market may augment the economic efficiency and productivity of a city, it may trigger housing affordability issues leading crucial economic and political crises side by side if not handled properly. In global cities e.g. Singapore and Hong Kong where affordable housing for all has become one of the greatest concerns of the Government, this issue can be tackled capably by the provision of public housing. In Singapore, nearly 90% of the total population lives in public housing including public rental and subsidized ownership, whereas the figure tally only about 45% in Hong Kong. Hence this study is an effort to scrutinizing the key drivers of success in affordable public housing through following a qualitative case study based research methodological approach to present successful experience and insight from different socio-economic and geo-political context. As a major intervention, this research has clinched that, housing affordability should be backed up by demand-side policies aiming to help occupants and proprietors to grow financial capacity e.g. subsidized rental and subsidized ownership can be an integral part of the public housing system to improve housing affordability.

Sequence analysis program is outlined that analyzes and investigates homology between various nucleic acid or protein sequence. The dot matrix technique compares the sequences and the consensus sequence is obtained by superimposing on each other all the dot matrices. Local Alignment and Global Alignment both sequence from start to end is the best possible alignment over the entire duration between the two sequences. This method is more important to align with two closely related sequences roughly the same length. This method may not able to generate optimal results for divergent sequences and variable length sequence because between the two sequences it does not recognize very similar local region.

The usual equation for both motions of a single planet around the sun and electrons in the deterministic Rutherford-Bohr atomic model is conservative with a singular potential at the origin. When a dissipation is added, new phenomena appear which were investigated thoroughly by R. Ortega and his co-authors between 2014 and 2017, in particular all solutions are bounded and tend to $0$ for $t$ large, some of them with asymptotically spiraling exponentially fast convergence to the center. We provide explicit estimates for the bounds in the general case that we refine under specific restrictions on the initial state, and we give a formal calculation which could be used to determine practically some special asymptotically spiraling orbits. Besides, a related model with exponentially damped central charge or mass gives some explicit exponentially decaying solutions which might help future investigations. An atomic contraction hypothesis related to the asymptotic dying off of solutions proven for the dissipative model might give a solution to some intriguing phenomena observed in paleontology, familiar electrical devices and high scale cosmology

A hemispheric asymmetry is known for the processing of global vs. local visual information. In this study, we investigated the existence of a hemispheric asymmetry for visual processing of low vs. high spatial frequency gratings. Event-related potentials were recorded in a group of healthy right-handed volunteers from 30 scalp sites. Six types of stimuli (1.5, 3 and 6 c/deg gratings) were randomly flashed 180 times in the left and right upper hemi-fields. Stimulus duration was 80 ms and ISI ranged between 850-1000 ms. Participants had to pay attention and respond to targets based on their spatial frequency and location, or to passively look at the stimuli. C1 and P1 visual responses, as well as a later Selection negativity and a P300 components of ERPs were quantified and subjected to repeated-measure ANOVAs. Overall, performance was faster for the RVF, thus suggesting a left hemispheric advantage for attentional selection of local elements. Similarly, the analysis of mean area amplitude of C1 (60-110 ms) sensory response showed a stronger attentional effect (F+L+ vs. F-L+) at left occipital areas, thus suggesting the sensory nature of this hemispheric asymmetry.

With the rapid development of earth observation, satellite navigation, mobile communication and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. Under this circumstance, a new form of spatial data organization emerged-the global discrete grid. This form of data management can be used for the efficient storage and application of large-scale global spatial data, which is a digital multi-resolution the geo-reference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing and application of current spatial data. There are different types of grid system according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, and establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves that the availability hexagonal grid-based remote sensing data of remote sensing images. And among the three sampling methods, the image obtained by the nearest interpolation sampling method has the highest correlation with the original image.

Accurate localization of road agents is the basis of intelligent transportation systems, which is still difficult to achieve for GNSS positioning in urban areas due to the signal interferences from buildings. Various collaborative positioning techniques are recently developed to improve the positioning performance by the aid from neighboring agents. However, it is still challenging to study their performances comprehensively. The GNSS measurement error behavior is complicated in urban areas and unable to be represented by naive models. On the other hand, real experiment requiring numbers of devices is hard to be conducted, especially for a large-scale test. Therefore, a GNSS realistic urban measurement simulator is developed to provide measurements for collaborative positioning studies. The proposed simulator employs a ray-tracing technique searching for all possible interferences in the urban area. Then, it categorizes them into direct, reflected, diffracted, and multipath signal to simulate the pseudorange, carrier-phase, 〖C/N〗_0, and Doppler shift measurements correspondingly. The performance of the proposed simulator is validated through real experimental comparisons with different scenarios. The proposed simulator is also applied with different positioning algorithms, which verifies it is sophisticated enough for the collaborative positioning studies in the urban area.

