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The armored scale insect Hemiberlesia lataniae (Signoret, 1869) (Hemiptera: Diaspididae) is reported for the first time in Central Brazil infesting Bauhinia x blakeana (Fabaceae) trees. Infestations of this armored scale insect were observed on the leaves of four trees located in the urban perimeter of Alto Paraíso de Goiás, Goiás. This work reinforces the polyphagous nature of the species, expanding its geographic distribution in Brazil and increasing the number of known hosts.

Recent research shows that the Cerrado has a great diversity of scale insects (Insecta: Hemiptera: Coccomorpha) in association with native plants. This work aimed to report the occurrence of Acutaspis oliveirai (Lepage & Giannotti, 1942) (Hemiptera: Diaspididae) found for the first time in Central Brazil and in plants of Myrsine guianensis (Primulaceae), a common species in the Brazilian Cerrado, that has potential for use in landscaping and the recovery of degraded areas. This is the first report of the occurrence of A. oliveirai in a native plant of the Cerrado biome and in the Central Brazil. Acutaspis oliveirai individuals were found on the leaf surface of M. guianensis leaves in two locations in the Federal District, Brazil, causing irregular yellowing and chlorotic spots throughout the leaf blade.

Universal access to electricity is beneficial for the socio-economic development of a country and the development of smart communities. Unfortunately, the electrification of remote off-grid areas, especially in developing countries, is rather slow due to geographic and economic barriers. In the Philippines, specifically, many electrified off-grid areas are underserved, with access to electricity being limited to only a few hours a day. This is mainly due to the high dependence on diesel power plants (DPPs) for electrifying these areas. To address these problems, hybrid renewable energy systems (HRESs) have been considered good electrification alternatives and have been extensively studied for their techno-economic and financial feasibility for Philippine off-grid islands. In this work, articles published from 2012 to 2023 focusing on off-grid Philippine rural electrification were reviewed and classified based on their topic. The taxonomical analysis of collected studies shows that there is a saturation of works focusing on the technical and economic aspects of off-grid electrification. Meanwhile, studies focusing on environmental and socio-political factors affecting HRES off-grid electrification are lagging. A bibliographic analysis of the reviewed articles also showed that there is still a lack of a holistic approach in studying off-grid electrification in the Philippines. There are only a few works that extend beyond the typical techno-economic study. Research works focusing on environmental and socio-political factors are also mainly isolated and do not cross over with technical papers. The gap between topic clusters should be addressed in future works on off-grid electrification.

Abstract Plants that produce allelopathic compounds against weeds have emerged as a potential solution for the development of ecologically correct bioherbicides. Talinum triangulare is noteworthy in this regard, as its phytochemical composition encompasses flavonoids, alkaloids and other metabolites that can be used to develop inhibitory weed growth solutions. Lactuca sativa (lettuce) has been widely applied as a bioindicator species for bioherbicides and several chemicals, animal waste, water and soil quality, and atmospheric contamination, among others. In this context, this study aimed to assess the potential allelopathic effect of aqueous T. triangulare extracts on the development of L. sativa seedlings. A completely randomized design employing a 2x4 factorial scheme (shoot and root extracts) x the concentration of each extract (0, 2.5, 5, 7.5%) was applied, comprising four replications. Lactuca sativa seeds were sown on germitest papers soaked with the extracts in a germination chamber at 20°C. Physiological seed evaluations comprising the germination test, where normal and abnormal seedlings are counted on the seventh day after sowing, first normal seedling counts on the fourth day after sowing, and seedling and root length measurements. At the end of the germination test, L. sativa seedlings were separated for morphoanatomical characterizations and chlorophyll a fluorescence analyses. The T. triangulare extracts significantly influenced L. sativa root growth, with shoot extract exposure leading to more abnormal plants and lower root lengths at increasing concentrations and compared to the root extract. Root extract exposure led to evident cellular changes and lower non-photochemical quenching and unregulated dissipation quantum yields at a 5% exposure dose compared to shoot extract exposure. These findings suggest that both aqueous T. triangulare root and shoot extracts from 5% exposure doses exhibit high potential as bioherbicides, acting directly on plant structure, anatomy, quality, size and physiology.

Microgrids have emerged as a crucial focus in power engineering and sustainable energy research, with utility-scale microgrids playing a significant role in both developed and developing countries like the Philippines. This study presents a comprehensive framework for utility-scale microgrid planning, emphasizing the sustainable integration of renewable energy resources to the distribution grid. The framework addresses the operational modes of grid-connected and islanded microgrids, emphasizing the seamless transition between these modes to ensure a continuous power supply. By leveraging local distributed energy resources, the microgrid aims to reduce dependence on the main transmission grid while enhancing resilience and reliability. The proposed planning framework not only eases the economic burden of constructing renewable energy sources but also aids distribution utilities in maximizing local resources to achieve sustainable energy goals. Through a detailed network analysis and modeling, the framework provides a robust foundation for optimizing the energy mix and enhancing the overall system performance. This research contributes to advancing microgrid technology as a key driver towards achieving UN Sustainable Development Goals, particularly in promoting clean and affordable energy access.

