External Sector and The Nigerian Manufacturing Sector Performance, 1981-2019

No country is an island. The globalization phenomenon is making all countries to be interdependent. The external sector environment has become critical for the success of every country and internal balance. Thus, it has become important to examine how much the externa sector environment impact on the performance of the domestic economy. The present study, therefore, examined the influence of Nigerian external sector environment on the performance of the Nigerian manufacturing sector between 1981 and 2019. The study adopted exp-post research design approach and the Autoregressive Distributed Lag (ARDL) model estimation techniques. The empirical model consists of the Nigerian manufacturing sector output index as the dependent variable and exchange rate, trade openness, and foreign direct investment as independent variables and external sector environment variables. Test of unit root results indicated that the variables have mix order of integration, while the co integration analysis results indicated that the variables in the model have stable long run relationship. Estimate of the ARDL model reveals that in the short run exchange rate variations have negative, but significant effect on manufacturing sector performance, while trade openness, and FDI have positive but insignificant influence on the manufacturing sector performance in the short run. In the long run, exchange rate level and FDI inflows have positive and significant effect on the manufacturing sector performance, while trade openness has negative and significant effect on the Nigerian manufacturing sector performance. The study therefore conclude that the Nigerian external sector Environment has significant influence on the performance of the Nigerian manufacturing sector.

Defining the dynamics of naive CD4 and CD8 T cells across the mouse lifespan

Naive CD4 and CD8 T cells are part of the foundation of adaptive immune responses, but multiple aspects of their behaviour remain elusive. Newly generated T cells continue to develop after they leave the thymus and their dynamics and 'rules of entry' into the mature naive population are challenging to define. The extents to which naive T cells' capacities to survive or self-renew change as they age are also unclear. Further, much of what we know about their behaviour derives from studies in adults, both mouse and human. We know much less about naive T cell dynamics early in life, during which the thymus is highly active and peripheral T cell populations are rapidly established. For example, it has been suggested that neonatal mice are lymphopenic; if so, does this environment impact the behaviour of the earliest thymic emigrants, for example through altered rates of division and loss? In this study we integrate data from multiple experimental systems to construct models of naive CD4 and CD8 T cell population dynamics across the entire mouse lifespan. We infer that both subsets progressively increase their capacity to persist through survival mechanisms rather than through self-renewal, and find that this very simple model of adaptation describes the population dynamics of naive CD4 T cells from birth into old age. In addition, we find that newly generated naive CD8 T cells are lost at an elevated rate for the first 3-4 weeks of life, which may derive from transiently increased recruitment into conventional and virtual memory populations. We find no evidence for elevated rates of division of naive CD4 or CD8 T cells early in life and indeed estimate that these cells divide extremely rarely. Markers of proliferation within peripheral naive T cells are instead inherited from division during thymic development. We also find no evidence for feedback regulation of rates of division or loss of naive T cells at any age in healthy mice, challenging the dogma that their numbers are homeostatically regulated. Our analyses show how confronting an array of mechanistic mathematical models with diverse datasets can move us closer to a complete, and remarkably simple, picture of naive CD4 and CD8 T cell dynamics in mice.

Quantifying the Causal Effect of Individual Mobility on Health Status in Urban Space

How does individual mobility in the urban environment impact their health status? Previous works have explored the correlation between human mobility behaviour and individual health, yet the study on the underlying causal effect is woefully inadequate. However, the correlation analysis can sometimes be bewildering because of the confounding effects. For example, older people visit park more often but have worse health status than younger people. The common associations with age will lead to a counter-intuitive negative correlation between park visits and health status. Obtaining causal effects from confounded observations remains a challenge. In this paper, we construct a causal framework based on propensity score matching on multi-level treatment to eliminate the bias brought by confounding effects and estimate the total treatment effects of mobility behaviours on health status. We demonstrate that the matching procedure approximates a de-confounded randomized experiment where confounding variables are balanced substantially. The analysis on the directions of estimated causal effects reveals that fewer neighbouring tobacco shops and frequent visits to sports facilities are related with higher risk in health status, which differs from their correlation directions. Physical mobility behaviours and environment features have more significant estimated effects on health status than contextual mobility behaviours. Moreover, we embed our causal analysis framework in health prediction models to filter out features with superficial correlation but insignificant effects that might lead to over-fitting. This strategy achieves better model robustness with more features filtered out than L1-regularization. Our findings shed light on individual healthy lifestyle and mobility-related health policymaking.

The Link Between Environment, Age, and Health in a Large Cohort of Companion Dogs from the Dog Aging Project

Exposure to social environmental adversity strongly predicts health and survival in many species such as non-human primates, wild mammals, and humans. However, little is known about how the health and mortality effects of these social determinants vary across the lifespan. Using the companion dog, which serves as a powerful comparative model for human health and aging due to our shared biology and environment, we examined which components of the social environment impact health, and how the effects vary with age, in dogs. We first drew on detailed survey data from owners of 27,547 dogs from the Dog Aging Project and identified six factors that together explained 35% of the variation in dog’s social environment. These factors all predicted measures of health, disease, and mobility, when controlling for dog age and weight. Factors capturing measures of financial and household adversity were linked to poorer companion dog health, while factors associated with the social companions, like dogs and adults, were linked to better health. Interestingly, some of these effects differed across a dog’s lifespan: for instance, the effect of neighborhood disadvantage on disease instances was strongest in older dogs. Together, our findings point to similar links between adversity and health in companion dogs, and set up future work on the molecular and biological changes associated with environmental variation in order to identify ways to mitigate or even reverse the negative environmental effects.

Evaluation of the environment impact of extraction of bioactive compounds from Darcyodes rostrata using Deep Eutectic Solvent (DES) using Life Cycle Assessment (LCA)

Polyphenols, the most abundant and naturally occurring antioxidants, was found to be the highest in Dacryodes rostrata seed as compared to the peel and pulp of the fruit. Growing technologies in the past decades have led to the interest of reviewing and developing environmental-friendly green extraction solvent, as the commonly used conventional solvent imposing various risks to human health and environment. An environmental-friendly extraction technique was established using deep eutectic solvent (DES) as the alternative extraction solvent has been considered. The main objective of this study was to analyse the environmental impact and performance of laboratory processes for phenolic compounds extraction from D. rostrata peel using different solvent, by means of life cycle assessment (LCA). A comparative analysis was carried out to evaluate the environmental impacts caused by both solvents, DES and conventional organic solvent, ethanol. The functional unit (FU) was defined as 104.6 mg of extracted polyphenols, measured as gallic acid equivalents (mg GAE)/g dw of D. rostrata seed used. The variation of environmental impacts between DES and ethanol as a function of optimum process conditions (temperature, time, solid/liquid ratio, and water addition) was evaluated. According to the environmental profile analyzed, the well-developed ethanol exerted lower impact and energy consumptions as compared to the environmental-friendly green solvent, DES. Besides, transport activities and electricity consumptions from the extraction process was identified contributing highest environment impact.

ENGINEERED NANO-MATERIALS FOR ENERGY AND THEIR POTENTIAL IMPACT ON ACTUAL ENVIRONMENTAL ISSUES

It is known for more than 2000 years that Damascus swords’ performances were not possible without the existence and usage of the “Damascus steel”, the first man made nano-hetero structural material that generalized is clearly showing that materials determine ultimate properties of the objects that made of. The actual world energy is manly based carbon emission materials, as coal, heavy oil, methane gas, with negative environment impact. Solar, wind and geothermal energy have also a negative impact on environment and have to be smartly used to minimize it. Nuclear energy, has lower CO2 emission, but because it is in its infancy it is complex, expensive and raises security and proliferation issues, has the potential for large scale accidents, and generates difficulties in dealing with waste fuel dispositioning.The novel developed families of engineered nano-materials, eliminate all the drawbacks of the actual nuclear power, rendering it among the most efficient and environmental friendly energy source. We learned from the global warming that the amount of energy man can produce on Earth is limited at 0.1% of sun delivered on Earth energy of 170 PW, which is of 200 TW, about 100 times more than today if it is chemical pollution free. Thermal pollution remains in place, therefore the upper clean power limit acceptable for the planet is at about 100 TW.The novel nuclear materials were developed in 6 families, each of them bringing in harmony a nuclear agent active inside that material as:- Micro-hetero structures, generally called “cer-Liq-Mesh”, that self-separates the fission products from the nuclear fuel and minimizes their fuel damage, allowing breed&burn to near perfect burning;- Nano-hetero structures generically called “CIci”, that form a super-capacitor, charged by nuclear energy and directly discharged as electricity;- Nano-clustered structure that enhances self-separation of transmutation products;- Fractal immiscible materials with radiation damage self-repairing capabilities eliminating the need for re-cladding in near perfect burning structures- Nano-structures with active NEMS used as fast control of nuclear reactivity by guiding neutrons in desired directions or ultralight shielding for mobile reactors.- Nano-structures that create active-quantum-nuclear-environment for long range nuclear reactions control by using quantum states entanglement and collective quantum states control.The use of these advanced materials in future nuclear energy related application will render a high efficiency, minimal nuclear waste, and optimal nuclear fuel cycle, delivering the needed planetary clean energy at will for the next 10,000 years.

