Single Period Research Articles

Volume Estimation of the Thickest Scoriaceous Tephra-Fall Deposits on the South-Southeastern Flank of Mt. Raung

Thick scoriaceous tephra-fall deposits are widely distributed in the south to the southeast flank of Mt. Raung, indicating the existence of past large explosive eruptions. The deposits are relatively young as the deposits are situated near the surface. Scoriaceous tephra-fall deposits can be divided into four layers from bottom to top, Scoria Fall 1, Scoria Fall 2, Scoria Fall 3, and Scoria Fall 4. There is no time gap between these layers, as evidenced by the deposits not being separated by any weathered layer or soil, suggesting that the deposits represent an eruptive product of a single active period. We estimated the volume of the deposits using isopach maps following Weibull method to identify the magnitude of the eruption. We limited the estimation only to Scoria Fall 2 and Scoria Fall 3 deposits which were consistently exposed on 13 and 9 observation points, respectively. The volume of Scoria Fall 2 is ~0.54 km3 and Scoria Fall 3 is ~0.26 km3 making the total volume of 0.8 km3 (VEI 4).

New Records of Seaweeds From The St. Martin’s Reef, Bangladesh. II.

Peyssonnelia conchicola Piccone and Grunow, Gymnothamnion elegans (Schousboe) J. Ag. (reds) and Spatoglossum schroederi (Mertens) Kütz. (brown) seaweeds as new records are described and reported here in the second part of studies in the St. Martin’s Reef. This along with the eight seaweeds (with six new records) recorded and described in the first part earlier, the total taxa now are 11 (eleven). Again, all the eight samples were collected in a single day light period. Through extensive studies including sub-littoral zones of the two tiny Reefs having crystal clear water is expected to yield many seaweed species, including new ones. Bangladesh J. Plant Taxon. 30(2): 249-254, 2023 (December)

Leveraging A Multi-Criteria Decision-Making Approach with AHP & TOPSIS Method for the Selection of IoT-Based Inverter Smart Grid System and Smart Meter in Solar Photovoltaic and Wind Turbine Installations at Pelabuhan Ratu CFPP.

The effective selection of inverters plays a critical role in optimising the efficiency and performance of solar photovoltaic (PV) and wind turbine systems. Inverters have a direct impact on overall energy conversion efficiency and system output by influencing their efficiency and reliability. Inverter selection also involves essential criteria such as cost, compatibility with renewable energy sources, and environmental considerations. Therefore, a comprehensive and systematic approach is necessary to thoroughly assess and compare various inverter options.
 This study utilises a multi-criteria decision-making methodology to address these challenges. It assesses the identified criteria using the Analytical Hierarchy Process (AHP) and ranks them to determine the most suitable solution through the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS). As a result, the investigation identifies smart grid and smart metre inverters as the optimal solutions, effectively addressing concerns related to power stability, communication and connectivity, security, data management, and cost.
 The proposed methodology yields a substantial total equity portion of USD 9,325.71, along with impressive annual earnings before interest, taxes, depreciation, and amortisation (EBITDA) of USD 1,734.09. The estimated payback period is 6.85 years, and the return on investment (ROI) reaches a remarkable 338.07%. Additionally, the nett income significantly reduces the production cost, amounting to USD 40,853.34 in a single period.

Clinical pharmacokinetic evaluation of Withania somnifera (L.) Dunal root extract in healthy human volunteers: A non-randomized, single dose study utilizing UHPLC-MS/MS analysis

Ethnopharmacological relevanceWithania somnifera (L.) Dunal; (Solanaceae), commonly known as Ashwagandha, is one of the most significant medicinal herbs in ‘Ayurveda’, a traditional Indian medicine used for centuries with evidence in scriptures. Ashwagandha was mentioned in old Ayurvedic medical literature such as Charaka Samhita and Sushruta Samhita for improving weight and strength, with multiple citations for internal and exterior usage in emaciation and nourishing the body. Ethnopharmacological evidence revealed that it was used to relieve inflammation, reduce abdominal swelling, as a mild purgative, and treat swollen glands. The root was regarded as a tonic, aphrodisiac, and emmenagogue in the Unani tradition of the Indian medicinal system. Further, Ashwagandha has been also described as an Ayurvedic medicinal plant in the Ayurvedic Pharmacopoeia of India extending informed therapeutic usage and formulations. Despite the widespread ethnopharmacological usage of Ashwagandha, clinical pharmacokinetic parameters are lacking in the literature; hence, the findings of this study will be relevant for calculating doses for future clinical evaluations of Ashwagandha root extract. AimThis study aimed to develop a validated and highly sensitive bioanalytical method for quantifying withanosides and withanolides of the Ashwagandha root extract in human plasma to explore its bioaccessibility. Further to apply a developed method to perform pharmacokinetics of standardized Withania somnifera (L.) Dunal root extract (WSE; AgeVel®/Witholytin®) capsules in healthy human volunteers. MethodsA sensitive, reliable, and specific ultra-high pressure liquid chromatography-mass spectrometry (UHPLC-MS/MS) method was developed and validated for the simultaneous quantification of five major withanosides and withanolides (withanoside IV, withanoside V, withanolide A, withaferin A, and 12-deoxy-withastramonolide) in human plasma. Further for the study, eighteen healthy male volunteers (18–45 years) were enrolled in a non-randomized, open-label, single period, single treatment, clinical pharmacokinetic study and given a single dose (500 mg) of WSE (AgeVel®/Witholytin®) capsules containing not less than 7.5 mg of total withanolides under fasting condition. Later, pharmacokinetic profiles were assessed using the plasma concentration of each bioactive constituent Vs. time data. ResultsFor all five constituents, the bioanalytical method demonstrated high selectivity, specificity, and linearity. There was no carryover, and no matrix effect was observed. Furthermore, the inter-day and intra-day precision and accuracy results fulfilled the acceptance criteria. Upon oral administration of WSE capsules, Cmax was found to be 0.639 ± 0.211, 2.926 ± 1.317, 2.833 ± 0.981, and 5.498 ± 1.986 ng/mL for withanoside IV, withanolide A, withaferin A, and 12-deoxy-withastramonolide with Tmax of 1.639 ± 0.993, 1.361 ± 0.850, 0.903 ± 0.273, and 1.375 ± 0.510 h respectively. Further, withanoside V was also detected in plasma; but its concentration was found below LLOQ. ConclusionThe novel and first-time developed bioanalytical method was successfully applied for the quantification of five bio-active constituents in human volunteers following administration of WSE capsules, indicating that withanosides and withanolides were rapidly absorbed from the stomach, have high oral bioavailability, and an optimum half-life to produce significant pharmacological activity. Further, AgeVel®/Witholytin® was found safe and well tolerated after oral administration, with no adverse reaction observed at a 500 mg dose.

Potato Leaf Chlorophyll Content Estimation through Radiative Transfer Modeling and Active Learning

Leaf chlorophyll content (LCC) significantly correlates with crop growth conditions, nitrogen content, yield, etc. It is a crucial indicator for elucidating the senescence process of plants and can reflect their growth and nutrition status. This study was carried out based on a potato nitrogen and potassium fertilizer gradient experiment in the year 2022 at Keshan Farm, Qiqihar Branch of Heilongjiang Agricultural Reclamation Bureau. Leaf hyperspectral and leaf chlorophyll content data were collected at the potato tuber formation, tuber growth, and starch accumulation periods. The PROSPECT-4 radiative transfer model was employed to construct a look-up table (LUT) as a simulated data set. This was accomplished by simulating potato leaves’ spectral reflectance and chlorophyll content. Then, the active learning (AL) technique was used to select the most enlightening training samples from the LUT based on the measured potato data. The Gaussian process regression (GPR) algorithm was finally employed to construct the inversion models for the chlorophyll content of potato leaves for both the whole and single growth periods based on the training samples selected by the AL method and the ground measured data of the potatoes. The R2 values of model validation accuracy for the potato whole plantation period and three single growth periods are 0.742, 0.683, 0.828, and 0.533, respectively with RMSE values of 4.207, 4.364, 2.301, and 3.791 µg/cm2. Compared with the LCC inversion accuracy through LUT with a cost function, the validation accuracies of the GPR_PROSPECT-AL hybrid model were improved by 0.119, 0.200, 0.328, and 0.255, and the RMSE were reduced by 3.763, 2.759, 0.118, and 5.058 µg/cm2, respectively. The study results indicate that the hybrid method combined with the radiative transfer model and active learning can effectively select informative training samples from a data pool and improve the accuracy of potato LCC estimation, which provides a valid tool for accurately monitoring crop growth and growth health.

Synchrotron X-ray operando study and multiphysics modelling of the solidification dynamics of intermetallic phases under electromagnetic pulses

In this paper, we used synchrotron X-ray radiography and tomography to study systematically and in operando conditions the growth dynamics of the primary Al3Ni intermetallic phases in an Al-15wt%Ni alloy in the solidification process with magnetic pulses of up to 1.5 T. The real-time observations clearly revealed the growth dynamics of the intermetallics in time scale from millisecond to minutes, including phase growth instability, side branching, fragmentation and orientation alignment under different magnetic pulse fluxes. A multiphysics numerical model was also developed to calculate the alternating and cyclic Lorentz forces and stresses acting on the Al3Ni phases and the nearby melt due to the applied pulses. Combining the results of the operando experiments and modelling, for the first time, the differential forces between the growing Al3Ni phases and the nearby melt were quantified. The forces can create slip dislocations at the growing crystal front which can further develop into nm and µm crystal steps for initiating phase branching. Furthermore, the magnitudes of the shear stresses are strongly related to the size, morphological and geometric features of the growing Al3Ni phases. Dependent on the magnitude of the shear stresses, phase fragmentation could occur in a single pulse period or in multiple pulse periods via fatigue mechanism. This systematic research work elucidate some of the long-time debated hypotheses concerning intermetallic phases growth instability and phase fragmentation in pulse magnetic fields. The research establishes a robust theoretical framework for quantitative understanding of the intermetallic phase growth dynamics in solidification under pulse magnetic fields.

Fractional-order modelling and dynamic analysis on a typical beam structure incorporated with a semi-active particle damping equipment

Semi-active particle damping equipments exhibit considerable adaptability when implemented in flexible structures. However, their dynamic characteristics become complex due to the presence of a substantial quantity of particles within the damping equipment, and the influence of the internal magnetic field necessitates careful consideration. The fractional-order model of this kind of equipment is established, wherein the designed parameters kp and α are respectively associated with the filling ratio and the input current. Depending on the Hertz-Mindlin contact model, the multi-body dynamic issues inner the damping equipment are addressed using the Discrete Element Method, and then the fractional-order parameters kp and α are identified based on the energy distribution observed within a single vibration period. The numerical simulations, conducted using the fractional-order model, show a fundamental consistency with the experimental results. This alignment serves to validate the accuracy and feasibility of the fractional-order model. Finally, the fractional-order model is utilized to investigate the optimized value of the input current and to analyze the motion trajectory of the damping equipment under various scenarios. The results indicate that the optimized input current is approximately 2.5 A; and as the parameter kp and α increase, the motion trajectory of the system will rotate in a counterclockwise direction, accompanied by a gradual outward displacement of the outermost curve relative to the origin position.

Grain yield estimation of wheat-maize rotation cultivated land based on Sentinel-2 multi-spectral image: A case study in Caoxian County, Shandong, China

Establishing the remote sensing yield estimation model of wheat-maize rotation cultivated land can timely and accurately estimate the comprehensive grain yield. Taking the winter wheat-summer maize rotation cultivated land in Caoxian County, Shandong Province, as test object, using the Sentinel-2 images from 2018 to 2019, we compared the time-series feature classification based on QGIS platform and support vector machine algorithm to select the best method and extract sowing area of wheat-maize rotation cultivated land. Based on the correlation between wheat and maize vegetation index and the statistical yield, we screened the sensitive vegetation indices and their growth period, and obtained the vegetation index integral value of the sensitive spectral period by using the Newton-trapezoid integration method. We constructed the multiple linear regression and three machine learning (random forest, RF; neural network model, BP; support vector machine model, SVM) models based on the integral value combination to get the best and and optimized yield estimation model. The results showed that the accuracy rate of extracting wheat and maize sowing area based on time-series features using QGIS platform reached 94.6%, with the overall accuracy and Kappa coefficient were 5.9% and 0.12 higher than those of the support vector machine algorithm, respectively. The remote sensing yield estimation in sensitive spectral period was better than that in single growth period. The normalized differential vegetation index and ratio vegetation index integral group of wheat and enhanced vegetation index and structure intensify pigment vegetable index integral group of maize could more effectively aggregate spectral information. The optimal combination of vegetation index integral was difference, and the fitting accuracy of machine learning algorithm was higher than that of empirical statistical model. The optimal yield estimation model was the difference value group-random forest (DVG-RF) model of machine learning algorithm (R2=0.843, root mean square error=2.822 kg·hm-2), with a yield estimation accuracy of 93.4%. We explored the use of QGIS platform to extract the sowing area, and carried out a systematical case study on grain yield estimation method of wheat-maize rotation cultivated land. The established multi-vegetation index integral combination model was effective and feasible, which could improve accuracy and efficiency of yield estimation.

A matrix game‐based coordinated optimisation method of distribution networks with multiple flexible resources

AbstractThe ‘Electric energy substitution’ project in rural areas of northern China aims to replace coal‐fired heating with electric heating. However, this could potentially lead to congestion problems on the local distribution networks (DNs) due to an increase in heating loads. Instead of expanding the lines, flexible resources such as microgrids (MGs) and heat pumps (HPs) could provide auxiliary services in a more cost‐effective manner. A bi‐level optimisation model that coordinates DNs, MGs, and HP clusters is proposed to address this issue. In the lower level, MGs and HP clusters provide auxiliary services through competitive bidding to maximise their own income over multiple periods, considering a series of technical operational constraints and comfort constraints. In the upper level, DNs clear the market based on the bidding information to minimise its operational costs while guaranteeing network constraints. The bi‐level optimisation model is formulated as a multi‐agent matrix game problem, and the Win or Learn Fast‐Policy Hill‐climbing algorithm is used to achieve fast market equilibrium in a decentralised manner. Simulation results demonstrate that the proposed method can improve the revenue of MGs by up to 2.6 times compared to the single period matrix game method, and reduce the convergence time by up to 81.3% compared to the multi‐agent Q‐learning method.

Inflection points during a disruptive event: planning within the sales force

PurposeThis paper aims to investigate business-to-business sales executives’ navigation of challenges and changes in planning during two separate periods (prevaccine and postvaccine) of time, which were impacted by a disruptive event (the COVID-19 pandemic).Design/methodology/approachThis study uses a two-phase qualitative data collection approach. Thirteen executives, primarily from the Business-to-Business (B2B) manufacturing industry, were interviewed in phase one (2–3 months before the first COVID-19 vaccine). The second period of data collection was collected 4–5 months after vaccines became available.FindingsThe prevaccine business environment focused on short-term challenges, while the vaccine created exponential changes to long-term sales practices, suggesting the need to focus on critical inflection points that occur after the initial disruptive event.Research limitations/implicationsThis exploratory study is a step toward developing a deeper understanding of managing disruptive events within a business-to-business sales environment by stressing the importance of both the actual disruptive event and the inflection points that follow the event.Practical implicationsNew business models are constantly developing and evolving. However, this study suggests the biggest changes could occur after an inflection point from the disruption. Thus, firms need to consider different planning strategies before and after certain inflection points following a disruptive event. First, firms should adapt from their predisruption strategy to focus on short-term challenges during the initial phases of a disruption, likely halting most of the long-term planning. Second, inflection points create the need to move beyond short-term challenges and changes to focus on long-term changes. Third, long-term strategies and planning postinflection point will be different, and likely more complex, than long-term strategies and planning predisruption.Originality/valueMost studies look at a disruptive event through a single data collection period. This longitudinal study compares prevaccine and postvaccine thought processes to explore the impact of an inflection point.

Winter Wheat Yield Estimation Based on Multi-Temporal and Multi-Sensor Remote Sensing Data Fusion

Accurate yield estimation before the wheat harvest is very important for precision management, maintaining grain market stability, and ensuring national food security. In this study, to further improve the accuracy of winter wheat yield estimation, machine learning models, including GPR, SVR, and DT, were employed to construct yield estimation models based on the single and multiple growth periods, incorporating the color and multispectral vegetation indexes. The results showed the following: (1) Overall, the performance and accuracy of the yield estimation models based on machine learning were ranked as follows: GPR, SVR, DT. (2) The combination of color indexes and multispectral vegetation indexes effectively improved the yield estimation accuracy of winter wheat compared with the multispectral vegetation indexes and color indexes alone. The accuracy of the yield estimation models based on the multiple growth periods was also higher than that of the single growth period models. The model with multiple growth periods and multiple characteristics had the highest accuracy, with an R2 of 0.83, an RMSE of 297.70 kg/hm2, and an rRMSE of 4.69%. (3) For the single growth period, the accuracy of the yield estimation models based on the color indexes was lower than that of the yield estimation models based on the multispectral vegetation indexes. For the multiple growth periods, the accuracy of the models constructed by the two types of indexes was very close, with R2 of 0.80 and 0.80, RMSE of 330.37 kg/hm2 and 328.95 kg/hm2, and rRMSE of 5.21% and 5.19%, respectively. This indicates that the low-cost RGB camera has good potential for crop yield estimation. Multi-temporal and multi-sensor remote sensing data fusion can further improve the accuracy of winter wheat yield estimation and provide methods and references for winter wheat yield estimation.

Incidence of sustainability in university performance: evidence of stakeholders’ perceptions at Colombian private higher education institutions

Purpose This paper aims to find the incidence of university sustainability, as sustainability practices, in university performance at private universities. Design/methodology/approach Quantitative research using structural equation modelling. Data collection and analysis followed sustainability and performance scales from previous research. The scales were validated by surveying students, teachers and administrative staff of five private universities in Medellin, Colombia. The responses (i.e. 5,344 useful answers) were collected between April 2019 and December 2020 and analysed using the Smart partial least square (PLS) software and the PLS calculation methodology. Findings The results confirmed the reliability and validity of the sustainability and performance university measurement models and validated the dimensions proposed to determine sustainability and performance holistically in private universities. The results confirmed that universities implementing sustainability holistically in their system positively impact their performance as higher education institutions. The university sustainability is forecasting the University Performance in about 60% of the universities analysed, with a considerable contribution from sustainability in outreach and strategic management. Research limitations/implications This study was cross-sectional and empirically validated the model of sustainability and performance at five private universities in a single period and territory. A broader validation from longitudinal studies considering other universities in Colombia and Latin America is suggested to understand local and regional trends better. Practical implications Results provided a model for better understanding the incidence of sustainability in performance holistically at private universities in developing countries such as Colombia. In addition, the proposed dimensions and model could help regional decision-making on higher education. Originality/value To the best of the authors’ knowledge, this paper is one of the first attempts relating a structural equation model and inter-university research on the incidence of sustainability in private university performance. This work contributes to a local consensus on sustainability and performance models at private universities. Furthermore, from this research emerged a joint policy framework for incorporating sustainability holistically and regionally as an effective strategy for universities and their commitment to sustainable development.

Critical periods in planar polynomial centers near a maximum number of cusps

We provide the best lower bound for the number of critical periods of planar polynomial centers known up to now. The new lower bound is obtained in the Hamiltonian class and considering a single period annulus. This lower bound doubles the previous one from the literature, and we end up with at least n2−2 (resp. n2−2n−1) critical periods for planar polynomial systems of odd (resp. even) degree n. Key idea is the perturbation of a vector field with many cusp equilibria, whose construction is by itself a nontrivial construction that uses elements of catastrophe theory.

Noisy soliton pulsation and its dynamics in a mid-infrared ultrafast fiber laser

We demonstrate the real-time dynamics of a unique pulsating soliton state featuring noisy behaviors in a mid-infrared ultrafast fiber laser at 2 μm. By virtue of the time-stretch dispersive Fourier transform method, the pulsating behaviors of the noisy solitons are investigated. We find that the noisy pulsating solitons are characterized by a special optical spectrum. The shot-to-shot spectra and pulse energy of these pulsating noisy pulses can evolve periodically with the roundtrips. Besides, the real-time optical spectra within a single period exhibit irregular fluctuations in terms of the spectral profile and intensity, suggesting that the pulsating solitons are made up of noisy wave packets with chaotic features. These results can further enrich the pulsating soliton dynamics and also give new insights into the nonlinear pulse dynamics of mid-infrared ultrafast fiber lasers.

Male fertility advantage within and between seasons in the perennial androdioecious plant Phillyrea angustifolia.

Androdioecy, the co-occurrence of males and hermaphrodites, is a rare reproductive system. Males can be maintained if they benefit from a higher male fitness than hermaphrodites, referred to as male advantage. Male advantage can emerge from increased fertility owing to resource reallocation. However, empirical studies usually compare sexual phenotypes over a single flowering season, thus ignoring potential cumulative effects over successive seasons in perennials. In this study, we quantify various components of male fertility advantage, both within and between seasons, in the long-lived perennial shrub Phillyrea angustifolia (Oleaceae). Although, owing to a peculiar diallelic self-incompatibility system and female sterility mutation strictly associated with a breakdown of incompatibility, males do not need fertility advantage to persist in this species, this advantage remains an important determinant of their equilibrium frequency. A survey of >1000 full-sib plants allowed us to compare males and hermaphrodites for several components of male fertility. Individuals were characterized for proxies of pollen production and vegetative growth. By analysing maternal progeny, we compared the siring success of males and hermaphrodites. Finally, using a multistate capture-recapture model we assessed, for each sexual morph, how the intensity of flowering in one year impacts next-year growth and reproduction. Males benefitted from a greater vegetative growth and flowering intensity. Within one season, males sired twice as many seeds as equidistant, compatible hermaphroditic competitors. In addition, males more often maintained intense flowering over successive years. Finally, investment in male reproductive function appeared to differ between the two incompatibility groups of hermaphrodites. Males, by sparing the cost of female reproduction, have a higher flowering frequency and vegetative growth, both of which contribute to male advantage over an individual lifetime. This suggests that studies analysing sexual phenotypes during only single reproductive periods are likely to provide inadequate estimates of male advantage in perennials.

Hierarchical fusion evaluation and optimization of radar intelligent tracking algorithm via hybrid weight design mechanism

In this paper, a hybrid weight design and optimization mechanism is proposed to ensure a better application effect in the multi-level weighted evaluation/optimization process of intelligent neural network (NN) guidance algorithm. According to different target tracking scenarios, the tracking index are divided into different periods, a single period score is given according to a linear-nonlinear hybrid scoring mechanism. Furthermore, in a single index, the internal scores of different time periods are weighted and fused for the second time to obtain the index overall score. Finally, the third weighted fusion of the multi-index scores is used to obtain the comprehensive score of the algorithm. Design the algorithm parameter evaluation case sets, repeat the above compound weighting, obtain the case with the highest comprehensive score. Finally, the algorithm is optimized by the highest score case. In the hybrid weight design mechanism, the objective grey correlation first defines the weight range, then the subjective expert decision method with local extreme expert elimination and standard deviation global test for double optimization finally ensures the weight reliability of the hierarchical evaluation optimization. The evaluation optimization experiment using fuzzy NN radar seeker verifies the effectiveness of the method.

Оконное стекло с поселения Горзувиты и Мангупского городища в Крыму: химический состав, происхождение и хронология в историко-культурном контексте

Chemical composition of 39 window panes of the Early and Middle Byzantine periods was studied with SEM-EDS technique. They originate from the Gorzuvity settlement in the Crimea Southern coast with the ruins of two churches, and Mangup, the largest medieval fortress in the SW Crimea. The presence of glass of groups Foy-3.2/2.1 and HIMT suggests that the earliest structures with glazed windows could have emerged on Mangup in the 5th century at the latest — i. e., before the construction of the Byzantine fortress. A homogenous composition of glass from Gorzuvity suggests a single period of glazing windows of structures existing here — the “lower” church with a shrine dated probably to the 11th century (terminus ante quem for the church construction) and some stone structures at the settlement. 37 samples represent natron glass of the Egyptian origin. Most of window panes are related to the 9th—10th/11th cc. Their glass belongs to the series Foy-2.2, the result of the recycling of the earlier glass of the 2nd half of the 5th/6th — mid-7th centuries (series Foy-2.1). It suggests that the remains of monumental structures of the early Byzantine period (window panes and probably tesserae) were used as raw materials during the construction campaign at Gorzuvity and Mangup in the middle Byzantine period. Two fragments from Mangup of mixed-alkali composition originate from the contexts of the 15 th c., where they could get from disturbed earlier deposits.

284 A Meta-Regression Analysis to Evaluate the Effects of Narasin on Grow-Finish Pig Performance

Abstract Ionophores are a separate class of non-medically important antibiotics used in animal production to increase growth rate. Narasin (Skycis; Elanco Animal Health, Greenfield, IN) is an ionophore labeled for increased rate of body weight gain and improved feed efficiency in growing-finishing swine. The mode of action of this ionophore is to increase energy availability by altering volatile fatty acid production in the hindgut in favor of propionate, which is the most efficient product of fermentation. Therefore, a meta-regression analysis was conducted to evaluate the effects of narasin inclusion in growing-finishing pig diets to predict average daily gain and feed efficiency. A database was developed that contained 21 papers from 2012 to 2021 representing 308 observations including both individual period data as well as overall trial data. For statistical analysis two models were created. The individual period model considered only data with single continuous narasin feeding periods while the overall trial model considered complete data sets representing periods with and without narasin feeding. Regression model equations were developed with the GLIMMIX procedure of SAS (Version 9.4, SAS institute, Cary, NC). Predictor variables were assessed with a step-wise manual forward selection for model inclusion. Predictor variables were required to provide an improvement of at least 2 Bayesian information criterion units to be included in the final model. For individual period data for G:F, the model selected included concentration of narasin in the feed, ADG and ADFI of the control group not provided narasin, and average BW of the control group categorized into greater than 105 kg or less than 105 kg (Table 1). There were 2 competing models to predict improvement in overall G:F. For model 1, significant predictors included concentration of narasin in feed and ADG of the control group. Model 2 for overall G:F included concentration of narasin in feed, ADG and ADFI of the control group. For the individual period model that predicted ADG, the predictors were concentration of narasin in the feed, ADFI, G:F of the control group and BW category for feeding period. The best fitting ADG model using the overall trial data included concentration of narasin in feed, ADFI and G:F of the control group, and feeding duration categorized as longer than 65 days or shorter than 65 days. Together, these models can be used to predict the response to narasin supplementation in finishing pigs. Based on the results, the overall response to narasin inclusion rate for ADG and G:F is quadratic in nature. Additionally, as ADG and G:F increase, the response to narasin supplementation decreases. In summary, using average values from the database for predictor variables, this meta-analysis demonstrates narasin would be expected to improve overall G:F from 0.74 to 1.13% and ADG from 1 to 3%.

Examining the Accuracy of Using a Single Short-Term Historical Flow Period to Assess the Nile’s Downstream Water Deficit from GERD Filling: A Technical Note

Increasing water and energy demands, hydroclimatic fluctuations, damming, and usage rights disputes present major challenges in managing transboundary rivers worldwide. Of particular interest is the Eastern Nile River Basin (ENRB), which is subject to broad debate over which modeling approach should be applied to resolve the disparities in transboundary water management among the river’s riparian nations, under increased upstream damming. Several studies have simulated the downstream High Aswan Dam (HAD) storage change during the Grand Ethiopian Renaissance Dam (GERD) filling under different hydrological conditions. However, their findings diverge regarding the impacts of GERD filling on HAD storage, especially when considering a specific, naturalized, historical 10-year period to represent the average flow condition used, as a benchmark for assessing potential downstream impacts. Our extended analysis of the Nile flow historical records demonstrates that considering a single historical 10-year period to simulate the downstream water budget, as performed in Wheeler et al. (Nat Commun 11:5222, 2020, https://doi.org/10.1038/s41467-020-19089-x), widely communicated to policymakers as a robust proof that GERD filling will not generate a deficit at HAD under average flow conditions, is inconclusive as it strongly depend on the selection of the historical inflow period, due to the river high interannual flow variability. Our simulation results of 20 average/near average historical flow periods in Wheeler et al. (Nat Commun 11:5222, 2020, https://doi.org/10.1038/s41467-020-19089-x)’s datasheet indicates that 60% of them generates a downstream water deficit ranging from 0.5 to 14.5 BCM under the same modeling conditions and filling policy. Therefore, considering the simulation results of multiple flow sequences is crucial for accurately reflecting the impact of the Nile’s high interannual flow variability on downstream water deficit assessments, thereby settling the disparities in transboundary water management forecasts for the impacts of GERD filling and operation.

Multi-mode microcavity frequency engineering through a shifted grating in a photonic crystal ring.

Frequency engineering of whispering-gallery resonances is essential in microcavity nonlinear optics. The key is to control the frequencies of the cavity modes involved in the underlying nonlinear optical process to satisfy its energy conservation criterion. Compared to the conventional method that tailors dispersion by cross-sectional geometry, thereby impacting all cavity mode frequencies, grating-assisted microring cavities, often termed as photonic crystal microrings, provide more enabling capabilities through mode-selective frequency control. For example, a simple single period grating added to a microring has been used for single frequency engineering in Kerr optical parametric oscillation (OPO) and frequency combs. Recently, this approach has been extended to multi-frequency engineering by using multi-period grating functions, but at the cost of increasingly complex grating profiles that require challenging fabrication. Here, we demonstrate a simple approach, which we term as shifted grating multiple mode splitting (SGMMS), where spatial displacement of a single period grating imprinted on the inner boundary of the microring creates a rotational asymmetry that frequency splits multiple adjacent cavity modes. This approach is easy to implement and presents no additional fabrication challenges compared to an unshifted grating, and yet is very powerful in providing multi-frequency engineering functionality for nonlinear optics. We showcase an example where SGMMS enables OPO across a wide range of pump wavelengths in a normal-dispersion device that otherwise would not support OPO.