Hybrid renewable energy systems have garnered considerable attention as sustainable power sources for remote off-grid islands in the Philippines. Consequently, they have been the subject of numerous techno-economic investigations. However, comprehensive explorations into the viability of 100 % renewable energy (RE) systems for these areas have been limited due to their exorbitant initial outlays. In this work, we modelled the prospective transition of off-grid island mini-grids in the Philippines from the contemporary status quo in 2020 to a fully integrated 100 % RE system by 2050. Our approach involves the gradual shift towards RE adoption instead of the abrupt deployment of RE systems. This maneuver serves a twofold purpose: firstly, it mitigates the adverse economic repercussions stemming from the substantial upfront costs inherent to RE technologies; secondly, it leverages the declining future costs of these technologies. We collected an energy generation and consumption dataset across 208 mini-grids in Philippine off-grid islands. We then simulate the RE transition based on prevailing technology costs at five-year intervals from 2020 to 2050. Afterwards, different scenarios that may affect the energy transition are simulated. Our results indicate that an energy transition steered solely by market dynamics cannot achieve a 100 % RE penetration; hence, we analysed alternative scenarios promoting RE utilization. The immediate discontinuation of all diesel generators by 2050 will lead to a substantial cost uptick at the end of the transition. Integrating biodiesel yields a more measured progression of costs, although this relies upon a nascent market, rendering it susceptible to feedstock supply risks. Recognizing the intermittent nature of RE technologies, we posit that allowing for a certain degree of unmet load fosters greater RE penetration. Nevertheless, this approach compromises the reliability of the system. Our work demonstrates that a 100 % RE transition in Philippine off-grid islands is technically and economically feasible. However, the energy trilemma or the tradeoff between affordability, reliability, and sustainability encumbers the realization of this transition.

Abstract Immunization with the Amastigote Surface Protein-2 (ASP-2) and Trans-sialidase (TS) antigens either in the form of recombinant protein, encoded in plasmids or human adenovirus 5 (hAd5) confers robust protection against various lineages of Trypanosoma cruzi. Herein we generated a chimeric protein containing the most immunogenic regions for T and B cells from TS and ASP-2 (TRASP) and evaluated its immunogenicity in comparison with our standard protocol of heterologous prime-boost using plasmids and hAd5. Mice immunized with TRASP protein associated to Poly-ICLC (Hiltonol) were highly resistant to challenge with T. cruzi, showing a large decrease in tissue parasitism, parasitemia and no lethality. This protection lasted for at least 3 months after the last boost of immunization, being equivalent to the protection induced by DNA/hAd5 protocol. TRASP induced high levels of T. cruzi-specific antibodies and IFNγ-producing T cells and protection was primarily mediated by CD8+ T cells and IFN-γ. We also evaluated the toxicity, immunogenicity, and efficacy of TRASP and DNA/hAd5 formulations in dogs. Mild collateral effects were detected at the site of vaccine inoculation. While the chimeric protein associated with Poly-ICLC induced high levels of antibodies and CD4+ T cell responses, the DNA/hAd5 induced no antibodies, but a strong CD8+ T cell response. Immunization with either vaccine protected dogs against challenge with T. cruzi. Despite the similar efficacy, we conclude that moving ahead with TRASP together with Hiltonol is advantageous over the DNA/hAd5 vaccine due to pre-existing immunity to the adenovirus vector, as well as the cost-benefit for development and large-scale production.

Hybrid renewable energy systems (HRES) have emerged as a promising solution for delivering sustainable energy to off-grid communities. However, the vulnerability of specific regions to extreme weather events has raised concerns about the resilience of these systems. This study undertakes a techno-economic analysis to assess the impact and significance of incorporating storm hardening measures and insurance into an HRES designed for the Busuanga island cluster. Central to our study is introducing a novel cost metric, the probability-averaged levelized cost of electricity (LCOE), which adeptly captures the inherently probabilistic nature of climate-induced damages to HRES energy assets. This metric serves as the linchpin for comparing the economic viability of HRES configurations, considering both scenarios with and without storm hardening or insurance. Our findings unveil a clear trend: for a solar photovoltaic (PV) panel with an annual probability of damage at 1%, insurance emerges as a financially prudent choice, while storm hardening gains merit at a probability of 4%. The weighted average cost of capital (WACC) is pivotal in shaping investment decisions. HRES setups featuring non-hardened solar PV panels become more economically appealing than their insured or hardened counterparts under higher WACC conditions, under the condition that the solar PV panels can maintain functionality for 15 years without impairment. Our study demonstrates the importance of accounting for often overlooked factors such as storm hardening and insurance premiums for solar PV panels in climate-vulnerable areas, which are commonly disregarded in many techno-economic studies. Moreover, our findings and conclusions on the optimal balance between capital costs, insurance premiums, and storm-hardening markups can readily extend to other climate-vulnerable areas.