Land cover and climate changes greatly influence hydrologic responses of a basin. However, the response vary from basin to basin depending on the nature and severity of the changes and basin characteristics. Moreover, the combined impacts of the changes affect hydrologic responses of a basin in an offsetting or synergistic manner. This study quantified the separate and combined impacts, and the relative contributions of land cover and climate changes on multiple hydrological regimes (i.e., surface runoff, streamflow, groundwater recharge evapotranspiration) for the Dhidhessa Subbasin. Land cover and climate change data were obtained from a recent study completed for the basin. Calibrated Soil and Water Analysis Tool (SWAT) was used to quantify the impacts. The result showed that SWAT model performed well for the Dhidhessa Subbasin in predicting the water balance components. Substantial land cover change as well as an increasing temperature and rainfall trends were reported in the river basin during the past three decades. In response to these changes, surface runoff, streamflow and actual evapotranspiration (AET) increased while groundwater recharge declined. Surface runoff was more sensitive to land cover than to climate changes whereas streamflow and AET were more sensitive to climate change than to land cover change. The combined impacts played offsetting effect on groundwater recharge and AET while inconsistent effects within study periods for other hydrologic responses. Overall, the predicted hydrologic responses will have negative impacts on agricultural production and water resources availability. Therefore, the implementation of integrated watershed management strategies such as soil and water conservation and afforestation could reverse the negative impacts.

The forest transition – or forest-area transition – has been put forward as a land-use concept by A.S. Mather in 1992 (The forest transition. Area 24, 367-379), to describe the historical trend generally observed in the forest area of developed countries, embodied in a V-shaped curve of the forest area over time, and that may serve as a paradigm to understand and anticipate deforestation in the developing world. Well in line with a geographical approach to forests, forest transition has thus been defined as one-dimensional, forest area being the reference state variable. From a forestry perspective, the analysis appears to be reductive, as forests are described by many other state variables than area, including forest growing stock, composition in tree species, or stand structure. Whether the drivers of forest transition (population dynamics, economic modes of production and consciousness, as classified by Mather) also impact these other forest state variables in a general way thus comes forth as a logical issue.From a deductive analysis of forest transition drivers, and from forest trends brought to light in Europe, France, and at other places in the world, we here argue that the forest transition concept can be extended to a multi-dimensional space of forest attributes, characterized by typical ideal dynamics. Cumulative impacts onto forests and irreversible losses in forest biodiversity over a forest transition are hence highlighted. Global change, as a parallel consequence of countries’ developing process, further appears as one additional albeit less coupled dimension of forest transition, as it modifies forest productivity and vitality over time. Since forest ecosystem services and forest profitability primarily depend on such attributes, we argue that the extension of the forest transition concept has significance for land-use change and forest protection issues. A prospect on future changes in the forests of developed countries with the European space as a benchmark is finally proposed that leads to extend the temporal significance of forest transition. Though poorly described, returning forests on abandoned agricultural lands are significant, and deserve greater attention.

Climate change is likely to have a complex effect on the growth of plants, their phenology, plant-pollinator interactions, and reproductive success. Therefore, we tested the impact of three key factors (temperature, water, and nitrogen supply) on traits, pollination, and seed production in Sinapis alba (Brassicaceae). We grew the plants in different combinations of temperature, water, and nitrogen supplementation, measured multiple vegetative and floral traits, and assessed the response of pollinators in the field. We also evaluated the effect of growing conditions on seed set in plants exposed to pollinators and hand-pollinated plants. Our results show that water stress impaired vegetative growth, decreased flower production, reduced visitation by pollinators and seed set, while nitrogen availability played an important role in nectar production. Temperature modulated the effect of water and nitrogen availability on vegetative and floral traits and strongly affected flowering phenology and flower production. We demonstrated that changes in temperature, water, and nitrogen availability induce changes in plant vegetative and floral traits which impact flower visitation and consequently plant reproduction. Climate change, particularly increasing temperature combined with reduced precipitation, thus may impact plant-pollinator interactions with negative consequences for the reproduction of wild plants and insect-pollinated crops.

The usual equation for both motions of a single planet around the sun and electrons in the deterministic Rutherford-Bohr atomic model is conservative with a singular potential at the origin. When a dissipation is added, new phenomena appear. It is shown that whenever the momentum is not zero, the moving particle does not reach the center in finite time and its displacement does not blow-up either, even in the classical context where arbitrarily large velocities are allowed. Moreover we prove that all bounded solutions tend to $0$ for $t$ large, and some formal calculations suggest the existence of special orbits with an asymptotically spiraling exponentially fast convergence to the center.

In the last decades farm animals kept in confined and mechanically ventilated livestock buildings are increasingly confronted with heat stress (HS) due to global warming. These adverse conditions cause a depression of animal health and welfare and a reduction of the performance up to an increase of the mortality. To facilitate sound management decisions, livestock farmers need relevant arguments, which quantify the expected economic risk and the corresponding uncertainty. The economic risk was determined for the pig fattening sector based on the probability of HS and the calculated decrease in the gross margin. The model calculation for confined livestock buildings showed, that HS indices calculated by easily available meteorological parameters can be used for assessment quantification of indoor HS, which is so far difficult to determine. These weather-related HS indices can be applied not only for an economic risk assessment but also for a weather-index based insurance for livestock farms. Based on the temporal trend between 1981 and 2017, a simple model was derived to assess the likelihood of HS for 2020 and 2030. Due to global warming, the return period for a 90-percentile HS index is reduced from 10 years in 2020 to 3-4 years in 2030. The economic impact of HS on livestock farms was calculated by the relationship between an HS index based on the temperature-humidity index (THI) and the reduction of the gross margin. From the likelihood of the HS and this economic impact function, the probability of the economic risk could be determined. The reduction of the gross margin for a 10 year return period was determined for 1980 with 0.27 € per year and animal place and increased by the 20-fold to 5.13 € per year and animal place in 2030.

School closures (SC) were adopted globally as a COVID-19 disease pandemic containment strategy. This extreme measure provoked a disruption of the educational system involving hundreds of million children worldwide. The return of children to school has been variable and is still an unresolved and contentious issue. Importantly the process has not been directly correlated to the severity of the pandemic s impact and has fueled the widening of disparities, disproportionately affecting the most vulnerable populations. Available evidence shows SC added little benefit to COVID-19 control whereas the harms related to SC severely affected children and adolescents. This unresolved issue has put children and young people at high risk of social, economic and health-related harm for years to come, triggering severe consequences during their lifespan. In this article we describe the process of SC and the reopening timetable across the globe. We highlight the data regarding the international state of educational systems around the world, putting emphasis on the rights of children to come back to school.

In this paper, by considering Einstein-Hilbert-Bumblebee (EHB) gravity around global monopole field, we derive exactly a black hole spacetime metric. To test the effect of global monopole field and bumblebee field, which causes the spontaneous Lorentz symmetry breaking, we calculate the weak deflection angle using the Gauss-Bonnet theorem.

In this paper, we investigate the dynamics of following higher order difference equation x_{n+1}=A+B((x_{n})/(x_{n-m}²)) with A,B and initial conditions are positive numbers, and m∈{2,3,⋯}. Especially we study the boundedness, periodicity, semi-cycles, global asymptotically stability and rate of convergence of solutions of related higher order difference equations.

It is common knowledge that increasing CO₂ concentration plays a major role in enhancement of the greenhouse effect and contributes to global warming. The purpose of this study is to complement the conventional and established theory that increased CO₂ concentration due to human emissions causes an increase of temperature, by considering the reverse causality. Since increased temperature causes an increase in CO₂ concentration, the relationship of atmospheric CO₂ and temperature may qualify as belonging to the category of “hen-or-egg” problems, where it is not always clear which of two interrelated events is the cause and which the effect. We examine the relationship of global temperature and atmospheric carbon dioxide concentration at the monthly time step, covering the time interval 1980–2019, in which reliable instrumental measurements are available. While both causality directions exist, the results of our study support the hypothesis that the dominant direction is T → CO₂. Changes in CO₂ follow changes in T by about six months on a monthly scale, or about one year on an annual scale. We attempt to interpret this mechanism by involving biochemical reactions, as at higher temperatures soil respiration, and hence CO₂ emission, are increasing.

Historical analysis of Australian bushfire data spanning 170 years addresses whether the strength of recent fire events has been exacerbated by human-induced climate change. The question of “cause” looks at the characteristics of a wider range of natural hazards. Fire characteristics are compared with earthquake hazard characteristics: (1) energy – termed “magnitude”; (2) severity – termed “intensity”; and (3) resultant damage to people and structures – termed “impact”.Published global, Northern and Southern hemisphere temperature data are shown to vary consistently in phase over 170 years, but vary in amplitude with statistical significance. CO₂ levels north and south of the Equator have tracked quite consistently. Thus, Southern Hemisphere bushfire magnitude and intensity is compared with the Southern Hemisphere climate record, rather than a global data set.28 major bushfires and associated droughts since 1850 show neither apparent drought extent, nor area burned, nor bushfire intensity, correlates with changes in Southern Hemisphere climate. Average rainfall from 1900 shows a wetter, rather than drier trend. Cyclone energy shows no significant trend with climate. Planet-wide “greening”, through CO₂ fertilisation, is an insignificant contributor to bushfire magnitude. Combustion theory shows recorded “global warming” could have had no significant influence on bushfire magnitude or intensity. Any increase in Australian bushfire impact, as judged by lives lost, similarly, shows no correlation with bushfire magnitude, nor indeed, any observed Southern Hemisphere global warming.Thus, bushfire magnitude seems much more likely driven by fuel load and any anomalous bushfire intensity is likely driven by anomalous ground level fuel load. The evidence suggests that any CO₂ emissions reduction will have no impact on future bushfire “severity.

This paper aims to investigate the global asymptotic stability of following system of higher order difference equations with quadratic terms: x_{n+1}=A+B((y_{n})/(y_{n-m}²)),y_{n+1}=A+B((x_{n})/(x_{n-m}²)) where A and B are positive numbers and the initial values are positive numbers. We also study the rate of convergence and oscillation behaviour of the solutions of related system.

Background: The ongoing COVID-19 pandemic and subsequent lockdown have adversely affected global health care services to varying extent. Emergency Services were also affected along with elective surgeries, which were deferred to accommodate the added burden of COVID 19 affected patients, on the healthcare systems. We aimed to assess the change in delivery of essential and emergency surgeries due to the pandemic. Methodology: A research consortium led by WHO Collaboration Centre (WHOCC) for Research in Surgical Care Delivery in Low- and Middle-Income countries (LMIC), India, conducted this retrospective cross-sectional study with 12 recruited centers. All surgeries performed during the months of April 2020 were compared with those performed in April 2019. These surgeries were stratified into emergency and elective, and further categorized based on NHS surgery prioritization documents. Results: A total of 4396 surgeries were performed at these centers in April 2019 and 1216 surgeries were performed in same month during 2020, yielding a fall of 72.3% (1216 /4396).We found a 54% reduction in emergency surgeries and a 91% reduction in the elective surgeries. Number of cesarean sections reduced by 29.7% and fracture surgeries declined by 85.3% Laparotomies and surgeries for local soft tissue infections with necrotic tissue reduced by 71.7% and 69.5% respectively. Conclusion: Our study quantifies the effects of COVID 19 pandemic on surgical care delivery in India and documents that the overall surgical volume reduced by three fourths in the pandemic period. Emergency surgeries reduced to half when compared with pre-pandemic period. Cesarean section surgeries were affected the least by pandemic, whereas the fracture surgeries and laparotomies were affected the most.

