Advancing sustainability in the food and nutrition system: a review of artificial intelligence applications

Promoting sustainability in food and nutrition systems is essential to address the various challenges and trade-offs within the current food system. This imperative is guided by key principles and actionable steps, including enhancing productivity and efficiency, reducing waste, adopting sustainable agricultural practices, improving economic growth and livelihoods, and enhancing resilience at various levels. However, in order to change the current food consumption patterns of the world and move toward sustainable diets, as well as increase productivity in the food production chain, it is necessary to employ the findings and achievements of other sciences. These include the use of artificial intelligence-based technologies. Presented here is a narrative review of possible applications of artificial intelligence in the food production chain that could increase productivity and sustainability. In this study, the most significant roles that artificial intelligence can play in enhancing the productivity and sustainability of the food and nutrition system have been examined in terms of production, processing, distribution, and food consumption. The research revealed that artificial intelligence, a branch of computer science that uses intelligent machines to perform tasks that require human intelligence, can significantly contribute to sustainable food security. Patterns of production, transportation, supply chain, marketing, and food-related applications can all benefit from artificial intelligence. As this review of successful experiences indicates, artificial intelligence, machine learning, and big data are a boon to the goal of sustainable food security as they enable us to achieve our goals more efficiently

Performance enhancement of Absolute Polar Duty Cycle Division Multiplexing with Dual-Drive Mach–Zehnder-Modulator in 40 Gbit/s optical fiber communication systems

We modeled and analyzed a method to improve receiver sensitivity of the Absolute Polar Duty Cycle Division Multiplexing (AP-DCDM) transmission system by using Dual-Drive Mach–Zehnder-Modulator (DD-MZM). It is found that by optimizing the bias voltage in DD-MZM, the sensitivity of the AP-DCDM can be improved. The optimizations lead towards the larger eye opening. As opposed to the previous work, in terms of receiver sensitivity and dispersion tolerance, similar performance for all channels was achieved. In comparison to the previously reported AP-DCDM system, this work resulted in almost 3.6 dB improvement of the receiver sensitivity, came together with acceptable chromatic dispersion tolerance

The Effect of Mesenchymal Stem Cells on the Expression of IDOand Qa2 Molecules in Dendritic Cells

Purpose: Mesenchymal stem cells (MSCs) have been shown to reduce the activity of immunecells, including dendritic cells (DCs). But the exact mechanism of mesenchymal inhibitionof DCs is still unknown. In this study, the effect of mesenchymal cells on the expression ofindoleamine dioxygenase (IDO) and Qa2 molecules in DCs was evaluated.Methods: MSCs and DCs were respectively isolated from the bone marrow and spleen of BALB/cmice. Then DCs were co-cultured with MSCs in the present and absence of lipopolysaccharides(LPS). Then the expression of mRNA and protein of IDO and Qa2 molecules were investigatedin DCs that were treated with MSCs.Results: The expression of IDO and Qa2 mRNA in DCs that were treated with MSCs did notsignificantly differ from the control group. The expression of IDO protein in DCs that were coculturedwith MSCs (in 1:10 and 1:50 ratios) in absence of LPS was increased, although theywere not statistically significant (P values: 0.24 and 0.18, respectively). The expression of Qa2protein in DCs that were co-cultured with MSCs (in 1:10 and 1:50 ratios) in presence of LPS wasincreased, although they were not statistically significant (P-values: 0.09 and 0.33, respectively).Conclusion: Our results denied the possibility that MSCs led to the induction of tolerogenic DCsby increasing the expression of the IDO and Qa2 immunomodulatory molecules

Serum HDL cholesterol uptake capacity in subjects from the MASHAD cohort study: its value in determining the risk of cardiovascular endpoints

Background: The efficiency of high-density lipoprotein (HDL) to efflux cholesterol contributes to the reverse cholesterol transport (RCT) pathway as one of HDL’s proposed functions and depends on the ability of HDL to uptake cholesterol. We aimed to investigate cholesterol uptake capacity (CUC) by a newly developed assay in samples from the MASHAD (Mashhad Stroke and Heart Atherosclerotic Disorders) cohort study. Method: The study population comprised 153 individuals developed CVD diagnosed by a specialist cardiologist, over 6 years of follow-up, and 350 subjects without CVD. We used a modified CUC method to evaluate the functionality of HDL in serum samples. Result: The CUC assay was highly reproducible with values for inter- and intra-assay variation of 13.07 and 6.65, respectively. The mean serum CUC was significantly lower in the CVD group compared to control (p = 0.01). Although, there were no significant differences in serum HDL-C between the groups and there was no significantly association with risk of progressive CVD. Multivariate logistic regression analysis showed that there was a significantly negative association between CUC and risk of CVD after adjustment for confounding parameters (OR = 0.57, 95% CI = 0.38–0.87, p = 0.009). The CUC was also inversely and independently associated with the risk of CVD event using Cox proportional hazards models analysis (HR = 0.62; 95% CI = 0.41–0.94, p = 0.02). We determined the optimum cutoff value of 1.7 a.u for CUC in the population. Furthermore, the CUC value was important in determining the CVD risk stratification derived from data mining analysis. Conclusions: Reduced HDL functionality, as measured by CUC, appears to predict CVD in population sample from north-eastern Iran

Mechanistic study to investigate the effects of different gas injection scenarios on the rate of asphaltene deposition: An experimental approach

Asphaltene deposition during enhanced oil recovery (EOR) processes is one of the most problematic challenges in the petroleum industry, potentially resulting in flow blockage. Our understanding of the deposition mechanism with emphasis on the rate of the asphaltene deposition is still in its infancy and must be developed through a range of experiments and modelling studies. This study aims to investigate the rate of asphaltene deposition through a visual study under different gas injection scenarios. To visualise the asphaltene deposition, a high-pressure setup was designed and constructed, which enables us to record high-quality images of the deposition process over time. Present research compares the effects of nitrogen (N2), carbon dioxide (CO2) and methane (CH4) on the rate of asphaltene deposition at different pressures. The experimental results in the absence of gas injection revealed that the rate of asphaltene deposition increases at higher pressures. The results showed that the rate of asphaltene deposition in the case of CO2 injection is 1.2 times faster than CH4 injection at 100 bar pressure. However, N2 injection has less effect on the deposition rate. Finally, it has been concluded that the injection of CO2 leads to more asphaltene deposition in comparison with CH4 and N2. Moreover, the experimental results confirmed that gas injection affects the mechanism of asphaltene flocculation and leads to the formation of bigger flocculated asphaltene particles. The findings of this study can help for a better understanding of the mechanism of the asphaltene deposition during different gas-EOR processes

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

Global fertility in 204 countries and territories, 1950–2021, with forecasts to 2100: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Accurate assessments of current and future fertility—including overall trends and changing population age structures across countries and regions—are essential to help plan for the profound social, economic, environmental, and geopolitical challenges that these changes will bring. Estimates and projections of fertility are necessary to inform policies involving resource and health-care needs, labour supply, education, gender equality, and family planning and support. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 produced up-to-date and comprehensive demographic assessments of key fertility indicators at global, regional, and national levels from 1950 to 2021 and forecast fertility metrics to 2100 based on a reference scenario and key policy-dependent alternative scenarios. Methods To estimate fertility indicators from 1950 to 2021, mixed-effects regression models and spatiotemporal Gaussian process regression were used to synthesise data from 8709 country-years of vital and sample registrations, 1455 surveys and censuses, and 150 other sources, and to generate age-specific fertility rates (ASFRs) for 5-year age groups from age 10 years to 54 years. ASFRs were summed across age groups to produce estimates of total fertility rate (TFR). Livebirths were calculated by multiplying ASFR and age-specific female population, then summing across ages 10–54 years. To forecast future fertility up to 2100, our Institute for Health Metrics and Evaluation (IHME) forecasting model was based on projections of completed cohort fertility at age 50 years (CCF50; the average number of children born over time to females from a specified birth cohort), which yields more stable and accurate measures of fertility than directly modelling TFR. CCF50 was modelled using an ensemble approach in which three sub-models (with two, three, and four covariates variously consisting of female educational attainment, contraceptive met need, population density in habitable areas, and under-5 mortality) were given equal weights, and analyses were conducted utilising the MR-BRT (meta-regression—Bayesian, regularised, trimmed) tool. To capture time-series trends in CCF50 not explained by these covariates, we used a first-order autoregressive model on the residual term. CCF50 as a proportion of each 5-year ASFR was predicted using a linear mixed-effects model with fixed-effects covariates (female educational attainment and contraceptive met need) and random intercepts for geographical regions. Projected TFRs were then computed for each calendar year as the sum of single-year ASFRs across age groups. The reference forecast is our estimate of the most likely fertility future given the model, past fertility, forecasts of covariates, and historical relationships between covariates and fertility. We additionally produced forecasts for multiple alternative scenarios in each location: the UN Sustainable Development Goal (SDG) for education is achieved by 2030; the contraceptive met need SDG is achieved by 2030; pro-natal policies are enacted to create supportive environments for those who give birth; and the previous three scenarios combined. Uncertainty from past data inputs and model estimation was propagated throughout analyses by taking 1000 draws for past and present fertility estimates and 500 draws for future forecasts from the estimated distribution for each metric, with 95% uncertainty intervals (UIs) given as the 2·5 and 97·5 percentiles of the draws. To evaluate the forecasting performance of our model and others, we computed skill values—a metric assessing gain in forecasting accuracy—by comparing predicted versus observed ASFRs from the past 15 years (2007–21). A positive skill metric indicates that the model being evaluated performs better than the baseline model (here, a simplified model holding 2007 values constant in the future), and a negative metric indicates that the evaluated model performs worse than baseline. Findings During the period from 1950 to 2021, global TFR more than halved, from 4·84 (95% UI 4·63–5·06) to 2·23 (2·09–2·38). Global annual livebirths peaked in 2016 at 142 million (95% UI 137–147), declining to 129 million (121–138) in 2021. Fertility rates declined in all countries and territories since 1950, with TFR remaining above 2·1—canonically considered replacement-level fertility—in 94 (46·1%) countries and territories in 2021. This included 44 of 46 countries in sub-Saharan Africa, which was the super-region with the largest share of livebirths in 2021 (29·2% [28·7–29·6]). 47 countries and territories in which lowest estimated fertility between 1950 and 2021 was below replacement experienced one or more subsequent years with higher fertility; only three of these locations rebounded above replacement levels. Future fertility rates were projected to continue to decline worldwide, reaching a global TFR of 1·83 (1·59–2·08) in 2050 and 1·59 (1·25–1·96) in 2100 under the reference scenario. The number of countries and territories with fertility rates remaining above replacement was forecast to be 49 (24·0%) in 2050 and only six (2·9%) in 2100, with three of these six countries included in the 2021 World Bank-defined low-income group, all located in the GBD super-region of sub-Saharan Africa. The proportion of livebirths occurring in sub-Saharan Africa was forecast to increase to more than half of the world's livebirths in 2100, to 41·3% (39·6–43·1) in 2050 and 54·3% (47·1–59·5) in 2100. The share of livebirths was projected to decline between 2021 and 2100 in most of the six other super-regions—decreasing, for example, in south Asia from 24·8% (23·7–25·8) in 2021 to 16·7% (14·3–19·1) in 2050 and 7·1% (4·4–10·1) in 2100—but was forecast to increase modestly in the north Africa and Middle East and high-income super-regions. Forecast estimates for the alternative combined scenario suggest that meeting SDG targets for education and contraceptive met need, as well as implementing pro-natal policies, would result in global TFRs of 1·65 (1·40–1·92) in 2050 and 1·62 (1·35–1·95) in 2100. The forecasting skill metric values for the IHME model were positive across all age groups, indicating that the model is better than the constant prediction. Interpretation Fertility is declining globally, with rates in more than half of all countries and territories in 2021 below replacement level. Trends since 2000 show considerable heterogeneity in the steepness of declines, and only a small number of countries experienced even a slight fertility rebound after their lowest observed rate, with none reaching replacement level. Additionally, the distribution of livebirths across the globe is shifting, with a greater proportion occurring in the lowest-income countries. Future fertility rates will continue to decline worldwide and will remain low even under successful implementation of pro-natal policies. These changes will have far-reaching economic and societal consequences due to ageing populations and declining workforces in higher-income countries, combined with an increasing share of livebirths among the already poorest regions of the world