As climate change is slowly materialising, the importance of alternative fuels has been magnified to aid in reducing carbon emissions. One of the most promising clean alternative fuels is green hydrogen which is produced via water electrolysis powered by renewable energy sources. The solar and wind power potential of the Philippines has been explored in published studies; however, the economic viability of green hydrogen production has not yet been evaluated. In this work, an assessment of the levelized cost of hydrogen (LCOH) produced from solar and wind power in the Philippines was performed. Representative locations within a province were selected based on the annual average resource availability for solar global horizontal irradiance (GHI) and wind speed. LCOH calculations identified the favourable locations for green H2 production by calculating the net present cost (NPC) of solar- and wind-powered electrolysis plants with deionised water as feedstock. Uncertainty analysis was performed via Monte Carlo simulations by perturbing component costs, feedstock water price, and discount rate. Additionally, LCOH calculations and Monte Carlo simulations showed the disparity of resource availability between solar and wind in the Philippines – supported by the calculated capacity factors. It was also shown that favourable conditions such as high solar GHI and high wind speed tend to have a narrower distribution and lower LCOH values – implying less economic risks in developing over these locations. Calculations identified that policy instruments such as subsidies and tax exemptions are still vital in commissioning green hydrogen plants, as LCOH values are generally higher than the cost of grey hydrogen.

With the growing popularity of electric vehicles, longer lasting batteries are necessary for better mileage. Battery chemistries with larger energy densities compared to Lithium-Ion Batteries (LIB) need to be developed. Lithium-Sulfur Battery (LSB) is a good alternative due to its high theoretical and practical energy densities. However, commercialization of LSBs has yet to be realized due to shorter lifetimes caused by non-ideal battery processes such as polysulfide shuttling. Through multiphysics modeling, the effects of shuttling can be observed. Additionally, cost analysis can determine the feasibility of LSBs for mass production and its competitiveness against LIBs. In this work, energy density optimization and LSB cost estimation were done using combined multiphysics modeling and cost modeling approaches. Using COMSOL Multiphysics®, the energy densities of the batteries with and without shuttling were optimized by changing the thickness and porosity of the cathode and separator. Then, a bottom-up cost analysis of the optimized battery cell was conducted using the BatPaC model. It was observed that shuttling leads to a lower optimized energy density. To compensate for the shuttling-induced capacity loss, the model’s optimized battery dimensions had a separator porosity increase by 22.08 % and a cathode thickness and porosity decrease by 23.72 % and 16.21 %. Additionally, shuttling increases battery material costs by 13.35 % because of the larger and more expensive current collectors must compensate for the size of the smaller electrodes. Future works may explore various C-rates and use cases to identify optimal battery parameters for each.

In regions heavily affected by recurrent typhoons, the need for more resilient electricity infrastructure is pressing. This emphasizes the importance of integrating resilience assessment, including incorporating resilience metrics, into the planning process of power distribution systems against any disruptive events. Although standardized metrics exist for assessing distribution system reliability, the absence of formalized resilience metrics hampers informed investments in critical infrastructure such as microgrid development. In this work, a set of resilience metrics is proposed by reconceptualizing reliability metrics. The metrics were formulated to account for both the type of extreme event and its specific impact on loads with varying levels of criticality. The effectiveness of the proposed metrics is demonstrated through a Philippine microgrid case study. A Monte Carlo framework incorporating an extreme event model, component fragility model, and system response model was used to quantify the resilience improvement before and after stand-alone microgrid operation of the power distribution system. Results show that the proposed metrics can effectively evaluate resilience enhancement and highlight the value of a holistic approach of considering critical loads and types of extreme events to strengthen societal and community resilience, making a compelling case for strategic investments in infrastructure upgrades such as microgrids.

Protection against SARS-CoV-2 infection involves T cell and B cell responses but only studying one or the other has proved difficult. Here the authors immunise with a fusion protein construct of N and RBD proteins from SARS-CoV-2 and find that this promotes protection in animal models preferentially via T cells.

Abstract Introduction Radio telemetry, one of the most widely used techniques for tracking wildlife and fisheries populations, has a false-positive problem. Bias from false-positive detections can affect many important derived metrics, such as home range estimation, site occupation, survival, and migration timing. False-positive removal processes have relied upon simple filters and personal opinion. To overcome these shortcomings, we have developed MAST (Movement Analysis Software for Telemetry data) to assist with false-positive identification, removal, and data management for large-scale radio telemetry projects. Methods MAST uses a naïve Bayes classifier to identify and remove false-positive detections from radio telemetry data. The semi-supervised classifier uses spurious detections from unknown tags and study tags as training data. We tested MAST on four scenarios: wide-band receiver with a single Yagi antenna, wide-band receiver that switched between two Yagi antennas, wide-band receiver with a single dipole antenna, and single-band receiver that switched between five frequencies. MAST has a built in a k-fold cross-validation and assesses model quality with sensitivity, specificity, positive and negative predictive value, false-positive rate, and precision-recall area under the curve. MAST also assesses concordance with a traditional consecutive detection filter using Cohen’s $$\kappa$$ κ . Results Overall MAST performed equally well in all scenarios and was able to discriminate between known false-positive detections and valid study tag detections with low false-positive rates (

This data article contains the location, energy consumption, renewable energy potential, techno-economics, and profitability of hybrid renewable energy systems (HRES) in 634 Philippine off-grid islands. The HRES under consideration consists of solar photovoltaics, wind turbines, lithium-ion batteries, and diesel generators. The islands were identified from Google Maps™, Bing Maps™, and the study of Meschede and Ocon et al. (2019) [1]. The peak loads of these islands were acquired from National Power Corporation – Small Power Utilities Group (NPC-SPUG), if available, or estimated from the island population otherwise. Hourly-resolution load profiles were synthesized using the normalized profiles reported by Bertheau and Blechinger (2018) [2]. Existing diesel generators in the islands were compiled from reports by NPC-SPUG, while monthly average global horizontal irradiance and wind speeds were taken from the Phil-LIDAR 2 database. Islands that are electrically interconnected were lumped into one microgrid, so the 634 islands were grouped into 616 microgrids. The HRES were optimized using Island System LCOEmin Algorithm (ISLA), our in-house energy systems modeling tool, which sized the energy components to minimize the net present cost. The component sizes and corresponding techno-economic metrics of the optimized HRES in each microgrid are included in the dataset. In addition, the net present value, internal rate of return, payback period, and subsidy requirements of the microgrid are reported at five different electricity rates. This data is valuable for researchers, policymakers, and stakeholders who are working to provide sustainable energy access to off-grid communities. A comprehensive analysis of the data can be found in our article “Techno-economic and Financial Analyses of Hybrid Renewable Energy System Microgrids in 634 Philippine Off-grid Islands: Policy Implications on Public Subsidies and Private Investments” [3].

Accurately estimating the capacity degradation of lithium-ion (Li-ion) batteries is vital in ensuring their safety and reliability in electric vehicles and portable electronics. Future capacity estimation using machine learning (ML) models allow battery lifetime predictions with minimal cycling data in the train set, well before capacity degradation occurs within the cell. The use of ML methods removes the need for prior knowledge of cell chemistry and the physical and chemical behaviors of batteries. In this paper, the data-driven ML models Gaussian process regression (GPR) and recurrent neural network – long short-term memory (RNN-LSTM) estimated the charge capacity of Li-ion batteries from the Oxford Battery Dataset, using only the battery's cycle index and capacity as input. With only 15 % of the battery’s lifetime as training data, the GPR model achieved a mean average percent error (MAPE) of 8.335 % and an R2 of 0.9755, while the LSTM model achieved a MAPE of 9.984 % and an R2 of 0.9898. These results indicate the goodness of fit and are comparable to results from similar models in the literature (MAPE = 9.1 to 15 %). The methodology may be applied to different features to help establish the relationship between health indicators and capacity fade and can be used in applications that require early capacity prediction such as in space technologies where lifetime and capacity are crucial in ensuring success and safety. This successful estimation highlights the promise and potential of accurately predicting Li-ion battery capacity degradation using a single-feature approach.

The global transition towards net-zero greenhouse gas emissions establishes a need for cleaner energy technologies. Hydrogen is a promising energy carrier whose global demand is steadily increasing and is conventionally produced through steam-methane reforming with carbon capture, or blue H2. Hydrogen production supplied by renewable energy (green H2) is an emerging process, but developing countries are not yet ready for a full transition. Augmenting blue H2 with green H2 production will allow a smoother transition until green H2 costs significantly decrease by 2050. In this work, a novel, low-cost teal hydrogen (teal H2) plant, a mixture of blue and green H2 technologies, located in the Philippines which combines steam-methane reforming, rice husk gasification, and carbon capture by monoethanolamine absorption, is proposed. Setting a production rate of 9,000 kg H2/h, the techno-economic potential of five cases with varying natural gas to rice husk contribution ratios were evaluated using AspenPlus. The levelized cost of the 25:75 teal H2 case at 1.06 USD/kg is cheaper than blue H2 and green H2 by 4.37 and 2.34 USD/kg, respectively. Moreover, the CO2-equivalent emissions of the 25:75 teal H2 case at 0.002 t CO2 -eq/1,000 Nm3 H2 is 57.10 % and 39.25 % lower than those from blue H2 and green H2. As green H2 becomes more economical, rice husk feed to the gasification process can be gradually increased to favor biomass- over petroleum-derived H2. This case study is a successful proof of concept that teal H2 may help transition the energy sector to carbon neutrality.

In this work, we propose an immersion corrosion measurement method with E10 bioethanol-gasoline blend on austenitic steel (SS304) and aluminum (Al6061). Immersion tests were designed to simulate a weekly refuel cycle and were performed over 4, 8, and 12-week durations. Polarization resistance, surface morphology, and corrosion products were then observed after the immersion tests. Corrosion rates were estimated from polarization resistance measurements via electrochemical impedance spectroscopy. Afterwards, the surface morphology of exposed samples was studied using scanning electron microscopy. Lastly, the corrosion products were characterized using scanning electron microscopy with energy dispersive X-ray analysis. Surface staining was observed in both metal substrates. It was observed that the corrosion rate of SS304 remained relatively constant throughout the immersion time. In contrast, an increment in the corrosion rate of Al6061 was observed after four weeks of immersion due to the peeling of the protective oxide layer.