In this paper, we study the global asymptotically stability of following system of difference equations with quadratic terms: x_{n+1}=A+B((y_{n})/(y_{n-1}²)),y_{n+1}=A+B((x_{n})/(x_{n-1}²)) where A and B are positive numbers and the initial values are positive numbers. We also investigate the rate of convergence and oscillation behaviour of the solutions of related system.

Despite continued efforts by educators, UN declarations and numerous international agreements, progress is still limited in handling major global challenges such as ecosystem collapse, accelerating climate change, poverty and inequity. The capacity to collaborate globally on addressing these issues remains weak. This systematic review of research on global learning for sustainable development (GLSD) aims to clarify the diverse directions research on GLSD has taken, to present the historical development of the research area, and highlight emerging research issues. The review summarises key findings of the English language literature in the period 1994-2020 identified with the search terms “global learning” and “sustainable development”, sustainability or GLSD, respectively. The review documented a gradually growing knowledge base, mostly authored by scholars located in the global North. Conclusions point to what we might achieve if we could learn from one another in new ways, moving beyond Northern-centric paradigms. It is also time to re-evaluate core assumptions that underlie education for sustainable development more generally, such as a narrow focus on formal learning institutions. The review provides a benchmark for future reviews of research on GLSD, reveals the emerging transformative structure of this transdisciplinary field, and offers reference points for further research

The COVID-19 crisis has brought unprecedented strain on healthcare systems around the world. It has perhaps taught us some key lessons that are worth considering and addressing to help build more sustainable health systems as well as improve our ability to combat future epidemics.

Policy induced decline of human mobility has been recognised to be effective in controlling the COVID-19 spread especially in the initial stage of the outbreak, although the relationship among mobility, policy implementation, and virus spread remains contentious. Coupling data of confirmed COVID-19 cases with Google mobility data in Australia, we present a state-level empirical study to: 1) inspect the temporal variation of COVID-19 spread and the change of mobility adherent to social restriction policies; 2) examine the extent that different types of mobility are associated with the COVID-19 spread in eight Australian states/territories; and 3) analyse the time-lag effect of mobility restriction on the COVID-19 spread. We find that social restriction policies implemented in the early stage of the pandemic controlled the COVID-19 spread effectively; the restriction of human mobility has a time-lag effect on growth rates, and the strength of the mobility-spread correlation increases up to seven days after policy implementation but decreases afterwards. The association between mobility and COVID-19 spread varies across space and time, and subjects to the types of mobility. Thus, it is important for governments to consider the degree to which lockdown conditions can be eased by accounting for this dynamic mobility-spread relationship.

Bone marrow-derived mesenchymal stem cells (BMSCs) have been considered a promising therapeutic approach to cardiovascular disease. This study intends to compare the effect of BMSCs through a standard active cardiac support device (ASD) and intravenous injection on global myocardial injury induced by isoproterenol. BMSCs were cultured in vitro, and the transplanted cells were labeled with a fluorescent dye CM-Dil. Isoproterenol (ISO) was injected into the rats; two weeks later, the labeled cells were transplanted into ISO-induced heart-injury rats through the tail vein or ASD device for five days. The rats were sacrificed on the first day, the third day, and the fifth day after transplantation to observe the distribution of cells in the myocardium by fluorescence microscopy. The hemodynamic indexes of the left ventricle were measured before sacrificing. H&E staining and Masson’s trichrome staining were used to evaluate the cardiac histopathology. In the ASD groups, after three days of transplantation, there were many BMSCs on the epicardial surface, and after five days of transplantation, BMSCs were widely distributed in the ventricular muscle. But in the intravenous injection group, there were no labeled-BMSCs distributed. In the ASD+BMSCs-three days treated group and ASD+BMSCs -five days-treated group, left ventricular systolic pressure (LVSP), the maximum rate of left ventricular pressure rise (+dP/dt), the maximum rate of left ventricular pressure decline (-dP/dt) increased compared with model group and intravenous injection group (P<0.05). By giving BMSCs through ASD device, cells can rapidly and widely distribute in the myocardium and significantly improve heart function.

In 2010, Parties to the Convention on Biological Diversity (CBD) adopted the Strategic Plan for Biodiversity 2011–2020 to address the loss and degradation of nature. Subsequently, most biodiversity indicators continued to decline. Nevertheless, conservation actions can make a positive difference for biodiversity. The emerging Post-2020 Global Biodiversity Framework has potential to catalyze efforts to ‘bend the curve’ of biodiversity loss. Thus, the inclusion of a goal on species, articulated as Goal B in the Zero Draft of the Post-2020 Framework, is essential. However, as currently formulated, this goal is inadequate for preventing extinctions, and reversing population declines; both of which are required to achieve the CBD’s 2030 mission. We contend it is unacceptable that Goal B could be met while most threatened species deteriorated in status and many avoidable species extinctions occurred. We examine the limitations of the current wording and propose an articulation with robust scientific basis. A goal for species that strives to end extinctions and recover populations of all species that have experienced population declines, and especially those at risk of extinction, would help to align actors towards the transformative actions and interventions needed for humans to live in harmony with nature.

