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The potential of the housefly maggot as a source of crude protein in the diet of broiler chickens
Get PDFThis study aimed to determine the effect of maggot meal inclusion in feed for broilers on their growth rate and weight gain. A total of thirty (30) day-old broiler chicks were randomly allocated into two groups of 15 each. One group was fed with commercial feed, while the second group was fed with self-formulated feed compounded with the housefly maggot as a source of crude protein. The experiment lasted for six (6) Weeks, and feed and water were offered ad libitum for 42 Days. The average live weight gain (2284.20 g/bird) observed in the commercial diet group was not significantly different from the self-formulated diet treatment group (2042.20 g/birds) (P>0.05). The P value (0.001) was found to be a significant relationship between the feed conversion ratio and the grouping. However, there is no significance found in the relationship between time (p-value = 0.11) and the treatment given. Cost evaluation Table revealed the maggot inclusion self-formulated diet had the least feed cost/kg gain of 320 units at the starter phase and 160 units at the finisher phase, as against 672 units and 336 units for commercial diets at starter and finisher phases, respectively. Cost evaluation also revealed that the self-formulated diet was cheaper to compound and had the lowest cos
Studying the effect of lactoferrin on some sensory attributes and properties Cream stored for 21 days
Get PDFThe study included determining the effectiveness of lactoferrin at concentrations (0, 3, 6, 12) mg/ml over extending the storage period of cream (0, 7, 14, 21) days. The cream was manufactured, and was fortified with lactoferrin, after which (peroxide number, viscosity, pH, sensory evaluation) of the cream was estimated and in a storage period of (0, 7, 14, 21) days of storage at a temperature of 5 C?, The results show that the peroxide number increases with the increase in storage time, the results reached (6.32, 6.25, 6.23, 6.14) mEq O2/g fat at a concentration of (0, 3, 6, 12) mg/ml respectively on the first day. The results of the viscosity showed a slight increase in viscosity in the first period of storage and then usually decreased viscosity. As for the PH, where it was in the first storage PH of the comparison sample, 6.73. At the end of storage, it reached 5.92. The storage period led to a change in taste and flavor. On the first day of manufacturing, the product received taste evaluation scores of (9.0, 8.3, 9.3, 8.6) for concentrations of (0, 3, 6, 12) mg/ml, respectively, and at the end of the storage period the product obtained grades (7.6, 8.0, 8.6, 8.6) for concentrations (0, 3, 6, 12) mg/ml respectively for taste grades, and in terms of flavor, no noticeable changes occurred, while the effect of adding Lactoferrin changes the color of the product
Electroretinography: A Comparative Study of Modalities and Analytical Approaches with Partial Integration of OCT Findings
Get PDFElectroretinography (ERG) is an essential tool for assessing retinal function, with responses from photoreceptors, ganglion cells, and inner layers. Clinical applications are often secondary to structural imaging, though dysfunction may appear before anatomical changes. This review compares three ERG types: full-field (ffERG), patterned (PERG), and multifocal (mfERG), highlighting differences in response, waveform components, and clinical uses. This review analyzes more than 60 studies (2014–2025). Advanced analyses in the time, frequency, and time–frequency domains demonstrated diagnostic accuracies between 85% and 97% for early detection of retinal dysfunctions such as glaucoma and retinitis pigmentosa. Integrating ERG with Optical Coherence Tomography (OCT) improved structure–function correlation by 15–25%. The findings highlight that combining ERG with quantitative feature extraction and OCT enhances early diagnosis and monitoring of retinal diseases and supports standardized clinical applications
Application of Resource Description and Access (RAD) standards in Iraqi University Libraries: A field study at the Central Library of the University of Baghdad
Get PDF??? ????? ?? ??? ??????? ????? ??? ??????? ??????? ???????? ?????? ????? ???????? ?? ????? AACR2 ??? ????? RDA. ??? ?? ??? ????? ???? ??????? ????? ???? ???? ???????? ??????????? ????????? ???????? ???? ??????? ???????? ?????? ????????? ???????? ?????? ????? ??????? RDA ??? ????????. ??? ??????? ??????? ????? ????? ????????? ???????? ????? ????? ?????? ?????? ??? ????? ???? ???????. ?? ????? ??????? ???? ?????? ????? ???? ????? 106 ?? ????? ???? ???????? ????? ?? 95 ?????. ?? ??? ???????? ???????? ?? ???? ????????? ?????? ??? ?????? ???????? ?????? ??????? ???????? ???? ??????? ????????????? ?????? ???????. ???? ??????? ?? ????? ????? ?? ????? ???????? ?????? RDA? ?? ??????? ???? ??? ???? ?? ???????? ??????? ?? ???????? ???????? ???????? ???? ?????? ???????. ??? ?????? ?? ????? ??????? ?? ?????? ?? ???? ??? ???????? MARC21 ??????? ??????? ?????????? ?? ???? ?????? ???? ????? ??? ??????? ??????? ??????? ???????? ??? ???????. ??? ?? ????? ???????? ??? ??????? ???????? ?????? ??????? ??????? ????????? ????? ?????? ???? ???? ????? ???????. ?????? ???????? ??? ??? RDA ???? ??????? ???? ?? ??????? ?? ???? ???? ???? ?? ?????? ??? ??????? ????? ???????? ???????. ??????? ??????? ????? ??????? ????? ????? ????? ??????? ????? ?????? ?????? ???????? ?????? ?????? ????? ?????.The purpose of this study was to determine how well the University of Baghdad’s Central Library could prepare for the transfer from the AACR2 to the RDA standard. The research was described with the purpose of completing plans for a thorough understanding of the library's technological, institutional, and human challenges, determining present practices, and analyzing RDA standards awareness among personnel. The study employed an applied research method, employing a case study design to provide an in-depth understanding of the library situation. A custom-designed questionnaire was delivered to a population of 106 staff members, yielding 95 replies. Additional data were gathered through interviews to generate qualitative insights, direct observations of cataloging operations, and examination of bibliographic records and training documents. The results revealed significant gaps in staff knowledge of the RDA; in fact, a large portion of the staff received training in specialized skills required for understanding and executing the standard. They observed that, for the most part, cataloging records are still done using MARC21 and traditional cataloging standards, with significant technical issues such as outdated software and inadequate infrastructure. A lack of specialized leadership and internal communication issues were identified as major impediments to content standard adoption. According to the report, RDA should be put into practice since it is expected to significantly enhance resource access and metadata quality. To manage the transformation, it also proposed creating concentrated training courses, improving technical infrastructures, and establishing unified leadership
Effect of biological control factors acting on population dynamics parameters insect of Sesamia cretica Led. (Noctuidae:Lepidoptera) Tow varities on corn Zea mays L in Ninavah providenceEffect of biological control factors acting on population dynamics parameters insect of Sesamia cretica Led. (Noctuidae:Lepidoptera) Tow varities on corn Zea mays L in Ninavah providence
No full textThe study was conducted under field conditions during the autumn season of the year 2023. A detailed account was given of the population dynamics of the corn stalk borer Sesamia cretica Led. (Noctuidae:Lepidoptera) infested two Varieties of corn Zia mays (Zwan and Samoray) in three regions belong to Ninavah provedence: Mosul city, Rabiaa and Nimrod districts. To investigate major mortality factors that are responsible for the change of S. cretica on corn were identified as density-dependent factors including predation and unknown factors which are independent. Predation by Anthocoris spp., green lacewings (Chrysopela spp.), and ladybugs (Coccinella semptempunctat and C. undecimpunctata) are a significant contributor to death. Birds also played a major role in predation of larvae and pupae that fed on tissue. Results showed that photoperiod and normal female mortality rate played an important role in reducing the pest level. Results revealed that S. cretica population were subjected to great biotic and abiotic mortality factors which played a major role in the destruction of their mature and immature stages. The trend index of the second generations was always below 1% , while for the first generations were above 1%
Seismic Guardians: Redefining Shear Walls for Unshakable Residential Structures
Get PDFThis thorough analysis provides a detailed overview of developments, obstacles, and future prospects in this important field of structural engineering by synthesizing current works on shear wall design for seismic protection in multi-story residential structures. Shear walls are discussed in terms of location, organization, and creative design strategies. Shear walls are essential for resisting lateral stresses and guaranteeing stability during seismic occurrences. Shear walls arranged in a central core are shown to be helpful in minimizing top-story displacement during seismic activity. Studies on materials show improved strength, ductility, and stiffness, such as corrugated steel plates. The article includes experiments that investigate the behavior of shear walls under different loading scenarios, including information on aspects ratio effects, overturning resistance, and the connection between panel height and drift/shear strength. The impact of anchoring solutions on wall movement is closely examined. Furthermore, research using computer tools such as STAAD.Pro and ETABS provide quantifiable data on the behavior of buildings, highlighting the beneficial effect of shear walls in minimizing displacement
