PERANCANGAN SISTEM OPTIMASI PENJADWALAN PENGANGKUTAN SAMPAH DI SURABAYA SECARA ADAPTIF MENGGUNAKAN METODE ALGORITMA GENETIKA

Sistem Pengangkutan sampah di Kota Surabaya dibagi menjadi dua bagian, yaitu sistem pengangkutan dari Kelurahan / Kecamatan (KK) ke LPS dan dari LPS ke LPA. Untuk melaksanakan sistem pengangkutan ini sehari-hari, tersedia gerobak tarik untuk mengangkut sampah dari KK ke LPS, dan armada truk pengangkut sampah yang disediakan oleh Dinas Kebersihan dan Pertamanan untuk mengangkut sampah dari LPS ke LPA. Setiap harinya, armada-armada yang bekerja dari LPS ke LPA ini selalu bekerja secara teratur dan sesuai dengan perintah yang diberikan. Namun, rute-rute yang dilewati dan jadwal pengangkutan tiap hari bisa berubah-ubah dan sesuai dengan keinginan sopir dari armada yang bersangkutan. Oleh karena itu, terkadang sampah masih menumpuk di satu LPS karena sampah yang datang dari KK lebih banyak daripada biasanya, sedangkan armada pengangkutan pun juga masih bekerja seperti biasanya, dan tidak bisa mengikuti jumlah sampah yang ada di LPS. Oleh karena itu, dibuatlah sebuah sistem optimasi dengan menggunakan Algoritma Genetika ini. Masing-masing solusi direpresentasikan kedalam tiap-tiap individu dalam algoritma tersebut, kemudian dengan melakukan beberapa operasi seperti seleksi, cross over dan mutasi, diharapkan bisa menghasilkan individu baru dengan nilai fitness yang semakin tinggi. Nilai fitness yang semakin tinggi artinya solusi tersebut adalah solusi paling optimal yang bisa dilakukan, meliputi rute terbaik beserta penugasan armadanya. Selain itu, untuk mempermudah penyampaian informasi digunakanlah Sistem Informasi Geografis (SIG) dengan menggunakan teknologi Google Maps API yang bisa menunjukkan rute-rute yang bisa dilewati untuk mengambil sampah di titik-titik LPS tersebut hingga dibawa ke LPA. Kata Kunci : Sistem Optimasi, SIG, Algoritma Genetika, Rute, Sampa

OPTIMASI PENJADWALAN PENGANGKUTAN SAMPAH DI SURABAYA SECARA ADAPTIF MENGGUNAKAN METODE ALGORITMA GENETIKA

Sistem Pengangkutan sampah di Kota Surabaya dibagi menjadi dua bagian, yaitu sistem pengangkutan dari Kelurahan/Kecamatan (KK) ke Lahan Pembuangan Sementara (LPS) kemudian ke Lahan Pembuangan Akhir (LPA). Untuk melaksanakan sistem pengangkutan ini, setiap harinya telah disediakan gerobak tarik untuk mengangkut sampah dari KK ke LPS. Juga terdapat armada truk pengangkut sampah yang disediakan oleh Dinas Kebersihan dan Pertamanan untuk mengangkut sampah dari LPS ke LPA. Armada-armada yang bekerja dari LPS ke LPA ini selalu bekerja secara teratur dan sesuai dengan perintah yang diberikan. Namun, rute-rute yang dilewati dan jadwal pengangkutan tiap hari bisa berubah-ubah dan sesuai dengan keinginan sopir dari armada yang bersangkutan. Oleh karena itu, terkadang sampah masih menumpuk di satu LPS karena sampah yang datang dari KK lebih banyak daripada biasanya, sedangkan kinerja armada pengangkutan tidak bisa menyesuaikan dengan kondisi tersebut. Pada penelitian ini, dikembangkan sebuah sistem optimasi penjadwalan tersebut dengan menggunakan Algoritma Genetika. Masing- masing solusi direpresentasikan kedalam tiap-tiap individu genetik dimana tiap individu merepresentasikan sebuah solusi rute pengangkutan. Kemudian dengan melakukan beberapa operasi seleksi, cross over dan mutasi terhadap individu-individu tersebut, akan menghasilkan individu baru berupa solusi paling optimal yang merepresentasikan rute terpendek yang dapat dilalui oleh truk armada pengangkutan sampah. Untuk mempermudah penyampaian informasi digunakanlah teknologi Google Maps API yang dapat menunjukkan rute-rute yang bisa dilewati untuk mengambil sampah di titik-titik LPS tersebut hingga dibawa ke LPA. Hasil dari sistem optimasi ini menunjukkan bahwa satu truk armada bisa digunakan untuk mengangkut sampah lebih dari satu LPS, asalkan volume sampah tidak melebihi kapasitas truk. Dengan demikian, sistem ini bisa menekan biaya bahan bakar untuk proses pengangkutan sampah sehari-hari. Kata Kunci: Sistem Optimasi, Algoritma Genetika, Rute Optimal, Google Maps AP

Photovoltaic power system simulation for small industry area

In this paper, modeling and simulation of 1MW grid connected PV system is simulated using National Renewable Energy Laboratory's (NREL) HOMER software, and the optimum system is analyzed to see the economic feasibility of the system in a small industry area in Malacca, Malaysia. The system is expected to foresee reduced grid energy consumption. Emphasis is also placed on reduction of green house gases emission. HOMER will simulate the system and perform optimization of system according to the available usage data and the available renewable energy (sun radiation) data. The lifecycle and cost of each system modules will also affect the optimization duly. In addition, HOMER also performs optimizations according to different assumption of uncertain factors to gauge the effect of sensitivity list

Protein secretion and outer membrane assembly in Alphaproteobacteria

The assembly of β-barrel proteins into membranes is a fundamental process that is essential in Gram-negative bacteria, mitochondria and plastids. Our understanding of the mechanism of β-barrel assembly is progressing from studies carried out in Escherichia coli and Neisseria meningitidis. Comparative sequence analysis suggests that while many components mediating β-barrel protein assembly are conserved in all groups of bacteria with outer membranes, some components are notably absent. The Alphaproteobacteria in particular seem prone to gene loss and show the presence or absence of specific components mediating the assembly of β-barrels: some components of the pathway appear to be missing from whole groups of bacteria (e.g. Skp, YfgL and NlpB), other proteins are conserved but are missing characteristic domains (e.g. SurA). This comparative analysis is also revealing important structural signatures that are vague unless multiple members from a protein family are considered as a group (e.g. tetratricopeptide repeat (TPR) motifs in YfiO, β-propeller signatures in YfgL). Given that the process of the β-barrel assembly is conserved, analysis of outer membrane biogenesis in Alphaproteobacteria, the bacterial group that gave rise to mitochondria, also promises insight into the assembly of β-barrel proteins in eukaryotes

Bid chimeras indicate that most BH3-only proteins can directly activate Bak and Bax, and show no preference for Bak versus Bax

The mitochondrial pathway of apoptosis is initiated by Bcl-2 homology region 3 (BH3)-only members of the Bcl-2 protein family. On upregulation or activation, certain BH3-only proteins can directly bind and activate Bak and Bax to induce conformation change, oligomerization and pore formation in mitochondria. BH3-only proteins, with the exception of Bid, are intrinsically disordered and therefore, functional studies often utilize peptides based on just their BH3 domains. However, these reagents do not possess the hydrophobic membrane targeting domains found on the native BH3-only molecule. To generate each BH3-only protein as a recombinant protein that could efficiently target mitochondria, we developed recombinant Bid chimeras in which the BH3 domain was replaced with that of other BH3-only proteins (Bim, Puma, Noxa, Bad, Bmf, Bik and Hrk). The chimeras were stable following purification, and each immunoprecipitated with full-length Bcl-xL according to the specificity reported for the related BH3 peptide. When tested for activation of Bak and Bax in mitochondrial permeabilization assays, Bid chimeras were ~1000-fold more effective than the related BH3 peptides. BH3 sequences from Bid and Bim were the strongest activators, followed by Puma, Hrk, Bmf and Bik, while Bad and Noxa were not activators. Notably, chimeras and peptides showed no apparent preference for activating Bak or Bax. In addition, within the BH3 domain, the h0 position recently found to be important for Bax activation, was important also for Bak activation. Together, our data with full-length proteins indicate that most BH3-only proteins can directly activate both Bak and Bax

Pemberdayaan Masyarakat dalam Pembuatan Sabun Padat dari Daun Sirih (Piper betle L.)

