Performance Trends Research Articles

Performance trend of the family physician referral system before and during the COVID-19 pandemic: a study in northern Iran

BackgroundConsidering the challenges of the referral system in the family physician program and the impact of COVID-19 pandemic on the performance of the relevant ministry’s programs, it is necessary to assess the performance of the referral system. This study was conducted with the aim of investigating the performance of the family physician referral system before and during COVID-19 in Golestan province.MethodsThe present repeated cross-sectional study was conducted on secondary data Recorded of 786,603 cases referred and cared by family physicians (including information on physicians’ and midwives’ visits, percentage of prescriptions and other information) in Golestan province from 2017 to 2022 in a census and retrospective manner. Data were collected using the reference ratio checklist and analyzed with SPSS 23 software at a significance level of less than 0.05.ResultsReferral to 10 types of medical specialties and 10 indicators of family physicians referral before and during COVID-19 were investigated. The highest and lowest percentages of referrals by family physicians were belonged to the surgical (17.6%) and infectious (2%) specialists before COVID-19, and internal medicine (15.07%) and urology (3%) specialists during COVID-19, respectively. Referral due to physician’s diagnosis increased by 19.3% compared to before Covid-19, target group increased by 0.86%, care decreased by 2.69% and reverse referral decreased by 36.1%. The amount of population covered by rural insurance, the amount of visits to midwives, the percentage of electronic appointments in the post-Covid-19 years have changed significantly compared to before.it (P-Value < 0.05).ConclusionThe present study showed that the COVID-19 pandemic had a significant impact on family physician referral indicators, such as the process of referral to specialists, drug prescriptions, insurance coverage, one-time service population, and patient care, which can be used to eliminate the weaknesses and Strengthening the strengths of the programs being implemented in the face of possible pandemics is very useful and effective and can be used in the country. Finally, the results obtained from this research provide evidence to discuss the importance of the family physicians care and referral system in the face of special conditions for quality control in health policies.

Vibrational Analysis on Cooling Fan with Induced Mechanical Faults

Abstract This paper reports the investigation of different mechanical faults such as unbalanced loading, broken blades, and deformed blades induced in a fan using vibration analysis. The fan used in this study was a CPU cooling fan as a representation of a basic fan system giving an idea of vibration signatures when it is subjected to faults conditions. This study assists in developing the techniques of condition monitoring for the diagnosis of failures and faults in fan systems while logging the operating status and trend in performance. The investigation is carried out in the turbine testing lab using a Tri-axial accelerometer and a commercial Intel® CPU cooling fan consisting of 7 blades. The fan was run at different RPMs with normal and fault conditions like unbalanced loading conditions induced by adding mass of different weights, breakage of blades, deformation of blades, and holes in the blades. These faults are induced to simulate various mechanical faults that frequently occur in fan-based systems. The vibration data obtained from the accelerometer are filtered and the time series of acceleration values are plotted using MATLAB. For further analysis of data, the Fast Fourier Transform is done to evaluate the peaks of vibration signals in normal and fault conditions. Vibrational amplitude in fault conditions like Hole-2 has 4.5 times higher amplitude than normal and Cut-2 has 31.5 times higher amplitude.

Effect of NMC-doping Concentration on the Structural Feature and Electrical Properties of Lithium Iron Phosphate Cathode for Use in Lithium-ion Batteries

T his study investigates the synthesis of Lithium Iron Phosphate (LFP) with NMC-doped cathode materials, aiming to enhance the performance of lithium-ion batteries. The NMC content was varied from 0.02 to 0.10wt%, and 1wt% of (NH4)3PO4 was added to all conditions to prevent phosphate loss during the calcination process. The composite powder was prepared using a straightforward mixed oxide method, with a calcination temperature of 600 °C for 5 hours under an argon gas flow. X-ray diffraction (XRD) analysis confirmed the successful formation of pure LFP with an orthorhombic crystal structure, devoid of any secondary phases. To further explore the impact of NMC doping on the structural characteristics, FTIR and Raman spectroscopy were employed. Results revealed that increasing NMC doping concentration beyond 0.02wt% led to the broadening of the PO43− symmetric stretching band at approximately 947 cm−1, indicating a higher degree of disorder in the LFP structures. This disorder was found to adversely affect electrochemical performance, resulting in decreased discharge capacity and increased impedance, as determined by electrochemical impedance spectroscopy (EIS), with higher concentrations of NMC and (NH4)3PO4. Scanning Electron Microscopy (SEM) analysis unveiled the presence of agglomerated particles ranging in size from 0.5 to 0.9 microns. Optimal conditions were identified with the addition of NMC doped at 0.02wt%, which exhibited a discharge capacity of approximately 119.41 mAh/g at 0.2 C, along with a low impedance of 200 Ohm. Moreover, the 0.02wt% sample demonstrated a promising linear trend in cycle performance, suggesting its potential for future applications in lithium-ion batteries.

Performance evaluation of fracturing fluids in the presence of NaCl, CaCl2 and KCl as hydrate inhibitors for extremely low temperature stimulation applications

Naturally occurring gas hydrates are established as an abundant reserve of natural gas. Production initiatives raised challenges such as low production rate, freezing problems, water, and sand production along with geomechanical concerns. Recent studies suggest that fracturing the sediment can significantly improve the conductivity and productivity of such reserves. This study is an initiative to verify the suitability of conventionally used polymer (guar) for fracturing at extremely low temperatures along with the integration of widely available gas hydrate inhibitors for efficient stimulation. Established inhibitors such as NaCl, CaCl2 and KCl were introduced to linear and crosslinked gels to study their compatibility with the reference guar-based gels. The inhibitor integrated linear gel samples demonstrated similar performance trends to that of the reference gel establishing their compatibility with the polymer, whereas the inhibitor integrated crosslinked samples displayed deswelling nature. The low concentration inhibitor integrated linear gel samples performed superior to the reference gel whereas the high concentration sample inhibited the swelling performance of the polymer. Both the reference and inhibitor integrated linear gel samples gradually disintegrated after 48 h leaving behind soft cloudy residue, whereas the inhibitor integrated crosslinked samples rapidly released water and contracted into a solid residue which can cause serious flow related disruptions during operations and apparently damage the conductivity of the sediment for long term. This study delivers crucial understanding on how various salts interact with guar polymers at low temperatures and whether their presence can be a boon or bane during the design of a fracturing fluid.

Prediction of accessibility testing using a generalized linear model for e-government

Using the United Nations’ Online Services Indicator (OSI) as a benchmark, the study analyzes Jordan’s e-government performance trends from 2008 to 2022, revealing temporal variations and areas of discontent. The research incorporates diverse testing strategies, considering technological, organizational, and environmental factors, and aligns with global frameworks emphasizing usability, accessibility, and security. The proposed model unfolds in three stages: data collection, performing data operations, and target selection using the Generalized Linear Model (GLM). Leveraging web crawling techniques, the data collection process extracts structured information from the Jordanian e-government portal. Results demonstrate the model’s efficacy in assessing accessibility and predicting web crawler behavior, providing valuable insights for policymakers and officials. This model serves as a practical tool for the enhancement of e-government services, addressing citizen concerns and improving overall service quality in Jordan and beyond.

Implantation of S1AIS has priority as a sacroiliac joint fixation technique.

The sacral alar-iliac screw (SAIS) fixation technique has evolved from spinopelvic fixation which originated from S2AIS to sacroiliac joint fixation, with more reports regarding its application of S2AIS than S1AIS. However, there is a lack of comparative evidence to determine which technique is superior for sacroiliac joint fixation. This study aimed to determine which of the screws was superior in terms of implantation safety and biomechanical stability for sacroiliac joint fixation. CT data of 80 normal pelvises were analyzed to measure the insertable range, trajectory lengths and widths of both S1AIS and S2AIS on 3D reconstruction models. Φ 6.5mm and 8.0mm screws were implanted on the left and right sides of fifty 3D printed pelvic models respectively to observe for breach of screw implantation. Ten synthetic pelvis models were used to simulate type C Tile injuries, and divided into 2 groups with an anterior plate and posterior fixation using one S1AIS or S2AIS on each side. The stiffness and maximum load of the plated and fixated models were measured under vertical loading. The trajectory lengths and widths of the S1AIS and S2AIS were similar (p > 0.05) and there was no breach for Φ 6.5mm SAIS. However, both the insertable range and trajectory length on the sacral side of S2AIS (234.56 ± 10.06mm2, 40.97 ± 2.81mm) were significantly less, and the breach rate of the posterior lateral cortex of the Φ 8.0mm S2AIS (46%) was significantly higher than the S1AIS (307.55 ± 10.42 mm2, 42.16 ± 3.06mm, and 2%, p < 0.05). The stiffness and maximum load of S2AIS were less than S1AIS but the difference was not statistically significant (p > 0.05). S1AIS and S2AIS have similar screw trajectories and stability. However, S1AIS has a larger insertable range, less breach of the posterior lateral sacral cortex and longer trajectory length on the sacral side than S2AIS, which indicates S1AIS has higher implantation safety and a trend of better mechanical performance over S2AIS for sacroiliac joint fixation. Furthermore, S2AIS with an excessively large diameter should be used with caution for sacroiliac joint fixation.

Screens and Preschools: The Bilingual English Language Learner Assessment as a Curriculum-Compliant Digital Application.

The increase in digital tools in early childhood education highlights the need for evidence-based assessments that support cognitive development and align with educational requirements and technological advances. This study contributes to the evaluation of the Bilingual English Language Learner Assessment (BELLA), designed to enhance early learning through curriculum-aligned tasks in preschool-aged children. Data were collected from 17 schools, including 506 preschool children, using a mixed-model approach to assess BELLA's capacity to appraise early numeracy, literacy, science, and social/emotional development. Analyses included a three-way ANOVA to examine the effects of sex, age, and sub-domain on pass rates and mixed-effects models to evaluate interactions between age and domain. The results indicated a significant effect of age on performance across all domains, with older children demonstrating higher pass rates (p < 0.0001). No significant gender bias was detected. The interaction between age and domain was also significant (p < 0.0001), suggesting domain-specific age-related performance trends, which aligns with internal validity requirements. These findings position BELLA within the growing body of literature on digital media use in early childhood assessment and education, highlighting its potential as a curriculum-compliant digital assessment tool that evaluates and supports cognitive development without a gender bias. This study contributes to the field by providing empirical evidence of BELLA's effectiveness and suggesting future research directions, including the exploration of its bilingual (and potentially multilingual) applications and external validation against existing evidence-based assessments.

Pursuing China's provincial sustainable development goals within a safe and just operating space: Past, present and future

As emphasized by the challenging sustainable development agenda, countries are facing a complicated combination of environmental stress and social challenges, leading the Earth system towards an unsustainable path. Therefore, it is crucial to accurately assess past fluctuations contributing to current situations and apprehend plausible future implications. This study integrates safe and just operating space (SJOS) with Sustainable Development Goals to depict multiple “windows” of environmental and social evolution in different historical periods, with 31 provinces in China as a case study. Then, we track the spatiotemporal evolution trajectory of environmental performance and social well-being in each province from 2012 to 2021. The Long Short-Term Memory (LSTM) model is utilized to capture the temporal relationships between various indicators and to forecast the spatial trends of SJOS in the provinces from 2022 to 2030. Research findings indicate that: (1) over the 2012–2021 period, the environmental performance of the majority of provinces far exceeds the warning thresholds, with no province falling within all threshold boundaries simultaneously. The phosphorus cycle is the most challenging boundary, with only 6.8% of provinces within the safe boundary over the past 10 years. In comparison, freshwater use performs the best, with 80% of provinces staying within the threshold. (2) Social well-being generally improves across all provinces from 2012 to 2021, but the spatial and temporal trajectories are more varied. All provinces meet the thresholds for the food security and employment indicators. However, none of the provinces meet the standard for the social equity indicator. (3) Over the 2022–2030 projection period, environmental performance and social well-being trend in opposite directions across provinces. This culminates in no province being entirely within the safe and just space by 2030. Sanitation shows the most significant change compared to other indicators. Xinjiang had the largest improvement at 59.12%, while Tianjin had the most significant downward trend at 53.88%. Adjustments in national policies and priorities are essential if China wants to accomplish the sufficiency of biophysical resources whilst ensuring social equity in the access and exploitation of these resources.

Health, Performance Ratings and Approachability of 50-60-Year-Old Sedentary Adults (ActIv-Study): Key Insights for Health Economy and Exercise Promotion.

Despite significant prevention efforts, the numbers of physically inactive individuals, chronic illnesses, exhaustion syndromes and sick leaves are increasing. A still unresolved problem with exercise promotion is the low participation of sedentary persons. This collective term covers heterogeneous subgroups. Their engagement with movement campaigns and resistance to change are influenced by numerous factors. Our aim was to analyse survey data on health, performance, lifestyle habits and the approachability to physical activity campaigns obtained from the Germany-wide ActIv survey. From 2888 study participants aged 50-60 years, 668 persons were categorised into the subgroups "never-athletes", "sports-dropouts", "always-athletes" and "sports-beginners". Large and significant group differences were found for BMI, assessment of quality of life, health and fitness, risk factors and health problems. In total, 42.5% of "never-athletes" and 32.5% of "sports-dropouts" did not state any barriers to sport. There are substantial disparities between the non-athlete groups in terms of their motivation to exercise. In contrast, there are comparatively minor differences in motivation between "sports-dropouts" and "sports-beginners", whose health and fitness are the primary motivators for sport. Our analyses suggest that (i) negative health and performance trends cannot be compensated for by appeals for voluntary participation in exercise programmes and (ii) powerful incentive systems are required.

Turbofan Performance Estimation Using Neural Network Component Maps and Genetic Algorithm-Least Squares Solvers

Computational models of turbofans that are oriented to assist the design and testing of innovative components are of fundamental importance in order to reduce their environmental impact. In this paper, we present an effective method for developing numerical turbofan models that allows reliable steady-state turbofan performance calculations. The main difference between the proposed method and those used in various commercial algorithms, such as GasTurb, GSP 12 and NPSS, is the use of neural networks as a multidimensional interpolation method for rotational component maps instead of classical β parameter. An additional aspect of fundamental importance lies in the simplicity of implementing this method in Matlab and the high degree of customization of the turbofan components without performing any manipulation of variables for the purpose of reducing the dimensionality of the problem, which would normally lead to a high condition number of the Jacobian matrix associated with the nonlinear turbofan system (and, thus, to significant error). In the proposed methodology, the component behavior can be modeled by analytical relationships and through the use of neural networks trained from component bench test data or data obtained from CFD simulations. Generalization of rotational component maps by feedforward neural networks leads to an average interpolation error up to around 1%, for all variables. The resulting nonlinear system is solved by a combined genetic algorithm and least squares algorithm approach, instead of the standard Newton’s method. The turbofan numerical model turns out to be convergent, and results suggest that the trend in overall turbofan performance, as flight conditions change, is in agreement with the outputs of the GSP 12 software.

Benchmarking of Aerodynamic Models for Isolated Propellers Operating at Positive and Negative Thrust

Operating a conventional propeller at negative thrust results in the operation of positively cambered blade sections at negative angles of attack, leading to flow separation. Consequently, accurately simulating the aerodynamics of propellers operating at negative thrust poses a greater challenge than at positive thrust. This study offers a comprehensive assessment of the aerodynamic modeling capabilities of numerical methods, spanning low to high fidelity, for computing propeller performance across both positive and negative thrust regimes. Low-fidelity methods, namely, blade-element momentum and lifting line theories, effectively predict propeller performance trends at positive thrust. However, they fail to capture trends at negative thrust beyond the maximum power output point due to the neglect of three-dimensional flow effects. Both steady and unsteady Reynolds-averaged Navier–Stokes (RANS) simulations with y+<1 perform well across both positive and negative thrust conditions, with errors below 2% for both thrust and power magnitudes near the maximum power output point. Lattice-Boltzmann very-large-eddy simulations (LB-VLESs) with y+≤10 exhibit excellent agreement with experimental data with less than 1% error near the maximum power output point but with significant computational costs. Conversely, LB-VLESs with y+≥15 offer a more economical approach to capture general trends with the computational cost of the same order as unsteady RANS. However, wall models introduce errors in modeling flow separation, leading to a 16% overestimation of power magnitude near the maximum power output point. The results highlight the necessity of using tools with increased fidelity levels when considering propeller operation at negative thrust compared to the conventional positive thrust regime.

A deep belief network-based energy consumption prediction model for water source heat pump system

To achieve optimal energy efficiency in buildings, accurately forecasting the energy consumption of air conditioning systems is crucial. This study develops an energy consumption prediction model based on a deep belief network, which is constructed according to the principles of a restricted Boltzmann machine. Actual experimental data from a water source heat pump system are collected, and feature variables are selected. The study discusses the impact of model parameters and training set sizes on the performance of energy consumption prediction model. Additionally, the trend in model prediction performance is analyzed through parameter adjustments. The results show that the coefficient of determination (R2) for the optimized model has increased to 0.585. The mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE) have been reduced to 6.311, 2.512, and 1.625, respectively. The deep belief network energy consumption prediction model outperforms other common machine learning models for water source heat pump systems.

Environmental performance and trends of the world's semiconductor foundry industry

AbstractThe semiconductor foundry industry faces the challenge of reducing its high environmental impact, mainly due to its energy‐ and water‐intensive processes and significant generation of waste. To date, no other study has focused on the assessment of the environmental performance and related historical trends of this industry as a whole. Methodologically, the first step was to analyze and process a large quantity of economic, production, and environmental data, available in the Corporate Social Responsibility reports of a companies’ sample, highly representative of the entire world's foundry industry (about 70% of the global revenue of the related sector). It was thus possible to calculate, using a common manufacturing index (MI) and after appropriate data processing, some key performance indicators, along a significant decade (2012–2021), marked by deep political, economic, and health crises. Some of the main findings of this study are that, over this 10‐year period, the increases in technological capacity (patents), wafer production, and revenue (400%, 183%, and 172%, respectively) are matched by a significant increase in hazardous waste generation per MI (20%; 239% in absolute value) and a much larger increase in general waste generation per MI (135%; 568% in absolute value). The indicators of energy, water, and revenue per MI are substantially unchanged. A substantial decrease occurs in GHG1&amp;2 emissions per MI (−32%), mainly due to significant investments in renewable energy sources. The findings of this research could help and guide upcoming sustainability policy decisions and encourage business‐to‐business collaboration and the adoption of better environmental production practices.

A novel LFSSA-LSTM algorithm for the remaining useful life prediction of lithium-ion batteries in whole life cycle

The accurate prediction of the remaining useful life (RUL) of lithium-ion batteries is essential to improve the safety of battery systems and optimize battery management strategies. Therefore, a new algorithm combining Sparrow search algorithm (SSA) improved by the Levy flight method and long short-term memory neural network (LSTM) is proposed in this paper. By extracting the National Aeronautics and Space Administration (NASA) battery aging datasets, the battery correlated health characteristics are obtained, and the deterioration trend of battery performance is effectively described. The sparrow search algorithm improved by the Levy flight method enhances the ability of the algorithm to jump out of the optimal solution. By using the improved algorithm, the hyper-parameter optimization problem of the long short-term memory network is solved, and the accuracy of the algorithm is improved. Finally, the probability density function is used to predict the remaining useful life of lithium-ion batteries, which effectively prevents the uncertainty caused by a single prediction result. Compared with long short-term memory neural network and the one optimized by a traditional sparrow search algorithm, the mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE) of the proposed algorithm are kept at 1.77 %, 2.24 %, and 1.25 %, respectively. The results indicate that the algorithm has better accuracy and fitting performance.

Financial Reporting, Tracking, and Analysis Practices Effect on Financial Performance of Commercial State Corporations in Kenya

In Kenya, legislative acts by parliament establish state corporations to promote social and economic progress. The state corporations advisory committee has identified eight distinct categories of these entities, which include financial, commercial, industrial, regulatory, public universities, training and research, service, regional development authorities, as well as tertiary education corporations. Out of the 33 state corporations in commercial and manufacturing category, 18 fall under manufacturing while 15 are commercial-oriented and therefore by their operational nature expected to make profits or operating surplus. The study focused on the fifteen (15) profit-making state corporations. Most commercial state corporations are in a state of perennial loss-making. Their financial performance trend between 2016-2020, shows that out of the 15 corporations in the commercial sector, only four (26.67%) are sustainable from their operations. This leaves over 73.33% of them struggling to survive and have to depend on government funding to address their liquidity challenges. This study sought to assess the impact of financial reporting and analysis on the financial performance of commercial state corporations in Kenya. The study assumed a descriptive study design. The study used a census procedure since all fifteen State Corporations under the commercial category were studied. Data was analysed using descriptive and inferential statistics. The inferential statistics results indicate that financial reporting and analysis have a positive and statistically significant effect on financial performance of commercial SOEs. The study found that improved financial performance was observed upon conducting periodical operational budget estimations, capital project estimations, periodical cash flow projections, and comparison of actual costs and budget variance analysis. The management and finance department to ensure that financial reporting processes are strengthened to enhance accuracy, openness, and compliance with governing requirements.

Evaluation of Trend of Foreign Exchange Reserve and Shipping Industry Trade Performance in Nigeria

This study focused on evaluation of the trend of Foreign Exchange Reserve (FX) and performance of shipping industry trade through examining the export and import trades within the periods 2011 to 2022. The objectives were to determine the correlation between trend values of FX with export and import shipping trades in Nigeria. Provisional data on Foreign Exchange Reserve, export and import trades from World Bank, CBN and Trend Economy were analyzed using spearman’s rank correlation coefficient analysis and it was observed that Foreign Exchange positively influences export and import shipping trades, however, the study infers that the impacts were not significant at 0.05 (2-tailed) Significance level. It concludes that the positive correlations between the data variables informs that decrease in FX influences decrease in export and import trade which also retar economic growth, development and reduced people’s standards of living in Nigeria. However, the reserve becomes the case. The study recommends immediate policy adjustment to hold and maintain strong Foreign Exchange which could boost country’s reserve for better performance of the shipping industry and other sectors of the economy.

The Effects of Liquid Density and Impeller Size with Volute Clearance on the Performance of Radial Blade Centrifugal Pumps: An Experimental Approach

This study was carried out to experimentally investigate the effect of impeller size with volute clearance and liquid density on the performance of radial blade centrifugal pumps. Three impeller sizes of 121.54mm, 109.38mm and 97.23mm with respective volute clearance of 6mm, 12mm and 18mm were considered, and five different liquid blend which comprise of water, two liquids that are denser than water and two other liquids that are less-dense than water (with respective liquid densities of: 1197 kg/m3 , 1097 kg/m3 , 1000kg/m3 , 898.2 kg/m3 and 798.4 kg/m3 ). In the experimental set-up, the pump flow capacity were varied from 12m3 /hr to 62m3 /hr at interval of 5m3 /hr and the corresponding pump power consumption, attained pump head were recorded and pump efficiency were determined. Microsoft excel was used to evaluate the trend, performance trend was used to develop the pump performance model showing the relationship between the various parameters. The results from the investigation revealed that with the various impeller sizes of 121.54mm, 109.38mm and 97.23mm of respective volute clearance of 6mm, 12mm and 18mm, the attained optimum efficiency were 74.42%, 54.78 and 33.54% respectively at a correspondence optimum pump head of 23.66m, 20.60m and 18.87m. The results also showed that there is a direct relationship between pump power consumption and process liquid density, while showing an inverse linear relationship between the pump instantaneous start up power and impeller diameter. It was therefore concluded among others that liquid with higher density will usually require higher power to initiate and maintain flow at constant flow rate and impeller size. It is then recommended among others that pump designers, application engineers and users of centrifugal pumps should consider possible increase in pump power consumption when working with a process application that has higher tendency for dynamic increase on the process fluid density.

TRENDS IN ESG PERFORMANCE REPORTING (ENVIRONMENT SOCIAL AND GOVERNANCE) IN ENTERPRISE

Implementation of ESG principles is essential for the Republic of Moldova to promote sustainable development, environmental protection, social responsibility and effective governance. This not only strengthens the country's position in the international community, but also contributes to sustainable growth and improved quality of life for its citizens. Trends in ESG performance reporting reflect a continuing evolution in companies' approach to sustainability and social responsibility, underlining the importance of integrating ESG issues into their business strategies and reporting transparent and detailed performance in these critical areas. Companies are adopting a more transparent and detailed approach to ESG reporting, including the provision of clear and accessible information on their environmental impact, social issues and corporate governance practices. ESG reports are becoming increasingly complex and comprehensive, reflecting their commitment to sustainability and social responsibility.

The effects of protein hydrolysates from rainbow trout by-products on growth, digestive and antioxidant enzymes, and liver lysozyme activity in sobaity (Sparidentex hasta) and Arabian yellowfin (Acanthopagrus arabicus) seabream juveniles

An eight-week feeding trial was conducted to elucidate the effects of rainbow trout by-products protein hydrolysates (FPH, 92 % peptides <1 kDa, ∼78.1 % crude protein, ∼2.7 % lipid) on growth and some selected physiological responses in sobaity (Sparidentex hasta) (1.7 ± 0.0 g) and Arabian yellowfin (Acanthopagrus arabicus) (0.9 ± 0.0 g) seabream. Fish meal in a basal diet (∼58 % crude protein, ∼12 % lipid) was replaced with FPH at four levels, including 0 (control), 1 % (FPH1), 2.5 % (FPH2.5), and 5 % (FPH5). Each experimental diet was offered thrice daily to fish in triplicate. At the end of the feeding trial, S. hasta fed with FPH diets showed positive linear and quadratic trends in growth performance, and those fed with FPH5 had the highest final weight (FBW; 9.8 ± 0.4) and better feed conversion ratio (FCR; 0.9 ± 0.0). Regarding A. arabicus it showed positive quadratic trend and fish fed FPH2.5 diet had the highest FBW (6.2 ± 0.3), and better FCR (1.2 ± 0.0) value. Trypsin and alkaline phosphatase (ALP) activities showed both positive linear and quadratic trends in S. hasta. In A. arabicus, both linear and quadratic trends were observed in the activities of trypsin and total proteases (P = 0.001), while positive quadratic trends in pepsin and ALP activities were noticed. Lysozyme activity significantly increased by supplementing the diet with FPH and showed both linear and quadratic trends in S. hasta, but it did not change in A. arabicus. Total antioxidant capacity (TAC) in A. arabicus increased and showed both linear and quadratic responses. The catalase and glutathione peroxidase activities in both species increased significantly in response to dietary FPH. This study showed that FPH effects in diet were species-specific and its supplementation levels at 2.5 and 5 % could be recommended in A. arabicus and S. hasta juveniles, respectively.

Viromic and Metagenomic Analyses of Commercial Spirulina Fermentations Reveal Remarkable Microbial Diversity.

Commercially produced cyanobacteria preparations sold under the name spirulina are widely consumed, due to their traditional use as a nutrient-rich foodstuff and subsequent marketing as a superfood. Despite their popularity, the microbial composition of ponds used to cultivate these bacteria is understudied. A total of 19 pond samples were obtained from small-scale spirulina farms and subjected to metagenome and/or virome sequencing, and the results were analysed. A remarkable level of prokaryotic and viral diversity was found to be present in the ponds, with Limnospira sp. and Arthrospira sp. sometimes being notably scarce. A detailed breakdown of prokaryotic and viral components of 15 samples is presented. Twenty putative Limnospira sp.-infecting bacteriophage contigs were identified, though no correlation between the performance of these cultures and the presence of phages was found. The high diversity of these samples prevented the identification of clear trends in sample performance over time, between ponds or when comparing successful and failed fermentations.