Low Means Research Articles

Design of Batteries for a Hybrid Propulsion System of a Training Aircraft

In this article, we propose the parameters of a battery that would be suitable for the conceptual design of a small training aircraft. The mass design of the battery is based on the requirements for real training flights performed by students in pilot training. Such a serial hybrid propulsion aircraft could be used in our UNIZA aviation, training and education center for pilot training. Due to socio-political pressures in reducing emissions generated by vehicles, there has also been massive research in the aviation industry in the field of hybrid and electric aircraft propulsion. In the introduction, the article deals with the energy sources used in aircraft propulsion. In hybrid propulsion, a combination of aviation fuel and electricity is used as the energy source. The required total energy must choose a suitable combination of these two energy sources. The biggest drawback of batteries that can be used in hybrid systems is their low energy density. Low energy density means that larger and heavier batteries need to be used to achieve the required performance, which is their main disadvantage. Therefore, it is necessary to find a suitable compromise between the hybrid’s percentage, i.e., the ratio between conventional and electric drive. We applied the hybrid aircraft system’s calculations to the real training flights to determine the necessary parameters of the hybrid aircraft suitable for pilot training. This calculation will help in obtaining an idea of the basic parameters of the hybrid drive and the battery parameters, which are necessary for particular applications in the training aircraft. The performed calculations of the hybrid configuration and, especially, the determination of the battery of the hybrid propulsion parameters provide the basic information necessary for the design of the hybrid system of a small training aircraft. These outputs can be used to determine the parameters of batteries that would be used in hybrid systems. A limiting factor to consider with hybrid aircrafts is that the aircraft must be charged on the ground before the flight, which poses interesting logistical and infrastructure problems at the airport.

Studies on the Nutritional, Mineral Composition, Mineral Ratio and Anti-nutritional Molar Ratio of Six Underutilized Wild Edible Vegetables in Ado-Ekiti, Ekiti State, Nigeria

Aim: Fruits and common vegetables are now becoming too expensive for the poor consumers in Nigeria. The search for cheap, readily available and (locally sourced for the people in need of) nutritious food prompted this research work.
 Study Design: Six underutilized wild vegetables (Solanum microcarpon, Strichium sparganophora, Crassocephalum crepidiodes, Solanum nigrum, Myrianthus arboreus and Sterculia tragacantha) from Ado- Ekiti, Ekiti State, Nigeria were evaluated for their nutritional, mineral and anti-nutritional potentials.
 Place and Duration of Study: The collection of the samples were done in the month of December, 2020 in Ado Ekiti, Ekiti State, Nigeria and air dried for three weeks.
 Methodology: Young shoots of five indigenous vegetables were collected, washed thoroughly, air dried, pulverized and analysed using standard methods of AOAC.
 Results: The proximate analyses of the vegetables indicated that the moisture content, ash, fat, crude fiber, crude protein and carbohydrates ranged as follows: 6.17-8.85%, 4.73-6.59 %, 2.00-3.13%, 3.89-7.27%, 7.77-12.23% and 63.84-70.61% respectively. The total energy ranged from 1,367.85 to 1,467.85KJ/100g with low Coefficient of Variation (CV%) of 2.22. Mineral contents are of the following order K>Mg>Ca> P>Na>Fe>Zn. The result of the mineral ratio showed that the calculated mineral ratio for Na/K, K/ Na, Ca/P, Ca/Mg, Ca/K, Zn/Cu and [K/(Ca+Mg)] were below the critical level. The calculated mineral safety indexes (MSI) were lower than the tabulated values. The anti-nutrient contents (Cyanide, Saponins, and Oxalate) were below the threshold levels,
 Conclusion: Low MSI means that the vegetables could not pose health risk when consumed. The low anti-nutrient contents of the samples is an indication that the consumer would not suffer from mineral overload. The nutrition and mineral potentials of these vegetables could suggest their uses as nutritional supplements and are highly promising for food security and sustainability for the populace.

Sensitive label-free Cu2O/Ag fused chemometrics SERS sensor for rapid detection of total arsenic in tea

Arsenic (As) is one of the toxic, persistent, and lethal heavy metalloids and requires rapid, less costly, and sensitive detection methods. This study proposed a label-free cuprous oxide/silver (Cu2O/Ag) surface-enhanced Raman scattering (SERS) nanoprobe to detect total As in tea. Different total As spiked tea concentrations were mixed with the Cu2O/Ag SERS nanoprobe for the SERS detection. Quantitative models were established for predicting the total As in tea by comparatively applying chemometric algorithms. Amongst the algorithms, competitive adaptive reweighted sampling partial least squares (CARS-PLS) optimized the most effective spectral variables to predict the total As in tea efficiently. The CARS-PLS gave the highest correlation coefficient value (Rp = 0.9935), very low root means square error (RMSEP = 0.0496 μg g−1) in the prediction set and recorded the highest RPD value of 8.819. The proposed nanoprobe achieved a lower detection limit (0.00561 μg g−1), excellent selectivity, satisfactory reproducibility, and stability. No significant difference was recorded when the performance of the Cu2O/Ag total As SERS sensor was compared with the inductively coupled plasma mass spectrometry (ICP-MS) method. Therefore, this developed Cu2O/Ag coupled chemometrics SERS sensing method could be used to efficiently determine, quantify, and predict total As in tea to promote monitoring of heavy metal contaminants.

Reactive Transport Modeling of Reflux Dolomitization of Carbonate Platforms: Enlightenment from Yingshan Formation in Shunnan Area, Tarim Basin

Dolomite plays an important role in carbonate reservoirs. The topography in the study area creates conditions for reflux dolomitization. The northeastward paleogeomorphy during the deposition of the Yingshan Formation was favorable for reflux dolomitization. Furthermore, the petrological and geochemical evidence indicated that the formation of finely crystalline dolomites was penecontemporaneous to sedimentation. The content of powder crystal dolomites increases from grainstone, to packstone, to mudstone. Previous studies only analyzed the origin of dolomites based on traditional geological methods, but did not analyze the spatial influence of reflux dolomitization on the reservoir quality. In this study, the reflux dolomitization of platform carbonate sediments was evaluated using three-dimensional reactive transport models. The sensitivity of dolomitization to a range of intrinsic and extrinsic controls was also explored. The reflux dolomitization involves replacement dolomitization and over-dolomitization. The porosity change is the result of the abundance change of dolomite and anhydrite. The fluid flow pattern in the model is related to the injection rate and geothermal gradient. According to the spatial and temporal change of mineral, ionic concentration, and physical property, the reflux dolomitization could be divided into five stages. From the sensitivity analysis, high permeability promotes dolomitization only in the initial stage, while low permeability and high porosity means stronger dolomitization. Besides, the injection rate, reactive surface area (RSA), geothermal gradient, and brine salinity are all proportional to the dolomitization. Differently from porosity change, the permeability change is concentrated in the upper part of the numerical model. The location of “sweet spot” varies with the locations of change centers of porosity and permeability. In the stage-1 and 4 of dolomitzation, it overlaps with porosity and permeability growth centers. While in the stage-2, 3 and 5, it lies between the porosity and permeability growth/reduction centers.

An IoT business model for public sector retail oil outlets

PurposeThe fuel retailing landscape in India is undergoing a structural shift with the reforms undertaken by the government that would help the private and foreign firms to enter this market. India is poised to become the world's largest growth market for energy by the mid-2020s. IoT has become an integral digital technology for the fuel retailers in the retail oil outlet (ROO) ecosystem. The purpose of this paper is to develop an Internet of Things (IoT) business model for the Indian oil marketing companies (OMCs') ROOs.Design/methodology/approachUsing literature review along with a survey among 660 respondents led to 402 valid observations, and the variables that contributed to IoT adoption at the OMCs' ROOs were identified. Using the BMC tool (Osterwalder and Pigneur, 2009), the relative importance of the variables within each building block was established. The means of all the variables were measured against the average of all the variables, and significant differences were searched for in each block. The notable differences of the means along with significant high and low means were highlighted.FindingsThis paper depicts empirical research that led to a framework of an IoT business model for Indian public sector ROOs. It also represents the usefulness of the Technology-Organization-Environment framework at the OMCs ROOs and extends the literature by incorporating “data security” to the existent framework of technology, organization and environment within the IoT ecosystem.Research limitations/implicationsThe outcome of the research should be analysed in the Indian context as all the respondents were from India. The study was conducted for the ROOs of Indian Oil Corporation Limited, Hindustan Petroleum Corporation Limited and Bharat Petroleum Corporation Limited and excluded their downstream operations. The dispensers in the OMCs vary along with their marketing strategies in the retail segments. The IoT business model can be customized for a particular OMC, which is scope of further research.Practical implicationsThe study has practical implications for those global fuel retailers embarking on the IoT adoption drive at their ROOs about the need to install “data security” measures in the connected IoT environment. The study provides insights on how the OMCs can stay ahead of competition in the Indian market vis-à-vis the private sector fuel retailers by embracing the IoT business model.Social implicationsThe new emerging technological business models provide competitive edge to those organizations adopting them (Barney, 1991; Clemons and Row, 1991; Feeny and Ives, 1990). The study will enable the OMCs to implement the IoT business model at their ROOs for enhancing their revenue streams and profitability and lowering of operating costs. The study provides insights on how the OMCs can stay ahead of competition in the Indian market vis-à-vis the private sector fuel retailers by embracing the IoT business model.Originality/valueThe contribution of the paper is that it is among the first to map the variables that contribute to IoT adoption at the OMCs' ROOs, within the building blocks of the BMC tool (Osterwalder and Pigneur, 2009), according to their importance. To retain their dominance and have a first-mover competitive advantage, this study enables the OMCs to adopt the IoT business model and transform their ROOs into Internet-connected intelligent fuel outlets.

Cycling performance prediction based on cadence analysis by using multiple regression

This project examined the influence of the cadence, speed, heart rate and power towards the cycling performance by using Garmin Edge 1000. Any change in cadence will affect the speed, heart rate and power of the novice cyclist and the changes pattern will be observed through mobile devices installed with Garmin Connect application. Every results will be recorded for the next task which analysis the collected data by using machine learning algorithm which is Regression analysis. Regression analysis is a statistical method for modelling the connection between one or more independent variables and a dependent (target) variable. Regression analysis is required to answer these types of prediction problems in machine learning. Regression is a supervised learning technique that aids in the discovery of variable correlations and allows for the prediction of a continuous output variable based on one or more predictor variables. A total of forty days’ worth of events were captured in the dataset. Cadence act as dependent variable, (y) while speed, heart rate and power act as independent variable, (x) in prediction of the cycling performance. Simple linear regression is defined as linear regression with only one input variable (x). When there are several input variables, the linear regression is referred to as multiple linear regression. The research uses a linear regression technique to predict cycling performance based on cadence analysis. The linear regression algorithm reveals a linear relationship between a dependent (y) variable and one or more independent (y) variables, thus the name. Because linear regression reveals a linear relationship, it determines how the value of the dependent variable changes as the value of the independent variable changes. This analysis use the Mean Squared Error (MSE) expense function for Linear Regression, which is the average of squared errors between expected and real values. Value of R squared had been recorded in this project. A low R-squared value means that the independent variable is not describing any of the difference in the dependent variable-regardless of variable importance, this is letting know that the defined independent variable, although meaningful, is not responsible for much of the variance in the dependent variable’s mean. By using multiple regression, the value of R-squared in this project is acceptable because over than 0.7 and as known this project based on human behaviour and usually the R-squared value hardly to have more than 0.3 if involve human factor but in this project the R-squared is acceptable.

Cultivo da microalga Chlorella sorokiniana em diversas concentrações de Victoria amazonica, enriquecido com fertilizante inorgânico (NPK) e sob diferentes temperaturas

The Chlorella genus has biotechnological potential and is suitable for high biomass production because of its large-scale cultivation technology. In order to define the conditions that best favor its development aiming to optimize crops for greater algal growth, this research aims to verify whether cell growth is different due to different concentrations of the macrophyte extract Victoria amazonica, enriched with NPK inorganic and under different temperatures. It was concluded that, the aquatic macrophyte substrate was efficient for cultivation, representing a low cost means for the production and maintenance of the cultivation of Chlorella sorokiniana.

Influence of Biot number and geometric parameters on the overall cooling effectiveness of double wall structure with pins

In this paper, the overall cooling effectiveness of double wall cooling structures with pins is experimentally investigated on the low-speed wind tunnel. The analysis of the single cooling technology contributions to improve the double wall cooling performance is provided. The effect of Biot number (Bi = 0.03, 0.32, 2.25) and the film hole size (de= 2 mm, 3 mm, 5 mm) on the overall cooling effectiveness are also studied. In order to further improve the overall cooling performance, the present study proposes two new shapes of film hole patterns with compound angles (compound configuration, double configuration). By numerically analyzing the cooling effectiveness of the outer film cooling and the heat transfer performance of the inner target wall, the mechanism by which film hole size and new film hole patterns affect the overall cooling performance of double wall structures is clarified. The results show that the area-averaged overall cooling effectiveness of the double cooling technology is more than 30% higher than that of the two single cooling technologies and the contribution of impingement cooling is higher than that of effusion cooling at high blowing ratios. The cooling performance of the double wall structure is greatly influenced by the Biot number of effusion plates. Low Biot number means higher thermal conductivity, resulting in higher overall cooling effectiveness under the same thermal load conditions. Increasing the film hole size could enhance the film cooling performance outside of the effusion plate, suppressing the unfavorable results of lower heat transfer performance at the inner side. The fitting correlation equation obtained using the binary linear regression method agrees well with the experimental results, with a maximum deviation of less than 4%. Both of the two compound structures can effectively improve the overall cooling performance of the double wall structure. The double configuration has the best cooling performance and the area-averaged cooling effectiveness improves by 15.1% compared to the reference configuration under the condition of M = 1.5. The experimental results provide a vital database for the future double wall cooling design.

Electric vehicle route planning using real-world charging infrastructure in Germany

Electric vehicles (EVs) are a way to reduce emissions from mobility. To replace conventional vehicles, EVs must be able to deliver a similar level of comfort on long-distance travel. A key enabler here is an adequate charging infrastructure (CI). In this paper, we evaluate the current CI in Germany, a leading adopter of EVs in Europe. The goal of this evaluation is to understand where innovations and investments need to take place such that overall costs are minimized while user comfort is maximized. We perform this evaluation by analysing travel duration for five typical EVs on 60 routes through Germany. We include non-linear, state-of-charge-dependent charging power as well the non-linear velocity-dependent energy consumption. EVs are modelled after five typically used vehicles in Germany and charging stations are based on real-world data taken from the federal registry. This level of detail in modelling allows for representative results. In our sample, travel time is ∼8% longer when charging compared to non-stop driving. The delay strongly depends on route distance where many routes with <300 km length can be driven non-stop while some extreme cases through areas with unsuitable infrastructure result in 30% more driving time. The necessary breaks were in line with recommendations for truck drivers in Germany. To understand the impact of key technical data we perform a sensitivity analysis. The most relevant factors are start state of charge (SOC) since a low SOC means that typically an additional stop is necessary, often at unfavourable locations. A start SOC of 30% results in 30% additional travel time compared to a non-stop drive. A low energy efficiency and battery capacity of the car (70% of base case) increases travel time by 20%. Increasing charging station power does not have a strong effect since current vehicles cannot charge at 350 kW. • Calculation of time required for recharging in Germany. • 60 routes calculated with 5 vehicle models. • Measured charging curves and energy consumption model for vehicles. • Parameter sweep for battery capacity, charging power, etc.

STUDENTS’ READINESS FOR E-LEARNING: A CASE STUDY OF STUDENTS IN HIGHER EDUCATION

The process of e-learning is the operations that involve humans, computers, the Internet, and instructional material and produce the outputs to learners and the organization. This research aimed to study students' readiness for e-learning of graduate students in IAIN Kendari, Indonesia. The research sample consisted of 168 graduate students who were selected purposively. The questionnaire was adapted from Watkins and interviewing 10% of the sample group was conducted to collect the data. The research findings showed that the students were ready for the e-learning, as shown by the overall mean score is 3.72, which is above Mo = 3.40. Due to the low means of statistical calculation, three important items need to be improved, such as Students' household distraction reduction, students' comfort to be involved in multiple online discussions, and students' ability to take notes during online discussions, should be considered. Based on the interview, some challenges met during online learning that reduced students' readiness were unstable internet connection, lecturer's presence on screen, inconducive learning environment, and inability to be a multitasker. Hence, it is recommended that the university and students discuss to improve students' readiness in motivation and technology access.

Demand-side flexibility in a residential district: What are the main sources of uncertainty?

With the increasing share of intermittent renewable energy sources in the energy mix, demand-side flexibility is likely to play a key role in the future. For buildings, flexibility is defined as the ability to shift their energy consumption away from “peak periods” i.e. high-demand periods of the electrical network. In France, these episodes occur mainly during the wintertime due to the significant demand for space heating. To achieve flexibility objectives, we explore an indirect control strategy at district scale by adjusting the dwelling thermostat during peak periods. The study is conducted over 337 dwellings in order to better predict the load curve by taking advantage of the aggregation effect. Three main research questions are addressed in relation to the assessment of flexibility potential: (i) the effect of aggregation, (ii) the identification of the most influencing factors, including occupant behavior, and (iii) the quantification of uncertainties. Using an urban building energy modeling tool populated with various national data sources (building envelope, energy class of equipment, etc), we perform a sensitivity analysis on 22 parameters representing the geometry, the appliances, the building characteristics, the occupants, and the grid. The output indicator is the average power shifted during the flexibility (or demand response) event. From this analysis, 7 parameters appear as being the most influential. A regression analysis on these parameters is performed, depending on both the duration of the event and the typology of district. The results show that the duration of the flexibility event and the occupant pre-selected temperature change are the most influential parameters. It results to approximately ± 90 W of uncertainty on an average potential of 290 W of shiftable power per household in a recent district. Furthermore, the occupants are highlighted as making a significant contribution to flexibility. Finally, we observed that the thermal properties investigated with the study of an old fabric district play a key role. Low thermal performance means high heating consumption and increased flexibility potential, but a similar relative uncertainty.

The Symmpact: A Direct-Impact Hopkinson Bar Setup Suitable for Investigating Dynamic Equilibrium in Low-Impedance Materials

BackgroundMeasuring the dynamic behavior of low-impedance materials such as foams is challenging. Their low acoustic impedance means that sensitive force measurement is required. The porous structure of foams also gives rise to dynamic compaction waves, which can result in unusual behavior, in particular if the foam material is so thick, that dynamic force equilibrium is not reached.ObjectiveThis work investigates comparatively large polyurethane foam specimens with densities in the range of 80 – 240 kg/m3 to deliberately achieve a state away from force equilibrium during high-rate compaction. The aim is to understand how an increase in strain rate leads to a reduction in strength for such materials.MethodsA specialized direct-impact Hopkinson bar is employed. It uses polycarbonate bars to achieve the required long pulse duration of 2.6 ms to compress the large specimens into the densification regime. In contrast to existing setups, both striker and output bar are instrumented with strain gauges to monitor force equilibrium. The absence of an input bar allows monitoring force equilibrium more accurately. Special attention is paid to the calibration of strain gauges, taking non-linear effects, wave dispersion and attenuation into account. Digital Image Correlation is employed to analyze elastic and plastic compaction waves by means of Lagrange diagrams.ResultsDepending on density, the specimens show saturation of dynamic strength increase at high rates of strain approx 500 /s, or even negative strain rate sensitivity in case of the lowest density. The occurrence of apparent negative strain rate sensitivity is accompanied by a localized structural collapse front, moving at a low velocity of approx 10 m/s through the material. This apparent strain rate sensitivity is a structural effect which is related to the thickness of the specimen.ConclusionsThe primary aim of material characterization using Hopkinson bars is to achieve a state of force equilibrium. For this reason, very thin specimens are usually employed. However, data gathered in this way is not representative for thick foam layers. Here, an increase of strain rate can lead to a decrease of strength if homogeneous deformation is replaced by a dynamic compaction wave. This behavior can occur at strain rates encountered under conditions such as automotive crash.

Ultralow longitudinal emittance storage rings

Low longitudinal emittance means small energy spread and short bunch length, which makes high-power short-wavelength coherent radiation possible. In a storage ring, due to quantum excitation, the equilibrium longitudinal emittance is mainly the overall contribution of all bend-related elements, such as bends, undulators and laser modulators. By introducing longitudinal Twiss function and analyzing the 6D one-turn map in 3D Twiss form, the longitudinal emittance contribution of all these elements is theoretically studied in this paper, and a general method for minimizing the storage ring equilibrium longitudinal emittance is proposed. An integrated optimization of longitudinal beta function shows, the longitudinal emittance scales as the third power of bending angle, and can be as low as subpicometer with a beam energy of 400 MeV in an ultimate state.

Petroleum Reservoir Control Optimization with the Use of the Auto-Adaptive Decision Trees

The global increase in energy demand and the decreasing number of newly discovered hydrocarbon reservoirs caused by the relatively low oil price means that it is crucial to exploit existing reservoirs as efficiently as possible. Optimization of the reservoir control may increase the technical and economic efficiency of the production. In this paper, a novel algorithm that automatically determines the intelligent control maximizing the NPV of a given production process was developed. The idea is to build an auto-adaptive parameterized decision tree that replaces the arbitrarily selected limit values for the selected attributes of the decision tree with parameters. To select the optimal values of the decision tree parameters, an AI-based optimization tool called SMAC (Sequential Model-based Algorithm Configuration) was used. In each iteration, the generated control sequence is introduced into the reservoir simulator to compute the NVP, which is then utilized by the SMAC tool to vary the limit values to generate a better control sequence, which leads to an improved NPV. A new tool connecting the parameterized decision tree with the reservoir simulator and the optimization tool was developed. Its application on a simulation model of a real reservoir for which the CCS-EOR process was considered allowed oil production to be increased by 3.5% during the CO2-EOR phase, reducing the amount of carbon dioxide injected at that time by 16%. Hence, the created tool allowed revenue to be increased by 49%.

Using Spatial Patterns of COVID-19 to Build a Framework for Economic Reactivation

In this article, we propose an application of humanitarian logistics theory to build a supportive framework for economic reactivation and pandemic management based on province vulnerability against COVID-19. The main research question is which factors are related to COVID-19 mortality between Peruvian provinces? We conduct a spatial regression analysis to explore which factors determine the differences in COVID-19 cumulative mortality rates for 189 Peruvian provinces up to December 2020. The most vulnerable provinces are characterized by having low outcomes of long-run poverty and high population density. Low poverty means high economic activity, which leads to more deaths due to COVID-19. There is a lack of supply in the set of relief goods defined as Pandemic Response and Recovery Supportive Goods and Services (PRRSGS). These goods must be delivered in order to mitigate the risk associated with COVID-19. A supportive framework for economic reactivation can be built based on regression results and a delivery strategy can be discussed according to the spatial patterns that we found for mortality rates.

Signalling Strategies of Exporters on Internet Business‐to‐Business Platforms

AbstractThe emergence of Internet business‐to‐business (B2B) platforms offers exporters an effective and low cost means to meet the needs of their foreign buyers. However, the online marketplace is noisy and crowded, and the information asymmetry between exporters and foreign buyers is significant. Little research has been done to investigate how exporters can best use these different platform services and their boundaries and conditions. Drawing on signalling theory, we categorize an exporter’s use of platform services as marketing‐ and trade‐risk‐focused services (less and more credible signals, respectively). We further investigate how these platform services influence export sales in different institutional environments, specifically exploring the moderating roles of formal and informal institutional distance between the home and host countries. We test our hypotheses using a unique dataset made up of survey and archival data on Chinese exporters’ using Alibaba.com. Findings indicate that using marketing‐ and trade‐risk‐focused services positively affect export sales performance. The effect, however, is contingent on the differences in the formal and informal institutional environments between home and host countries. Trade‐risk‐focused services are more pronounced under greater formal and informal institutional distance. In contrast, marketing‐focused services are less pronounced under greater informal institutional distance. Taken together, our findings extend signalling theory to an online and international context. We deepen our understanding of how firms can utilize online signals with different levels of credibility and of how differences of institutional environments differently impact their effectiveness. We also advance corporate strategy literature by highlighting the importance of geographic markets and institutional differences in shaping firm’s online signalling strategies.

Spawning Parvocalanus crassirostris at a high adult density: Explaining low adult population numbers and means for improving their intensive culture

In calanoid copepods, intensive culture is preferred, but currently, densities do not exceed a few adults per milliliter. Several explanations exist, but none have allowed increasing the density of adults. This study proposes a new explanation for the problem of adult density in intensive culture, using the copepod Parvocalanus crassirostris as a model. First: eggs (2 h old) were supplied to adults kept at 20 adults mL−1 in 1 L containers with and without microalgae; constant aeration was supplied to determine egg survival to damage caused by the adults. Different samples were taken up to 175 min. Second: A high-density spawning test (5–80 adults mL−1) was performed, using shallow depth (2.5 cm) and supersaturation level of oxygen for rapid egg separation and sufficient oxygen for adults, respectively. The SEP (egg female−1 day−1) and REP (egg mL−1 day−1) were determined. Third: two systems of continuous egg harvesting, filtration and sedimentation, were evaluated under a high density of adults culture (10 adults mL−1). The adults of P. crassirostris quickly damaged the eggs, but the presence of food reduces the damage caused. Adults presented high SEP up to 10 adults mL−1; however, REP increased significantly to more than 170 eggs mL−1 day-1 using densities of 20 and 30 adults mL−1 (p <.05). A continuous harvesting system by filtration generated deformation of the eggs and a lower SEP and REP compared to the passive harvesting system by sedimentation (p <.01). The present study showed that even P. crassirostris, considered herbivore copepod, can damage its eggs. The fragility of newly spawned eggs (without hardened chorion) can generate difficulties when increasing adult density in culture. This new explanation contributes to the generation of new egg harvesting strategies in calanoid copepods of aquaculture importance.

Trialling camera traps to determine occupancy and breeding in burrowing seabirds

AbstractBurrowing seabirds are important in ecological and conservation terms. Many populations are in flux due to both negative and positive anthropogenic impacts, but their ecology makes measuring changes difficult. Reliably recording key metrics, the proportion of burrows with breeding pairs and the success of breeding attempts requires burrow‐level information on occupancy. We investigated the use of camera traps positioned at burrow entrances for determining the number of breeding pairs in a sample to inform population estimates, and for recording breeding success. The performance of two cameras makes we tested differed markedly, with Spypoint Force 10 trail cameras prone to malfunction while Reconyx HC600 Hyperfire cameras performed well. Nevertheless, both makes yielded season‐long activity patterns for individual burrows, eliminating uncertainty around successful fledging attempts. Dimensionality reduction of activity metrics derived from camera time series suggests breeding and non‐breeding burrows may be identifiable using linear discriminant analyses but sample sizes from our trial were low and group means were only significantly different during certain breeding stages (permutational multivariate analysis of variance: early chick‐rearing f = 3.64, P = 0.06; late chick‐rearing f = 8.28, P = 0.009). Compared with traditional techniques for determining burrow occupancy (e.g. manual burrow inspection and playback of conspecific calls at burrow entrances), camera traps can reduce uncertainty in estimated breeding success and potentially breeding status of burrows. Significant up‐front investment is required in terms of equipment and human resources but for long‐term studies, camera traps may deliver advantages, particularly when unanticipated novel observations and the potential for calibrating traditional methods with cameras are factored in.

SuMO-Fil: Supervised multi-omic filtering prior to performing network analysis.

Multi-omic analyses that integrate many high-dimensional datasets often present significant deficiencies in statistical power and require time consuming computations to execute the analytical methods. We present SuMO-Fil to remedy against these issues which is a pre-processing method for Supervised Multi-Omic Filtering that removes variables or features considered to be irrelevant noise. SuMO-Fil is intended to be performed prior to downstream analyses that detect supervised gene networks in sparse settings. We accomplish this by implementing variable filters based on low similarity across the datasets in conjunction with low similarity with the outcome. This approach can improve accuracy, as well as reduce run times for a variety of computationally expensive downstream analyses. This method has applications in a setting where the downstream analysis may include sparse canonical correlation analysis. Filtering methods specifically for cluster and network analysis are introduced and compared by simulating modular networks with known statistical properties. The SuMO-Fil method performs favorably by eliminating non-network features while maintaining important biological signal under a variety of different signal settings as compared to popular filtering techniques based on low means or low variances. We show that the speed and accuracy of methods such as supervised sparse canonical correlation are increased after using SuMO-Fil, thus greatly improving the scalability of these approaches.

Straw as an Alternative to Grass Forage in Horses-Effects on Post-Prandial Metabolic Profile, Energy Intake, Behaviour and Gastric Ulceration.

Simple SummaryMany leisure horses have low energy requirements and obesity is common. Straw has a low energy content and could be a forage option for these horses. However, a previous study suggested that providing straw as the only forage was associated with an increased risk for gastric ulcers. This study evaluated replacing 50% of the daily forage allowance with a good hygienic quality wheat straw. Six horses were fed both the control diet (grass forage only, CON) and the straw diet (50:50 grass forage and straw, S). Each diet was fed for three weeks and all horses were evaluated on both diets. Diet did not affect the prevalence of gastric ulcers. Feed intake time was longer and daily energy intake lower on diet S, compared to CON. Plasma insulin levels were lower on diet S compared to CON, which could be beneficial for horses with overweight or insulin dysregulation. The results suggest that good hygienic wheat straw provided at 50% of the forage ration does not cause gastric ulcers, but may prolong feeding time and promote a metabolic profile more suitable for overweight horses. Including straw as part of the ration therefore may improve welfare for horses with low energy requirements.Straw’s low energy content means it is a roughage option for horses with low energy requirements. Previously, in a field study, straw was associated with an increased risk for gastric ulcers. This study evaluated the effect on gastric ulcers, metabolic profile and behaviour of replacing, in a forage-only ration, 50% of the daily allowance with wheat straw. Six equines were studied in a 2 × 21-day cross-over design. The control diet (CON: 100% grass forage) and the straw diet (S: 50% grass forage and 50% straw [DM basis]) were iso-energetic. Gastroscopy was performed prior to the study and on day 21 and blood samples were collected and behavioural observations were performed. Diet did not affect squamous or glandular gastric ulcer scores (p > 0.05). Feed intake time was longer (p < 0.05) plus energy intake and plasma insulin concentrations were lower on diet S compared to CON (p < 0.0001). Plasma serotonin concentrations tended to be higher on diet S compared to CON (p = 0.05). The results suggest that good hygienic quality wheat straw can be included for up to 50% of the diet without causing gastric ulcers and that it can extend feeding time and promote a metabolic profile more suitable for overweight horses.