Convection-permitting fully coupled WRF-Hydro ensemble simulations in high mountain environment: impact of boundary layer- and lateral flow parameterizations on land–atmosphere interactions

Numerical climate models have been upgraded by the improved description of terrestrial hydrological processes across different scales. The goal of this study is to explore the role of terrestrial hydrological processes on land–atmosphere interactions within the context of modeling uncertainties related to model physics parameterization. The models applied are the Weather Research and Forecasting (WRF) model and its coupled hydrological modeling system WRF-Hydro, which depicts the lateral terrestrial hydrological processes and further allows their feedback to the atmosphere. We conducted convection-permitting simulations (3 km) over the Heihe River Basin in Northwest China for the period 2008–2010, and particularly focused on its upper reach area of complex high mountains. In order to account for the modeling uncertainties associated with model physics parameterization, an ensemble of simulations is generated by varying the planetary boundary layer (PBL) schemes. We embedded the fully three-dimensional atmospheric water tagging method in both WRF and WRF-Hydro for quantifying the strength of land–atmosphere interactions. The impact of PBL parameterization on land–atmosphere interactions is evaluated through its direct effect on vertical mixing. Results suggest that enabled lateral terrestrial flow in WRF-Hydro distinctly increases soil moisture and evapotranspiration near the surface in the high mountains, thereby modifies the atmospheric condition regardless of the applied PBL scheme. The local precipitation recycling ratio in the study area increases from 1.52 to 1.9% due to the description of lateral terrestrial flow, and such positive feedback processes are irrespective of the modeling variability caused by PBL parameterizations. This study highlights the non-negligible contribution of lateral terrestrial flow to local precipitation recycling, indicating the potential of the fully coupled modeling in land–atmosphere interactions research.

Hydrothermal Regime Variation and Ecological Effects on Fish Reproduction in the Yangtze River

Water temperature, as one of the important water environment impact factors, has a significant impact on the survival and development of aquatic organisms. We selected water temperature data (1959–2017) from four key hydrological stations in the Yangtze River: Cuntan, Yichang, Hankou, and Datong. We analyzed the characteristics and variability of the Yangtze River hydrothermal regime by the Mann-Kendall method, wavelet analysis, and by the IHA-RVA method to analyze hydrothermal regime variations of the Yangtze River, and the response mechanisms of fish to variations in hydrothermal regimes were explored. The results show that (1) The annual average water temperature of the Yangtze River is warming, and Cuntan Station, Yichang Station, Hankou Station, and Datong Station have a sudden increase in temperature in 2002, 1995, 2003, and 2004, and the periodicity analysis demonstrates that Cuntan, Yichang, and Datong stations all have main periods of 24~32 years; (2) The overall variations of 32 hydrothermal indicators at Cuntan Station and Yichang Station reached 65% and 61%, which are close to the height variation; (3) With the construction of the Three Gorges Dam, the stagnant cooling effect caused the arrival date of the upper reproduction water temperature of “The four major fish species” to be delayed by about 23 days, and the stagnant heat effect caused the arrival date of the Chinese sturgeon reproduction upper limit water temperature to be delayed by about 30 days.