TALKIE TIME AND RECAP Learning Competencies 1

TALKIE TIME AND RECAP

Learning Competencies: 1. Consolidates significant findings (addendum) 2. forms logical conclusions (CG) 3. makes recommendations based on conclusions (CG)

Activity: WHAT DO YOU REMEMBER ABOUT STATING SIGNIFICANT FINDINGS, CONCLUSION AND RECOMMENDATIONS?

CHAPTER 3 Summary of Findings, Conclusions and Recommendations Significant Findings - Narrowed findings from chapter 2 - Major statements of factual information based on the analyzed data. - Only the major and salient findings are included in this chapter. - All sub-problems must have their respective findings. - The results of the hypothesis must be included. - No numerical data should be included

The Larvicidal Effect of Neem (Azadirachta indica) Leaves Extract on Mortality of Second Instar Stage of Common House Mosquito (Culex pipiens fatigans)

THE PROBLEM Statement of the Problem The main focus of this study was to determine the larvicidal effect of Neem (Azadirachta indica) Leaves Extract on the Mortality of second instar stage of Common House Mosquito (Culex pipiens fatigans). Specifically, this study sought to answer the following queries:

1. What is the mean count of mosquito larvae before the treatment on the following groups: 1. 1 Control Group (resmethrin brand); and 1. 2 Experimental Group? 2. What is the mean count of dead mosquito larvae (mortality) after the treatment (24 and 48 hours) in the following groups: 2. 1 Positive Control Group; and 2. 2 Experimental Group concentrations: 2. 2. 1 25% 2. 2. 2 50% 2. 2. 3 75% 2. 2. 4 100%?

3. Is there a significant difference in the mean count of dead mosquito larvae (mortality) before and after the treatments of the 2 groups in (24 & 48 hours)? 4. Is there a significant difference in the mean count of dead mosquito larvae (mortality) after the treatments in the two groups in (24 and 48 hours)? 5. Is there a significant difference in the mean count of dead mosquito larvae (mortality) after the treatments in the different concentrations of the experimental group?

Null Hypotheses Ho 1. There is no significant difference in the mean count of dead mosquito larvae (mortality) before and after the treatments of the 2 groups in (24 & 48 hours). Ho 2. There is no significant difference in the mean count of dead mosquito larvae (mortality) after the treatments in the two groups in (24 and 48 hours). Ho 3. There is no significant difference in the mean count of dead mosquito larvae (mortality) after the treatments in the different concentrations of the experimental group.

Table 1 Mean Count of Mosquito Larvae Before Treatment Groups Replicate 1 Replicate 2 Replicate 3 Total Mortality Rate Control 20 20 20 60 0 20 20 20 60 0 100 100 300 0 (Resmithrin Brand) Experimental 1 (25%) Experimental 2 (50%) Experimental 3 (75%) Experimental 4 (100%) Total

Table 2 -A Mean Count of Mosquito Larvae After Treatment (in 24 Hours) Groups Control Replicate 1 Replicate 2 Replicate 3 Total Left Mortality Rate 17 18 18 53 7 88 6 8 4 18 42 30 10 9 11 30 30 50 15 16 18 49 11 82 16 16 19 51 9 85 (Resmithrin Brand) Experimental 1 (25%) Experimental 2 (50%) Experimental 3 (75%) Experimental 4 (100%)

Table 2 -B Mean Count of Mosquito Larvae After Treatment (in 48 Hours) Groups Replicate 1 Replicate 2 Replicate 3 Total Left Mortality Rate Control 19 18 56 4 93 (Resmithrin Brand) Experimental 1 11 9 7 27 33 45 12 11 13 36 24 60 17 18 18 53 18 18 18 54 (25%) Experimental 2 (50%) Experimental 3 7 88 (75%) Experimental 4 (100%) 6 90

Table 3 Difference in the mean count of dead mosquito larvae (mortality) before and after the treatments of the 2 groups in (24 hours) Groups Control Experimental 1 Before After Differenc Treatment Treatm e ent (24 Hrs) 53 7 60 60 42 18 Computed Critical T Decision T 3. 32 1. 21 Reject Ho 1. 04 1. 21 Accept Ho Not (25%) Experimental Interpretatio n Significant 60 30 30 60 11 49 60 9 51 1. 75 1. 21 Reject Ho Significant 3. 09 1. 21 Reject Ho Significant 3. 17 1. 21 Reject Ho Significant (50%) Experimental (75%) Experimental (100%)

