Efektifitas Metode Pendekatan Sosiologi Personal Dalam Meminimalisasi Terhadap Kenakalan Remaja (Studi Di SMP Negeri 1 Boyolangu)

Paradigma kenakalan remaja lebih luas cakupannya dan lebih dalam bobot isinya, kenakalan remaja meliputi perbuatan-perbuatan yang sering menimbulkan keresahan di lingkungan masyarakat. Hal ini tidak terjadi di lingkungan masyarakat saja melainkan juga di lingkungan sekolah, contoh sederhana dalam hal ini antara lain perkelahian di kalangan antar perserta didik (siswa) yang kerap berkembang menjadi perkelahian antar sekolah. Tujuan dari penelitian ini menjelaskan bentuk-bentuk penerapan metode pendekatan personal sosiologi di SMPN 1 BOYOLANGU dan Menjelaskan efektifitas metode pendekatan personal sosiologi dalam meminimalisasi tingkat kenakalan remaja di SMPN 1 BOYOLANGU. Metode yang peneliti gunakan adalah pendekatan kualitatif yang terdiri dari rancangan penelitian, kehadiran peneliti . Lokasi penelitian. Tahapan penelitian : pra penelitian, tahap penelitian, penulisan laporan. Data dan sumber data : primer yaitu guru-guru,  sekunder yaitu dokumentasi, serta arsip-arsip. Teknik pengumpulan data : observasi, wawancara, dokumentasi. Teknik analisis data. Pemeriksaan keabsahan temuan, pemeriksaan teman sejawat. Dari hasil penelitian ini dapat disimpulkan : metode berupa pendekatan sosiologi personal dapat memberikan pengaruh besar kepada siswa yang sering melakukan pelanggaran untuk membantu guru lebih dekat kepada siswa, sehingga siswa mudah di berikan nasehat

The value of economic and cultural capital to college readiness among Filipino senior high school graduates

Guided by the lens of Bourdieu, this study examined the relationship of the students' economic capital (parents' monthly income and students' weekly allowance) and cultural capital (parents' highest educational attainment and students' community involvement) to their college readiness. The study utilized a descriptive-correlational design, and data were collected from 6,626 K-12 graduates enrolled in one state-university in Cagayan Valley Region, Philippines. The results reveal that the respondents have parents who have income below the Philippine poverty threshold level and have obtained a secondary level of education. They, too, are college-unready, implying that the competencies they obtained from their basic education need further enhancement. Moreover, economic and cultural capital becomes significant resources that are valuable in explaining the college readiness of Filipino Senior High School (SHS) graduates. Those who come from families with higher economic and cultural capital tend to have higher college readiness. Remarkably, the low economic and cultural capital of the students possibly explains their lack of college readiness. As they have less economic and cultural capital, they tend to have fewer competencies to capacitate them in hurdling tertiary education. Hence, these disadvantaged students generally struggle to achieve more and to be successful in life

Academic Profile and College Preparedness of K-12 Graduates: The Case of the Indigenous Peoples (IPs) in the Northern Philippines

The indigenous peoples (IPs) are recognized as one of the disadvantaged social groups constituting Philippine minorities. While there have been several studies seeking to explain issues relating to IPs’ participation in education, these have not adequately provided baseline data on the their academic profile and college preparedness, which are essential in understanding their effective transition from basic to tertiary education. Using descriptive-correlational design, this study investigated the association of academic profile and college preparedness of 1,860 IPs enrolled in a public university in the northern Philippines. The results revealed that the majority of respondents were college unprepared. Moreover, the level of preparedness differed significantly in terms of the type of senior high school (SHS) where they graduated, as well as the SHS track and strand they had taken. Kendall's tau-b statistic results showed that IPs who had higher SHS grade point average (GPA), more academic and nonacademic awards, greater participation in organizations and more involvement in cocurricular activities tended to be more college prepared. In regard to educational practice, improving college preparedness with due consideration of the academic profile facilitates an increased ability for IPs to be admitted to college and to succeed without remediation in college foundation courses

Urbanization and Vehicle Electrification in the United States: Life Cycle CO2 Emissions Estimation and Climate Policy Implications

<p>Recent sustainability research has focused on urban systems given their high share of environmental impacts and potential for centralized impact mitigation. Most previous works rely on descriptive statistics obtained from place-based case studies representing major cities, metropolitan areas, and counties using emissions inventories that may have inconsistent and/or limited scope (e.g., transportation and residential emissions only). This limits the potential for general insights and decision support related to the role of urbanization in CO2 emissions reduction. Here, I implement generalized linear and multiple linear regression analyses to obtain robust insights on the relationship between urbanization and CO2 emissions in the U.S. I used consistently derived county-level scope 1 & 2 CO2 inventories for my response variable while predictor variables included dummy-coded variables for county geographic type (central, outlying, and non-metropolitan), median household income, population density, and climate indices (heating degree days (HDD) and cooling degree days (CDD)). There is statistically significant difference in per capita emissions by sector for different county types, with transportation and residential emissions highest in nonmetropolitan (rural) counties, transportation emissions lowest in central (most urbanized) counties, and commercial sector emissions highest in central counties. More importantly, contrary to most previous findings, there is not enough statistical evidence indicating that per capita scope 1 & 2 emissions differ by geographic type, ceteris paribus. These results are robust for different assumed electricity emissions factors. Given that emissions production rate in more urban counties are not significantly different from that of less urban ones and population is concentrated in urban counties, significant national emissions reduction could be achieved if efforts are focused on central counties. There are various climate mitigation techniques – both from the supply and demand side. Given the large contribution of transportation in total county emissions and the fact that this technology bridges the transportation and electricity sector which is currently the biggest contributor to CO2 emissions, I investigated the emission reduction benefits from driving electric instead of gasoline vehicles. Vehicle electrification has also received sustained support from the local to the supranational level and is seeing an optimistic market trend. I characterize and assess the uncertainty in CO2 emissions per mile travelled for vehicles in the U.S. given regional variation and uncertainty in electricity emissions factor (marginal vs average, generation- vs consumption-based, different regional boundaries), driving pattern, and daily vehicle miles traveled (DVMT). I also investigate vehicle emissions estimates under convenience (vehicle starts charging when it arrives at home) and delayed (vehicle starts charging at 12am) charging. Using marginal emissions factors results in electric vehicle emissions estimate that are higher than average emissions estimates in the northeastern and north central U.S., and lower emissions in the south central U.S. In other regions, using marginal emissions versus average emissions factors may lead to differences in emissions estimates by as much as 28%. Delayed charging leads to higher emissions, given that off-peak electricity demand is supplied by fossil generators in most regions (e.g., coal). Using marginal emissions estimates, the Nissan Leaf electric vehicle has lower operation emissions compared to the Toyota Prius (the most efficient US gasoline vehicle) in western U.S., and the Leaf has higher operation emissions in the north central, regardless of assumed charging scheme and estimation method. In other regions the comparison is uncertain because of regional variation and uncertainty in emission factor estimates. Consumption- and generation-based marginal emissions also significantly (5 % - 28%), enough to result unclear comparison results. Average vehicle emissions estimates under different regional boundary definitions also differ significantly (e.g., state-based estimates deviate from National Electricity Reliability Commission (NERC) region-based estimates by as much as 122%). Other factors such as driving pattern and daily vehicle miles traveled also influence vehicle emissions. I conduct a locational comparison of electric and gasoline vehicle life cycle emissions in the U.S. taking into consideration the regional variation in the joint effect of consumption-based marginal electricity emission factors, driving pattern (city, highway or combined), and daily vehicle miles traveled (DVMT) distribution. I find that electricity generation emissions rate, determined by grid mix and charging scheme, has the largest influence on electric vehicle emission levels and the emissions differences of gasoline and electric vehicles. Secondary to this is urbanization level, especially for PHEVs, as it influences driving pattern and daily vehicle miles traveled. Highest CO2 emission reductions from electric vehicles can be attained in metropolitan counties in CA, TX, FL, NY, and New England states. Policies for wider adoption of electric vehicles such as incentives and other adoption facilitating mechanisms including investments in public charging infrastructure are encouraged in metropolitan counties, especially the denser ones. On the other hand, these policies are discouraged in north central states where electric vehicles would only increase emissions because of a relatively carbon-intensive grid. These findings reflect the pivotal role of the electricity and transportation sectors nexus in achieving national goals of CO2 emission reductions. Unless the U.S. decarbonizes its electricity system further, electric vehicles will only be beneficial in climate mitigation efforts in certain locations in the country. </p

Do US metropolitan core counties have lower scope 1 and 2 CO2 emissions than less urbanized counties?

Recent sustainability research has focused on urban systems given their high share of environmental impacts and potential for centralized impact mitigation. Recent research emphasizes descriptive statistics from place-based case studies to argue for policy action. This limits the potential for general insights and decision support. Here, we implement generalized linear and multiple linear regression analyses to obtain more robust insights on the relationship between urbanization and greenhouse gas (GHG) emissions in the US We used consistently derived county-level scope 1 and scope 2 GHG inventories for our response variable while predictor variables included dummy-coded variables for county geographic type (central, outlying, and nonmetropolitan), median household income, population density, and climate indices (heating degree days (HDD) and cooling degree days (CDD)). We find that there is not enough statistical evidence indicating per capita scope 1 and 2 emissions differ by geographic type, ceteris paribus. These results are robust for different assumed electricity emissions factors. We do find statistically significant differences in per capita emissions by sector for different county types, with transportation and residential emissions highest in nonmetropolitan (rural) counties, transportation emissions lowest in central counties, and commercial sector emissions highest in central counties. These results indicate the importance of regional land use and transportation dynamics when planning local emissions mitigation measures

Effects of biochar source, level of inclusion and particle size on in vitro dry matter disappearance, total gas and methane production and ruminal fermentation parameters in a barley silage-based diet

This study evaluated the effects of biochar differing in source, inclusion level, and particle size on DM disappearance (DMD), total gas and methane (CH4) production, and ruminal fermentation in a barley silage-based diet. The seven biochar products used were coconut (CP001 and CP014) or pine (CP002, CP015, CP016, CP023, CP024)-based. Experiment 1 evaluated these biochars at 4.5, 13.5 and 22.5% level of diet inclusion, whereas Experiment 2 evaluated CP002, CP016 and CP023 at 2.25 and 4.50% of the diet atThe accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Techno-Economic Assessment of Offshore Wind Energy in the Philippines

The technical and economic assessments for emerging renewable energy technologies, specifically offshore wind energy, is critical for their improvement and deployment. These assessments serve as one of the main bases for the construction of offshore wind farms, which would be beneficial to the countries gearing toward a sustainable future such as the Philippines. This study presents the technical and economic viability of offshore wind farms in the Philippines. The analysis was divided into four phases, namely, application of exclusion criteria, technical analysis, economic assessment, and sensitivity analysis. Arc GIS 10.5 was used to spatially visualize the results of the study. Exclusion criteria were applied to narrow down the potential siting for offshore wind farms, namely, active submerged cables, local ferry routes, marine protected areas, reefs, oil and gas extraction areas, bathymetry, distance to grid, typhoons, and earthquakes. In the technical analysis, the turbines SWT-3.6-120 and 6.2 M126 Senvion were considered. The offshore wind speed data were extrapolated from 80 m to 90 m and 95 m using power law. The wind power density, wind power, and annual energy production were calculated from the extrapolated wind speed. Areas in the Philippines with a capacity factor greater than 30% and performance greater than 10% were considered technically viable. The economic assessment considered the historical data of constructed offshore wind farms from 2008 to 2018. Multiple linear regression was done to model the cost associated with the construction of offshore wind farms, namely, turbine, foundation, electrical, and operation and maintenance costs (i.e., investment cost). Finally, the levelized cost of electricity and break-even selling price were calculated to check the economic viability of the offshore wind farms. Sensitivity analysis was done to investigate how LCOE and price of electricity are sensitive to the discount rate, capacity factor, investment cost, useful life, mean wind speed, and shape parameter. Upon application of exclusion criteria, several sites were determined to be viable with the North of Cagayan having the highest capacity factor. The calculated capacity factor ranges from ~42% to ~50% for SWT-3.6-120 and ~38.56% to ~48% for 6.2M126 turbines. The final regression model with investment cost as the dependent variable included the minimum sea depth and the plant capacity as the predictor variables. The regression model had an adjusted R2 of 90.43%. The regression model was validated with existing offshore wind farms with a mean absolute percentage error of 11.33%. The LCOE calculated for a 25.0372 km2 offshore area ranges from USD 157.66/MWh and USD 154.1/MWh. The breakeven electricity price for an offshore wind farm in the Philippines ranges from PHP 8.028/kWh to PHP 8.306/kWh

Effect of regional grid mix, driving patterns and climate on the comparative carbon footprint of gasoline and plug-in electric vehicles in the United States

We compare life cycle greenhouse gas (GHG) emissions from several light-duty passenger gasoline and plug-in electric vehicles (PEVs) across US counties by accounting for regional differences due to marginal grid mix, ambient temperature, patterns of vehicle miles traveled (VMT), and driving conditions (city versus highway). We find that PEVs can have larger or smaller carbon footprints than gasoline vehicles, depending on these regional factors and the specific vehicle models being compared. The Nissan Leaf battery electric vehicle has a smaller carbon footprint than the most efficient gasoline vehicle (the Toyota Prius) in the urban counties of California, Texas and Florida, whereas the Prius has a smaller carbon footprint in the Midwest and the South. The Leaf is lower emitting than the Mazda 3 conventional gasoline vehicle in most urban counties, but the Mazda 3 is lower emitting in rural Midwest counties. The Chevrolet Volt plug-in hybrid electric vehicle has a larger carbon footprint than the Prius throughout the continental US, though the Volt has a smaller carbon footprint than the Mazda 3 in many urban counties. Regional grid mix, temperature, driving conditions, and vehicle model all have substantial implications for identifying which technology has the lowest carbon footprint, whereas regional patterns of VMT have a much smaller effect. Given the variation in relative GHG implications, it is unlikely that blunt policy instruments that favor specific technology categories can ensure emission reductions universally