Despite several attempts by governments and non-governmental organizations to eliminate female genital mutilation or cutting, it is puzzling that this traditional procedure is widely practiced today in many parts of sub-Saharan Africa (SSA). Scholarly arguments on the influence of female genital mutilation on sexual behavior up until now remain inconclusive. The current study sought to examine the association between female genital mutilation and early sexual initiation among girls and young women (AGYW) in SSA. Data from Demographic and Health Surveys (DHS) of 12 SSA countries were combined. A total of 30,089 AGYW (15-24 years) who had ever had sex and had complete information on all the variables of interest were considered. The outcome variable for the study was early sexual initiation. The study employed multilevel logistic regression for the data analysis, with reported odds ratio and associated 95% confidence intervals (CIs). The overall prevalence of female genital mutilation among AGYW was 49.9%, with the highest and lowest prevalence in Guinea (95.8%) and Togo (3.3%) respectively. The prevalence of early sexual initiation was 42.4%, with the highest and lowest prevalence in Niger (59.9%) and Burkina Faso (30.6%) respectively. AGYW who had not experienced female genital mutilation were less likely to have early sexual initiation [OR= 0.74, CI= 0.70-0.78], compared to those who had experienced female genital mutilation, after controlling for significant covariates. The likelihood of early sexual initiation was high among AGYW aged 15-19 [OR=2.38, CI=2.26-2.51] but low among AGYW with secondary education [AOR=0.58, CI=0.54-0.63], those who had never married [OR=0.68, CI=0.60-0.78], those in households with richest wealth quintile [OR=0.64, CI=0.57-0.72], those who were exposed to mass media [OR=0.88, CI=0.83-0.93], and those working [OR=0.91, CI=0.87-0.96]. Not undergoing female genital mutilation in the midst of socio-economic factors (e.g., education level, household wealth) could limit AGYW from early sexual debut. These findings underscore the need for effective campaign and programs (e.g., educational programs, entrepreneurial training, micro-finance schemes) against the practice of female genital mutilation. Policy interventions (e.g., “schooling for the girl-child” initiatives) that might delay early sexual initiation among adolescent girls and young women in the midst of identified socio-economic factors should be developed.

A global approach towards quality management highlights the need for constructing a new body of knowledge that views the field of global quality from a systems perspective. Based on the results of field experiments, and in light of the need to develop new global quality management terminology, the current article presents several key concepts in this field, with emphasis on a systems-oriented rationale and perspective. As such, the article is an important stage in building this body of knowledge, and towards the conceptualization of key variables used in global quality management, from a systems approach that interacts with the fields of international management and strategic management.

A methodology based on the concepts that arise from Density Functional Theory named Conceptual Density Functional Theory (CDFT) was chosen for the calculation of some global and local reactivity descriptors of the Discodermins A-H family of marine peptides through the consideration of the KID (Koopmans in DFT) technique that was successfully used in previous studies of this kind of molecular systems. The determination of active sites of the studied molecules for different kind of reactivities was achieved by resorting to some CDFT-based descriptors like the Fukui functions as well as the Parr functions derived from Molecular Electron Density Theory (MEDT). A few properties identified with their ability to behave as a drug and the bioactivity of the peptides considered in this examination were acquired by depending on a homology model by studying the correlation with the known bioactivity of related molecules in their interaction with various biological receptors. With the further object of analyzing their bioactivity some parameters of usefulness for future QSAR studies, their predicted biological targets and the the ADME (Absorption, Distribution, Metabolism, and Excretion) parameters related to the Discodermins A-H pharmacokinetics are also reported.

Man-made shallow fishponds in the Czech Republic have been facing a high eutrophication since 1950s. Anthropogenic eutrophication and feeding of fish have strongly affected the physico-chemical properties of water and its aquatic community composition leading to harmful algal bloom formation. In our current study, we have characterised the phytoplankton community across three hypertrophic ponds to assess the phytoplankton dynamics during the vegetation season. We microscopically identified and quantified 29 cyanobacterial taxa comprised of non-toxigenic and toxigenic species. Further, a detailed cyanopeptides (CNPs) profiling was performed using molecular networking analysis of liquid chromatography tandem mass spectrometry (LC–MS/MS) data coupled with dereplication strategy. This MS networking approach coupled with dereplication on online global natural product social networking (GNPS) web platform led us to putatively identify forty CNPs: fourteen anabaenopeptins, ten microcystins, five cyanopeptolins, six microginins, two cyanobactins, a dipeptide radiosumin, a cyclooctapeptide planktocyclin and epidolastatin12. We have applied the binary logistic regression to estimate the CNPs producer by correlating the GNPS data with the species abundance. Usage of The combination of molecular networking and dereplication on online global natural product social networking (GNPS) web platform has proved as a valuable approach for rapid and simultaneous detection of high number of peptides, and rapidly assessing the risk for harmful bloom.

The South African Weather Service (SAWS) manages an in-situ solar irradiance radiometric network of 13 stations and a very dense sunshine recording network; located in all six macro-climate zones of South Africa. A sparsely distributed radiometric network and over a landscape with dynamic climate and weather shifts is inadequate for solar energy studies and applications. Therefore, there is a need to develop mathematical models to estimate solar irradiation for a multitude of diverse climates. In this study, the annual regression coefficients, a and b, of the Ångström-Prescott (AP) model that can be used to estimate global horizontal irradiance from observed sunshine hours were calibrated and validated with observed station data. The AP regression coefficients were calibrated and validated for each of the six macro-climate zones of South Africa using the observation data that spans 2013 to 2019. The predictive effectiveness of the calibrated AP model coefficients was evaluated by comparing estimated and observed daily global horizontal irradiance. The maximum annual relative Mean Bias Error (rMBE) was 0.371 %, relative Mean Absolute Error (rMAE) was 0.745 %, relative Root Mean Square Error (rRMSE) was 0.910 % and the worst-case correlation coefficient (R2) was 0.910. The statistical validation metrics results show that there is a strong correlation and linear relation between observed and estimated solar radiation values. The AP model coefficients calculated in this study can be used with quantitative confidence in estimating daily GHI data at locations in South Africa where the daily observation sunshine duration data is available.

The KID (Koopmans in DFT) procedure usually applies in organic molecules of the closed–shell type. We used the KID procedure in an open–shell system for the first time to choose the most suitable density functional to compute global and local reactivity descriptors coming from the Conceptual Density–Functional Theory. From a set of 18 density functionals spread from the second until the fourth rung of the Jacob’s ladder: BP86, B97-D, BLYP, CAM-B3LYP, M06-L, M11-L, MN12-L, B3LYP, PBE0, N12-SX, M06-2X, M11, MN12-SX, CAM-B3LYP, LC-ωHPBE, ωB97X-D, APFD, MN15 and MN15-L, we concluded that CAM-B3LYP provides the best outcome.

Hand gestures may play an important role in medical applications for health care of elderly people, where providing a natural interaction for different requests can be executed by making specific gestures. In this study we explored three different scenarios using a Microsoft Kinect V2 depth sensor then evaluated the effectiveness of the outcomes. The first scenario utilized the default system embedded in the Kinect V2 sensor, which depth metadata gives 11 parameters related to the tracked body with five gestures for each hand. The second scenario used joint tracking provided by Kinect depth metadata and depth threshold together to enhance hand segmentation and efficiently recognize the number of fingers extended. The third scenario used a simple convolutional neural network with joint tracking by depth metadata to recognize five categories of gestures. In this study, deaf-mute elderly people execute five different hand gestures to indicate a specific request, such as needing water, meal, toilet, help and medicine. Then, the requests were sent to the care provider’s smartphone because elderly people could not execute any activity independently. The system transferred these requests as a message through the global system for mobile communication (GSM) using a microcontroller.

Indirect effects of global change via changing species interactions have been largely ignored in studies predicting global change impacts on ecosystems. Antagonistic biotic interactions, however, can strongly affect ecosystems and are likely to be affected by global change drivers themselves. We synthesize current knowledge on the impact of invertebrate herbivores and pathogens on plant productivity, diversity and community composition, and outline theory and expectations on how important global change drivers – nitrogen enrichment, climate change and elevated CO², and plant and insect diversity loss, may affect enemy impact on plant communities. We illustrate that our ability to predict global change impact requires a holistic perspective, taking into account direct as well as indirect effects via the biotic component of ecosystems.

Frailty is an important age-associated risk-state. Despite this, many countries lack population estimates and large heterogeneity exists amongst studies. The Global Burden of Disease (GBD) study, provides comparable high-quality population-level data for 195 countries and territories. Frailty has never been measured in the GBD studies. This analysis applies the deficit accumulation model to construct a novel frailty index (FI) using the GBD 2017 dataset. Standard FI criteria were applied to all GBD categories such that selected items were health-related, age-correlated, sufficiently prevalent, did not saturate at an early age, had little redundancy/duplication, covered a range of systems, were plausible and were available serially for the same population. From all 554 GBD items, 36 were selected including 26 non-communicable diseases, 3 metabolic risks, 3 biological impairments, infectious diarrheal diseases, protein-energy malnutrition, injurious falls, and low physical activity. Variable face validity was displayed against a selection of established FIs. The mean GBD-FI score for the global population aged ≥70 years in 2017 was 0.16; scores were higher in females than males (0.16 vs 0.15, respectively). Deficits accumulated with age at an estimated rate of 0.026 per year. Adding the mean GBD-FI scores to a regression model including country-level variables for demographics (proportion ≥85 years, proportion female), healthcare quality (HAQ index), and development (SDI) increased the adjusted r2 value from 27.0% to 39.6% (p<0.001) for predicting country-level death rates from non-communicable diseases, suggesting that the GBD-FI is a useful predictor of mortality. Further analysis is required to compare the reliability and predictive validity of the GBD-FI with existing frailty tools

The Needleman-Wunsch process is a classic tool in bioinformatics, being a dynamic programming algorithm that performs a pairwise alignment of two input biological sequences, either protein or nucleic acid. A distance matrix between the tokens used in the sequences is also required as input. The distance matrix is used to generate a positional pairwise similarity matrix between the input sequences, which is in turn used to generate a dynamic programming matrix. The best path through the dynamic programming matrix is navigated using a traceback procedure that maximises similarity, inserting gaps as necessary. Needleman-Wunsch can align both nucleic acids or proteins, which use alphabets of size 4 and 20 tokens respectively. It can also be applied to any other kind of sequence where distance matrices can be specified. Here, we apply it to chains of Pousseur’s Scambi electronic music fragments, of which there are 32, and which Pousseur categorised by their sonic properties, thus permitting the consecutive construction of distance, similarity and dynamic programming matrices. Traceback through the dynamic programming matrix thus produces contrapuntal duet compositions in which two Scambi chains are played in the maximally euphonious manner, providing also an illustration of the principles of biological sequence alignment in sound.

The COVID-19 outbreak has severely affected the social and economic conditions across this globe. Little is known about the relationship of COVID-19 with countries’ economic and socio-demographic status. Publicly available data on COVID-19 test rate, attack rate, case fatality rate, and recovery rate were analyzed in relation to country’s economic status, population density, median age, and urban population ratio. We also conducted multinomial logistic regression analysis to predict the influence of countries’ social and economic factors on COVID-19. The results revealed that the median age had significant positive correlation with attack rate (r=0.2389, p=0.003), case fatality rate (r=0.3207, p=0.000) and recovery rate (r=0.4847, p=0.000). The urbanization has positive significant correlation with recovery rate (r=0.1957, p= 0.016). The multinomial logistic regression analysis revealed low-income countries are less likely to have an increased recovery rate (p=0.000) and attack rate (p=0.016) compare to high-income countries. The lower-middle-income and upper-middle-income countries are less likely to have an increased recovery rate (p=0.000 and p=0.001, respectively) compared to high-income countries. Based on the result of this study, these economic and socio-demographic factors should consider in designing appropriate preventive measures as a next step. The low and lower-middle-income countries should invest more in health care services to lower the case fatality rate and increase test and recovery rates as part of pandemic preparation like COVID-19. As the number of COVID-19 attacks, death and recovery rates are constantly changing; however, the intensive study is required to obtain a clear picture.

Can investing in women’s agriculture increase productivity? This paper argues that it can. We assess climate impacts and gender bias on women’s production in the global South and North and challenge the male model of agricultural development to argue further that women’s farming approaches can be more sustainable. Level-based analysis (global, regional, local) draws on literature review, including authors’ published longitudinal field research in Ghana and the United States. Women farmers are shown to be undervalued and to work harder, with fewer resources, for less compensation; gender bias challenges are shared globally while economic disparities differentiate; breaches of distributive, gender, and intergenerational justices as well as compromise of food sovereignty affect women everywhere. We conclude that investing in women’s agriculture needs more than standard approaches of capital and technology investment. Effective ‘investment’ would include systemic interventions into agricultural policy, governance, education, and industry; be directed at men as well as women; and use gender metrics, e.g. quotas, budgets, vulnerability and impacts assessments, to generate assessment reports and track gender parity in agriculture. Increasing women’s access, capacity, and productivity cannot succeed without men’s awareness and proactivity. Systemic change can increase productivity and sustainability.

A recent review of global vitamin C status indicated a high prevalence of deficiency, particularly in low- and middle-income countries, as well as in specific subgroups within high-income countries. Here we provide a narrative of potential factors influencing vitamin C status. The in vivo status of vitamin C is primarily affected by dietary intake and supplement use. Dietary intake can be influenced by cultural aspects such as staple foods and traditional cooking practices. Environmental factors can also affect vitamin C intake and status; these include geographic region, season and climate, as well as pollution. Demographic factors such as sex, age, and race are known to affect vitamin C status, as do socioeconomic factors such as deprivation, education and social class, and institutionalization. Various health aspects affect vitamin C status; these include body weight, pregnancy and lactation, genetic variants, smoking, and disease states, including severe infections as well as various non-communicable diseases such as cardiovascular disease and cancer. Some of these factors have changed over time, therefore we also explore if vitamin C status has shown temporal changes. Overall, there are numerous factors that can affect vitamin C status to different extents in various regions of the world. Many of these factors are not taken into consideration during the setting of global recommended dietary intakes for vitamin C.

This study investigates the impact of global financial crisis and the present COVID-19 pandemic on daily and weekly Crude oil futures using four variants of ARMA-GARCH models: ARMA-sGARCH, ARMA-eGARCH, ARMA-TGARCH and ARMA- aPARCH with dummy variables We also investigated the persistence, half-life and backtesting of the models. This study therefore seeks to contribute to the body of literature on the impact of global financial crisis and the present COVID-19 pandemic on crude oil futures market. This investigation of the impact of global financial crisis and the COVID-19 on crude oil futures has not been much studied at present. We obtained and analyzed the daily and weekly crude oil futures from secondary sources. Daily crude oil futures used in this study covers the period from the 4th January 2000 to 27th April 2020 while the weekly crude oil futures covered from 2ndJanuary 2000 to 26th April 2020 . The global financial crisis period covered from 2nd July 2007 to 31st March 2009 and the current COVID-19 pandemic covered from 1st January 2020 to 27th April, 2020. The study used both student t and skewed student t innovations with AIC, goodness-of-test fit and backtesting to select the best model. Most of the estimated ARMA-GARCH models are supported by skewed student t distribution while most of the ARMA-GARCH models exhibited high persistence values in the presence of global financial crisis and the COVID-19 pandemic. In the overall, the estimated ARMA(1,0)-eGARCH(2,1) and ARMA(1,0)-eGARCH(2,2) model for daily crude oil futures and weekly crude oil futures respectively have been significantly impacted by the global financial crisis and the Present COVID-19 pandemic while the preferred estimated models also passed the goodness-of-test fit and backtesting.This study recommends shareholders and investors should think outside the box as crude oil futures tend to be affected by global financial crisis and COVID-19 pandemic while countries also that depend mostly on crude oil are encouraged to diversify their economy in other to survive and be sustained during financial and health crisis.

The pandemic caused by SARS-CoV-2 virus obstructed the Chinese economy and has expanded to the rest of the world at a rapid pace affecting at least 215 countries, areas and territories. The advancement of the disease and its economic repercussions is profoundly ambiguous, making it challenging for policymakers to formulate suitable microeconomic and macroeconomic policy responses. The scenarios in this paper illustrate how an outbreak could significantly affect the global economy in the short run. It has been estimated that each additional month of crisis would cost from about 2.5-3% of the global GDP and that the GDP growth would take a blow, reaching about 3-6%, depending on the country. Scenarios also suggest that GDP can drop by more than 10% and even exceed 15% in some countries. Via addressing the economic consequence of COVID-19 in different industries and countries, the paper presents assessments of the likely global economic costs of COVID-19 and the GDP growth of different countries. Economies will be negatively affected because of the high number of jobs at risk. Countries highly dependent on foreign trade are more negatively affected. Given that disease and its economic influence are highly unpredictable in numerous aspects, the global economy at the moment is the most critically threatened in history.

Global emerge of zoonotic novel corona virus (COVID-19) became a pandemic and its effect to mankind is talk of the town now a days. This tiny, invisible enemy has affected every country in the world and almost every living directly or indirectly and nationwide complete lockdown has triggered a short-term environmental impact. Since 2003, corona virus came into existence in the form of Severe Acute Respiratory Syndrome (SARS) and more evolved Middle East Respiratory Syndrome (MERS) in 2012. This time, at the end of December 2019, outbreak of novel corona virus COVID-19 (also known as SARS-CoV₂, nCoV-2019) draw attention as global health emergency. World Health Organization (WHO) report says that the outbreak of this virus is so immense, it has already affected 35,57,235 people and caused death to 2,45,150 people worldwide and 46,433 Indians got affected with 1568 death as on 5^th May 2020 (2:00 am) and these numbers are increasing exponentially day by day. Virologist, micro-biologist and science community are hammering their head very hard to find out cure and vaccine against this powerful virus and to prevent mass demise of mankind. In order to curb the spread of COVID-19, Janta curfew on 22.03.2020 and nationwide complete lockdown was implemented in India for 21 days (phase-I, from 25.03.2020 to 14.04.2020) to stop community transmission of third stage, for 19 days (phase-II, 15.04.2020 to 03.05.2020) and 14 days (phase-III, 04.05.2020 to 17.05.2020) complete lockdown to minimize the community transmission effect. During complete lockdown and quarantine period a drastic change in Earth’s atmosphere, including reduction in emission of greenhouse gases, air pollution (~50% fall in air quality index), noise pollution, water pollution and solid waste pollution, have been recorded by government agencies as well as private agencies. In this paper we considered data of Janta curfew, phase-I and phase-II lockdown to link between geological and environmental aspect related to environmental impact due to emerge of COVID-19 and massive reduction in pollution level during complete lockdown in India. We propose future lockdown strategies to minimize the emission of greenhouse gas by ~100 Mt to ~200Mt (3.33% to 6.66%) of GHG_total per year by 2-4 days per month nationwide lockdown or ~70 Mt to ~140 Mt (2.33% to 4.66%) of GHG_total per year by 2-4 days per month complete lockdown of energy sectors only.

This theoretical paper continues a spectrum of research on sign character of narrative discourse on the background of modern post-classical theory of narrativity. It aims to uncover the relationships between the meaning of the narrative text and a sign signitication, assuming an intentional character of the narrative discourse governed by telic aspects (global semiotics). Global semiotic approach (Thomas Sebeok, 2001) views a narrative discourse as a self-organizing entity with purposeful (telic) character of all its constituent parts which turn a static text into a dynamic whole in the process of reading/perception/interpretation. The key notion for analysis of emergency is the term Umwelt (Jakob von Uexküll) to denote the perceptional world in which an organism (and a human) exists and acts as a subject. Therefore, Umwelt represents human’s perceptual boundary, which modifies the surrounding in accordance with the human’s subjective perspective. As Umwelt can be attributed to both biological and abiotic texts, meaning creation in the narrative discourse is compared to a semiotic study of comparative Umwelten (Cobley, 2014) where narrative is defined as a modeling device for the world creation through embodied subjectivity. It has been confirmed, that stressing on the subjective sphere of information eхchange and processing from the position of global semiotics necessitates introduction of basic principles of biosemiotics (i.e. semiotic scaffolding etc.) and teleology (i.e. cause, purpose, result) to analysis of narrative discourse and it constitutes the perspectives for further research in this domain.