Table 3 -b Difference in the mean count of dead mosquito larvae (mortality) before and after the treatments of the 2 groups in (48 hours) Groups Before Treatme nt Control 60 Experimental 1 60 After Differenc Computed T Critical T Decision Treatme e nt (48 Hrs) 4 56 3. 56 1. 21 Reject Ho 33 27 24 36 7 53 6 54 Interpretatio n Significant 1. 38 1. 21 Reject Ho Significant 2. 26 1. 21 Reject Ho Significant 3. 32 1. 21 Reject Ho Significant 3. 42 1. 21 Reject Ho Significant (25%) Experimental 60 (50%) Experimental 60 (75%) Experimental (100%) 60

Table 4 -a Difference in the mean count of dead mosquito larvae (mortality) after the treatments in the two groups in (24 hrs) Groups Control vs Experimental (25%) After Treatment (24 Hrs) 7 Difference 42 1 35 Computed T 4. 01 Critical T Decision Interpretation 1. 21 Reject Ho Significant Control vs Experimental (50%) Control vs Experimental (75%) Control vs Experimental (100%) 7 30 3. 72 23 1. 21 Reject Ho Significant 0. 72 1. 21 Accept Ho Not Significant 0. 41 1. 21 Accept Ho Not Significant 7 11 4 7 9 2

Table 4 -b Difference in the mean count of dead mosquito larvae (mortality) after the treatments in the two groups in (48 hrs) Groups Control vs Experimental (25%) After Treatment (48 Hrs) 4 1 Difference 33 29 Computed T 3. 80 Critical T Decision Interpretation 1. 21 Reject Ho Significant Control vs Experimental (50%) 4 Control vs Experimental (75%) Control vs Experimental (100%) 4 7 3 4 6 2 24 3. 53 20 1. 21 Reject Ho Significant 0. 61 1. 21 Accept Ho Not Significant 0. 41 1. 21 Accept Ho Not Significant

Table 5 -a Difference in the mean count of dead mosquito larvae (mortality) after the treatments in the different concentrations of the experimental group 24 hrs. ) Groups Experimental 1 After Computed Critical T Treatment (24 F Hrs) 42 30 11 (75%) Experimental (100%) 4. 46 Reject Ho Significant 6. 11 (50%) Experimental Interpretation (25%) Experimental Decision 9

Table 5 -b Difference in the mean count of dead mosquito larvae (mortality) after the treatments in the different concentrations of the experimental group (48 hrs. ) Groups Experimental 1 After Treatment Computed F (48 Hrs) (25%) Experimental 24 7 (75%) Experimental (100%) Interpretation 4. 46 Reject Ho Significant 5. 91 (50%) Experimental Decision 33 Critical T 6

Summary of Findings A. Mean Count of Dead Mosquito Larvae After the Treatment (24 & 48 Hours) The positive control group, resmithrin aerosol brand is an effective larvecide as revealed in 24 and 48 hours observation. In the experimental group, the first 24 hours has significantly produced a noteworthy mortality rate and higher after 48 hrs. , especially the 75 and 100% concentrations of the neem extracts. This means that the neem extracts with deferring concentrations can potentially kill the larvae of the second instar stage of the common house hold mosquitos.

B. Difference in the mean count of dead mosquito larvae (mortality) before and after the treatments of the 2 groups in (24 & 48 hours) In positive control group, the pre-to-post treatment yielded a significant difference of the mortality rate in both 24 and 48 hours. This is expected as the aerosol is a known larvecide. In the experimental group in the first 24 hours, out of the 4 experimental groups, 3 groups (50%, 75% and 100%) concentrations of neem extracts rendered significant difference in the pre-and post treatments. While four out of 4 experimental groups (25%, 50%, 75% and 100%) concentrations of neem extracts rendered significant difference in the pre-and post treatments after 48 hours. The time element is a factor contributing to the mortality rate of the larvae.

C. Difference in the mean count of dead mosquito larvae (mortality) after the treatments in the two groups in (24 & 48 hrs). Between positive control group and experimental group 1 (25%) concentration, it yielded a significant result. This means that the positive control group is more effective than the 25% neem concentration in both 24 & 48 Hours. Between positive control group and experimental group 2 (50%) concentration, it yielded a significant result. This means that the positive control group is more effective than the 50% neem concentration in both 24 and 48 hours. Between positive control group and experimental group 3 (75%) concentration, it yielded an insignificant result. This means that the experimental group 3 (75% concentration) is as effective as the positive control group in both 24 and 48 hours. Between positive control group and experimental group 4 (100%) concentration, it yielded an insignificant result. This means that the experimental group 4 (100% concentration) is as effective as the positive control group in both 24 and 48 hours.

D. Difference in the mean count of dead mosquito larvae (mortality) after the treatments in the different concentrations of the experimental group (24 & 48 hrs. ) The F test (ANOVA) reveals that there is a significant difference in the mortality rate produced by the 4 different concentrations of neem extract in the experimental set up. The 75% and 100% concentrations were highly effective compared to 25% and 50 % concentrations. This means that the different neem concentrations have different effects on the larvae. The higher is the concentration, the more effective it is as larvecide.

Guidelines on Conclusion 1. Conclusion should not contain numerals 2. No conclusions should be drawn from the implied effects of the findings. 3. Never repeat the findings in the conclusions section. 4. Conclusions should be formulated concisely and briefly stated but must convey as required in the sub-problems. 5. No conclusions should be made that were not based from the findings.

Conclusion - This is the part that provides implications based on significant findings - This should be an answer to the Hypothesis or assumptions - This could provide prognosis for existing theory/concept or principle or a new one.

CONCLUSIONS 1. The experimental groups (75% & 100% concentrations) are as effective as the positive control group. The neem extract is comparable to commercial aerosol as larvecide. 2. The time element is a factor contributing to the mortality rate of the larvae as revealed in the 24 hrs and 48 hrs interval results. 3. The different neem concentrations have different effects on the larvae. The higher is the concentration, the more effective it is as larvecide.

CONCLUSIONS Conclusively, it can be said that neem has some biologically active components which show insecticidal activity- the Azadirachtin. This conclusion is supported by the previous investigations of various workers. So neem products may be used as mosquito population controlling agent, which is a vector of many diseases. They are cheaper and biodegadable and can be used easily by an ordinary man without hazardous effects.

Recommendations 1. 2. 3. 4. 5. . Drawn from the findings and conclusions of the study. They must be feasible to be implemented. Workable or functional, doable, adaptable and flexible. They must be specific or general or both. A suggestion for further study must be included.

RECOMMENDATIONS 1. Further study could be done on testing the Phytochemical of the Neem extracts. This is explained by the different solvents properties, such as polarity that enables them to extract different type of compound(s), and variety of compounds that results in different larvicidal properties. 2. Further study is needed for isolation and identification of bioactive compounds by different separation methods (such as column chromatography, TLC, and HPLC) and for identification methods using spectroscopy which includes UV, IR, MS and NMR. 3. Different parts of the Neem could also be tested not just the leaves. In other studies, the order of larvicidal potency among all the parts were leaf > root > seed > bark. 4. The experiment could also be tested on other species of mosquito like aedes aegypti and anopheles which gave most devastating cause of malaria and dengue. 5. The screening, handling and identification of mosquitos could be improved.

Drainage Management System Using Ultrasonic Sensors

THE PROBLEM Statement of the Problem The researcher sought to innovate a new drainage system management with use of ultrasonic sensor. The main aim of this study is to provide a real-time information on the drainage condition and water level detection. Specifically, the study sought to answer the following questions: 1. What is the Operation Design of the researcher-made drainage management system? 2. What Materials and Procedures are used the researcher-made drainage management system? 3. How functional is the proposed design based on its purpose? Assumption: The researcher-made drainage management system is effective in providing a real-time information on the drainage condition

I-A. The Operation Design – Block Diagram The operation design of the proposed drainage management system using ultrasonic sensors is to locate clogs for an early flood response. Figures 1 illustrates the block diagram of the ultrasonic sensor of the design project. Figure 1. Block diagram of the ultrasonic sensor

I-B. Operation Design - The Programming The researcher collected different programs for each sensor from the Arduino website. The codes were compiled and modified to fit the use to be obtained using the Arduino 1. 6. 9 software. Extensive revision and analysis were done in order to achieve the expected code. Figure 2 illustrates the program flow chart of the whole project.

Figure 2. Program Flow C

I-C. Operation Design – The Set Up Mechanism of Ultrasonic Sensor The Ultrasonic sensor detects the distance of any object without the sense of touch. It is set into repeatable mode, meaning it will continue to detect any object’s distance until it ends. The sensor is given a ten-second calibration time and after that, it runs. This sensor contains lenses that determines its detection range. It is said to have a minimum and maximum range of 2 to 400 centimeters according to the manual. The sensor is then set to its maximum range.

Figure 3. Ultrasonic Sensor Schematic Diagram

According to the program, the sensor will only send a high signal once the distance of uneven water levels are detected. The system was then tested in various situations with a clog in different areas of the drainage system. This is to ensure the accuracy of the whole system. An LED, along with a piezo element buzzer, is paired up with each Ultrasonic set-up that turns on when the coniditon is met. Thus, if an LED and buzzer emit light aand sound respectively, then it must mean there is a block within its area.

Figure 4. Ultrasonic Range Finder

II. Materials and Procedures : The researcher will use the following materials: 3 HC-SR 04 Ultrasonic Sensors Male-Male Connectors Male-Female Connectors Female-Female Connectors USB Cable A to B Arduino Mega 2560 Microcontroller 3 Piezo Element Buzzer 3 LEDs Arduino Software (version 1. 6. 9) Soldering iron Lead Sealant 32 in x 6. 5 in x 13. 5 in Case (Prototype Set-Up) The researcher obtained the materials needed from 3 M Electronix in Basak-Marigondon Road, Lapu-Lapu City, from

1 x HC-SR 04 module

VCC = +5 VDC Trig = Trigger input of Sensor Echo = Echo output of Sensor GND = GND

The Arduino Mega 2560 is a microcontroller board based on the ATmega 2560 (datasheet). It has 54 digital input/output pins (of which 14 can be used as PWM outputs), 16 analog inputs, 4 UARTs (hardware serial ports), a 16 MHz crystal oscillator, a USB connection, a power jack, an ICSP header, and a reset button. It contains everything needed to support the microcontroller; simply connect it to a computer with a USB cable or power it with a AC-to-

Figure 6. 3. Programming of the First Ultrasonic Sensor

Figure 6. 5. Programming of the Third Ultrasonic Sensor

Figure 8. Primary Set Up of the Program

Figure 9. 1. Creation of the Prototype Drainage 1

Figure 10. 3. Creation of the Drainage Prototype 2

III. Functionality Test LOCATION READINGS (in cm) Depth of OF THE BLOCK Sector 1 LOCATION OF THE BLOCK Sector 2 Set-Up 27 cm Depth of Set-Up 1 st Sensor 17 2 nd Sensor 3 rd Sensor 27 27 Block in Sector 1 was detected READINGS (in cm) 1 st 2 nd 3 rd Sensor 27 cm Conclusion Sensor 27 16 27 Block in Sector 2 was detected

Conclusion The functionality of the ultrasonic sensor, based on research, used the reflection mode to retrieve data to process in the set-up. The operation of the set-up is based on the real-time readings of the ultrasonic sensors, therefore the function of this system is to detect clogs and blocks based on the ultrasonic sensors’ readings and the conditions programmed.

Recommendations 1. It is recommended that the future researchers try other sensors that still provides and implements the functions of the study and to integrate the possibility of multiple clogs or blocks and to also create a limiting range for the sensors’ trigger in identifying a possible clog in the drain. 2. It is also recommended to use a bigger set up and to use a GSM shield for better data gathering and monitoring of the system.

APPLICATION BASED ON PREVIOUS OUTPUT PROVIDE THE SIGNIFICANT FINDINGS; CONCLUSIONS AND RECOMMENDATIONS