Covid-19 is an infection channel in human respiratory caused by coronavirus, which spread all over the world in 2020, thus implementing lockdown to lower the spread of the corona virus. Because Covid-19 communities have a reduced income especially in birds watching Isyo Hills in Nimbokrang especially in Muaif Village, and in Rhepang village it has a rich diversity of life, including betle leaves, where betle leaves have many benefits and properties such as betlephenol, saponin, sesterypen, starch, kovikol, where a natural antiseptic agent is available, The purpose of this activities is to make a solid soap of betel leaves (Piper betle L.) as antibacterias, and to support the economic growth of people in reple-betel leaves  is 10%, and the cost of rhi-leaf extract is 15 g, the respondents of society are 82% approved, 18% agree once in "a compact soap tutorial of the betel leaf," and 73%, 45%, and 64% in turn favor to smell, shape, and the color of the soap. Then, according to 73% of participants feel the tools and materials used in the manufacture of soap. And finally, the number of attendees who filled the questionnaire's list was attracted to making solid soap after a solid soapmaking tutorial.Keyword: antibacteria; betel leaves; Covid-19; Rhepang Muaif villages; solid soa

Severity of COVID-19 after Vaccination among Hemodialysis Patients: An Observational Cohort Study.

BACKGROUND AND OBJECTIVES: Patients receiving hemodialysis are at high risk from coronavirus disease 2019 (COVID-19) and demonstrate impaired immune responses to vaccines. There have been several descriptions of their immunologic responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination, but few studies have described the clinical efficacy of vaccination in patients on hemodialysis. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In a multicenter observational study of the London hemodialysis population undergoing surveillance PCR testing during the period of vaccine rollout with BNT162b2 and AZD1222, all of those positive for SARS-CoV-2 were identified. Clinical outcomes were analyzed according to predictor variables, including vaccination status, using a mixed effects logistic regression model. Risk of infection was analyzed in a subgroup of the base population using a Cox proportional hazards model with vaccination status as a time-varying covariate. RESULTS: SARS-CoV-2 infection was identified in 1323 patients of different ethnicities (Asian/other, 30%; Black, 38%; and White, 32%), including 1047 (79%) unvaccinated, 86 (7%) after first-dose vaccination, and 190 (14%) after second-dose vaccination. The majority of patients had a mild course; however, 515 (39%) were hospitalized, and 172 (13%) died. Older age, diabetes, and immune suppression were associated with greater illness severity. In regression models adjusted for age, comorbidity, and time period, prior two-dose vaccination was associated with a 75% (95% confidence interval, 56 to 86) lower risk of admission and 88% (95% confidence interval, 70 to 95) fewer deaths compared with unvaccinated patients. No loss of protection was seen in patients over 65 years or with increasing time since vaccination, and no difference was seen between vaccine types. CONCLUSIONS: These data demonstrate a substantially lower risk of severe COVID-19 after vaccination in patients on dialysis who become infected with SARS-CoV-2

Burden of cancer in the Eastern Mediterranean Region, 2005–2015: findings from the Global Burden of Disease 2015 Study

Objectives: To estimate incidence, mortality, and disability-adjusted life years (DALYs) caused by cancer in the Eastern Mediterranean Region (EMR) between 2005 and 2015. Methods: Vital registration system and cancer registry data from the EMR region were analyzed for 29 cancer groups in 22 EMR countries using the Global Burden of Disease Study 2015 methodology. Results: In 2015, cancer was responsible for 9.4% of all deaths and 5.1% of all DALYs. It accounted for 722,646 new cases, 379,093 deaths, and 11.7 million DALYs. Between 2005 and 2015, incident cases increased by 46%, deaths by 33%, and DALYs by 31%. The increase in cancer incidence was largely driven by population growth and population aging. Breast cancer, lung cancer, and leukemia were the most common cancers, while lung, breast, and stomach cancers caused most cancer deaths. Conclusions: Cancer is responsible for a substantial disease burden in the EMR, which is increasing. There is an urgent need to expand cancer prevention, screening, and awareness programs in EMR countries as well as to improve diagnosis, treatment, and palliative care services.The funding source played no role in the design of thestudy, the analysis and interpretation of data, and the writing of thepaper. GBD 2015 is funded by Bill & Melinda Gates Foundation

Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

© 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license Background: Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of “leaving no one behind”, it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health-related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990–2017, projected indicators to 2030, and analysed global attainment. Methods: We measured progress on 41 health-related SDG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health-related SDG index, we transformed the value for each indicator on a scale of 0–100, with 0 as the 2·5th percentile and 100 as the 97·5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings: The global median health-related SDG index in 2017 was 59·4 (IQR 35·4–67·3), ranging from a low of 11·6 (95% uncertainty interval 9·6–14·0) to a high of 84·9 (83·1–86·7). SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attainment by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation: The GBD study offers a unique, robust platform for monitoring the health-related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health-related SDG indicators, NCDs, NCD-related risks, and violence-related indicators will require a concerted shift away from what might have driven past gains—curative interventions in the case of NCDs—towards multisectoral, prevention-oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the SDGs. What is clear is that our actions—or inaction—today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Funding: Bill & Melinda Gates Foundation

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017 (The Lancet (2018) 392(10159) (1923–1994), (S0140673618322256), (10.1016/S0140-6736(18)32225-6))

Copyright © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Background The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 comparative risk assessment (CRA) is a comprehensive approach to risk factor quantification that offers a useful tool for synthesising evidence on risks and risk–outcome associations. With each annual GBD study, we update the GBD CRA to incorporate improved methods, new risks and risk–outcome pairs, and new data on risk exposure levels and risk–outcome associations. Methods We used the CRA framework developed for previous iterations of GBD to estimate levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs), by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017. This study included 476 risk–outcome pairs that met the GBD study criteria for convincing or probable evidence of causation. We extracted relative risk and exposure estimates from 46 749 randomised controlled trials, cohort studies, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. Using the counterfactual scenario of theoretical minimum risk exposure level (TMREL), we estimated the portion of deaths and DALYs that could be attributed to a given risk. We explored the relationship between development and risk exposure by modelling the relationship between the Socio-demographic Index (SDI) and risk-weighted exposure prevalence and estimated expected levels of exposure and risk-attributable burden by SDI. Finally, we explored temporal changes in risk-attributable DALYs by decomposing those changes into six main component drivers of change as follows: (1) population growth; (2) changes in population age structures; (3) changes in exposure to environmental and occupational risks; (4) changes in exposure to behavioural risks; (5) changes in exposure to metabolic risks; and (6) changes due to all other factors, approximated as the risk-deleted death and DALY rates, where the risk-deleted rate is the rate that would be observed had we reduced the exposure levels to the TMREL for all risk factors included in GBD 2017. Findings In 2017, 34·1 million (95% uncertainty interval [UI] 33·3–35·0) deaths and 1·21 billion (1·14–1·28) DALYs were attributable to GBD risk factors. Globally, 61·0% (59·6–62·4) of deaths and 48·3% (46·3–50·2) of DALYs were attributed to the GBD 2017 risk factors. When ranked by risk-attributable DALYs, high systolic blood pressure (SBP) was the leading risk factor, accounting for 10·4 million (9·39–11·5) deaths and 218 million (198–237) DALYs, followed by smoking (7·10 million [6·83–7·37] deaths and 182 million [173–193] DALYs), high fasting plasma glucose (6·53 million [5·23–8·23] deaths and 171 million [144–201] DALYs), high body-mass index (BMI; 4·72 million [2·99–6·70] deaths and 148 million [98·6–202] DALYs), and short gestation for birthweight (1·43 million [1·36–1·51] deaths and 139 million [131–147] DALYs). In total, risk-attributable DALYs declined by 4·9% (3·3–6·5) between 2007 and 2017. In the absence of demographic changes (ie, population growth and ageing), changes in risk exposure and risk-deleted DALYs would have led to a 23·5% decline in DALYs during that period. Conversely, in the absence of changes in risk exposure and risk-deleted DALYs, demographic changes would have led to an 18·6% increase in DALYs during that period. The ratios of observed risk exposure levels to exposure levels expected based on SDI (O/E ratios) increased globally for unsafe drinking water and household air pollution between 1990 and 2017. This result suggests that development is occurring more rapidly than are changes in the underlying risk structure in a population. Conversely, nearly universal declines in O/E ratios for smoking and alcohol use indicate that, for a given SDI, exposure to these risks is declining. In 2017, the leading Level 4 risk factor for age-standardised DALY rates was high SBP in four super-regions: central Europe, eastern Europe, and central Asia; north Africa and Middle East; south Asia; and southeast Asia, east Asia, and Oceania. The leading risk factor in the high-income super-region was smoking, in Latin America and Caribbean was high BMI, and in sub-Saharan Africa was unsafe sex. O/E ratios for unsafe sex in sub-Saharan Africa were notably high, and those for alcohol use in north Africa and the Middle East were notably low. Interpretation By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning