Identifikasi Pengaruh Penggunaan Heatsink Terhadap Keluaran Modul Surya

Panas matahari yang diserap oleh modul surya dapat menaikkan suhu dan menurunkan tegangan keluarannya. Upaya penurunan suhu modul surya agar dalam kondisi standar diperlukan untuk menjaga agar kinerjanya tetap optimal. Pemasangan bahan penyerap panas seperti heatsink merupakan salah satu metode yang dapat digunakan sebagai upaya mendinginkan modul surya. Heatsink mampu mengurangi suhu rata-rata modul surya hingga 2,43°C dan meningkatkan tegangan keluaran rata-rata modul surya hingga 2,23 Volt. Kondisi ini dapat dilihat dari rata-rata tegangan output Voc modul surya yang ditambahkan heatsink dapat mencapai tegangan rata- rata 20,76 Volt dibandingkan dengan modul tanpa penambahan heatsink 18,52 Volt. Disimpulkan bahwa penambahan bahan penyerap panas berupa heatsink lebih efektif menurunkan suhu modul surya dari pada tanpa menggunakan heatsink

Pengaruh Perendaman Dan Letak Posisi Biji Dalam Buah Terhadap Perkecambahan Dan Pertumbuhan Kecambah Biji Kakao (Theobroma Cacao L.)

Kakao (Theobroma cacao L.) merupakan salah satu tanaman yang banyak dibudidayakan di Indonesia. Kakao sendiri menjadi penyumbang devisa negara terbesar ke 3 dari sektor perkebunan setelah karet dan sawit. banyaknya jumlah perkebunan kakao menyebabkan kebutuhan akan bibit kakao meningkat. Penelitian ini bertujuan untuk mengetahui Pengaruh Perendaman Dan Letak Posisi Biji Dalam Buah Terhadap Perkecambahan Dan Pertumbuhan Kecambah Biji Kakao. Penelitian dilaksanakan pada bulan NovemberDesember 2017 di laboratorium Botani Jurusan Biologi Fakultas matematika dan Ilmu Pengetahuan Alam Universitas Lampung.penelitian ini menggunakan Rancangan Acak Lengkap Faktorial , faktor A perendaman (0 jam dan 24 jam), faktor b letak posisi biji dalam buah kakao (pangkal, tengah, ujung buah). Sehingga di dapatkan 6 kombinasi perlakuan yang masing-masing perlakuan diulang sebanyak 4x. Variabel yang diukur dalam penelitian ini adalah panjang akar, berat kering dan kandungan klorofil. Data yang diperoleh akan dianalisis dengan analisis ragam pada α 5%, jika ada perbedaan signifikan pada interaksi antara faktor A dan faktor B, dilanjutkan dengan uji Beda Nyata Terkecil (BNT) α 5%. Hasil penelitian menunjukan kombinasi perlakuan perendaman dan letak posisi biji memberikan pengaruh nyata terhadap persentase perkecambahan, tinggi tanaman dan berat kering, klorofil b dan klorofil total Namun tidak berpengaruh nyata untuk rasio tunas akat dan klorofil a. Perlakuan A2B1 dan A2B2 menjadi perlakuan yang paling efektif dalam menstimulasi perkecambahan dan pertumbuhan kecambah biji kakao

Decline of seagrass (Posidonia oceanica) production over two decades in the face of warming of the Eastern Mediterranean Sea

* The response of Posidonia oceanica meadows to global warming of the Eastern Mediterranean Sea, where the increase in sea surface temperature (SST) is particularly severe, is poorly investigated. * Here, we reconstructed the long-term P. oceanica production in 60 meadows along the Greek Seas over two decades (1997–2018), using lepidochronology. We determined the effect of warming on production by reconstructing the annual and maximum (i.e. August) SST, considering the role of other production drivers related to water quality (i.e. Chla, suspended particulate matter, Secchi depth). * Grand mean (±SE) production across all sites and the study period was 48 ± 1.1 mg DW per shoot yr−1. Production over the last two decades followed a trajectory of decrease, which was related to the concurrent increase in annual SST and SSTaug. Annual SST \u3e 20°C and SSTaug \u3e 26.5°C was related to production decline (GAMM, P \u3c 0.05), while the rest of the tested factors did not help explain the production pattern. * Our results indicate a persistent and increasing threat for Eastern Mediterranean meadows, drawing attention to management authorities, highlighting the necessity of reducing local impacts to enhance the resilience of seagrass meadows to global change threats

Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

Background The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic; characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic; and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting System (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95$7·3 trillion (95% UI 7·2–7·4) in 2019; 293·7 times the $24·8 billion (95$43·1 billion in development assistance was provided to maintain or improve health. The pandemic led to an unprecedented increase in development assistance targeted towards health; in 2020 and 2021, $1·8 billion in DAH contributions was provided towards pandemic preparedness in LMICs, and$37·8 billion was provided for the health-related COVID-19 response. Although the support for pandemic preparedness is 12·2% of the recommended target by the High-Level Independent Panel (HLIP), the support provided for the health-related COVID-19 response is 252·2% of the recommended target. Additionally, projected spending estimates suggest that between 2022 and 2026, governments in 17 (95% UI 11–21) of the 137 LMICs will observe an increase in national government health spending equivalent to an addition of 1% of GDP, as recommended by the HLIP. Interpretation There was an unprecedented scale-up in DAH in 2020 and 2021. We have a unique opportunity at this time to sustain funding for crucial global health functions, including pandemic preparedness. However, historical patterns of underfunding of pandemic preparedness suggest that deliberate effort must be made to ensure funding is maintained

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation