26800 research outputs found
Sort by
RENEWABLE ENERGY’S IMPACT ON ECONOMIC GROWTH: THE ROLE OF INSTITUTIONS – A CASE STUDY FROM AFRICA
Full text linkThis study investigates the impact of renewable energy consumption (REC) on African economy, and particularly the moderating effect of institutional quality. Since the world remains concerned with sustainability and its heavy reliance on fossil fuels, it is relevant to determine the economic impacts of REC. Using Driscoll-Kraay Fixed Effects Standard Estimate (DKSE) on a panel data of 49 African countries from 1974 to 2023, the findings indicate that there is a statistically significant low negative correlation between REC and economic growth, suggesting that higher dependence on renewable energy tends to be associated with slower economic performance in Africa based on the data. This does not mean Africans must reduce REC to improve their economy but to encourage them increase energy infrastructure. The moderating effect of institutional quality determinants which include control of corruption, regulatory quality, and rule of law is nevertheless important. Nations with better institutions tend to have higher economic returns on investment in renewable energy, while the nations with weaker institutions have inefficiencies and bottlenecks towards effective implementation. The study emphasizes policy intervention not just to render the use of renewable energy convenient, but also to enhance institutions of governance to gain economic benefits to the extent possible. The findings have long- term policy implications for policymakers, investors, and development agencies that are keen on maintaining sustainable economic development in Africa
Study on the Effect of Equal Volume Filled Copper Foam on Radiator Temperature
No full textAbstract: In this study, copper foam with varying filling rates (porosity of 95% and pore density of 20 ppi) was combined with paraffin wax and integrated into a heat sink to investigate temperature fluctuations within the heat sink after charging and discharging of copper foam phase change materials (PCM) and an empty heat sink with varying filling rates. The study focused on three key PCMs: RT-42HC, RT-50HC, and RT-60HC. The PCMs had copper foam filling ratios of,, and, with three heating loads (0.9 kW/m2, 1.8 kW/m2, and 2.7 kW/m2). The data suggest that after 90 minutes of charging, RT-42HC () can decrease the baseline temperature by 20.29% at 0.9 kW/m2 and a maximum of 35.49% with a foam filling ratio of. Under a heating load of 2.7 kW/m2, RT-50HC () can reduce the baseline temperature by up to 35.49%. At the same load, RT-50HC () can reduce the reference temperature by 32.45%.RT-42HC () has a maximum enhancement ratio of 4.38 at SPT = 50° and a heating load of 18 W, whereas RT-50HC () has a maximum enhancement ratio of 4.3 at SPT=60° and a load of 27 W. In the cycle test with an 18 W heating load, RT-42HC () had the most favorable influence, lowering the reference temperature by a maximum of 21.94%
Direct water reuse: a hydraulic economic analysis of connecting the wastewater treatment effluent to water treatment influent
Full text linkClimate change is causing increased flooding and droughts. Droughts can cause drinking water sources to run dry. Therefore, recycling water from the wastewater plant effluent to the water treatment plant influent, also called ‘direct reuse’ is becoming necessary. A connection between a city\u27s wastewater treatment plant (WWTP) effluent and water treatment plant (WTP) influent via pipe was simulated to provide an understanding of the capital costs and feasibility of execution. Hydraulic pipe-flow and pump equations were used to calculate the pipe and pump sizes needed for various flow rate and elevation head values. Various flow rate recycle rates were modeled by taking the WWTP effluent flow and in percentages ranging from 5 to 100% to estimate the pipe and pump requirements to send that amount to the WTP influent, including greenhouse gas emissions from pumping. The costs of installation were then determined using current market values for parts and trenching. Data analysis showed that the cost of this project is driven by the pump size requirements
Great Lakes Wave Height Trends
Full text linkWith the advent of the industrial revolution, greenhouse gases have been emitted into the atmosphere causing the alteration of weather across the globe. These gases have caused the global temperature to warm. This has also caused a change in precipitation, wind speeds, and wave heights. The Great Lakes have many cities located on their shores and millions of people are affected by waves. Effects include shoreline erosion, infrastructure damage, and loss of valuable property and lives. It is imperative to future planning and engineering that the trends of wave height are understood. This study uses linear regression, a well-known and easily understood method, to analyze all the Great Lakes’ wave heights, moving average, moving standard deviation, and 100-year recurrence value. Nineteen wave buoys were selected for analysis, encompassing all the Great Lakes. It was found that some locations have increasing wave height trends while other locations have decreasing trends. Five stations had positive trends for both storm magnitude and standard deviation. Five stations had one positive and one negative trend. Nine stations had decreasing storm average and standard deviations. The 100-year wave height value is also increasing at 11 stations and decreasing at 8 stations. This goes to show that waves are changing, but in different ways for different station locations. Planners can use this information to plan future erosion and infrastructure activities and budgets
Development of a Noninvasive Genotyping-In-Thousands (GTseq) Panel for Long-Term Conservation of Western Great Lakes Gray Wolves (Canis lupus)
Full text linkThe application of noninvasive genetic methods toward the field of conservation has increased our understanding of many wildlife populations that are difficult to sample, allowing for better management. In molecular ecology, the use of noninvasive sampling became widely feasible with the advent of microsatellites, a highly polymorphic, short-length marker that could be genotyped from low-quality DNA sources. Despite decades of use, many microsatellite panels continue to suffer from high genotyping error rates, allelic dropout, and limited reproducibility across laboratories. To address these issues, single nucleotide polymorphisms (SNPs) offer advantages such as lower genotyping error rates, avoidance of allelic dropout due to consistent allele length, and automated calling through bioinformatic pipelines, reducing human subjectivity and error. Given the advantages SNPs provide relative to microsatellites as a molecular marker, the use of SNP panels and specifically, the method of genotyping-in-thousands by sequencing (GTseq) has gained popularity. Here, we developed a GTseq panel for western Great Lakes canids comprised of 196 loci, capable of species identification, accurately inferring sex (97.2%), identifying unique individuals (probability of identity = 6.71e), assigning relationships (false positive rate = 9.34e), and assigning genotypes with low error (0.39%). In an attempt to improve genotyping success with low-quality samples, we found that while increasing the number of PCR cycles yielded a higher percentage of genotyped loci, it also increased on-target reads in negative PCR controls. We suggest approaching this manipulation with caution and emphasize the importance of including and reporting negative PCR controls. Further, quantitative PCR was a powerful method to estimate host-specific DNA concentrations, enabling conservative sample selection for library preparation with respect to GTseq affordability
Brain-Targeted Reactive Oxygen Species in Hypertension: Unveiling Subcellular Dynamics, Immune Cross-Talk, and Novel Therapeutic Pathways
Full text linkHypertension (HTN) is a complex disease with significant global health implications, driven by neural and oxidative mechanisms. Reactive oxygen species (ROS), once considered mere metabolic byproducts, are now recognized as one of the key contributors to dysfunction of the autonomic nerve system, which involves the onset and progression of HTN. This review highlights the dynamic roles of ROS in neuronal signaling, subcellular compartmentalization, and brain-immune interactions, focusing on their impacts on synaptic remodeling, neuroinflammation, and epigenetic modifications within key autonomic regions such as the paraventricular nucleus and rostral ventrolateral medulla. We discuss novel ROS sources, including microglia-derived and endoplasmic reticulum stress-related ROS, and their contributions to HTN. Subcellular dynamics, such as ROS signaling at mitochondria-associated membranes and neuronal microdomains, are explored as activators of the sympathetic nerve system. Emerging evidence has linked ROS to epigenetic regulation, including histone modifications and non-coding RNA expression, with sex-specific differences offering insights for the development of personalized therapies. Innovative therapeutic strategies targeting ROS involve precision delivery systems, subcellular modulators, and circadian-optimized antioxidants. We propose several priorities for future research, including the real-time imaging of brain ROS, translating preclinical findings into clinical applications, and leveraging precision medicine to develop tailored interventions based on ROS activity and genetic predisposition. Through emphasizing the spatial and temporal complexity of ROS in HTN, this review identifies novel therapeutic opportunities and establishes a foundation for targeted treatments to address this health challenge
Optimizing Source Apportionment of OVOCs With Machine Learning-Enhanced Photochemical Models
No full textThe photochemical age parameterization model is widely used to analyze primary and secondary sources of oxygenated volatile organic compounds (OVOCs). However, a key challenge lies in selecting appropriate tracers chemicals used to estimate contributions from different emission sources. Accurate tracer selection is crucial for improving source apportionment accuracy, yet it is often constrained by local emission inventories and may not fully capture rapid atmospheric chemical transformations introducing uncertainty in OVOC apportionment. This study presents a novel approach integrating eight different machine learning methods to identify optimal tracers for OVOCs during extreme summer temperatures (experimental group) and average spring temperatures (control group). Our results demonstrated notable differences in tracer effectiveness between these two groups. In the spring, toluene and carbon monoxide (CO) were identified as the most effective tracers for OVOCs with high and low reactivity, respectively. In the summer, acetylene or CO were better suited for moderate and low reactivity OVOCs. By incorporating machine learning for tracer selection, we significantly improved the accuracy of the photochemical age parameterization model. The machine learning outputs correlated well with the model\u27s performance particularly in terms of fitting accuracy of OVOCs. However, extremely high temperatures during summer disrupted the usual patterns of OVOC production and removal, which led to inconsistencies in matching high reactivity OVOCs with their tracers. Future research involves collecting more data on OVOC behavior under high-temperature conditions and applying Fourier transformation techniques. This will help in identifying characteristic patterns and improving the dynamic accuracy of our model
COMMUNITY DIVERSITY AND MAKEUP AFFECT THE CAPACITY FOR BIOCONVERSION OF CHEMICALLY DECONSTRUCTED PET PLASTIC WASTE INTO BIOMASS
