Performance Index Research Articles

Influence of CuO nanoparticles on photosystem II structural stability and functional activity of corn (Zea mays L.) under drought stress

Photoinhibition and photooxidation of photosystem II (PSII) is one of the key damages caused by drought stress. The present study aimed to assess whether or not foliar application of copper oxide nanoparticles (CuO NPs) is effective in promoting PSII stability and activity in corn plants under drought stress. Three-week old plants of corn were subjected to drought stress and varying levels of CuO nano-particles (0, 25, 50, and 100 mM) of the rooting medium. In this study, the effects of foliar application of copper oxide nanoparticles were assessed on growth, plant water status, nutrient uptake and structural stability of photosystem II of drought stressed corn plants. Drought stress impeded overall growth of the corn plants by reducing leaf relative water content, water potential, chlorophyll a content, and accumulation of K+ in plant leaves and roots. Exogenous application of 25 mM CuO NPs significantly enhanced the growth of corn. Exogenous application of CuO NPs improved the dry biomass and length of roots of the corn plants under drought stress. Although the application of nano-particles did not change leaf photosynthetic pigments, relative water content, K+ accumulation, it enhanced the accumulation of K+ in roots. Drought stress did not affect the structural stability of PSII, but it reduced its activity (performance index, PIABS) due to changes in the reaction center density and the biochemical reaction efficiency or electron transport capability. Exogenous application of CuO NPs improved PIABS due to increase in active reaction center density and electron transport efficiency. However, 100 mM CuO NPs application caused PSII damage at the donor end and reduced active reaction center density in the corn plants under both normal and drought stress conditions. The present findings provide a baseline information that foliar application of CuO-nanoparticles in low concentrations can improve the growth of corn by improving accumulation of K+ and increasing PSII activity. Further research is required to explore its effect on cellular redox balance and activities of PSII and PSI, and optimum dose of CuO-nanoparticles for developing formulations for their commercial applications in farmers’ fields.

Risk-Based Completion Cost Overrun Ratio Estimation in Construction Projects Using Machine Learning Classification Algorithms: A Case Study

Estimating the completion cost accurately in the early phases of construction projects is critical to their success. However, cost overruns are almost inevitable due to the risks inherent in construction projects. Hence, the completion cost fluctuates throughout the execution phase and requires periodic updates. There is a need for a prompt and user-friendly completion cost estimation model that accounts for fluctuating risk scores and their impacts on the total cost during the execution phase. Machine learning (ML) techniques could address these requirements by providing effective methods for tackling dynamic systems. The proposed approach aims to predict the cost overrun ratio classes of the completion cost according to the changes in the total risk scores at any time of the project. Six classification algorithms were utilized and validated by employing 110 data points from a globally operating construction company. The performances of the algorithms were evaluated with validation and performance indices. The decision tree classifier surpassed other algorithms. Although there are some research limitations, including risk perception, data gathering restrictions, and selecting proper ML algorithms upon data properties, this research improves the planning abilities of construction executives by providing a cost overrun ratio based on changing total risk scores, facilitating swift and simple assessments at any stage of a construction project’s execution.

Selection indexes in terms of functional features in modern dairy cattle breeding in Europe

Abstract The increase in demand for dairy products requires continued progress in dairy farming for a sustainable supply. Europe, known as the world's leading milk producer, plays a key role in meeting this growing demand. Modern dairy farming has moved beyond its historical focus on milk yield and now focuses on functional traits such as udder health, fertility and calf survival. As a result, selection indicators have become essential tools, combining multiple attributes to support selective decisions. However, these rates show considerable variability across countries, reflecting their distinct breeding goals. Poland's production and functionality (PF) Index emphasizes production and functional traits to enhance dairy cattle. Portugal uses the total economic merit (M€T) and total performance index (IPT) for a broader assessment covering a wider range of traits. Ukraine is transitioning towards a more comprehensive breeding system incorporating stress tolerance and longevity. Factors such as climate change and the need for sustainable practices drive this evolution, underscoring the economic importance of traits beyond mere production. Future trends may include features such as feed efficiency, methane emissions reduction and stress resistance. Diverse breeding objectives across countries lead to different selection index constructions, essential for effective selection, ranking and breeding of superior individuals. This comprehensive review offers insight into constantly evolving dairy farming strategies in Europe, with a focus on Poland, Portugal and Ukraine, while highlighting the key role of functional traits in shaping the future of dairy farming.

Numerical simulation study on discharge characteristics of the Dual hollow cathode plasma source using magnetic mirror field

The Dual hollow cathode plasma source uses hollow cathode cylindrical sputtering and ionizing metal elements, which has a high material utilization rate and has potential application in the field of material modification. Its performance index requires the cooperation of electrode discharge parameters and the rational utilization of the inner surface of the hollow cathode. In this paper, a two-dimensional fluid model of a Dual hollow cathode structure is developed to simulate the basic distribution of the Dual hollow cathode discharge, which fills the central region of the Dual hollow cathode structure and the electrons oscillate on the axis. The effects of electrode parameters and hollow cathode radius on the discharge were investigated. The results show that the radial electron density of the hollow cathode increases with increasing heated cathode voltage, but as the hot cathode voltage continues to expand beyond 1200 V this trend becomes less obvious. The enhancement of the wall ion current by the heated cathode voltage is very pronounced, and the hollow cathode discharge is the result of the mutual enhancement of the heated cathode voltage and the hollow cathode voltage. Hollow cathode sputtering needs to reach a voltage threshold of 300 V, and the existence of an optimal radius (r = 4 mm−6 mm) to achieve a high plasma density and at the same time favor hollow cathode sputtering.

Influence of alkali molarity on compressive strength of high-strength geopolymer concrete using machine learning techniques based on curing regimes and temperature

The compressive strength behavior of high-strength geopolymer concrete (HSGPC) has been studied in this research work with varying alkali concentration using the novel machine learning techniques. The alkali concentration in the activation solution plays a significant role in the geopolymerization process and affects the resulting compressive strength. In this research work, the range between 4 M and 16 M for alkali molarity (M), 18 kg/m3 and 160 kg/m3 for NaOH and 41 kg/m3 and 229 kg/m3 for NaSi was collected from literature and used in the various design mixes of this exercise. This was necessary because higher alkali concentrations promote a more efficient dissolution and activation of the aluminosilicate compounds, leading to increased geopolymerization and the formation of more calcium silicate hydrate (C-S-H) gel. The increased C-S-H gel content contributes to improved strength development. However, there is an optimal alkali concentration range for the sustainable production of geopolymer concrete, and exceeding this range can have a negative impact on compressive strength and ecofriendly handling of concrete. A total of fifty-three records were collected from literature and deployed in modeling the compressive strength (Fc) considering various curing regimes. Three symbolic machine learning techniques such as genetic programming (GP), evolutionary polynomial regression (EPR), and the artificial neural network (ANN) are used in this research model. The relative importance values for each input parameter were also evaluated, which indicated that all factors have significant impacts on (Fc), but Age (i.e., curing regime) has the most influence compared to FA, NaOH, and CAg then the other inputs. From the model relations between the calculated and predicted values, it can be shown that the decisive model, ANN produced line of parametric equation of y = 0.995x, and produced performance indices; MAE of 2.13 MPa, RMSE of 2.86 MPa and R-squared of 0.981, which makes the ANN the most reliable model in agreement with previous applications of the technique. These are against the poor performance of the EPR and GP, which produced R-squared less than 0.8 with higher error rates. The Taylor chart and the variance distribution, which further compares the accuracy and variances of the developed models support the outcomes. Generally, alkali molarity has shown its potential in the production of HSGPC due to its role in the reactivity phases of the concrete formulation; hydration, activation, pozzolanic, and geopolymerization reactions producing the gel needed for the strength gain in HSGPC.

Performance Assessment of the Small and Medium-Scale Coconut Weeder Cum Fertilizer Applicator Developed by Rajarata University of Sri Lanka

The enhancement of coconut yield significantly hinges on proper weeding and chemical fertilizer application. In Sri Lanka, several mechanical methods have been introduced for weeding and fertilizer application of coconut, but the traditional manual approach persists most popular, despite being time, labor cost intensive. Moreover, the introduced technologies were suited for large-scale coconut cultivation and could not cope with medium or small-scale. Furthermore, most of them are designed for a single application; weeding or fertilizing. Thus, the Faculty of Agriculture, Rajarata University of Sri Lanka (RUSL), developed a coconut weeder cum fertilizer applicator for medium and small-scale coconut cultivations. However, it has not been properly evaluated and recommended for farmers. Consequently, this study sought to evaluate the performance of the above machine by conducting a comparative performance evaluation with the conventional method. A healthy, well-maintained, proper-spacing coconut plantation was selected from the faculty research unit, and each weeding and fertilizer application method was replicated ten times. In terms of performance parameters: effective field capacity, field efficiency, and weeding efficiency in mechanical and manual methods were 0.172 ha h-1, 61.86%, 66.62%, and 0.048 ha h-1, 55.34%, 60.35%, respectively. Statistical analysis indicates the mechanical method had higher field capacity and efficiency than the manual method, while weeding efficiency was not significantly different (p≤0.05). In addition, the machine had a fertilizer spreading uniformity of around 99.98% when operating at an optimum speed of 1.45 km h-1. Fertilizer application rate and performance index as a weeder were 1.7 kg/min and 1145.86, respectively. Furthermore, the fuel consumption rate of the machine was 0.733 L h-1 and its break-even point was recorded as 2.85 ha yr-1. Consequently, the coconut weeder cum fertilizer applicator proves suitable for medium and small-scale coconut cultivations in Sri Lanka.

Comparative assessment of the energy performance index of modern urban and traditional rural housing in lower Himachal Pradesh, India to develop prediction model

Comparative assessment of the energy performance index of modern urban and traditional rural housing in lower Himachal Pradesh, India to develop prediction model

The synthesis of logistics performance and technological innovation on environmental quality

PurposeThis study aims to examine the impact of logistics performance and technological innovation on environmental quality in Africa, focusing on carbon dioxide (CO2) emissions and renewable energy consumption as indicators of environmental quality.Design/methodology/approachThe study employs a panel data analysis of 43 African countries over the period 1990–2021. Data on logistics performance, technological innovation, CO2 emissions, and renewable energy consumption are sourced from the World Development Indicators database of the World Bank. Grounded in the Triple Bottom Line (TBL) framework, which integrates economic, social and environmental dimensions of sustainability, the analysis utilises the generalised method of moments (GMM) technique to address the issue of endogeneity.FindingsThe regression results reveal significant relationships between logistics performance, technological innovation and environmental quality indicators. Logistics performance demonstrates a negative impact on CO2 emissions, while technological innovation positively influences renewable energy consumption. The interactive effect of logistics performance and technological innovation mitigates CO2 emissions, aligning with the TBL framework’s environmental dimension by promoting sustainability. Furthermore, trade openness exhibits a significant negative effect on both CO2 emissions and renewable energy consumption. The findings highlight the potential synergies between logistics performance and technological innovation in driving environmental sustainability while offering economic benefits and addressing social well-being.Practical implicationsThe findings suggest the importance of prioritising investments in enhancing logistics performance and fostering technological innovation to achieve environmental sustainability goals in Africa.Originality/valueTo the best of the researchers’ knowledge, this study presents an initial attempt to examine the nexus between logistics performance and environmental quality in Africa using the logistics performance index. Furthermore, beyond assessing the individual effects of logistics performance and technological innovation on environmental quality, we delve into their interactive dynamics, adding novelty to the study.

Relationship between Myocardial Performance Index (Tei Index) and angiographic severity of coronary artery disease in patients with Acute ST Elevation Myocardial Infarction

Background: Tei index is a Doppler derived measure of combined systolic and diastolic myocardial function and a better predictor of global LV function and outcome in patients with acute STEMI. The objective of this study was to determine the relationship between the myocardial performance index of LV (Tei index) and angiographic severity of coronary artery disease as assessed by SYNTAX score in patients with acute STEMI. Methods: This was a prospective, observational single centered study conducted from March 2022 to November 2022 at Manmohan Cardiothoracic Vascular and Transplant Centre, Institute of Medicine. (MCVTC, IOM). 160 patients with acute STEMI were enrolled. LV Tei index was calculated with the help of 2D and Tissue Doppler imaging, and the lesion severity was categorized with the help of SYNTAX score after the patients underwent coronary angiography. Results: The mean age was 61.23±12.33 years with a male preponderance. 107 (67%) were male with male to female ratio of 2:1. Tei index was significantly higher among the hypertensive (0.74±0.17) and diabetic (0.78±0.18) patients. 64 (40%), 51(31.9%) and 45(28.1%) had Single vessel disease (SVD), Double vessel disease (DVD) and Triple vessel disease (TVD) respectively with the Mean Tei index values 0.57 ± 0.10, 0.76 ± 0.11, and 0.88±0.11 (p<0.05). The Tei index increased when patients were divided into low, mid, and high SYNTAX score groups as 0.58±0.11, 0.61±0.73, 0.88±0.13 respectively, p-value < 0.05). Moreover, the study showed a positive correlation between Tei index and SYNTAX score with increasing severity of coronary artery stenosis. (r=0.654, p-value<0.001). Proximal LAD, LCx and RCA lesions had greater Tei index than the distal lesions. Conclusion: More proximally located LAD, LCx, RCA lesions had higher value of Tei index, as assessed with the SYNTAX score.

Modified Shooting with Discretization Validation for Non-Standard Optimal Control Problem: Case Study for Four-Stage Royalty Payment Problem

A modified shooting method augmented by discretization validation is presented in this paper to address the challenges inherent in non-standard optimal control problems. Specifically, a specific case study involving four-stage royalty payment functions is focused on, with the aim of effectively optimizing these complex, non-differentiable functions. The shooting method is adapted and enhanced to compute optimal solutions, and its accuracy is rigorously confirmed through discretization techniques. The primary objectives involve maximizing the performance index and determining optimal control strategies for scenarios where the final state variable remains unknown. In this study, the royalty payment is defined as a four-stage piecewise function. The incorporation of piecewise royalty functions introduces non-differentiability at specific time intervals, necessitating innovative approaches for finding optimal solutions. This, in turn, leads to the utilization of the continuous hyperbolic tangent (tanh) function to address the non-differentiability issue. A hybrid shooting method, combining the Newton and Golden Section Search methods, is employed in the C++ programming language to compute the unknown final state value. A new natural boundary condition, based on established theory, is introduced to further facilitate the investigation. Discretization methods such as Euler, Runge-Kutta, Trapezoidal, and Hermite-Simpson approximations are employed for validation. The validation process entails the use of the AMPL programming language with the MINOS solver. Comparative analyses reveal that the modified shooting method yields more accurate optimal results than discretization methods, thus demonstrating the method’s effectiveness in addressing non-standard optimal control problems. The significance of fundamental theories in addressing real-world challenges is underscored by this research, providing valuable insights for future researchers exploring mathematical approaches in similar contexts. The study contributes to the continued relevance of the academic field, particularly in science and mathematics education.

Research on high-quality factor sensing characteristics of all-dielectric nanopore array metasurface based on POA-DELM

Abstract Based on the optical properties of symmetric structures independent of each other in the orthogonal direction, an all-dielectric nano-square hole array metasurface which is symmetric along the diagonal is proposed. By changing the size of square nanopores, the symmetry of the periodic unit structure is broken and the double Fano resonance can be excited. The influence of each structural parameter on the sensing performance of the metasurface is analyzed respectively. As the main structural parameters and performance index, the metasurface height and the lengths of the main and sub-diagonal square nanoholes are selected as the input parameters, and the figure of merit (FOM) value is used as the output value. Then the nonlinear mapping relationship between the input and the output is established through deep extreme learning machine (DELM). Different optimization algorithms are used to optimize the weighted FOM values globally. The four evaluation indicators including root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and model fit (R-squared, R2) are used to assess the training effectiveness of the model. It is shown that the indexes are 0.9986, 0.9725, 3.1612 and 0.9733 respectively, and the FOM values of the dual Fano resonance after pelican optimization algorithm ( POA ) optimization are as high as 9.88 × 103 and 1.28 × 105, which demonstrate the effectiveness of POA-DELM proposed in this paper.

Characterization of insecticide resistance and their mechanisms in field populations of the German cockroach (Blattodea: Ectobiidae) in Taiwan under different treatment regimes.

This study investigated how management strategies influence resistance profiles in German cockroach (Blattella germanica (L.)) populations and their impact on the performance of commercial gel baits containing fipronil, imidacloprid, and indoxacarb. Field populations from premises managed under 3 different strategies: Baiting, random insecticide (RI) used, and insecticide rotation (IR) were tested. Almost all populations under RI and IR were resistant to deltamethrin, but low to moderate resistance was observed under the Baiting approach. Cytochrome P450 monooxygenases (P450) were involved in deltamethrin resistance in these resistant populations. All individuals under Baiting and RI were homozygous for the L993F mutation, but the populations under IR lacked homozygous-resistant individuals. Eighty-three percent of field populations with complete homozygosity for the Rdl mutation displayed low mortality upon exposure to 3× LD95 fipronil. The effect of P450 and the Rdl mutation conferred high fipronil resistance in populations under the Baiting approach, recording moderate performance indices (PI) of 44-67 in fipronil bait. By contrast, those populations under RI and IR, in which involve glutathione S-transferases in fipronil resistance, had high PIs of 78-93. Almost 80% of populations exhibited over 90% mortality at 3× LD95 indoxacarb treatment, accompanied by high PIs of 90-100 in indoxacarb bait. Partial mortality from 1× LD95 imidacloprid occurred across all field populations due to the involvement of P450. PIs of imidacloprid bait ranged 5-57 and 20-94 in populations under RI and IR, respectively. Field populations demonstrate different resistance profiles depending on the treatment regimes, and the resistance mechanisms involved influenced gel bait's effectiveness.

Impact of comb type on production performance, egg production quality, reproductive performance, and blood biochemical indexes in Tianfu chickens

Impact of comb type on production performance, egg production quality, reproductive performance, and blood biochemical indexes in Tianfu chickens

Growth, mortality, exploitation, and recruitment patterns of Labeobarbus altianalis (Boulenger, 1900) in River Kuja-Migori, Kenya

The Ripon barbel, Labeobarbus altianalis, a riverine fish found in the Lake Victoria Basin is regarded as species of less concern, but it is vulnerable to overfishing and population decline. This study aimed at determining growth, mortality, exploitation rate, and recruitment patterns of L. altianalis (Boulenger, 1900) in River Kuja-Migori. A total of 1,217 specimens with overall total lengths ranging from 9.5-41.5 cm (mean 28.5 ± 2.7) were collected monthly from January to December 2021. The fish were caught using an electrofisher in wadable areas and monofilament nets in deeper areas. Electronic length frequency analysis (ELEFAN) software in Fish Stock Assessment Tools (FiSAT II) program was used to analyze data. Natural mortality (M) Fishing mortality (F) and total mortality (Z) coefficients were 0.15 year-1, 0.52 year-1 and 0.67 year-1 respectively. The asymptotic length (L∞) was 44.94 cm TL while the instantaneous growth rate (K) was 0.15 year-1. The exploitation rate was 0.44 year-1 and the length-based growth performance index (Ø’) was 3.03. Results indicated that the longevity of L. altianalis was 9 years. Recruitment occurs throughout the year with bimodal annual recruitment peaks coinciding with the two rainy seasons in the region. This study provides important information for developing management advice for the L. altianalis riverine fishery.

An Examination of Calculations: From Anaerobic Mono-digestion to Co-digestion

Anaerobic digestion is a biochemical process and form of sustainable technology. In comparison to mono-digestion, co-digestion is more effective in the utilization of diverse resources, supply of nutrient balance, and overall digestibility and stability. The co-digestion biodegradability index, co-digestion performance index, and synergistic effect index are generally used as anaerobic metrics to evaluate the co-digestion performance. Although they are numerical parameters, little information on their working procedures has been revealed. There is also a lack of supporting calculations for some published data hence their values cannot be verified. The aim of this article is to reconsider and examine the mathematical calculations from anaerobic mono-digestion to co-digestion. The method of study is a pen-and-paper analysis that processes both experimental and theoretical data from past studies. The article serves four purposes. First, it identifies processing parameters. Second, it shows step-by-step procedures of a series of calculations. Third, it identifies the core parameter in the calculation of anaerobic co-digestion. Fourth, it establishes the relationships between co-digestion biodegradability index, co-digestion performance index, and synergistic effect index. Critically, the mass fraction of volatile solid is identified as the core parameter that determines the valid calculations of co-digestion.

The Input of Nanoclays to the Synergistic Flammability Reduction in Flexible Foamed Polyurethane/Ground Tire Rubber Composites

Currently, postulated trends and law regulations tend to direct polymer technology toward sustainability and environmentally friendly solutions. These approaches are expressed by keeping materials in a loop aimed at the circular economy and by reducing the environmental burdens related to the production and use of polymers and polymer-based materials. The application of recycled or waste-based materials often deals efficiently with the first issue but at the expense of the final products’ performance, which requires various additives, often synthetic and petroleum-based, with limited sustainability. Therefore, a significant portion of research is often required to address the drawbacks induced by the application of secondary raw materials. Herein, the presented study aimed to investigate the fire performance of polymer composites containing highly flammable matrix polyurethane (PU) foam and filler ground tire rubber (GTR) originating from car tire recycling. Due to the nature of both phases and potential applications in the construction and building or automotive sectors, the flammability of these composites should be reduced. Nevertheless, this issue has hardly been analyzed in literature and dominantly in our previous works. Herein, the presented work provided the next step and investigated the input of nanoclays to the synergistic flammability reduction in flexible, foamed PU/GTR composites. Hybrid compositions of organophosphorus FRs with expandable graphite (EG) in varying proportions and with the addition of surface-modified nanoclays were examined. Changes in the parameters obtained during cone calorimeter tests were determined, discussed, and evaluated with the fire performance index and flame retardancy index, two parameters whose goal is to quantify the overall fire performance of polymer-based materials.

Population Dynamics of Nile Tilapia (Oreochromis niloticus, L. 1758) in Lake Nubia, Sudan

This study aims to investigate the population dynamics of Nile tilapia (Oreochromis niloticus, Linnaeus, 1758) in Lake Nubia, Sudan. Monthly samples were collected from fishermen from January to December 2021, and recorded total lengths (TL) of 996 specimens nearest to 1.0 mm using a standardized measuring board; the lengths (TL) exhibited a range from 5.2 to 41.3 cm. Population parameters were assessed using the ELEFAN I routine within FiSAT II software, which produced von Bertalanffy growth parameters as follows: an asymptotic length (L∞) of 43.05 cm, a growth curvature (K) of 0.230 yr⁻¹, and a theoretical length at age zero (t0) of -0.1816. The growth performance index (Φ') was calculated to be 2.639. The instantaneous mortality rates were evaluated, revealing total mortality (Z) at 0.65 yr⁻¹, natural mortality (M) at 0.63 yr⁻¹, and fishing mortality (F) at 0.02 year⁻¹; While the exploitation rate (E) was determined to be 0.04 yr⁻¹. The size at first capture (Lc) was obtained as 5.2 cm, while L50 was estimated at 10.07 cm, both being below the size at first maturity (Lₘ) of 13.5 cm, and the longevity (Tmax) was noted to be 12.86 years. The results indicated poor utilization of the Nile tilapia population in Lake Nubia, and its size at first capture and L50 was below the size at first maturity. This situation is an indication of the need for a continuous process of monitoring and managing to reduce the harvesting of smaller individuals and to improve productivity toward achieving levels that optimize sustainable yield.

Study on Performance Deterioration of Asphalt and Asphalt Mixtures Containing Mafilon under Internal Salt Freeze-Thaw Cycles

The purpose of this work is to determine the implications of internal salt freeze-thaw cycles on performance deterioration to asphalt and asphalt mixtures containing Mafilon (MFL). The deterioration to different numbers of F-TCs and different MFL contents on asphalt properties and mechanism were investigated by physical properties tests and microcosmic tests. Then the damages of road performance indexes of asphalt mixtures containing different MFL contents were studied by road performance tests. The experimental results show that asphalt containing MFL after F-TCs has a remarkable decline in ductility and penetration, while growth in softening point. Internal salt F-TCs are most damaging to the cryogenic properties of asphalt. Chemical reactions and salt aging effects occur in salt F-TCs, raising the glass transition temperature of asphalt. Road performance tests indicate the deterioration of internal salt F-TCs to high temperature stability and water stability is the most pronounced, with 29.18% and 21.78% reduction, respectively.

A Linear Quadratic Regulation Controller Based on Radial Basis Function Network Approximation

This paper proposes a linear quadratic regulation (LQR) tracking control method based on a radial basis function (RBF) that successfully compensates for the shortcomings of the LQR method. The LQR method depends on the linearity of a model. Specifically, an RBF neural network is used to approximate and compensate for the nonlinear part of a controlled object in the PID type-I, type-II and type-III control loops to improve the performance of the system. Through the simulation of different industrial systems, such as underdamped, overdamped and critically damped systems, the method significantly improves the dynamic response performance indices, such as the rise time and settling time, of the system.

Broiler Chicken Performance with The Addition of Moringa Leaf Flour (Moringa oleifera) and Garlic Flour (Allium sativum L)

This study aims to determine the effect of giving Moringa leaf flour at 1, 2.5% and 5% and garlic flour at 2% on the performance of broiler chickens. The materials used are 64 broiler chickens. Moringa leaf flour and garlic flour. This study used a completely randomized design with four treatments and four replications. P0 = 100% commercial feed, P1 = 1% Moringa leaf flour and 2% garlic flour, P2 = 2.5% Moringa leaf flour and 2% garlic flour, P3 = 5% Moringa leaf flour and 2% garlic flour for 35 days. The variables observed were feed intake, body weight gain, feed conversion ratio, mortality and performance index. The data obtained were analyzed using variance analysis, and the Duncan test was continued. The results showed that the treatment had no significant effect (P>0.05) on feed intake, weight gain, FCR, mortality and IP. Based on the study results, it can be concluded that administering Moringa leaf flour at up to 5% and garlic flour at 2% yielded good results on weight gain, FCR, and mortality.