Optimization of Biomethane Production via Fermentation of Chicken Manure Using Marine Sediment: A Modeling Approach Using Response Surface Methodology

In this study, marine sediment (MS) was successfully used as a source of methanogenic bacteria for the anaerobic digestion (AD) of chicken manure (CM). Using MS showed high production in liquid and semi-solid conditions. Even in solid conditions, 169.3 mL/g volatile solids of chicken manure (VS-CM) was produced, despite the accumulation of ammonia (4.2 g NH3-N/kg CM). To the best of our knowledge, this is the highest methane production from CM alone, without pretreatment, in solid conditions (20%). Comparing MS to Ozouh sludge (excess activated sewage sludge) (OS), using OS under semi-solid conditions resulted in higher methane production, while using MS resulted in more ammonia tolerance (301 mL/gVS-CM at 8.58 g NH3-N/kg). Production optimization was carried out via a response surface methodology (RDM) model involving four independent variables (inoculum ratio, total solid content, NaCl concentration, and incubation time). Optimized methane production (324.36 mL/gVS-CM) was at a CM:MS ratio of 1:2.5 with no NaCl supplementation, 10% total solid content, and an incubation time of 45 days

A Pilot Model for the Treatment of Slaughterhouse Wastewater Using Zeolite or Psidium-Leaf Powder as a Natural Coagulant, Followed by Filtration with Rice Straw, in Comparison with an Inorganic Coagulant

Slaughterhouse wastewater (SHWW) is classified as industrial waste, which is exceptionally harmful to the environment due to its high content of biological oxygen demand (BOD), chemical oxygen demand (COD), and suspended solids, which result from high organic and nutrient loading. This study used a pilot system to treat SHWW from the Kafrelsheikh Governorate slaughterhouse, which includes a three-step process. It started with sedimentation, then coagulation and flocculation using different concentrations of each: natural zeolites (Z) and Psidium guajava-leaf powder (GLP) as green and environmentally friendly agents, and alum (A) as an inorganic coagulant. The final step was filtration with physically treated rice straw (RS). Each step was judged separately by measuring the removal percentages of each analyzed pollutant, and finally, the overall process was evaluated using the same method. A jar test was used to determine the best concentration of each coagulant used. The measured pollutants were physico-chemical, such as COD, BOD, TSS, TKN, and turbidity. The bacteriological examination included TBC, TCC, and FC. The jar-test results determined that Z 1200 mg/L SHWW, GLP 1 g/L, and A 6 g/L were the best concentrations for each coagulant used. In the coagulation step, GLP 1 g/L gave the highest removal percentage of TSS, TKN, EC, and turbidity, while Z 1200 mg/L gave the highest removal percentage of COD, TDS, TBC, and TCC. From these results, it was concluded that a natural coagulant performs better than a chemical one. Finally, judging the overall pilot test system after applying the filtration with physically treated RS, we found that the best removal efficiencies were obtained from Z 1200 mg/L combined with RS. This combination resulted in 90.58, 83.47, 88.75, 54.89, 21.39, 34.49, 84.16, 99.98, and 99.93 removal percentages for BOD, COD, TSS, TKN, EC, turbidity, TBC, and TCC, respectively

Boosting for Learning From Imbalanced, Multiclass Data Sets

In many real-world applications, it is common to have uneven number of examples among multiple classes. The data imbalance, however, usually complicates the learning process, especially for the minority classes, and results in deteriorated performance. Boosting methods were proposed to handle the imbalance problem. These methods need elongated training time and require diversity among the classifiers of the ensemble to achieve improved performance. Additionally, extending the boosting method to handle multi-class data sets is not straightforward. Examples of applications that suffer from imbalanced multi-class data can be found in face recognition, where tens of classes exist, and in capsule endoscopy, which suffers massive imbalance between the classes. This dissertation introduces RegBoost, a new boosting framework to address the imbalanced, multi-class problems. This method applies a weighted stratified sampling technique and incorporates a regularization term that accommodates multi-class data sets and automatically determines the error bound of each base classifier. The regularization parameter penalizes the classifier when it misclassifies instances that were correctly classified in the previous iteration. The parameter additionally reduces the bias towards majority classes. Experiments are conducted using 12 diverse data sets with moderate to high imbalance ratios. The results demonstrate superior performance of the proposed method compared to several state-of-the-art algorithms for imbalanced, multi-class classification problems. More importantly, the sensitivity improvement of the minority classes using RegBoost is accompanied with the improvement of the overall accuracy for all classes. With unpredictability regularization, a diverse group of classifiers are created and the maximum accuracy improvement reaches above 24%. Using stratified undersampling, RegBoost exhibits the best efficiency. The reduction in computational cost is significant reaching above 50%. As the volume of training data increase, the gain of efficiency with the proposed method becomes more significant

Impact of using raw or fermented manure as fish feed on microbial quality of water and fish

The microbial water and fish quality was assessed due to feeding of chicken manure (CM) and fermented chicken manure (FCM) to fish in ponds, using Nile tilapia (Oreochromis niloticus) which were classified into 7 groups (G). Each group received different mixtures of CM or FCM with fish ration (FR), 0:100, 25:75, 50:50 and 100:0 (%CM or FCM:% FR). The obtained results revealed that total bacterial count (TBC) and total coliform count (TCC) were significantly high at P ⩽ 0.05 in CM than both FCM and fish ration (FR). Escherichia coli and Salmonella were isolated from CM but not from FCM or FR. Additionally, TBC and TCC were significantly high at P ⩽ 0.05 at water and fish samples raised at CM ponds followed by FCM ponds in comparison with FR. Both E. coli and Salmonella were isolated from water and fish raised in ponds receiving either CM or FCM with higher incidence in those with CM. However all water and fish samples examined were free from E-coli O157: H7. The obtained results, proved the influence of CM on water and fish quality and recommend the use of FCM as a bacteriologically safe fish pond fertilizer

Assessment of variable drinking water sources used in Egypt on broiler health and welfare

Aim: This study assessed the impact of four water sources used as drinking water in Egypt for broiler chickens on its performance, carcass characteristic, hematological, and immunological responses. Materials and Methods: A total of 204 unsexed 1-day old Indian River broiler chickens were used in this study. They were randomly allocated into four treatment groups of 51 birds in each, with three replicates, 17 birds per replicate. Groups were classified according to water source they had been received into (T1) received farm tap water; (T2) received filtered tap water (T3) received farm stored water at rooftop tanks, (T4) received underground (well) water. Results: All water sources showed no significant differences among treated groups at (p>0.05) for most of the performance parameters and carcass characteristics. However (T2) group showed higher records for body weight (BWT), BWT gain (BWG), feed conversion ratio, bursa weight, serum total protein, globulin (G), albumin (A) and A/G ratio, Ab titer against New castle disease virus vaccine. On the other hand, it showed lower records for water intake (WI), WI/Feed intake ratio, total leukocytes count %, heterophil %, lymphocyte %, H/L ratio, liver weight, glutamic oxaloacetic transaminase, glutamic pyruvic transaminase, serum uric acid and creatinine. Where filtered water reverse osmosis showed lowest records for bacterial load, the absence of coliform bacteria, total dissolved solids (TDS), electrical conductivity (EC) and salinity. On the other hand stored water showed higher numerical values for TDS, EC, alkalinity, salinity, pH, bacterial count, and coliform count. Conclusion: Base on the results of this study, it is concluded that different water sources could safely be used as drinking water for poultry; as long as it is present within the acceptable range of drinking water quality for chickens. Suggesting the benefits of treatment of water sources on improving chickens’ health and welfare. Draw attention to the importance of maintaining the hygienic quality of stored water

Green HRM and green competitive advantage in hotel and tourism industry: a mediated moderation model using eco-innovation and green psychological climate

This study investigates the impact of green HRM (GHRM) on green competitive advantage (GCA), examining the mediating role of eco-innovation and the moderating role of green psychological climate (GPC). The study surveyed 472 fulltime employees in five-star hotels and travel agencies, developing and testing a five-hypothesis research model using PLS-SEM. Results revealed that GHRM positively impacts GCA and eco-innovation. Eco-innovation positively impacts GCA. In addition, GPC has a positive moderating influence on the relationship between GHRM and eco-innovation. Furthermore, Eco-innovation significantly mediates the relationship between GHRM and GCA

On the solution of Large Scale Bi-Level Linear Vector Optimization Problems through TOPSIS

In this paper, we extend TOPSIS (Technique for Order Preference by Similarity Ideal Solution) for solving Large Scale Bi-level Linear Vector Optimization  Problems (LS-BL-LVOP). In order to obtain a compromise ( satisfactory) solution to the LS-BL-LVOP problems using the proposed TOPSIS approach, a modified formulas for the distance function from the positive ideal solution (PIS ) and the distance function from the negative ideal solution (NIS) are proposed and modeled to include all the objective functions of both the first and the second levels. An  interactive decision  making algorithm for generating a compromise ( satisfactory) solution through TOPSIS approach is provided where the first level decision maker (FLDM) is asked to specify the relative importance of  the objectives. Finally, a numerical example is given to clarify the main results developed in the paper