Full text linkPlastic waste management is an issue worldwide, particularly for locations with challenging logistics, such as remote locations, those impacted by natural disasters, and regions with armed conflict. These locations also struggle with food logistics and malnutrition. It is possible to tackle both issues by combining chemical deconstruction to depolymerize plastic waste with microbial conversion of the liquid product into biomass that can be used as an edible protein powder. The focus of this work is on the bioconversion of products from the chemical deconstruction of polyethylene terephthalate (PET) using ammonium hydroxide. Microbial communities have previously been shown to utilize the various products generated from the chemical deconstruction of PET (terephthalic acid (TPA), TPA monoamide, terephthalamide, and ethylene glycol). Bioreactors allow for large-scale continuous production of biomass, however, there are challenges to this process. First, the formation of biofilms causes issues during processing. This work demonstrates that increased airflow and increased agitation speed can reduce biofilm formation, however, there is a negative impact on biomass production when the shear stresses are too strong. Using microbial communities of lower diversity can also reduce biofilm formation. The second problem to address is how the different products from the chemical deconstruction of PET affect microbial growth. Using Monod kinetics to estimate parameters to characterize growth on various substrates, it was determined that for Rhodococcus sp. TE21C, terephthalic acid becomes inhibitory to growth as the concentration increases, while Paracoccus sp. RL32C was not able to utilize terephthalic acid as a substrate. Ethylene glycol was shown to not be inhibitory to both organisms at the concentrations evaluated. Using both substrates simultaneously in a mixture showed no effect on substrate interactions on growth of either organism. The final problem addressed here is how temperature perturbations affect biomass productivity. In locations where utilities can be easily disrupted or are restricted, keeping the temperature controlled may be difficult or impossible and variability in bioreactor temperature is expected to impact biomass production. This work shows that by using communities of higher diversity, the system is more stable and better able to recover in the middle of a long-term temperature perturbation
Turn-on fluorescent glucose transport bioprobe enables wash-free real-time monitoring of glucose uptake activity in live cells and small organisms
Full text linkThe direct link between sugar uptake and metabolic diseases highlights the iminent need for molecular tools to detect and evaluate alterations in sugar uptake efficiency as approaches to identify disease-relevant metabolic alterations. However, the strict requirements of facilitative glucose transporters regarding substrate binding and translocation pose challenges for developing effective fluorescence molecular probes. Based on the state-of-the-art understanding of glucose recognition by facilitative transporters (GLUTs), we designed a glucopyranoside mimic - GluRho - that delivers the “turn-on” rhodamine B to live cells via glucose transport, including major transporters GLUTs 1-4. The high binding affinity achieved through the secondary interaction between the fluorophore and a GLUT protein supports the delivery of the probe in nutrient-rich conditions, facilitating its use as a tool for a direct assessment of glucose GLUT activity in live cells and organisms and across various experimental settings, including uptake evaluation in the presence of sugars or GLUT activity modulators. The lack of metabolic contribution to the probe uptake due to the elimination of the phosphorylation site contributes to the high efficacy of the GluRho probe in reflecting alterations in glucose uptake efficiency in live cells, between cell lines, and in multicellular model organisms, such as Drosophila melanogaster. The molecular modeling analysis of GluRho complexes with GLUT1 and GLUT2 provided essential information on GLUT-probe interactions, highlighting the residues facilitating the effective binding and translocation of the probe through transporters, thus setting the basis for developing glucose-based glycoconjugates as a cargo-delivering platform
Topography and mineralogy of clay deposits signify an epoch of warm and humid climate on early Mars
No full textLittle is known about the surface of Earth for the first billion years of its history, because subaerial deposits of this age are very poorly preserved in the geologic record. Such deposits could answer important questions about the atmosphere, climate, and emergence of life on primordial terrestrial planets. In contrast, the ancient crust of Mars is far better preserved and has undergone minimal deformation. Outcrops of \u3e3.6 Ga clay sequences where aluminous clay minerals overlie iron/magnesium smectite have been interpreted as evidence for warm and habitable surface environments early in Martian history. Two main hypotheses for the origin of these clay sequences have been proposed: subaerial formation through pedogenic leaching, or subaqueous formation via detrital deposition and/or alteration. The topographic properties of these clay deposits could be used to test between these two hypotheses. However, the few previous topographic analyses were restricted to a handful of sites and usually only measured vertical thickness, which fails to account for strike/dip of geologic layers. Here, we report true thicknesses of clay stratigraphies at 46 outcrops globally, extract vertical profiles of clay mineralogy from orbital reflectance spectra at 14 areas, and investigate the relationship with antecedent topography at Mawrth Vallis. We find strong support for the pedogenic leaching model, especially for the upper aluminous portion. The very high total true thickness of these weathering profiles (global mean 59 m), rivaled only by temperate-tropical analogs on Earth, suggests intense aqueous leaching under ∼0.2–8 m.y. of warm and humid conditions or a longer period of oscillating climates. Our findings add to a growing body of evidence that early Mars experienced epochs of prolonged habitable surface environments conducive to microbial life