A Comparison Study Between Hysteresis and Sinusoidal Pulse Width Modulation for Induction Motor Drive
Get PDFIn This paper compares the control strategies for three phase voltage source inverters, which have been the subject of extensive research in the last few years. Even if the inverter topologies that require the fewest switching elements yield the most efficient results, the switching technique that is as effective as the topology, at least. In addition, the inverter's selected switching technique will effectively suppress harmonic components while generating the optimal output voltage and current. To manage voltage source inverters, to regulate three phase voltage source inverters, several PWM approaches are frequently employed. Sinusoidal PWM and hysteresis band PWM are two examples of these techniques. MATLAB/SIMULINK has been used to model these modulation techniques that are applied in voltage source inverters to generate variable frequency and amplitude output voltage and current. Furthermore, a comparison is made between the overall harmonic distortions of the output voltages and current. Simulation tests have revealed that there is greater THD in the output current and voltages of voltage source inverter when sinusoidal pwm is used. Hysteresis band pwm has shown the ability to produce a lower overall harmonic distortion and more efficient output voltage and current
Early Prediction of Stroke Risk Using Machine Learning Approaches and Imbalanced Data
Get PDFClassifying medical datasets using machine learning algorithms could help physicians to provide accurate diagnosing and suitable treatment. For instance, stroke is one of the serious diseases that attacks many patients annually, and analyzing it is symptoms in advance could save patients’ lives. The warning signs of the stroke can be investigated to be used as attributes or predictors for machine learning models. This study evaluates the performance of four machine learning models to classify stroke datasets. Specifically, Decision Tree, Naïve Bayes, K- Nearest Neighbor (KNN) and Linear discriminant Analyses (LDA) models were trained on 11 attributes collected from 5110 patients to predict stroke risk. The findings showed that KNN outperformed the three other models with an achieved accuracy of 90%. The study also considered balancing the employed data prior validating the models to provide accurate classification. Cross-validation technique was used to avoid over-fitting and under-fitting during training phases.
AI-based ACL Exercises Recognition System Using Wearable Multi-Sensor Data Fusion
Get PDFHuman activity recognition has attracted researchers’ attention in the last two decades. Anterior Cruciate Ligament (ACL) exercises are example of these activities that have to be performed correctly to ensure efficient knee joint recovery. Hence, Machine and Deep Learning algorithms have been employed to classify ACL exercises and evaluate its correctness. This study investigates the accuracy of five machine learning algorithms, SVM, Decision Tree, Random Forest, Gradient boosting and KNN, with CNN in terms of their ability to classify ACL exercises. The data of seven ACL exercises, performed by four subjects, were collected using Accelerometer and gyroscope sensors, then these data were used to train the algorithms. Results showed that both CNN and Random Forest models performed well and achieved higher accuracy among the other algorithms with real accelerometer and gyroscope data. However, Random Forest model outperformed other models when relying on real accelerometer data only or with synthesized data. Moreover, it is also found that gyroscope data are essential for such systems to train the algorithms efficiently and excluding such data leads to downgrade the classification performance
Analyzing Power Plant Data Using Artificial Intelligence to Enhance Maintenance Strategy
Get PDFThis research aims to optimize maintenance strategies in power plants by leveraging artificial intelligence (AI) techniques to analyze historical operational data. The study adopts a quantitative analytical approach, utilizing deep learning algorithms—including GRU, LSTM, and TCN—to detect anomalies and predict equipment malfunctions. Historical data from a power plant, encompassing sensor readings, fault logs, and operational parameters, were collected, pre-processed, and analyzed. The results demonstrate that the GRU algorithm outperforms other models, achieving an accuracy exceeding 83% and the lowest loss value, thereby proving its robustness in generalization and predictive capability. The proposed system significantly reduces unplanned downtime, minimizes maintenance costs, and enhances operational efficiency. A practical case study confirms the effectiveness of the approach in real-world settings. The integration of AI into power plant maintenance not only improves system reliability but also supports sustainability objectives, establishing AI-driven predictive maintenance as a strategic asset for the modern energy sector