Different energy storage technologies have particular applications with advantageous techno-economic characteristics. For this reason, the present and future Levelised Costs Of Storage (LCOS) of commercially mature energy storage technologies have been analysed in the current literature. Emerging energy storage technologies, such as long-duration flywheels, are also vying to capture the energy storage market, but uncertainties linger as to which applications they can capture due to limited and reliable publicly available data. In this work, we determined the future LCOS of a typical 1 MW installation of stationary electrochemical energy storage (lead-acid, sodium-sulphur, and lithium-ion battery) and mechanical energy storage technologies (short-duration flywheel and long-duration flywheel) under different applications from 2020 to 2050 using updated relevant techno-economic parameters. Based on the present costs of energy storage, lithium-ion batteries yield the lowest LCOE across different energy storage applications, corroborating with previous outlooks from different scholarly works. The cost advantage of lithium-ion batteries compared to other storage technologies continues to rise over the years due to their rapid cost decline. In the absence of lithium-ion batteries, long-duration flywheels initially provide the lowest cost for a wide range of applications, but they face stiff competition with sodium-sulphur batteries. By 2040, sodium-sulphur batteries are projected to have a lower LCOS than long-duration flywheels. Promoters and manufacturers of emerging energy storage technologies must find ways to rapidly decrease storage costs to secure their niche in the energy storage market.

With the rising energy demand, safe and efficient energy storage technologies have been increasing in importance. Lithium Polymer (LiPo) batteries use a gel polymer to act as both separator and electrolyte, which is thermally and electrochemically more stable and safer than conventional liquid electrolytes. Besides exploring new materials, engineering a reliable multiphysics model is vital to exploiting and optimizing existing LiPo batteries' potential. This study developed a multiphysics model for a Lithium Cobalt Oxide (LCO)-graphite- Poly(vinylidene fluoride - hexafluoropropylene) (PVdF-HFP) pouch-type mobile phone LiPo. A pseudo-2-dimensional electrochemical model was coupled with a 3D thermal model using COMSOL Multiphysics® to determine the working voltage and temperature during discharge and was compared with experimental data from a commercial LiPo battery and evaluated using Root Mean Square Error (RMSE). The simulated discharge curve agrees remarkably well with the experimental results. The simulated temperature profile has shown appreciable discrepancies primarily due to the generated entropic change coefficient values that significantly affect the battery's heat generation. Overall, the models can be employed as a design tool to evaluate the component design and estimate the system performance of LiPo batteries for commercial applications. Furthermore, researchers can expand the study to investigate more advanced electrochemical phenomena and performances of state-of-the-art lithium and post-lithium chemistries.

Primary alkaline batteries have been widely used in portable electronics due to their low cost and safety. The consumption and disposal of these batteries has prompted notable research on their recycling. Another approach to reducing alkaline battery disposal is to extend their lifetime by increasing their energy density. In this work, the energy density of an AA primary alkaline battery was maximized by determining the optimum amount of electrode materials through multiphysics modeling. An electrochemical model of the alkaline battery is developed in COMSOL Multiphysics® and validated with discharge curves (i.e., voltage vs. time) obtained under constant resistance loads. The electrode thicknesses are then optimized to maximize the energy density of the battery while maintaining its exterior dimensions. The sensitivity of the energy density with respect to the electrode porosities and interfacial areas is then analyzed. The electrochemical model was able to replicate the discharge curves obtained under a 250 mA constant current discharge. The energy density is maximized by decreasing the thickness of the zinc anode. However, this results in anode dissolution near the current collectors and could compromise the electrical continuity in the battery. Increasing the anode thickness prevents dissolution at the current collectors but increases unused mass in the battery. The results of this study can be used to develop longer-lasting alkaline batteries. Furthermore, the model can be improved by considering thermal effects or modified to aid the development of rechargeable alkaline batteries.

Sodium-sulfur (NaS) batteries are a promising energy storage technology that features high energy density, high cycle life, and no self-discharge. One of the cell design considerations that can affect the performance and construction of NaS batteries is cell geometry. While the planar geometry has advantages in power output, cell packing, ease of assembly, and thermal management, it has thermo-mechanical issues in sealing, which makes it less commercialized than the tubular geometry. In this work, the first multiphysics model of a NaS cell with a planar geometry was developed by extending an existing multiphysics model for a NaS cell with a tubular geometry. A previously developed multiphysics model for the tubular NaS cell was first adapted into COMSOL Multiphysics®. The model’s results were then validated against experimental discharge profiles and surface temperatures. After this, a planar NaS cell was simulated using the dimensions of an experimental planar cell, with the mass, heat, and charge transfer equations and parameters previously used in the tubular multiphysics model. The results from the planar model were then validated through comparison to experimental discharge profiles for a planar cell. The developed model can be used in future research and development of NaS batteries by comparing performance parameters of the planar geometry such as discharge profiles, energy densities, and temperatures with a multiphysics model of the tubular NaS battery.

Acid-alkaline electrolyzers utilize an acidic catholyte and alkaline anolyte, which lower the thermodynamic voltage requirement for water splitting. Experiments have demonstrated the feasibility of acid-alkaline electrolyzers with proton exchange membranes, but a mathematical model has yet to be developed to understand their operation. This work developed a multiphysics model of a batch acid-alkaline electrolyzer with a H2SO4 catholyte, a NaOH anolyte, and a proton exchange membrane. The model was formulated in COMSOL Multiphysics® and validated using experimental current vs. voltage data in literature. The electrolyzer’s reactions and ion transport were analyzed based on the electrolyte potential, concentration profiles, and ion fluxes calculated by the model. The charge imbalance due to the consumption of H+ and OH- in the catholyte and anolyte, respectively, is addressed by Na+ transport from the anolyte to the catholyte. This contradicts the prevailing hypothesis that electroneutrality in a proton exchange membrane acid-alkaline electrolyzers is preserved by the Second Wien Effect, or water splitting in high electric fields. H+ is transported from the catholyte to the anolyte, which results in undesired acid-base neutralization. This is minimized by increasing the applied voltage, which shows a tradeoff between power and reactant consumption. Na+-selective membranes also hinder the neutralization reaction, but their realization is challenging due to the smaller Stokes radius of H+. The proposed model can be used to optimize the parameters of a batch electrolyzer and aid in the design of a continuous electrolyzer stack.

The renewable energy transition requires energy storage technologies for grid-balancing and transportation. Lithium-ion batteries have been widely adopted for these applications, but supply risks due to geopolitical tensions have motivated the search for alternative chemistries less dependent on critical raw materials. Sodium-ion batteries have garnered notable attention as promising post-lithium chemistry due to the relative abundance of sodium and its similar manufacturing process to lithium-ion batteries. This work estimated the cost of producing sodium-ion battery packs from cells optimized via multiphysics modeling for energy or power-based applications. This study replicated a multiphysics model of a pouch format sodium-ion battery from literature in COMSOL Multiphysics®. This model determined the optimal active material used in batteries under 0.1C to 10C discharge rates to maximize the energy density. The cost of battery packs produced from the optimized cells was then determined using the Battery Performance and Cost (BatPaC) model of Argonne National Laboratory, which considers material and manufacturing costs. The optimization results reveal that energy cells have thicker electrodes and lower porosities (217 µm thick 0.11 porosity anode, 237 µm thick 0.10 porosity cathode for 0.1C), which maximize the amount of active material per unit mass. Power cells have thinner electrodes and larger porosities to minimize electrical resistance (58 µm thick 0.32 porosity anode, 63 µm thick 0.31 porosity cathode for 10C), reducing energy losses at high currents. Moreover, we compared the calculated production cost for energy and power applications for sodium-ion batteries, highlighting essential parameters affecting the price. The model observed a 26.42% increase in total material cost per kWh when transitioning from energy to power cells. The model may also be refined by considering sodium-ion batteries with different cathode and anode chemistries in different formats and their applications in different use cases.

Battery energy storage systems are essential for stabilizing the intermittent power generation of renewable energy (RE) technologies. Their integration into RE systems is typically studied using energy systems modeling software that utilize either idealized models or complex models that require experimental data. Reduced order modeling offers minimal experimental costs through the use of a multiphysics model in lieu of experimental battery data. In this work, a previously reported multiphysics model of a lithium ion lithium iron phosphate (Li ion LFP) battery was simulated in COMSOL Multiphysics® and reduced into an equivalent circuit model (ECM). The reduced order ECM was then implemented as a battery systems model in an energy systems modeling tool to perform RE-based hybridization studies. Techno economic case studies were conducted on RE based systems powering a household and an off grid island to validate the reduced order ECM with the idealized battery model with HOMER Pro. Optimal component sizes computed using the two software generally showed good agreement and deviations were attributed to electrical losses. The state of charge (SOC) vs. time graphs generated by the two software had an average root mean square error of 0.00173 SOC units across the different case studies. Discrepancies were observed during rapid charging or high SOC values, which were characteristic of the reduced order ECM. This model reduction framework can be applied to other energy storage and conversion technologies, such as other Li ion chemistries, fuel cells, and supercapacitors, to generate chemistry specific models for energy systems research.

The shipping industry is vital for archipelagic countries like the Philippines as they allow transport between islands, but it is a notable contributor of greenhouse gases. In this work, a framework for analyzing the techno-economic potential of hybridizing a sea vessel with solar photovoltaics, lithium-ion batteries, and diesel generators was presented. The roll on/roll off vessel Filipinas Ozamis was considered as a case study due to its commercial use. A 3D model of the roll-on/roll-off vessel was used to measure the ship’s dimensions. The load profile of the vessel was estimated from the ship’s dimensions, operational profile, route, and speed according to the MarineTraffic AIS database. Afterwards, diesel-only and hybrid energy systems were sized in HOMER Pro to power the electrified ship while minimizing its costs and noting the available space on the sea vessel. Lastly, the profitability of the hybrid energy system was determined. The hybrid system was marked with increased capital costs, but the fuel consumption and CO2 emissions were 18.50 % and 27.90 % lower than those of the diesel-only system, respectively. The hybrid system also had lower generation costs and 23.64 % higher net present value than the diesel-only system. This framework can be used in the absence of measured load profiles and can be extended to other sea vessels to conduct a national techno-economic assessment of hybridizing the country’s maritime industry.

The Philippines is home to thousands of off grid islands that are too distant from the mainland and consequently expensive to connect to the main grid. These islands are typically powered by diesel generators, which will require more subsidies as fuel costs continue to increase. Hybrid renewable energy systems (HRES) are an alternative energy source with lower reliance on fuel and generation costs. In this work, the financial sustainability of deploying HRES in Philippine off grid islands of various sizes was evaluated. Patongong Island, Lapinigan Island, Balabac Island, and Sibuyan Island were selected as case studies as their peak electrical demand varies from 4.4 kW in Patongong Island to 3.2 MW in Sibuyan Island, representing a large fraction of off-grid islands in the country. HRES consisting of solar photovoltaics, wind turbines, lithium ion batteries, and diesel generators in these islands were modeled in Island Systems LCOEmin Algorithm (ISLA), an in house energy systems modeling tool. Profitability metrics, such as the net present value, internal rate of return (IRR), and payback period (PBP), were then calculated at varying electricity prices. The large Sibuyan island was already profitable at 0.2 USD/kWh, comparable to the mainland rate, which suggests that subsidies in large islands can be removed. The low 11 % IRR and 13 year PBP may not be attractive to private investors, but this may be alleviated by raising electricity prices. Other islands, however, will still require subsidies as the small Patongong Island becomes profitable only at 1.5 times the mainland rate. This work encourages private sector participation by providing financial insights absent in many techno economic studies. Moreover, this study enlightens the public sector about the necessity of subsidies for providing energy access in small off grid islands.

The archipelagic geography of the Philippines has resulted in thousands of inhabited off grid islands wherein energy and water access are hindered. Electricity in these islands is provided by diesel generators, while water is obtained from rainwater, groundwater, or imports from the mainland. As an alternative to these costly and unsustainable sources, hybrid renewable energy systems (HRES) coupled with reverse osmosis (RO) desalination has been investigated for the cogeneration of electricity and water. In this work, the techno economic potential of coupled RO HRES in selected off grid areas in the Philippines was evaluated. Solar photovoltaics, wind turbines, lithium ion batteries, and diesel generators were considered as HRES components. Dumaran Island and Bantayan Island were chosen as case studies because both islands have faced electricity and water supply concerns. Moreover, these islands present different use cases as Dumaran Island is mainly residential while Bantayan Island has a growing resort industry. Three scenarios were considered in this work to analyze the transition from the status quo to the energy water system: diesel only, HRES, and RO HRES. The islands and scenarios were modeled using the Island Systems LCOEmin Algorithm, an in house energy systems modeling tool written in Python 3. Transition from the diesel only system to HRES decreased the system costs by an average of 15.1 % in both islands. However, the installation of RO was primarily beneficial for the resort island wherein electricity costs increased by only 0.8 % from the HRES scenario and water costs were 80 % lower than current rates in surrounding islands. In contrast, RO deployment in the residential island raised electricity prices by 10.8 %.

The bovine appeasing substance (BAS) is expected to have calming effects in cattle experiencing stressful situations. Therefore, this study investigated the impacts of BAS administration during two of the most stressful events within beef production systems: weaning and feedlot entry. In experiment 1, 186 Bos indicus-influenced calves (73 heifers, 113 bulls) were weaned at 211 ± 1 days of age (day 0). At weaning, calves were ranked by sex and BW, and assigned to receive BAS (Nutricorp, Araras, SP, Brazil; n = 94) or water (CON; n = 92). Treatments (5 ml) were topically applied to the nuchal skin area of each animal. Calf BW was recorded and samples of blood and tail-switch hair were collected on days 0, 15 and 45. Calves that received BAS had greater (P < 0.01) BW gain from day 0 to 15 compared with CON. Overall BW gain (days 0 to 45) and BW on days 15 and 45 were also greater (P ≤ 0.03) in BAS v. CON. Plasma haptoglobin concentration was less (P < 0.01) in BAS v. CON on day 15, whereas cortisol concentrations in plasma and tail-switch hair did not differ between treatments (P ≥ 0.13). In experiment 2, 140 B. indicus-influenced bulls (∼27 months of age) from 2 different pasture-based systems (70 bulls/origin) were transported to a commercial feedlot (≤ 200-km transport; day -1). On day 0, bulls were ranked by source and BW, and assigned to receive BAS (n = 70) or CON (n = 70) and the same sampling procedures as in experiment 1. Bulls receiving BAS had greater (P = 0.04) BW gain from day 0 to 15, but less (P < 0.01) BW gain from day 15 to 45 compared to CON. No other treatment effects were detected (P > 0.14). Therefore, BAS administration to beef calves alleviated the haptoglobin response associated with weaning, and improved calf growth during the subsequent 45 days. Administration of BAS to beef bulls at feedlot entry improved BW gain during the initial 15 days, but these benefits were not sustained throughout the 45-day experiment.

PurposeCOVID-19 pandemic has multifaceted presentations with rising evidence of immune-mediated mechanisms underplay. We sought to explore the outcomes of severe COVID-19 patients treated with a multi-mechanism approach (MMA) in addition to standard-of-care (SC) versus patients who only received SC treatment.Materials and methodsData were collected retrospectively for patients admitted to the intensive care unit (ICU). This observational cohort study was performed at five institutions, 3 in the United States and 2 in Honduras. Patients were stratified for MMA vs. SC treatment during ICU stay. MMA treatment consists of widely available medications started immediately upon hospitalization. These interventions target immunomodulation, anticoagulation, viral suppression, and oxygenation. Primary outcomes included in-hospital mortality and length of stay (LOS) for the index hospitalization and were measured using logistic regression.ResultsOf 86 patients admitted, 65 (76%) who had severe COVID-19 were included in the study; 30 (46%) patients were in SC group, compared with 35 (54%) patients treated with MMA group. Twelve (40%) patients in the SC group died, compared with 5 (14%) in the MMA group (p-value = 0.01, Chi squared test). After adjustment for gender, age, treatment group, Q-SOFA score, the MMA group had a mean length of stay 8.15 days, when compared with SC group with 13.55 days. ICU length of stay was reduced by a mean of 5.4 days (adjusted for a mean age of 54 years, p-value 0.03) and up to 9 days (unadjusted for mean age), with no significant reduction in overall adjusted mortality rate, where the strongest predictor of mortality was the use of mechanical ventilation.ConclusionThe finding that MMA decreases the average ICU length of stay by 5.4 days and up to 9 days in older patients suggests that implementation of this treatment protocol could allow a healthcare system to manage 60% more COVID-19 patients with the same number of ICU beds.

Extrapulmonary Histoplasma capsulatum infections in the immunocompetent population are rare and pose a diagnostic challenge. Upper extremity histoplasmosis without a primary lung infection is uncommon. It is possible to acquire it by inadvertent trauma with direct inoculation.Our case describes an immunocompetent patient with progressive swelling with minimal pain in the wrist associated with a small puncture wound on the left dorsal forearm. The initial workup failed to identify a specific etiology. For the following six weeks, the patient experienced progressive worsening of symptoms, warranting a referral to an orthopedichand surgeon. Left lower extremity magnetic resonance imaging (MRI) findings were non-specific.The surgeon performed a surgical exploration and debridement with the excision of hypertrophic tissue. Initial stains showed a granulomatous tissue but did not reveal an organism; however, a month later, mold was identified on the growth medium. The patient was initiated in isavuconazole empiric therapy. Four weeks later, a matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) confirmed the diagnosis as Histoplasma capsulatum. The patient had clinical remission with isavuconazole used as the United States Food and Drug Administration (FDA) off label use.

The purple trumpet tree [Handroanthus impetiginosus (Mart. Ex DC.) Mattos - Bignoniaceae] is one of the most prominent tree species in the Brazilian Federal District, with more than 150 trees in the Plano Piloto region of Brasília. In March 2017, weevils (Coleoptera) were observed in ripe fruits of purple trumpet trees feeding on already dried seeds. The objective of this paper is to report and describe the main damage to seeds and pods of H. impetiginosus in Brasília, Brazil, caused by this beetle. The insect was identified as Cleogonus insulcatus Fiedler, 1954 (Coleoptera: Curculionidae). Of the 126 fruits analyzed, 104 exhibited predation by C. insulcatus (82.5%) and 377 larvae were collected inside the pods feeding on the seeds. This is the first report of C. insulcatus in Brazil and the first record of damage to H. impetiginosus pods and seeds caused by this insect.

Aphis craccivora Koch, 1854 (Hemiptera: Aphididae) is a highly polyphagous aphid that is considered a pest of many crops with economic interest. The present study reports the occurrence and plant damages caused by the aphid A. craccivora on mahogany seedlings (Swietenia macrophylla King, Meliaceae) and scarlet jade vines (Mucuna bennettii F. Muell., Fabaceae) in the Distrito Federal, Brazil. Infestations of this aphid were found in twelve mahogany seedlings and two scarlet jade vines. The infestations caused deformations in the young leaflets of mahogany plants as well as leaves and inflorescences of scarlet jade vine. A. craccivora negatively affected the development of S. macrophylla and might become a limiting factor for seedlings production.

For many years, developmental and physiological differences have been known to exist between anatomic segments of the colorectum. Because of different outcomes, prognoses, and clinical responses to chemotherapy, the distinction between right colon cancer (RCC) and left colon cancer (LCC) has gained attention. Furthermore, variations in the molecular features and gut microbiota between right and LCCs have recently been a hot research topic. CpG island methylator phenotype-high, microsatellite instability-high colorectal cancers are more likely to occur on the right side whereas tumors with chromosomal instability have been detected in approximately 75% of LCC patients and 30% of RCC patients. The mutation rates of oncogenes and tumor suppressor genes also differ between RCC and LCC patients. Biofilm is more abundant in RCC patients than LLC patients, as are Prevotella, Selenomonas, and Peptostreptococcus. Conversely, Fusobacterium, Escherichia/Shigella, and Leptotrichia are more abundant in LCC patients compared to RCC patients. Distinctive characteristics are apparent in terms of molecular features and gut microbiota between right and LCC. However, how or to what extent these differences influence diverging oncologic outcomes remains unclear. Further clinical and translational studies are needed to elucidate the causative relationship between primary tumor location and prognosis.